system

Abstract

We provide the system. [Solution] A means for the user to input basic information, Means of collecting food data, A means of suggesting food and recipes based on user information, A means for users to select and order food and recipes, The means of delivering the ordered food, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, food loss is a serious social problem. In households, it is difficult to manage food ingredients in busy daily life, and food past its expiration date is often discarded. Also, among producers and distributors, substandard vegetables and fruits, as well as unsold products, are often discarded. As a result, waste of resources and the environmental burden increase. There is a need for a mechanism that can solve such problems and enable consumers, producers, and distributors to all enjoy the benefits.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means. The system of the present invention includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, and means for delivering the ordered food. It also includes means for suggesting optimal food and recipes based on allergy information and food preferences registered by the user, and means for managing a food database and organizing and managing newly added food data. This reduces food waste and provides an efficient system from which consumers, producers, and distributors can all enjoy the benefits.

[0006] A "user" refers to an individual or group that uses the system to input food information, select suggested foods and recipes, and place an order.

[0007] "Basic information" refers to individual data about the user, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[0008] "Means" refers to the devices or methods by which a system performs a specific function or process.

[0009] "Food data" refers to information such as the type, quantity, expiration date, and price of food products provided by distributors and producers.

[0010] "Means for suggesting food and recipes" refers to a device or program that has the function of automatically selecting the most suitable food and recipe based on the user's basic information and presenting them to the user.

[0011] "Means of ordering" refers to a device or program that allows a user to review suggested food items or recipes, select them, and confirm their purchase.

[0012] "Means of delivery" refers to the process and equipment used to package the food ordered by the user and deliver it to the specified address.

[0013] "Allergy information" refers to data about allergic reactions a user has to specific foods.

[0014] "Food preference information" refers to individual preference data regarding whether a user likes or dislikes certain foods.

[0015] A "database" refers to a computer system used to organize and store large amounts of information, and to efficiently search and update that information.

[0016] "Means of organization and management" refers to devices or programs for classifying, properly storing, and updating or retrieving collected food data as needed. [Brief explanation of the drawing]

[0017] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10]Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0021] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food.

[0039] Overall system flow

[0040] 1. User registration and information gathering

[0041] Users access the Ecolicious system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[0042] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[0043] 2. Food data collection

[0044] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[0045] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[0046] 3. Food and recipe suggestions

[0047] The user logs into the system from their device and requests suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences.

[0048] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[0049] As a concrete example, consider a case where the user is a housewife with a dairy allergy. We know that the user has purchased a lot of vegetables in the past. Based on this information, the server suggests a dairy-free recipe using off-grade cabbage and sweet potatoes: "Sweet Potato Vegan Curry."

[0050] 4. Confirm your order

[0051] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[0052] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[0053] 5. Food delivery and pickup

[0054] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[0055] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0056] In this way, the system of the present invention efficiently collects and manages food data and proposes optimal foods and recipes for users, thereby reducing food waste in households. Furthermore, it enables producers and distributors to improve the efficiency of inventory management and sales, thus minimizing overall resource waste.

[0057] The following describes the processing flow.

[0058] Step 1:

[0059] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0060] Step 2:

[0061] When a user submits their basic information, the server receives it and stores it in the database. It also automatically generates a user ID and links it to each piece of information.

[0062] Step 3:

[0063] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[0064] Step 4:

[0065] Food information entered by producers and distributors is sent to the server, which then adds, organizes, and manages this information in a database.

[0066] Step 5:

[0067] Users log in to the system from their devices and request food and recipe suggestions.

[0068] Step 6:

[0069] The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, and food preferences.

[0070] Step 7:

[0071] The server sends a list of selected foods and recipes to the user's device. The user can then review the suggestions.

[0072] Step 8:

[0073] Users review the suggestions on their devices, select their favorite foods and recipes, and confirm their order.

[0074] Step 9:

[0075] Once a user confirms an order, the server receives the order details and automatically sends the order data to the distributor.

[0076] Step 10:

[0077] The server generates an order confirmation email and sends it to the user's email address.

[0078] Step 11:

[0079] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[0080] Step 12:

[0081] The user receives the delivered food. The server generates a delivery completion notification and sends it to the user's device.

[0082] In this way, the Ecolicious system can function efficiently and reduce food waste.

[0083] (Example 1)

[0084] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0085] In modern society, food waste in homes and businesses has become a serious problem. Furthermore, consumers are required to make food choices based on their preferences and allergy information, necessitating the provision of appropriate information to support this. Producers and distributors are also required to improve the efficiency of inventory management and sales, but the current system makes it difficult to do so effectively.

[0086] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0087] This invention includes a server that receives data entered by a user, stores it in a database, and assigns a unique ID to each user; a server that organizes and manages food data entered by producers and distributors and generates a list to provide to the user; and a server that selects and proposes optimal foods and recipes to the user based on the user's past purchase history, allergy information, and food preferences. This enables a reduction in food waste in households and businesses, food selection that meets the diverse needs of consumers, and improved inventory management and sales efficiency for producers and distributors.

[0088] A "user" is an individual or group that accesses the system using a home terminal and enters basic information and preferences regarding food.

[0089] A "server" is a central processing unit that receives data transmitted from users, producers, and distributors, stores, organizes, and analyzes it, and provides the necessary information to various stakeholders.

[0090] A "terminal" is an input device used by a user to access a system and enter information, and specifically refers to devices such as smartphones and personal computers.

[0091] "Basic information" refers to user-specific information that users enter into the system, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[0092] "Food data" refers to detailed information about food products, such as expiration dates, types, quantities, and prices, that producers and distributors enter into the system.

[0093] A "database" is a collection of information that is systematically stored and managed to allow for easy searching and access of basic user information and food data.

[0094] A "User ID" is a unique identifier assigned by the server to each user, and is an identification number used to manage user information and transactions.

[0095] "Suggestion" refers to the server selecting and presenting the most suitable foods and recipes to the user based on their past purchase history, allergy information, and food preferences.

[0096] "Order data" refers to information about the food items and recipes selected by the user, along with their quantities, which is received, processed, and provided to distributors by the server.

[0097] A "confirmation email" is a purchase confirmation notification sent from the server to the user's email address after the user has confirmed their order.

[0098] A "food list" is a list of selectable foods that the server provides to the user based on collected food data.

[0099] A "notification" is a message generated by a system to convey important information to a user or relevant party.

[0100] Modes for carrying out the invention

[0101] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The following describes in detail specific embodiments for carrying out this invention.

[0102] System Overview

[0103] The system mainly consists of the following elements:

[0104] 1. Means (terminals) by which the user enters basic information.

[0105] 2. Means of collecting food data (server and terminal)

[0106] 3. Means (server) for suggesting food and recipes based on user information.

[0107] 4. A means (terminal) for users to select and order food and recipes.

[0108] 5. Means of delivering ordered food products (distributors)

[0109] Hardware and software

[0110] User side

[0111] Users access the system using their home or company devices (e.g., smartphones, tablets, PCs, etc.). They use a browser or dedicated application running on these devices to enter basic information and food preferences.

[0112] Server side

[0113] The server receives, stores, organizes, and analyzes data sent from users, producers, and distributors. Specifically, the following software can be used:

[0114] Database management systems (e.g., MySQL (registered trademark), PostgreSQL)

[0115] Server-side scripts (e.g., PHP, Node.js)

[0116] Data analysis tools (e.g., Python, Apache Spark®)

[0117] This system also utilizes a generative AI model, which allows it to suggest optimal foods and recipes based on the user's purchase history, preferences, and allergy information.

[0118] Program processing and specific examples

[0119] 1. User registration and information gathering

[0120] Users access the system's registration form using a terminal and enter information such as their name, address, contact information, allergy information, food preferences, and past purchase history. The server receives this information, stores it in a database, and assigns a unique user ID to each user.

[0121] 2. Collection of food data

[0122] Producers and distributors use terminals to input data on products with short shelf lives or substandard vegetables and fruits from a management screen. The server receives this data, organizes it, and stores it in a database.

[0123] 3. Food and recipe suggestions

[0124] The server uses a generative AI model to select the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The selected list of suggestions is sent to the user's device for review.

[0125] Specific example: Suppose the user is a housewife with a dairy allergy and has a history of purchasing a lot of vegetables. Based on this information, the server suggests a dairy-free "sweet potato vegan curry" recipe and suggests off-spec cabbage and sweet potatoes.

[0126] The following is an example of a prompt message for a generative AI model:

[0127] "We are designing a system to reduce food waste in homes and businesses. We're considering a user who is a housewife with a dairy allergy and who buys a lot of vegetables. Please design a process that suggests the most suitable foods and recipes for this user."

[0128] 4. Order Confirmation and Delivery

[0129] Once the user reviews the suggested food items and recipes and confirms their order, the server processes the order data and provides it to the distributor. The server also generates a confirmation email and sends it to the user's email address. The distributor prepares the food based on the order data received from the server and delivers it to the user's address.

[0130] 5. Notification of delivery completion

[0131] Upon completion of delivery, the distributor updates the status through the system, and the server generates and sends a delivery completion notification to the user. The user can then receive the delivery completion notification on their device.

[0132] As described above, this system efficiently collects and manages food data and suggests optimal foods and recipes to users, thereby reducing food waste in households and businesses and providing benefits to consumers, producers, and distributors alike.

[0133] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0134] Step 1:

[0135] Users access the system from their home devices (smartphones or PCs) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. The entered data is sent to the server when the user presses the "Submit" button. The server validates the received input data and saves it to the database in the appropriate format. As output, a unique user ID is generated for the user, and a registration confirmation screen is displayed on the device.

[0136] Step 2:

[0137] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server by pressing the "Submit" button. The server validates the received food data and adds it to the database in the appropriate format. As output, the food list is updated and the correct data is reflected on the management screen.

[0138] Step 3:

[0139] The user logs into the system using their device and requests suggestions. The server queries the user's past purchase history, allergy information, and food preferences, and sends this information to a generative AI model. The generative AI model processes this data and selects the most suitable foods and recipes. As output, the server sends a list of selected foods and recipes to the user's device, allowing the user to review the suggestion list.

[0140] Step 4:

[0141] The user reviews the suggested food items and recipes and presses the "Confirm Order" button on their terminal. The order data is sent to the server. The server validates the order data, performs the necessary processing, and provides it to the distributor. As output, the server generates a confirmation email and sends it to the user's email address, and the distributor is provided with the necessary order information.

[0142] Step 5:

[0143] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are then delivered to the user's address. Specifically, the distributor's logistics system takes in the order data and calculates the optimal delivery route. As an output, the delivery schedule is finalized, and the user is notified of the delivery date.

[0144] Step 6:

[0145] The user receives the delivered food and cooks it using the recipe. Upon completion of delivery, the distributor sends a delivery completion status to the server. The server receives this information, generates a delivery completion notification, and sends it to the user's terminal. As output, the user receives the delivery completion notification, and the system records that all processing is complete.

[0146] (Application Example 1)

[0147] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0148] Existing food delivery systems lack effective means to reduce food waste, and are particularly hesitant to utilize foods with short shelf lives or those that do not meet specifications. Furthermore, they are insufficient in optimizing delivery based on user allergy information and preferences. In addition, the delivery system for ordered foods lacks efficiency, compromising user convenience. To address these challenges, more advanced information processing and the use of smart devices are necessary.

[0149] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0150] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. This makes it possible to reduce food waste and improve user convenience.

[0151] A "user" is an individual or legal entity that uses the system to request and order food and recipes.

[0152] "Basic information" refers to information such as the user's name, address, contact information, allergy information, preferred foods, and past purchase history.

[0153] "Food data" refers to information such as the type, quantity, expiration date, and price of food products provided by producers and distributors.

[0154] The "suggestion method" refers to a system function that selects the most suitable food and recipe based on user information and presents them to the user.

[0155] "Ordering method" refers to a system function that allows users to select selected food items and recipes and confirm their order.

[0156] "Delivery method" refers to the service or function used to deliver ordered food items to the address specified by the user.

[0157] A "smart device" is a device that connects to the internet and provides or retrieves information, such as a smartphone, smart glasses, a head-mounted display, or a robot.

[0158] A "database" is a recording device or a system that includes a recording device for organizing and managing information.

[0159] "Reducing food waste" refers to reducing the amount of food that is wasted by offering and delivering food that is nearing its expiration date or that does not meet standard specifications to customers.

[0160] "User information" refers to information that includes basic information and additional information provided by smart devices.

[0161] The system for realizing this invention includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. Specific embodiments are described below.

[0162] User registration and information gathering

[0163] Users access the system from a home device (e.g., a smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. Once this information is submitted, the server receives the data and stores it in a database.

[0164] Food data collection

[0165] Producers and distributors access the system through a management screen and input data on products with short shelf lives or off-spec vegetables and fruits. This includes the type of food, quantity, expiration date, and price. The data is sent to the server and added to the database.

[0166] Food and recipe suggestions

[0167] Users log in to the system from their devices and request suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The list of selected foods and recipes is sent to the user's device for review. For example, a user with a dairy allergy who buys a lot of vegetables might be suggested a dairy-free "sweet potato vegan curry."

[0168] Order Confirmation

[0169] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which provides the order data to the distributor. The user receives an order confirmation email.

[0170] Food delivery and pickup

[0171] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's address, and the user receives the delivered food. The user receives a delivery completion notification on their device.

[0172] Use of smart devices

[0173] This system efficiently acquires and provides food data and recipe information by utilizing smart devices. These include smartphones, smart glasses, head-mounted displays, and robots. These devices perform functions such as acquiring additional user information, presenting suggestions, and even processing orders.

[0174] Prompt statements as concrete examples

[0175] "User Profile: Name: Taro Yamada, Address: Minato-ku, Tokyo, Contact: 090-1234-5678, Allergies: Dairy, Favorite Foods: Vegetables. Past Purchase History: Cabbage, Sweet Potatoes. Available Food List: Non-standard Cabbage, Non-standard Sweet Potatoes. Suggested Recipes: Can be cooked without using dairy. Please generate suggested recipes."

[0176] In this way, the system of the present invention realizes a process that utilizes the user's basic information and food data to propose, order, and deliver optimal food and recipes. This is expected to reduce food waste and improve user convenience.

[0177] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0178] Step 1:

[0179] Users access the system from their home devices (smartphones or PCs) and enter basic information (name, address, contact information, allergy information, food preferences, and past purchase history). The entered data is sent to the server and stored in the database. The input here is the user's basic information, and the output is data to which a user ID is assigned.

[0180] Step 2:

[0181] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. The data is sent to the server and added to the database. The input here is detailed product data, and the output is organized and managed food data.

[0182] Step 3:

[0183] The user logs into the system from their device and requests suggestions. The server uses the user's past purchase history, allergy information, and food preferences to select the most suitable foods and recipes using an AI model. A list of selected foods and recipes is sent to the user's device. The inputs here are user profile information and food data, and the output is a list of suggested foods and recipes.

[0184] Step 4:

[0185] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order data is sent to the server, which provides the order details to the distributor. The server generates an order confirmation email and sends it to the user's email address. The input here is the user's selected data, and the output is the confirmed order data and confirmation email.

[0186] Step 5:

[0187] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are delivered to the user's address. Upon completion of delivery, the server generates a delivery completion notification and sends it to the user's terminal. The input here is the order data, and the output is the delivered food items and the delivery completion notification.

[0188] Step 6:

[0189] Smart devices (smartphones, smart glasses, head-mounted displays, robots, etc.) acquire and present user information and suggestions. Additional user information is acquired, and suggestions are effectively displayed to the user. The input here is data acquired by the smart device, and the output is optimal food and recipe information provided to the user.

[0190] The above describes the specific operation of each program processing step in the system that implements the application example.

[0191] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0192] This invention is a system that reduces food waste in homes and businesses, allowing consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to suggest food and recipes that respond to the user's emotions.

[0193] Overall system flow

[0194] 1. User registration and information gathering

[0195] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[0196] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[0197] 2. Food data collection

[0198] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[0199] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[0200] 3. Emotion recognition by an emotion engine

[0201] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using cameras and microphones.

[0202] The emotion engine analyzes this data and recognizes the emotions the user is currently feeling (e.g., stress, joy, excitement, etc.).

[0203] 4. Food and recipe suggestions

[0204] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and sentiment data obtained from the sentiment engine.

[0205] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[0206] For example, if the emotion engine detects that a user is experiencing work-related stress, the server will suggest a recipe using ingredients with relaxing properties (e.g., herbal tea and a refreshing salad). Also, if the user lives alone and leads a busy life, the server will prioritize suggesting easy-to-prepare foods.

[0207] 5. Confirm your order

[0208] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[0209] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[0210] 6. Food delivery and pickup

[0211] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[0212] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0213] In this way, the system of the present invention efficiently collects and manages food data and emotional data, and reduces food waste in households by suggesting the most suitable foods and recipes for the user. Furthermore, by providing suggestions that respond to the user's emotions, it offers a more personalized service and improves the user experience.

[0214] The following describes the processing flow.

[0215] Step 1:

[0216] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0217] Step 2:

[0218] When a user submits their basic information, the server receives this information and stores it in a database. The server assigns a unique user ID to each user and uses it to manage future transactions.

[0219] Step 3:

[0220] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[0221] Step 4:

[0222] Food information entered by producers and distributors is sent to the server, which adds, organizes, and manages it in a database. This generates a list of food products to be offered to users.

[0223] Step 5:

[0224] Users log in to the system using their devices and request food and recipe suggestions.

[0225] Step 6:

[0226] The user answers interactive questions to provide emotional data, or their facial expressions and voice tone are analyzed using a camera and microphone. The emotion engine then generates the user's emotional data.

[0227] Step 7:

[0228] The emotion engine generates emotional data, which the server receives and combines with the user's purchase history, allergy information, and food preferences to select the most suitable foods and recipes.

[0229] Step 8:

[0230] The server sends a list of selected foods and recipes to the user's device. The user reviews the suggestions, selects their favorite foods and recipes, and confirms their order.

[0231] Step 9:

[0232] Once the user confirms their order, the server receives the order details and automatically sends the order data to the distributor. The server then generates an order confirmation email and sends it to the user's email address.

[0233] Step 10:

[0234] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[0235] Step 11:

[0236] The user receives the delivered food and enjoys cooking it according to the set recipe. After delivery is complete, the server generates a delivery completion notification and sends it to the user's device.

[0237] As a concrete example, consider a situation where a user is busy and stressed. The emotion engine recognizes this stress, and the server suggests a recipe for a relaxing herbal tea and a light snack. Furthermore, if the user has a dairy allergy, that information is also taken into consideration in the suggestions. This allows the user to receive foods and recipes that are best suited to their situation, reducing food waste while simultaneously improving the user experience.

[0238] (Example 2)

[0239] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0240] Food waste has become a significant social problem in both households and businesses. In particular, poor management of expiration dates and food waste are contributing factors. Furthermore, consumers face the challenge of selecting foods and recipes that suit their health and emotional needs. Traditional systems lack mechanisms for users to select foods and recipes based on their emotions, resulting in a lack of personalized suggestions and making it difficult to increase user satisfaction.

[0241] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0242] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes the user's emotions. This makes it possible to suggest personalized food and recipes that are tailored to the user's individual health condition and emotions.

[0243] A "user" is an individual or legal entity that utilizes the system and is the entity that provides basic information, food preferences, emotional data, and so on.

[0244] "Basic information" refers to data entered by the user, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[0245] "Food data" refers to information such as the type, quantity, expiration date, and price of food products entered by producers and distributors.

[0246] "Means of suggestion" refers to the methods and processes by which the server selects and suggests the most suitable food and recipes based on the user's basic information and sentiment data.

[0247] "Method of ordering" refers to the method or process by which users review suggested food items and recipes and confirm their orders through the system.

[0248] "Means of delivery" refers to the methods and processes by which distributors prepare food based on order data from a server and deliver it to the user's address.

[0249] An "emotion engine" refers to a technology that collects and analyzes emotional data using interactive questions, cameras, microphones, etc., in order to recognize the user's emotions.

[0250] A "database" is a collection of information managed by a server, and refers to a system for organizing and storing basic user information and food data.

[0251] "Personalized suggestions" refer to food and recipe suggestions that are customized based on the user's individual health status, emotions, preferences, and other factors.

[0252] This invention is a system that reduces food waste in homes and businesses, bringing benefits to consumers, producers, and distributors alike. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, means for delivering ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes user emotions.

[0253] System Overview

[0254] User registration and information gathering

[0255] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form. This information is then sent to the server, and a unique ID is generated for each user. For example, users may enter information on how to reduce stress into the registration form. This data is received by the server and stored in a database.

[0256] Food data collection

[0257] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server, where it is organized and stored in a database. The server lists the food data and manages it so that users can select from it.

[0258] Emotion recognition by an emotion engine

[0259] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using the camera and microphone. An emotion engine analyzes this data to recognize the emotions the user is currently feeling (stress, joy, excitement, etc.). This makes it possible to understand the user's real-time emotional state.

[0260] Food and recipe suggestions

[0261] When a user logs into the system and requests food and recipe suggestions, the server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and emotional data. The selected list is sent to the user's device, where the user can visually review the suggestions. For example, if the emotional engine detects that the user is stressed at work, the server will suggest a recipe using ingredients with relaxing effects (e.g., herbal tea and a refreshing salad).

[0262] User orders and food delivery

[0263] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor. The distributor receives the order data from the server, prepares the necessary food items, and delivers them to the user's address. After receiving the food items, the user enjoys cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0264] This allows the entire system to work together, enabling efficient reduction of food waste while individually personalizing each user's diet.

[0265] Example prompt statements

[0266] "Based on the basic information registered by the user, use an emotion engine to recognize the user's current emotions and generate food and recipe suggestions that correspond to those emotions. For example, if the user is feeling stressed, the goal is to suggest foods and recipes that have a relaxing effect."

[0267] Thus, advanced, personalized food recommendation systems that integrate with an emotion engine are expected to make a significant contribution to reducing food waste in homes and businesses.

[0268] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0269] Step 1: User registration and information gathering

[0270] Users access the system using a home device (smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form.

[0271] Input: Basic information entered by the user.

[0272] The device sends this information to the server.

[0273] The server stores the received information in a database and assigns a unique user ID to each user.

[0274] Output: User information and a unique user ID stored in the database.

[0275] Step 2: Food data collection

[0276] Producers and distributors access the system using management terminals and input food data (type, quantity, expiration date, price, etc.).

[0277] Input: Food data entered by producers and distributors.

[0278] The terminal sends this information to the server.

[0279] The server adds the received information to the database and organizes it while maintaining consistency with the existing data.

[0280] Output: Food data added to and updated in the database.

[0281] Step 3: Emotion recognition by the emotion engine

[0282] The user answers interactive questions through the terminal or uses the camera and microphone to analyze facial expressions and voice tones.

[0283] Input: User's answer data, camera video, microphone audio.

[0284] The terminal sends this information to the server.

[0285] The server analyzes the received data using the emotion engine and recognizes the user's emotional state.

[0286] Output: User's emotional state data (e.g., stress, joy, excitement).

[0287] Step 4: Food and recipe recommendations

[0288] The user logs in to the system using the terminal and requests food and recipe recommendations.

[0289] Input: User's login information, recommendation request.

[0290] The terminal sends the request to the server.

[0291] The server analyzes the user's purchase history, allergy information, favorite and disliked ingredient information, and emotion data to select the optimal food and recipes.

[0292] Output: A list of selected foods and recipes.

[0293] The server sends the selection result to the user's terminal.

[0294] Step 5: Confirmation of Order

[0295] The user checks the proposed foods and recipes on the terminal and presses the order button to confirm the order.

[0296] Input: Foods and recipes selected by the user.

[0297] The terminal sends the order data to the server.

[0298] The server accepts the order data and records it in the database.

[0299] The server performs processing to provide the order data to the distributor.

[0300] Output: Order confirmation notice, order data transmitted to the distributor.

[0301] The server generates a confirmation email and sends it to the user's email address.

[0302] Step 6: Delivery and Receipt of Food

[0303] The distributor prepares the food based on the order data received from the server.

[0304] Input: Order data received from the server.

[0305] The distributor delivers the food to the user's address.

[0306] Output: Delivered food.

[0307] The user receives the food and enjoys cooking using the recipe.

[0308] The server generates a delivery completion notification and sends it to the user's device.

[0309] (Application Example 2)

[0310] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0311] Traditional food delivery systems primarily suggested food items and recipes based on the user's basic information and past transaction history. However, these systems did not consider the user's emotions, meaning the suggestions offered were sometimes unsuitable for the user's current mood or situation. This resulted in a poor user experience and hindered the effective reduction of food waste.

[0312] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for collecting user emotion data using a camera and microphone, means for suggesting food and recipes based on the user's emotion data, and means for notifying the user when delivery is complete. This makes it possible to suggest optimal food and recipes according to the user's emotions, improving the user experience and reducing food waste.

[0313] "Means for users to input basic information" refers to technical means that provide an interface for users to input information such as their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0314] "Means of collecting food data" refers to technical means for producers and distributors to input data on products with short shelf lives or substandard vegetables and fruits, and to manage and store this data.

[0315] "Means for suggesting food and recipes based on user information" refers to technical means for selecting and suggesting the most suitable food and recipes based on the user's basic information and past purchase history that has been collected.

[0316] "Means for users to select and order food and recipes" refers to technical means that provide an interface for users to review a list of suggested food and recipes, make selections, and confirm their orders.

[0317] "Means of delivering ordered food" refers to the technical means by which a distributor prepares the food ordered by a user and delivers it to the user's address.

[0318] "Means for collecting user emotional data using a camera and microphone" refers to technical means that use a camera and microphone to collect emotional data in order to analyze the user's facial expressions and tone of voice.

[0319] "Means for suggesting food and recipes based on user emotional data" refers to technical means for analyzing collected emotional data and suggesting food and recipes that are best suited to the user's current emotional state.

[0320] "Means of notifying the user upon completion of delivery" refers to technical means of sending a notification to the user's device when the food has been delivered, informing them of the completion of the delivery.

[0321] This invention provides a food delivery system that analyzes user emotions and suggests appropriate food items and recipes. This system consists of the following main hardware and software components.

[0322] First, users access the system using a home device such as a smartphone and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This information is stored in RDS (Relational Database Service) on Amazon Web Services (AWS®).

[0323] Next, food data is entered by producers and distributors. This food data is stored in an AWS DynamoDB database and includes information such as type, quantity, expiration date, and price. This allows the system to organize and manage up-to-date food information.

[0324] Furthermore, this system includes an emotion engine that uses the smartphone's camera and microphone to collect the user's facial expressions and voice tone, and obtains emotion data. This data is processed in real time on AWS Lambda and the user's emotions are analyzed using the OpenAI® GPT-4® API.

[0325] When a user logs into the system and requests food and recipe suggestions, the server first accesses the user's basic information and sentiment data. Based on this, it uses a GPT-4 model to select and suggest the most suitable foods and recipes. Specifically, it inputs prompt statements like the following into the generating AI model:

[0326] User information: {Name: Tanaka, Allergy: Nuts, Favorite food: Fish, Stress level: High}

[0327] Emotional data: {stress}

[0328] Please generate the suggested recipe.

[0329] The generated list of food items and recipes is sent to the user's device. The user reviews this list, selects the food items and recipes as needed, and confirms the order. The order data is sent to the distributor using AWS SNS (Simple Notification Service), and the appropriate food items are prepared and delivered to the user's address. Once delivery is complete, the server sends a notification to the user's device informing them that the delivery is complete.

[0330] In this way, by utilizing user sentiment data to suggest food and recipes and providing optimal delivery services, it is possible to create a better user experience and contribute to reducing food waste.

[0331] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0332] Step 1:

[0333] Users access the system using their devices and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This input data is sent to a server, which extracts important information from the received data and stores it in Amazon Web Services (AWS) RDS (Relational Database Service). This allows the data to be managed based on the user's unique identification code.

[0334] Step 2:

[0335] Producers and distributors access the system through a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to a server, which adds, organizes, and manages the received data in an AWS DynamoDB database. This ensures that the latest food information is always updated and used to generate food lists for users.

[0336] Step 3:

[0337] The user interacts with the device to answer interactive questions and uses the camera and microphone to collect facial expressions and voice tone. The server sends this input data to AWS Lambda, where it performs sentiment analysis using the OpenAI GPT-4 API. This process identifies the emotions the user is currently experiencing (e.g., stress, joy, excitement), and this data is stored on the server.

[0338] Step 4:

[0339] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's basic information, allergy information, food preferences, past purchase history, and sentiment data. This selection uses a generative AI model powered by the OpenAI GPT-4 API, which generates prompt messages like the following:

[0340] User information: {Name: User X, Allergies: Nuts, Favorite food: Fish, Stress level: High}

[0341] Emotional data: {stress}

[0342] Please generate the suggested recipe.

[0343] A list of generated foods and recipes is sent from the server to the user's terminal.

[0344] Step 5:

[0345] The user reviews a list of suggested foods and recipes and selects them as needed. Once the user confirms their selection, the data is sent to the server and notified to the distributor via AWS SNS (Simple Notification Service).

[0346] Step 6:

[0347] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's registered address. Once delivery is complete, the server generates a delivery completion notification and sends it to the user's device. This allows the user to check the delivery progress in real time.

[0348] Through these steps, personalized food and recipe suggestions and deliveries are realized by leveraging user sentiment data.

[0349] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0350] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0351] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0352] [Second Embodiment]

[0353] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0354] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0355] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0356] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0357] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0358] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0359] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0360] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0361] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0362] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0363] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0364] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0365] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food.

[0366] Overall system flow

[0367] 1. User registration and information gathering

[0368] Users access the Ecolicious system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[0369] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[0370] 2. Food data collection

[0371] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[0372] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[0373] 3. Food and recipe suggestions

[0374] The user logs into the system from their device and requests suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences.

[0375] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[0376] As a concrete example, consider a case where the user is a housewife with a dairy allergy. We know that the user has purchased a lot of vegetables in the past. Based on this information, the server suggests a dairy-free recipe using off-grade cabbage and sweet potatoes: "Sweet Potato Vegan Curry."

[0377] 4. Confirm your order

[0378] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[0379] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[0380] 5. Food delivery and pickup

[0381] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[0382] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0383] In this way, the system of the present invention efficiently collects and manages food data and proposes optimal foods and recipes for users, thereby reducing food waste in households. Furthermore, it enables producers and distributors to improve the efficiency of inventory management and sales, thus minimizing overall resource waste.

[0384] The following describes the processing flow.

[0385] Step 1:

[0386] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0387] Step 2:

[0388] When a user submits their basic information, the server receives it and stores it in the database. It also automatically generates a user ID and links it to each piece of information.

[0389] Step 3:

[0390] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[0391] Step 4:

[0392] Food information entered by producers and distributors is sent to the server, which then adds, organizes, and manages this information in a database.

[0393] Step 5:

[0394] Users log in to the system from their devices and request food and recipe suggestions.

[0395] Step 6:

[0396] The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, and food preferences.

[0397] Step 7:

[0398] The server sends a list of selected foods and recipes to the user's device. The user can then review the suggestions.

[0399] Step 8:

[0400] Users review the suggestions on their devices, select their favorite foods and recipes, and confirm their order.

[0401] Step 9:

[0402] Once a user confirms an order, the server receives the order details and automatically sends the order data to the distributor.

[0403] Step 10:

[0404] The server generates an order confirmation email and sends it to the user's email address.

[0405] Step 11:

[0406] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[0407] Step 12:

[0408] The user receives the delivered food. The server generates a delivery completion notification and sends it to the user's device.

[0409] In this way, the Ecolicious system can function efficiently and reduce food waste.

[0410] (Example 1)

[0411] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0412] In modern society, food waste in homes and businesses has become a serious problem. Furthermore, consumers are required to make food choices based on their preferences and allergy information, necessitating the provision of appropriate information to support this. Producers and distributors are also required to improve the efficiency of inventory management and sales, but the current system makes it difficult to do so effectively.

[0413] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0414] This invention includes a server that receives data entered by a user, stores it in a database, and assigns a unique ID to each user; a server that organizes and manages food data entered by producers and distributors and generates a list to provide to the user; and a server that selects and proposes optimal foods and recipes to the user based on the user's past purchase history, allergy information, and food preferences. This enables a reduction in food waste in households and businesses, food selection that meets the diverse needs of consumers, and improved inventory management and sales efficiency for producers and distributors.

[0415] A "user" is an individual or group that accesses the system using a home terminal and enters basic information and preferences regarding food.

[0416] A "server" is a central processing unit that receives data transmitted from users, producers, and distributors, stores, organizes, and analyzes it, and provides the necessary information to various stakeholders.

[0417] A "terminal" is an input device used by a user to access a system and enter information, and specifically refers to devices such as smartphones and personal computers.

[0418] "Basic information" refers to user-specific information that users enter into the system, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[0419] "Food data" refers to detailed information about food products, such as expiration dates, types, quantities, and prices, that producers and distributors enter into the system.

[0420] A "database" is a collection of information that is systematically stored and managed to allow for easy searching and access of basic user information and food data.

[0421] A "User ID" is a unique identifier assigned by the server to each user, and is an identification number used to manage user information and transactions.

[0422] "Suggestion" refers to the server selecting and presenting the most suitable foods and recipes to the user based on their past purchase history, allergy information, and food preferences.

[0423] "Order data" refers to information about the food items and recipes selected by the user, along with their quantities, which is received, processed, and provided to distributors by the server.

[0424] A "confirmation email" is a purchase confirmation notification sent from the server to the user's email address after the user has confirmed their order.

[0425] A "food list" is a list of selectable foods that the server provides to the user based on collected food data.

[0426] A "notification" is a message generated by a system to convey important information to a user or relevant party.

[0427] Modes for carrying out the invention

[0428] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The following describes in detail specific embodiments for carrying out this invention.

[0429] System Overview

[0430] The system mainly consists of the following elements:

[0431] 1. Means (terminals) by which the user enters basic information.

[0432] 2. Means of collecting food data (server and terminal)

[0433] 3. Means (server) for suggesting food and recipes based on user information.

[0434] 4. A means (terminal) for users to select and order food and recipes.

[0435] 5. Means of delivering ordered food products (distributors)

[0436] Hardware and software

[0437] User side

[0438] Users access the system using their home or company devices (e.g., smartphones, tablets, PCs, etc.). They use a browser or dedicated application running on these devices to enter basic information and food preferences.

[0439] Server side

[0440] The server receives, stores, organizes, and analyzes data sent from users, producers, and distributors. Specifically, the following software can be used:

[0441] Database management systems (e.g., MySQL, PostgreSQL)

[0442] Server-side scripts (e.g., PHP, Node.js)

[0443] Data analysis tools (e.g., Python, Apache Spark)

[0444] This system also utilizes a generative AI model, which allows it to suggest optimal foods and recipes based on the user's purchase history, preferences, and allergy information.

[0445] Program processing and specific examples

[0446] 1. User registration and information gathering

[0447] Users access the system's registration form using a terminal and enter information such as their name, address, contact information, allergy information, food preferences, and past purchase history. The server receives this information, stores it in a database, and assigns a unique user ID to each user.

[0448] 2. Collection of food data

[0449] Producers and distributors use terminals to input data on products with short shelf lives or substandard vegetables and fruits from a management screen. The server receives this data, organizes it, and stores it in a database.

[0450] 3. Food and recipe suggestions

[0451] The server uses a generative AI model to select the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The selected list of suggestions is sent to the user's device for review.

[0452] Specific example: Suppose the user is a housewife with a dairy allergy and has a history of purchasing a lot of vegetables. Based on this information, the server suggests a dairy-free "sweet potato vegan curry" recipe and suggests off-spec cabbage and sweet potatoes.

[0453] The following is an example of a prompt message for a generative AI model:

[0454] "We are designing a system to reduce food waste in homes and businesses. We're considering a user who is a housewife with a dairy allergy and who buys a lot of vegetables. Please design a process that suggests the most suitable foods and recipes for this user."

[0455] 4. Order Confirmation and Delivery

[0456] Once the user reviews the suggested food items and recipes and confirms their order, the server processes the order data and provides it to the distributor. The server also generates a confirmation email and sends it to the user's email address. The distributor prepares the food based on the order data received from the server and delivers it to the user's address.

[0457] 5. Notification of delivery completion

[0458] Upon completion of delivery, the distributor updates the status through the system, and the server generates and sends a delivery completion notification to the user. The user can then receive the delivery completion notification on their device.

[0459] As described above, this system efficiently collects and manages food data and suggests optimal foods and recipes to users, thereby reducing food waste in households and businesses and providing benefits to consumers, producers, and distributors alike.

[0460] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0461] Step 1:

[0462] Users access the system from their home devices (smartphones or PCs) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. The entered data is sent to the server when the user presses the "Submit" button. The server validates the received input data and saves it to the database in the appropriate format. As output, a unique user ID is generated for the user, and a registration confirmation screen is displayed on the device.

[0463] Step 2:

[0464] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server by pressing the "Submit" button. The server validates the received food data and adds it to the database in the appropriate format. As output, the food list is updated and the correct data is reflected on the management screen.

[0465] Step 3:

[0466] The user logs into the system using their device and requests suggestions. The server queries the user's past purchase history, allergy information, and food preferences, and sends this information to a generative AI model. The generative AI model processes this data and selects the most suitable foods and recipes. As output, the server sends a list of selected foods and recipes to the user's device, allowing the user to review the suggestion list.

[0467] Step 4:

[0468] The user reviews the suggested food items and recipes and presses the "Confirm Order" button on their terminal. The order data is sent to the server. The server validates the order data, performs the necessary processing, and provides it to the distributor. As output, the server generates a confirmation email and sends it to the user's email address, and the distributor is provided with the necessary order information.

[0469] Step 5:

[0470] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are then delivered to the user's address. Specifically, the distributor's logistics system takes in the order data and calculates the optimal delivery route. As an output, the delivery schedule is finalized, and the user is notified of the delivery date.

[0471] Step 6:

[0472] The user receives the delivered food and cooks it using the recipe. Upon completion of delivery, the distributor sends a delivery completion status to the server. The server receives this information, generates a delivery completion notification, and sends it to the user's terminal. As output, the user receives the delivery completion notification, and the system records that all processing is complete.

[0473] (Application Example 1)

[0474] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0475] Existing food delivery systems lack effective means to reduce food waste, and are particularly hesitant to utilize foods with short shelf lives or those that do not meet specifications. Furthermore, they are insufficient in optimizing delivery based on user allergy information and preferences. In addition, the delivery system for ordered foods lacks efficiency, compromising user convenience. To address these challenges, more advanced information processing and the use of smart devices are necessary.

[0476] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0477] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. This makes it possible to reduce food waste and improve user convenience.

[0478] A "user" is an individual or legal entity that uses the system to request and order food and recipes.

[0479] "Basic information" refers to information such as the user's name, address, contact information, allergy information, preferred foods, and past purchase history.

[0480] "Food data" refers to information such as the type, quantity, expiration date, and price of food products provided by producers and distributors.

[0481] The "suggestion method" refers to a system function that selects the most suitable food and recipe based on user information and presents them to the user.

[0482] "Ordering method" refers to a system function that allows users to select selected food items and recipes and confirm their order.

[0483] "Delivery method" refers to the service or function used to deliver ordered food items to the address specified by the user.

[0484] A "smart device" is a device that connects to the internet and provides or retrieves information, such as a smartphone, smart glasses, a head-mounted display, or a robot.

[0485] A "database" is a recording device or a system that includes a recording device for organizing and managing information.

[0486] "Reducing food waste" refers to reducing the amount of food that is wasted by offering and delivering food that is nearing its expiration date or that does not meet standard specifications to customers.

[0487] "User information" refers to information that includes basic information and additional information provided by smart devices.

[0488] The system for realizing this invention includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. Specific embodiments are described below.

[0489] User registration and information gathering

[0490] Users access the system from a home device (e.g., a smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. Once this information is submitted, the server receives the data and stores it in a database.

[0491] Food data collection

[0492] Producers and distributors access the system through a management screen and input data on products with short shelf lives or off-spec vegetables and fruits. This includes the type of food, quantity, expiration date, and price. The data is sent to the server and added to the database.

[0493] Food and recipe suggestions

[0494] Users log in to the system from their devices and request suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The list of selected foods and recipes is sent to the user's device for review. For example, a user with a dairy allergy who buys a lot of vegetables might be suggested a dairy-free "sweet potato vegan curry."

[0495] Order Confirmation

[0496] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which provides the order data to the distributor. The user receives an order confirmation email.

[0497] Food delivery and pickup

[0498] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's address, and the user receives the delivered food. The user receives a delivery completion notification on their device.

[0499] Use of smart devices

[0500] This system efficiently acquires and provides food data and recipe information by utilizing smart devices. These include smartphones, smart glasses, head-mounted displays, and robots. These devices perform functions such as acquiring additional user information, presenting suggestions, and even processing orders.

[0501] Prompt statements as concrete examples

[0502] "User Profile: Name: Taro Yamada, Address: Minato-ku, Tokyo, Contact: 090-1234-5678, Allergies: Dairy, Favorite Foods: Vegetables. Past Purchase History: Cabbage, Sweet Potatoes. Available Food List: Non-standard Cabbage, Non-standard Sweet Potatoes. Suggested Recipes: Can be cooked without using dairy. Please generate suggested recipes."

[0503] In this way, the system of the present invention realizes a process that utilizes the user's basic information and food data to propose, order, and deliver optimal food and recipes. This is expected to reduce food waste and improve user convenience.

[0504] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0505] Step 1:

[0506] Users access the system from their home devices (smartphones or PCs) and enter basic information (name, address, contact information, allergy information, food preferences, and past purchase history). The entered data is sent to the server and stored in the database. The input here is the user's basic information, and the output is data to which a user ID is assigned.

[0507] Step 2:

[0508] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. The data is sent to the server and added to the database. The input here is detailed product data, and the output is organized and managed food data.

[0509] Step 3:

[0510] The user logs into the system from their device and requests suggestions. The server uses the user's past purchase history, allergy information, and food preferences to select the most suitable foods and recipes using an AI model. A list of selected foods and recipes is sent to the user's device. The inputs here are user profile information and food data, and the output is a list of suggested foods and recipes.

[0511] Step 4:

[0512] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order data is sent to the server, which provides the order details to the distributor. The server generates an order confirmation email and sends it to the user's email address. The input here is the user's selected data, and the output is the confirmed order data and confirmation email.

[0513] Step 5:

[0514] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are delivered to the user's address. Upon completion of delivery, the server generates a delivery completion notification and sends it to the user's terminal. The input here is the order data, and the output is the delivered food items and the delivery completion notification.

[0515] Step 6:

[0516] Smart devices (smartphones, smart glasses, head-mounted displays, robots, etc.) acquire and present user information and suggestions. Additional user information is acquired, and suggestions are effectively displayed to the user. The input here is data acquired by the smart device, and the output is optimal food and recipe information provided to the user.

[0517] The above describes the specific operation of each program processing step in the system that implements the application example.

[0518] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0519] This invention is a system that reduces food waste in homes and businesses, allowing consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to suggest food and recipes that respond to the user's emotions.

[0520] Overall system flow

[0521] 1. User registration and information gathering

[0522] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[0523] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[0524] 2. Food data collection

[0525] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[0526] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[0527] 3. Emotion recognition by an emotion engine

[0528] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using cameras and microphones.

[0529] The emotion engine analyzes this data and recognizes the emotions the user is currently feeling (e.g., stress, joy, excitement, etc.).

[0530] 4. Food and recipe suggestions

[0531] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and sentiment data obtained from the sentiment engine.

[0532] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[0533] For example, if the emotion engine detects that a user is experiencing work-related stress, the server will suggest a recipe using ingredients with relaxing properties (e.g., herbal tea and a refreshing salad). Also, if the user lives alone and leads a busy life, the server will prioritize suggesting easy-to-prepare foods.

[0534] 5. Confirm your order

[0535] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[0536] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[0537] 6. Food delivery and pickup

[0538] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[0539] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0540] In this way, the system of the present invention efficiently collects and manages food data and emotional data, and reduces food waste in households by suggesting the most suitable foods and recipes for the user. Furthermore, by providing suggestions that respond to the user's emotions, it offers a more personalized service and improves the user experience.

[0541] The following describes the processing flow.

[0542] Step 1:

[0543] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0544] Step 2:

[0545] When a user submits their basic information, the server receives this information and stores it in a database. The server assigns a unique user ID to each user and uses it to manage future transactions.

[0546] Step 3:

[0547] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[0548] Step 4:

[0549] Food information entered by producers and distributors is sent to the server, which adds, organizes, and manages it in a database. This generates a list of food products to be offered to users.

[0550] Step 5:

[0551] Users log in to the system using their devices and request food and recipe suggestions.

[0552] Step 6:

[0553] The user answers interactive questions to provide emotional data, or their facial expressions and voice tone are analyzed using a camera and microphone. The emotion engine then generates the user's emotional data.

[0554] Step 7:

[0555] The emotion engine generates emotional data, which the server receives and combines with the user's purchase history, allergy information, and food preferences to select the most suitable foods and recipes.

[0556] Step 8:

[0557] The server sends a list of selected foods and recipes to the user's device. The user reviews the suggestions, selects their favorite foods and recipes, and confirms their order.

[0558] Step 9:

[0559] Once the user confirms their order, the server receives the order details and automatically sends the order data to the distributor. The server then generates an order confirmation email and sends it to the user's email address.

[0560] Step 10:

[0561] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[0562] Step 11:

[0563] The user receives the delivered food and enjoys cooking it according to the set recipe. After delivery is complete, the server generates a delivery completion notification and sends it to the user's device.

[0564] As a concrete example, consider a situation where a user is busy and stressed. The emotion engine recognizes this stress, and the server suggests a recipe for a relaxing herbal tea and a light snack. Furthermore, if the user has a dairy allergy, that information is also taken into consideration in the suggestions. This allows the user to receive foods and recipes that are best suited to their situation, reducing food waste while simultaneously improving the user experience.

[0565] (Example 2)

[0566] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0567] Food waste has become a significant social problem in both households and businesses. In particular, poor management of expiration dates and food waste are contributing factors. Furthermore, consumers face the challenge of selecting foods and recipes that suit their health and emotional needs. Traditional systems lack mechanisms for users to select foods and recipes based on their emotions, resulting in a lack of personalized suggestions and making it difficult to increase user satisfaction.

[0568] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0569] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes the user's emotions. This makes it possible to suggest personalized food and recipes that are tailored to the user's individual health condition and emotions.

[0570] A "user" is an individual or legal entity that utilizes the system and is the entity that provides basic information, food preferences, emotional data, and so on.

[0571] "Basic information" refers to data entered by the user, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[0572] "Food data" refers to information such as the type, quantity, expiration date, and price of food products entered by producers and distributors.

[0573] "Means of suggestion" refers to the methods and processes by which the server selects and suggests the most suitable food and recipes based on the user's basic information and sentiment data.

[0574] "Method of ordering" refers to the method or process by which users review suggested food items and recipes and confirm their orders through the system.

[0575] "Means of delivery" refers to the methods and processes by which distributors prepare food based on order data from a server and deliver it to the user's address.

[0576] An "emotion engine" refers to a technology that collects and analyzes emotional data using interactive questions, cameras, microphones, etc., in order to recognize the user's emotions.

[0577] A "database" is a collection of information managed by a server, and refers to a system for organizing and storing basic user information and food data.

[0578] "Personalized suggestions" refer to food and recipe suggestions that are customized based on the user's individual health status, emotions, preferences, and other factors.

[0579] This invention is a system that reduces food waste in homes and businesses, bringing benefits to consumers, producers, and distributors alike. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, means for delivering ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes user emotions.

[0580] System Overview

[0581] User registration and information gathering

[0582] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form. This information is then sent to the server, and a unique ID is generated for each user. For example, users may enter information on how to reduce stress into the registration form. This data is received by the server and stored in a database.

[0583] Food data collection

[0584] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server, where it is organized and stored in a database. The server lists the food data and manages it so that users can select from it.

[0585] Emotion recognition by an emotion engine

[0586] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using the camera and microphone. An emotion engine analyzes this data to recognize the emotions the user is currently feeling (stress, joy, excitement, etc.). This makes it possible to understand the user's real-time emotional state.

[0587] Food and recipe suggestions

[0588] When a user logs into the system and requests food and recipe suggestions, the server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and emotional data. The selected list is sent to the user's device, where the user can visually review the suggestions. For example, if the emotional engine detects that the user is stressed at work, the server will suggest a recipe using ingredients with relaxing effects (e.g., herbal tea and a refreshing salad).

[0589] User orders and food delivery

[0590] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor. The distributor receives the order data from the server, prepares the necessary food items, and delivers them to the user's address. After receiving the food items, the user enjoys cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0591] This allows the entire system to work together, enabling efficient reduction of food waste while individually personalizing each user's diet.

[0592] Example prompt statements

[0593] "Based on the basic information registered by the user, use an emotion engine to recognize the user's current emotions and generate food and recipe suggestions that correspond to those emotions. For example, if the user is feeling stressed, the goal is to suggest foods and recipes that have a relaxing effect."

[0594] Thus, advanced, personalized food recommendation systems that integrate with an emotion engine are expected to make a significant contribution to reducing food waste in homes and businesses.

[0595] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0596] Step 1: User registration and information gathering

[0597] Users access the system using a home device (smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form.

[0598] Input: Basic information entered by the user.

[0599] The device sends this information to the server.

[0600] The server stores the received information in a database and assigns a unique user ID to each user.

[0601] Output: User information and a unique user ID stored in the database.

[0602] Step 2: Food data collection

[0603] Producers and distributors access the system using management terminals and input food data (type, quantity, expiration date, price, etc.).

[0604] Input: Food data entered by producers and distributors.

[0605] The device sends this information to the server.

[0606] The server adds the received information to the database and organizes it while maintaining consistency with existing data.

[0607] Output: Food data added or updated in the database.

[0608] Step 3: Emotion recognition by the emotion engine

[0609] Users can answer interactive questions through their devices and have their facial expressions and voice tone analyzed using the camera and microphone.

[0610] Input: User response data, camera video, microphone audio.

[0611] The device sends this information to the server.

[0612] The server uses an emotion engine to analyze the received data and recognize the user's emotional state.

[0613] Output: User emotional state data (e.g., stress, joy, excitement).

[0614] Step 4: Food and recipe suggestions

[0615] Users log in to the system using their devices and request food and recipe suggestions.

[0616] Input: User login information, suggestion request.

[0617] The terminal sends a request to the server.

[0618] The server analyzes the user's purchase history, allergy information, food preferences, and emotional data to select the most suitable foods and recipes.

[0619] Output: A list of selected foods and recipes.

[0620] The server sends the selection results to the user's terminal.

[0621] Step 5: Confirm your order

[0622] The user reviews the suggested food items and recipes on their device and confirms their order by pressing the order button.

[0623] Input: Food and recipe selected by the user.

[0624] The terminal sends the order data to the server.

[0625] The server receives the order data and records it in the database.

[0626] The server performs processing to provide order data to distributors.

[0627] Output: Order confirmation notification, order data transmitted to distributors.

[0628] The server generates a confirmation email and sends it to the user's email address.

[0629] Step 6: Food delivery and pickup

[0630] The distributor prepares the food based on the order data received from the server.

[0631] Input: Order data received from the server.

[0632] Distributors deliver food products to users' addresses.

[0633] Output: Delivered food.

[0634] Users receive food and enjoy cooking using the recipes.

[0635] The server generates a delivery completion notification and sends it to the user's device.

[0636] (Application Example 2)

[0637] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0638] Traditional food delivery systems primarily suggested food items and recipes based on the user's basic information and past transaction history. However, these systems did not consider the user's emotions, meaning the suggestions offered were sometimes unsuitable for the user's current mood or situation. This resulted in a poor user experience and hindered the effective reduction of food waste.

[0639] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for collecting user emotion data using a camera and microphone, means for suggesting food and recipes based on the user's emotion data, and means for notifying the user when delivery is complete. This makes it possible to suggest optimal food and recipes according to the user's emotions, improving the user experience and reducing food waste.

[0640] "Means for users to input basic information" refers to technical means that provide an interface for users to input information such as their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0641] "Means of collecting food data" refers to technical means for producers and distributors to input data on products with short shelf lives or substandard vegetables and fruits, and to manage and store this data.

[0642] "Means for suggesting food and recipes based on user information" refers to technical means for selecting and suggesting the most suitable food and recipes based on the user's basic information and past purchase history that has been collected.

[0643] "Means for users to select and order food and recipes" refers to technical means that provide an interface for users to review a list of suggested food and recipes, make selections, and confirm their orders.

[0644] "Means of delivering ordered food" refers to the technical means by which a distributor prepares the food ordered by a user and delivers it to the user's address.

[0645] "Means for collecting user emotional data using a camera and microphone" refers to technical means that use a camera and microphone to collect emotional data in order to analyze the user's facial expressions and tone of voice.

[0646] "Means for suggesting food and recipes based on user emotional data" refers to technical means for analyzing collected emotional data and suggesting food and recipes that are best suited to the user's current emotional state.

[0647] "Means of notifying the user upon completion of delivery" refers to technical means of sending a notification to the user's device when the food has been delivered, informing them of the completion of the delivery.

[0648] This invention provides a food delivery system that analyzes user emotions and suggests appropriate food items and recipes. This system consists of the following main hardware and software components.

[0649] First, users access the system using a home device such as a smartphone and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This information is stored in RDS (Relational Database Service) on Amazon Web Services (AWS).

[0650] Next, food data is entered by producers and distributors. This food data is stored in an AWS DynamoDB database and includes information such as type, quantity, expiration date, and price. This allows the system to organize and manage up-to-date food information.

[0651] Furthermore, this system includes an emotion engine that uses the smartphone's camera and microphone to collect the user's facial expressions and voice tone, thereby obtaining emotion data. This data is processed in real time on AWS Lambda and the OpenAI GPT-4 API is used to analyze the user's emotions.

[0652] When a user logs into the system and requests food and recipe suggestions, the server first accesses the user's basic information and sentiment data. Based on this, it uses a GPT-4 model to select and suggest the most suitable foods and recipes. Specifically, it inputs prompt statements like the following into the generating AI model:

[0653] User information: {Name: Tanaka, Allergy: Nuts, Favorite food: Fish, Stress level: High}

[0654] Emotional data: {stress}

[0655] Please generate the suggested recipe.

[0656] The generated list of food items and recipes is sent to the user's device. The user reviews this list, selects the food items and recipes as needed, and confirms the order. The order data is sent to the distributor using AWS SNS (Simple Notification Service), and the appropriate food items are prepared and delivered to the user's address. Once delivery is complete, the server sends a notification to the user's device informing them that the delivery is complete.

[0657] In this way, by utilizing user sentiment data to suggest food and recipes and providing optimal delivery services, it is possible to create a better user experience and contribute to reducing food waste.

[0658] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0659] Step 1:

[0660] Users access the system using their devices and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This input data is sent to a server, which extracts important information from the received data and stores it in Amazon Web Services (AWS) RDS (Relational Database Service). This allows the data to be managed based on the user's unique identification code.

[0661] Step 2:

[0662] Producers and distributors access the system through a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to a server, which adds, organizes, and manages the received data in an AWS DynamoDB database. This ensures that the latest food information is always updated and used to generate food lists for users.

[0663] Step 3:

[0664] The user interacts with the device to answer interactive questions and uses the camera and microphone to collect facial expressions and voice tone. The server sends this input data to AWS Lambda, where it performs sentiment analysis using the OpenAI GPT-4 API. This process identifies the emotions the user is currently experiencing (e.g., stress, joy, excitement), and this data is stored on the server.

[0665] Step 4:

[0666] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's basic information, allergy information, food preferences, past purchase history, and sentiment data. This selection uses a generative AI model powered by the OpenAI GPT-4 API, which generates prompt messages like the following:

[0667] User information: {Name: User X, Allergies: Nuts, Favorite food: Fish, Stress level: High}

[0668] Emotional data: {stress}

[0669] Please generate the suggested recipe.

[0670] A list of generated foods and recipes is sent from the server to the user's terminal.

[0671] Step 5:

[0672] The user reviews a list of suggested foods and recipes and selects them as needed. Once the user confirms their selection, the data is sent to the server and notified to the distributor via AWS SNS (Simple Notification Service).

[0673] Step 6:

[0674] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's registered address. Once delivery is complete, the server generates a delivery completion notification and sends it to the user's device. This allows the user to check the delivery progress in real time.

[0675] Through these steps, personalized food and recipe suggestions and deliveries are realized by leveraging user sentiment data.

[0676] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0677] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0678] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0679] [Third Embodiment]

[0680] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0681] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0682] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0683] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0684] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0685] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0686] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0687] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0688] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0689] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0690] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0691] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0692] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food.

[0693] Overall system flow

[0694] 1. User registration and information gathering

[0695] Users access the Ecolicious system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[0696] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[0697] 2. Food data collection

[0698] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[0699] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[0700] 3. Food and recipe suggestions

[0701] The user logs into the system from their device and requests suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences.

[0702] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[0703] As a concrete example, consider a case where the user is a housewife with a dairy allergy. We know that the user has purchased a lot of vegetables in the past. Based on this information, the server suggests a dairy-free recipe using off-grade cabbage and sweet potatoes: "Sweet Potato Vegan Curry."

[0704] 4. Confirm your order

[0705] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[0706] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[0707] 5. Food delivery and pickup

[0708] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[0709] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0710] In this way, the system of the present invention efficiently collects and manages food data and proposes optimal foods and recipes for users, thereby reducing food waste in households. Furthermore, it enables producers and distributors to improve the efficiency of inventory management and sales, thus minimizing overall resource waste.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0714] Step 2:

[0715] When a user submits their basic information, the server receives it and stores it in the database. It also automatically generates a user ID and links it to each piece of information.

[0716] Step 3:

[0717] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[0718] Step 4:

[0719] Food information entered by producers and distributors is sent to the server, which then adds, organizes, and manages this information in a database.

[0720] Step 5:

[0721] Users log in to the system from their devices and request food and recipe suggestions.

[0722] Step 6:

[0723] The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, and food preferences.

[0724] Step 7:

[0725] The server sends a list of selected foods and recipes to the user's device. The user can then review the suggestions.

[0726] Step 8:

[0727] Users review the suggestions on their devices, select their favorite foods and recipes, and confirm their order.

[0728] Step 9:

[0729] Once a user confirms an order, the server receives the order details and automatically sends the order data to the distributor.

[0730] Step 10:

[0731] The server generates an order confirmation email and sends it to the user's email address.

[0732] Step 11:

[0733] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[0734] Step 12:

[0735] The user receives the delivered food. The server generates a delivery completion notification and sends it to the user's device.

[0736] In this way, the Ecolicious system can function efficiently and reduce food waste.

[0737] (Example 1)

[0738] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0739] In modern society, food waste in homes and businesses has become a serious problem. Furthermore, consumers are required to make food choices based on their preferences and allergy information, necessitating the provision of appropriate information to support this. Producers and distributors are also required to improve the efficiency of inventory management and sales, but the current system makes it difficult to do so effectively.

[0740] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0741] This invention includes a server that receives data entered by a user, stores it in a database, and assigns a unique ID to each user; a server that organizes and manages food data entered by producers and distributors and generates a list to provide to the user; and a server that selects and proposes optimal foods and recipes to the user based on the user's past purchase history, allergy information, and food preferences. This enables a reduction in food waste in households and businesses, food selection that meets the diverse needs of consumers, and improved inventory management and sales efficiency for producers and distributors.

[0742] A "user" is an individual or group that accesses the system using a home terminal and enters basic information and preferences regarding food.

[0743] A "server" is a central processing unit that receives data transmitted from users, producers, and distributors, stores, organizes, and analyzes it, and provides the necessary information to various stakeholders.

[0744] A "terminal" is an input device used by a user to access a system and enter information, and specifically refers to devices such as smartphones and personal computers.

[0745] "Basic information" refers to user-specific information that users enter into the system, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[0746] "Food data" refers to detailed information about food products, such as expiration dates, types, quantities, and prices, that producers and distributors enter into the system.

[0747] A "database" is a collection of information that is systematically stored and managed to allow for easy searching and access of basic user information and food data.

[0748] A "User ID" is a unique identifier assigned by the server to each user, and is an identification number used to manage user information and transactions.

[0749] "Suggestion" refers to the server selecting and presenting the most suitable foods and recipes to the user based on their past purchase history, allergy information, and food preferences.

[0750] "Order data" refers to information about the food items and recipes selected by the user, along with their quantities, which is received, processed, and provided to distributors by the server.

[0751] A "confirmation email" is a purchase confirmation notification sent from the server to the user's email address after the user has confirmed their order.

[0752] A "food list" is a list of selectable foods that the server provides to the user based on collected food data.

[0753] A "notification" is a message generated by a system to convey important information to a user or relevant party.

[0754] Modes for carrying out the invention

[0755] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The following describes in detail specific embodiments for carrying out this invention.

[0756] System Overview

[0757] The system mainly consists of the following elements:

[0758] 1. Means (terminals) by which the user enters basic information.

[0759] 2. Means of collecting food data (server and terminal)

[0760] 3. Means (server) for suggesting food and recipes based on user information.

[0761] 4. A means (terminal) for users to select and order food and recipes.

[0762] 5. Means of delivering ordered food products (distributors)

[0763] Hardware and software

[0764] User side

[0765] Users access the system using their home or company devices (e.g., smartphones, tablets, PCs, etc.). They use a browser or dedicated application running on these devices to enter basic information and food preferences.

[0766] Server side

[0767] The server receives, stores, organizes, and analyzes data sent from users, producers, and distributors. Specifically, the following software can be used:

[0768] Database management systems (e.g., MySQL, PostgreSQL)

[0769] Server-side scripts (e.g., PHP, Node.js)

[0770] Data analysis tools (e.g., Python, Apache Spark)

[0771] This system also utilizes a generative AI model, which allows it to suggest optimal foods and recipes based on the user's purchase history, preferences, and allergy information.

[0772] Program processing and specific examples

[0773] 1. User registration and information gathering

[0774] Users access the system's registration form using a terminal and enter information such as their name, address, contact information, allergy information, food preferences, and past purchase history. The server receives this information, stores it in a database, and assigns a unique user ID to each user.

[0775] 2. Collection of food data

[0776] Producers and distributors use terminals to input data on products with short shelf lives or substandard vegetables and fruits from a management screen. The server receives this data, organizes it, and stores it in a database.

[0777] 3. Food and recipe suggestions

[0778] The server uses a generative AI model to select the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The selected list of suggestions is sent to the user's device for review.

[0779] Specific example: Suppose the user is a housewife with a dairy allergy and has a history of purchasing a lot of vegetables. Based on this information, the server suggests a dairy-free "sweet potato vegan curry" recipe and suggests off-spec cabbage and sweet potatoes.

[0780] The following is an example of a prompt message for a generative AI model:

[0781] "We are designing a system to reduce food waste in homes and businesses. We're considering a user who is a housewife with a dairy allergy and who buys a lot of vegetables. Please design a process that suggests the most suitable foods and recipes for this user."

[0782] 4. Order Confirmation and Delivery

[0783] Once the user reviews the suggested food items and recipes and confirms their order, the server processes the order data and provides it to the distributor. The server also generates a confirmation email and sends it to the user's email address. The distributor prepares the food based on the order data received from the server and delivers it to the user's address.

[0784] 5. Notification of delivery completion

[0785] Upon completion of delivery, the distributor updates the status through the system, and the server generates and sends a delivery completion notification to the user. The user can then receive the delivery completion notification on their device.

[0786] As described above, this system efficiently collects and manages food data and suggests optimal foods and recipes to users, thereby reducing food waste in households and businesses and providing benefits to consumers, producers, and distributors alike.

[0787] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0788] Step 1:

[0789] Users access the system from their home devices (smartphones or PCs) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. The entered data is sent to the server when the user presses the "Submit" button. The server validates the received input data and saves it to the database in the appropriate format. As output, a unique user ID is generated for the user, and a registration confirmation screen is displayed on the device.

[0790] Step 2:

[0791] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server by pressing the "Submit" button. The server validates the received food data and adds it to the database in the appropriate format. As output, the food list is updated and the correct data is reflected on the management screen.

[0792] Step 3:

[0793] The user logs into the system using their device and requests suggestions. The server queries the user's past purchase history, allergy information, and food preferences, and sends this information to a generative AI model. The generative AI model processes this data and selects the most suitable foods and recipes. As output, the server sends a list of selected foods and recipes to the user's device, allowing the user to review the suggestion list.

[0794] Step 4:

[0795] The user reviews the suggested food items and recipes and presses the "Confirm Order" button on their terminal. The order data is sent to the server. The server validates the order data, performs the necessary processing, and provides it to the distributor. As output, the server generates a confirmation email and sends it to the user's email address, and the distributor is provided with the necessary order information.

[0796] Step 5:

[0797] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are then delivered to the user's address. Specifically, the distributor's logistics system takes in the order data and calculates the optimal delivery route. As an output, the delivery schedule is finalized, and the user is notified of the delivery date.

[0798] Step 6:

[0799] The user receives the delivered food and cooks it using the recipe. Upon completion of delivery, the distributor sends a delivery completion status to the server. The server receives this information, generates a delivery completion notification, and sends it to the user's terminal. As output, the user receives the delivery completion notification, and the system records that all processing is complete.

[0800] (Application Example 1)

[0801] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0802] Existing food delivery systems lack effective means to reduce food waste, and are particularly hesitant to utilize foods with short shelf lives or those that do not meet specifications. Furthermore, they are insufficient in optimizing delivery based on user allergy information and preferences. In addition, the delivery system for ordered foods lacks efficiency, compromising user convenience. To address these challenges, more advanced information processing and the use of smart devices are necessary.

[0803] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0804] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. This makes it possible to reduce food waste and improve user convenience.

[0805] A "user" is an individual or legal entity that uses the system to request and order food and recipes.

[0806] "Basic information" refers to information such as the user's name, address, contact information, allergy information, preferred foods, and past purchase history.

[0807] "Food data" refers to information such as the type, quantity, expiration date, and price of food products provided by producers and distributors.

[0808] The "suggestion method" refers to a system function that selects the most suitable food and recipe based on user information and presents them to the user.

[0809] "Ordering method" refers to a system function that allows users to select selected food items and recipes and confirm their order.

[0810] "Delivery method" refers to the service or function used to deliver ordered food items to the address specified by the user.

[0811] A "smart device" is a device that connects to the internet and provides or retrieves information, such as a smartphone, smart glasses, a head-mounted display, or a robot.

[0812] A "database" is a recording device or a system that includes a recording device for organizing and managing information.

[0813] "Reducing food waste" refers to reducing the amount of food that is wasted by offering and delivering food that is nearing its expiration date or that does not meet standard specifications to customers.

[0814] "User information" refers to information that includes basic information and additional information provided by smart devices.

[0815] The system for realizing this invention includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. Specific embodiments are described below.

[0816] User registration and information gathering

[0817] Users access the system from a home device (e.g., a smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. Once this information is submitted, the server receives the data and stores it in a database.

[0818] Food data collection

[0819] Producers and distributors access the system through a management screen and input data on products with short shelf lives or off-spec vegetables and fruits. This includes the type of food, quantity, expiration date, and price. The data is sent to the server and added to the database.

[0820] Food and recipe suggestions

[0821] Users log in to the system from their devices and request suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The list of selected foods and recipes is sent to the user's device for review. For example, a user with a dairy allergy who buys a lot of vegetables might be suggested a dairy-free "sweet potato vegan curry."

[0822] Order Confirmation

[0823] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which provides the order data to the distributor. The user receives an order confirmation email.

[0824] Food delivery and pickup

[0825] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's address, and the user receives the delivered food. The user receives a delivery completion notification on their device.

[0826] Use of smart devices

[0827] This system efficiently acquires and provides food data and recipe information by utilizing smart devices. These include smartphones, smart glasses, head-mounted displays, and robots. These devices perform functions such as acquiring additional user information, presenting suggestions, and even processing orders.

[0828] Prompt statements as concrete examples

[0829] "User Profile: Name: Taro Yamada, Address: Minato-ku, Tokyo, Contact: 090-1234-5678, Allergies: Dairy, Favorite Foods: Vegetables. Past Purchase History: Cabbage, Sweet Potatoes. Available Food List: Non-standard Cabbage, Non-standard Sweet Potatoes. Suggested Recipes: Can be cooked without using dairy. Please generate suggested recipes."

[0830] In this way, the system of the present invention realizes a process that utilizes the user's basic information and food data to propose, order, and deliver optimal food and recipes. This is expected to reduce food waste and improve user convenience.

[0831] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0832] Step 1:

[0833] Users access the system from their home devices (smartphones or PCs) and enter basic information (name, address, contact information, allergy information, food preferences, and past purchase history). The entered data is sent to the server and stored in the database. The input here is the user's basic information, and the output is data to which a user ID is assigned.

[0834] Step 2:

[0835] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. The data is sent to the server and added to the database. The input here is detailed product data, and the output is organized and managed food data.

[0836] Step 3:

[0837] The user logs into the system from their device and requests suggestions. The server uses the user's past purchase history, allergy information, and food preferences to select the most suitable foods and recipes using an AI model. A list of selected foods and recipes is sent to the user's device. The inputs here are user profile information and food data, and the output is a list of suggested foods and recipes.

[0838] Step 4:

[0839] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order data is sent to the server, which provides the order details to the distributor. The server generates an order confirmation email and sends it to the user's email address. The input here is the user's selected data, and the output is the confirmed order data and confirmation email.

[0840] Step 5:

[0841] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are delivered to the user's address. Upon completion of delivery, the server generates a delivery completion notification and sends it to the user's terminal. The input here is the order data, and the output is the delivered food items and the delivery completion notification.

[0842] Step 6:

[0843] Smart devices (smartphones, smart glasses, head-mounted displays, robots, etc.) acquire and present user information and suggestions. Additional user information is acquired, and suggestions are effectively displayed to the user. The input here is data acquired by the smart device, and the output is optimal food and recipe information provided to the user.

[0844] The above describes the specific operation of each program processing step in the system that implements the application example.

[0845] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0846] This invention is a system that reduces food waste in homes and businesses, allowing consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to suggest food and recipes that respond to the user's emotions.

[0847] Overall system flow

[0848] 1. User registration and information gathering

[0849] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[0850] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[0851] 2. Food data collection

[0852] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[0853] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[0854] 3. Emotion recognition by an emotion engine

[0855] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using cameras and microphones.

[0856] The emotion engine analyzes this data and recognizes the emotions the user is currently feeling (e.g., stress, joy, excitement, etc.).

[0857] 4. Food and recipe suggestions

[0858] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and sentiment data obtained from the sentiment engine.

[0859] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[0860] For example, if the emotion engine detects that a user is experiencing work-related stress, the server will suggest a recipe using ingredients with relaxing properties (e.g., herbal tea and a refreshing salad). Also, if the user lives alone and leads a busy life, the server will prioritize suggesting easy-to-prepare foods.

[0861] 5. Confirm your order

[0862] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[0863] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[0864] 6. Food delivery and pickup

[0865] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[0866] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0867] In this way, the system of the present invention efficiently collects and manages food data and emotional data, and reduces food waste in households by suggesting the most suitable foods and recipes for the user. Furthermore, by providing suggestions that respond to the user's emotions, it offers a more personalized service and improves the user experience.

[0868] The following describes the processing flow.

[0869] Step 1:

[0870] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0871] Step 2:

[0872] When a user submits their basic information, the server receives this information and stores it in a database. The server assigns a unique user ID to each user and uses it to manage future transactions.

[0873] Step 3:

[0874] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[0875] Step 4:

[0876] Food information entered by producers and distributors is sent to the server, which adds, organizes, and manages it in a database. This generates a list of food products to be offered to users.

[0877] Step 5:

[0878] Users log in to the system using their devices and request food and recipe suggestions.

[0879] Step 6:

[0880] The user answers interactive questions to provide emotional data, or their facial expressions and voice tone are analyzed using a camera and microphone. The emotion engine then generates the user's emotional data.

[0881] Step 7:

[0882] The emotion engine generates emotional data, which the server receives and combines with the user's purchase history, allergy information, and food preferences to select the most suitable foods and recipes.

[0883] Step 8:

[0884] The server sends a list of selected foods and recipes to the user's device. The user reviews the suggestions, selects their favorite foods and recipes, and confirms their order.

[0885] Step 9:

[0886] Once the user confirms their order, the server receives the order details and automatically sends the order data to the distributor. The server then generates an order confirmation email and sends it to the user's email address.

[0887] Step 10:

[0888] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[0889] Step 11:

[0890] The user receives the delivered food and enjoys cooking it according to the set recipe. After delivery is complete, the server generates a delivery completion notification and sends it to the user's device.

[0891] As a concrete example, consider a situation where a user is busy and stressed. The emotion engine recognizes this stress, and the server suggests a recipe for a relaxing herbal tea and a light snack. Furthermore, if the user has a dairy allergy, that information is also taken into consideration in the suggestions. This allows the user to receive foods and recipes that are best suited to their situation, reducing food waste while simultaneously improving the user experience.

[0892] (Example 2)

[0893] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0894] Food waste has become a significant social problem in both households and businesses. In particular, poor management of expiration dates and food waste are contributing factors. Furthermore, consumers face the challenge of selecting foods and recipes that suit their health and emotional needs. Traditional systems lack mechanisms for users to select foods and recipes based on their emotions, resulting in a lack of personalized suggestions and making it difficult to increase user satisfaction.

[0895] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0896] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes the user's emotions. This makes it possible to suggest personalized food and recipes that are tailored to the user's individual health condition and emotions.

[0897] A "user" is an individual or legal entity that utilizes the system and is the entity that provides basic information, food preferences, emotional data, and so on.

[0898] "Basic information" refers to data entered by the user, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[0899] "Food data" refers to information such as the type, quantity, expiration date, and price of food products entered by producers and distributors.

[0900] "Means of suggestion" refers to the methods and processes by which the server selects and suggests the most suitable food and recipes based on the user's basic information and sentiment data.

[0901] "Method of ordering" refers to the method or process by which users review suggested food items and recipes and confirm their orders through the system.

[0902] "Means of delivery" refers to the methods and processes by which distributors prepare food based on order data from a server and deliver it to the user's address.

[0903] An "emotion engine" refers to a technology that collects and analyzes emotional data using interactive questions, cameras, microphones, etc., in order to recognize the user's emotions.

[0904] A "database" is a collection of information managed by a server, and refers to a system for organizing and storing basic user information and food data.

[0905] "Personalized suggestions" refer to food and recipe suggestions that are customized based on the user's individual health status, emotions, preferences, and other factors.

[0906] This invention is a system that reduces food waste in homes and businesses, bringing benefits to consumers, producers, and distributors alike. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, means for delivering ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes user emotions.

[0907] System Overview

[0908] User registration and information gathering

[0909] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form. This information is then sent to the server, and a unique ID is generated for each user. For example, users may enter information on how to reduce stress into the registration form. This data is received by the server and stored in a database.

[0910] Food data collection

[0911] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server, where it is organized and stored in a database. The server lists the food data and manages it so that users can select from it.

[0912] Emotion recognition by an emotion engine

[0913] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using the camera and microphone. An emotion engine analyzes this data to recognize the emotions the user is currently feeling (stress, joy, excitement, etc.). This makes it possible to understand the user's real-time emotional state.

[0914] Food and recipe suggestions

[0915] When a user logs into the system and requests food and recipe suggestions, the server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and emotional data. The selected list is sent to the user's device, where the user can visually review the suggestions. For example, if the emotional engine detects that the user is stressed at work, the server will suggest a recipe using ingredients with relaxing effects (e.g., herbal tea and a refreshing salad).

[0916] User orders and food delivery

[0917] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor. The distributor receives the order data from the server, prepares the necessary food items, and delivers them to the user's address. After receiving the food items, the user enjoys cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[0918] This allows the entire system to work together, enabling efficient reduction of food waste while individually personalizing each user's diet.

[0919] Example prompt statements

[0920] "Based on the basic information registered by the user, use an emotion engine to recognize the user's current emotions and generate food and recipe suggestions that correspond to those emotions. For example, if the user is feeling stressed, the goal is to suggest foods and recipes that have a relaxing effect."

[0921] Thus, advanced, personalized food recommendation systems that integrate with an emotion engine are expected to make a significant contribution to reducing food waste in homes and businesses.

[0922] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0923] Step 1: User registration and information gathering

[0924] Users access the system using a home device (smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form.

[0925] Input: Basic information entered by the user.

[0926] The device sends this information to the server.

[0927] The server stores the received information in a database and assigns a unique user ID to each user.

[0928] Output: User information and a unique user ID stored in the database.

[0929] Step 2: Food data collection

[0930] Producers and distributors access the system using management terminals and input food data (type, quantity, expiration date, price, etc.).

[0931] Input: Food data entered by producers and distributors.

[0932] The device sends this information to the server.

[0933] The server adds the received information to the database and organizes it while maintaining consistency with existing data.

[0934] Output: Food data added or updated in the database.

[0935] Step 3: Emotion recognition by the emotion engine

[0936] Users can answer interactive questions through their devices and have their facial expressions and voice tone analyzed using the camera and microphone.

[0937] Input: User response data, camera video, microphone audio.

[0938] The device sends this information to the server.

[0939] The server uses an emotion engine to analyze the received data and recognize the user's emotional state.

[0940] Output: User emotional state data (e.g., stress, joy, excitement).

[0941] Step 4: Food and recipe suggestions

[0942] Users log in to the system using their devices and request food and recipe suggestions.

[0943] Input: User login information, suggestion request.

[0944] The terminal sends a request to the server.

[0945] The server analyzes the user's purchase history, allergy information, food preferences, and emotional data to select the most suitable foods and recipes.

[0946] Output: A list of selected foods and recipes.

[0947] The server sends the selection results to the user's terminal.

[0948] Step 5: Confirm your order

[0949] The user reviews the suggested food items and recipes on their device and confirms their order by pressing the order button.

[0950] Input: Food and recipe selected by the user.

[0951] The terminal sends the order data to the server.

[0952] The server receives the order data and records it in the database.

[0953] The server performs processing to provide order data to distributors.

[0954] Output: Order confirmation notification, order data transmitted to distributors.

[0955] The server generates a confirmation email and sends it to the user's email address.

[0956] Step 6: Food delivery and pickup

[0957] The distributor prepares the food based on the order data received from the server.

[0958] Input: Order data received from the server.

[0959] Distributors deliver food products to users' addresses.

[0960] Output: Delivered food.

[0961] Users receive food and enjoy cooking using the recipes.

[0962] The server generates a delivery completion notification and sends it to the user's device.

[0963] (Application Example 2)

[0964] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0965] Traditional food delivery systems primarily suggested food items and recipes based on the user's basic information and past transaction history. However, these systems did not consider the user's emotions, meaning the suggestions offered were sometimes unsuitable for the user's current mood or situation. This resulted in a poor user experience and hindered the effective reduction of food waste.

[0966] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for collecting user emotion data using a camera and microphone, means for suggesting food and recipes based on the user's emotion data, and means for notifying the user when delivery is complete. This makes it possible to suggest optimal food and recipes according to the user's emotions, improving the user experience and reducing food waste.

[0967] "Means for users to input basic information" refers to technical means that provide an interface for users to input information such as their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[0968] "Means of collecting food data" refers to technical means for producers and distributors to input data on products with short shelf lives or substandard vegetables and fruits, and to manage and store this data.

[0969] "Means for suggesting food and recipes based on user information" refers to technical means for selecting and suggesting the most suitable food and recipes based on the user's basic information and past purchase history that has been collected.

[0970] "Means for users to select and order food and recipes" refers to technical means that provide an interface for users to review a list of suggested food and recipes, make selections, and confirm their orders.

[0971] "Means of delivering ordered food" refers to the technical means by which a distributor prepares the food ordered by a user and delivers it to the user's address.

[0972] "Means for collecting user emotional data using a camera and microphone" refers to technical means that use a camera and microphone to collect emotional data in order to analyze the user's facial expressions and tone of voice.

[0973] "Means for suggesting food and recipes based on user emotional data" refers to technical means for analyzing collected emotional data and suggesting food and recipes that are best suited to the user's current emotional state.

[0974] "Means of notifying the user upon completion of delivery" refers to technical means of sending a notification to the user's device when the food has been delivered, informing them of the completion of the delivery.

[0975] This invention provides a food delivery system that analyzes user emotions and suggests appropriate food items and recipes. This system consists of the following main hardware and software components.

[0976] First, users access the system using a home device such as a smartphone and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This information is stored in RDS (Relational Database Service) on Amazon Web Services (AWS).

[0977] Next, food data is entered by producers and distributors. This food data is stored in an AWS DynamoDB database and includes information such as type, quantity, expiration date, and price. This allows the system to organize and manage up-to-date food information.

[0978] Furthermore, this system includes an emotion engine that uses the smartphone's camera and microphone to collect the user's facial expressions and voice tone, thereby obtaining emotion data. This data is processed in real time on AWS Lambda and the OpenAI GPT-4 API is used to analyze the user's emotions.

[0979] When a user logs into the system and requests food and recipe suggestions, the server first accesses the user's basic information and sentiment data. Based on this, it uses a GPT-4 model to select and suggest the most suitable foods and recipes. Specifically, it inputs prompt statements like the following into the generating AI model:

[0980] User information: {Name: Tanaka, Allergy: Nuts, Favorite food: Fish, Stress level: High}

[0981] Emotional data: {stress}

[0982] Please generate the suggested recipe.

[0983] The generated list of food items and recipes is sent to the user's device. The user reviews this list, selects the food items and recipes as needed, and confirms the order. The order data is sent to the distributor using AWS SNS (Simple Notification Service), and the appropriate food items are prepared and delivered to the user's address. Once delivery is complete, the server sends a notification to the user's device informing them that the delivery is complete.

[0984] In this way, by utilizing user sentiment data to suggest food and recipes and providing optimal delivery services, it is possible to create a better user experience and contribute to reducing food waste.

[0985] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0986] Step 1:

[0987] Users access the system using their devices and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This input data is sent to a server, which extracts important information from the received data and stores it in Amazon Web Services (AWS) RDS (Relational Database Service). This allows the data to be managed based on the user's unique identification code.

[0988] Step 2:

[0989] Producers and distributors access the system through a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to a server, which adds, organizes, and manages the received data in an AWS DynamoDB database. This ensures that the latest food information is always updated and used to generate food lists for users.

[0990] Step 3:

[0991] The user interacts with the device to answer interactive questions and uses the camera and microphone to collect facial expressions and voice tone. The server sends this input data to AWS Lambda, where it performs sentiment analysis using the OpenAI GPT-4 API. This process identifies the emotions the user is currently experiencing (e.g., stress, joy, excitement), and this data is stored on the server.

[0992] Step 4:

[0993] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's basic information, allergy information, food preferences, past purchase history, and sentiment data. This selection uses a generative AI model powered by the OpenAI GPT-4 API, which generates prompt messages like the following:

[0994] User information: {Name: User X, Allergies: Nuts, Favorite food: Fish, Stress level: High}

[0995] Emotional data: {stress}

[0996] Please generate the suggested recipe.

[0997] A list of generated foods and recipes is sent from the server to the user's terminal.

[0998] Step 5:

[0999] The user reviews a list of suggested foods and recipes and selects them as needed. Once the user confirms their selection, the data is sent to the server and notified to the distributor via AWS SNS (Simple Notification Service).

[1000] Step 6:

[1001] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's registered address. Once delivery is complete, the server generates a delivery completion notification and sends it to the user's device. This allows the user to check the delivery progress in real time.

[1002] Through these steps, personalized food and recipe suggestions and deliveries are realized by leveraging user sentiment data.

[1003] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1004] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1005] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1006] [Fourth Embodiment]

[1007] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1008] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1009] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1010] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1011] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1012] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1013] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1014] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1015] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1016] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1017] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1018] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1019] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1020] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food.

[1021] Overall system flow

[1022] 1. User registration and information gathering

[1023] Users access the Ecolicious system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[1024] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[1025] 2. Food data collection

[1026] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[1027] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[1028] 3. Food and recipe suggestions

[1029] The user logs into the system from their device and requests suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences.

[1030] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[1031] As a concrete example, consider a case where the user is a housewife with a dairy allergy. We know that the user has purchased a lot of vegetables in the past. Based on this information, the server suggests a dairy-free recipe using off-grade cabbage and sweet potatoes: "Sweet Potato Vegan Curry."

[1032] 4. Confirm your order

[1033] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[1034] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[1035] 5. Food delivery and pickup

[1036] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[1037] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[1038] In this way, the system of the present invention efficiently collects and manages food data and proposes optimal foods and recipes for users, thereby reducing food waste in households. Furthermore, it enables producers and distributors to improve the efficiency of inventory management and sales, thus minimizing overall resource waste.

[1039] The following describes the processing flow.

[1040] Step 1:

[1041] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[1042] Step 2:

[1043] When a user submits their basic information, the server receives it and stores it in the database. It also automatically generates a user ID and links it to each piece of information.

[1044] Step 3:

[1045] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[1046] Step 4:

[1047] Food information entered by producers and distributors is sent to the server, which then adds, organizes, and manages this information in a database.

[1048] Step 5:

[1049] Users log in to the system from their devices and request food and recipe suggestions.

[1050] Step 6:

[1051] The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, and food preferences.

[1052] Step 7:

[1053] The server sends a list of selected foods and recipes to the user's device. The user can then review the suggestions.

[1054] Step 8:

[1055] Users review the suggestions on their devices, select their favorite foods and recipes, and confirm their order.

[1056] Step 9:

[1057] Once a user confirms an order, the server receives the order details and automatically sends the order data to the distributor.

[1058] Step 10:

[1059] The server generates an order confirmation email and sends it to the user's email address.

[1060] Step 11:

[1061] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[1062] Step 12:

[1063] The user receives the delivered food. The server generates a delivery completion notification and sends it to the user's device.

[1064] In this way, the Ecolicious system can function efficiently and reduce food waste.

[1065] (Example 1)

[1066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1067] In modern society, food waste in homes and businesses has become a serious problem. Furthermore, consumers are required to make food choices based on their preferences and allergy information, necessitating the provision of appropriate information to support this. Producers and distributors are also required to improve the efficiency of inventory management and sales, but the current system makes it difficult to do so effectively.

[1068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1069] This invention includes a server that receives data entered by a user, stores it in a database, and assigns a unique ID to each user; a server that organizes and manages food data entered by producers and distributors and generates a list to provide to the user; and a server that selects and proposes optimal foods and recipes to the user based on the user's past purchase history, allergy information, and food preferences. This enables a reduction in food waste in households and businesses, food selection that meets the diverse needs of consumers, and improved inventory management and sales efficiency for producers and distributors.

[1070] A "user" is an individual or group that accesses the system using a home terminal and enters basic information and preferences regarding food.

[1071] A "server" is a central processing unit that receives data transmitted from users, producers, and distributors, stores, organizes, and analyzes it, and provides the necessary information to various stakeholders.

[1072] A "terminal" is an input device used by a user to access a system and enter information, and specifically refers to devices such as smartphones and personal computers.

[1073] "Basic information" refers to user-specific information that users enter into the system, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[1074] "Food data" refers to detailed information about food products, such as expiration dates, types, quantities, and prices, that producers and distributors enter into the system.

[1075] A "database" is a collection of information that is systematically stored and managed to allow for easy searching and access of basic user information and food data.

[1076] A "User ID" is a unique identifier assigned by the server to each user, and is an identification number used to manage user information and transactions.

[1077] "Suggestion" refers to the server selecting and presenting the most suitable foods and recipes to the user based on their past purchase history, allergy information, and food preferences.

[1078] "Order data" refers to information about the food items and recipes selected by the user, along with their quantities, which is received, processed, and provided to distributors by the server.

[1079] A "confirmation email" is a purchase confirmation notification sent from the server to the user's email address after the user has confirmed their order.

[1080] A "food list" is a list of selectable foods that the server provides to the user based on collected food data.

[1081] A "notification" is a message generated by a system to convey important information to a user or relevant party.

[1082] Modes for carrying out the invention

[1083] This invention is a system that reduces food waste in homes and businesses, and allows consumers, producers, and distributors to all benefit. The following describes in detail specific embodiments for carrying out this invention.

[1084] System Overview

[1085] The system mainly consists of the following elements:

[1086] 1. Means (terminals) by which the user enters basic information.

[1087] 2. Means of collecting food data (server and terminal)

[1088] 3. Means (server) for suggesting food and recipes based on user information.

[1089] 4. A means (terminal) for users to select and order food and recipes.

[1090] 5. Means of delivering ordered food products (distributors)

[1091] Hardware and software

[1092] User side

[1093] Users access the system using their home or company devices (e.g., smartphones, tablets, PCs, etc.). They use a browser or dedicated application running on these devices to enter basic information and food preferences.

[1094] Server side

[1095] The server receives, stores, organizes, and analyzes data sent from users, producers, and distributors. Specifically, the following software can be used:

[1096] Database management systems (e.g., MySQL, PostgreSQL)

[1097] Server-side scripts (e.g., PHP, Node.js)

[1098] Data analysis tools (e.g., Python, Apache Spark)

[1099] This system also utilizes a generative AI model, which allows it to suggest optimal foods and recipes based on the user's purchase history, preferences, and allergy information.

[1100] Program processing and specific examples

[1101] 1. User registration and information gathering

[1102] Users access the system's registration form using a terminal and enter information such as their name, address, contact information, allergy information, food preferences, and past purchase history. The server receives this information, stores it in a database, and assigns a unique user ID to each user.

[1103] 2. Collection of food data

[1104] Producers and distributors use terminals to input data on products with short shelf lives or substandard vegetables and fruits from a management screen. The server receives this data, organizes it, and stores it in a database.

[1105] 3. Food and recipe suggestions

[1106] The server uses a generative AI model to select the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The selected list of suggestions is sent to the user's device for review.

[1107] Specific example: Suppose the user is a housewife with a dairy allergy and has a history of purchasing a lot of vegetables. Based on this information, the server suggests a dairy-free "sweet potato vegan curry" recipe and suggests off-spec cabbage and sweet potatoes.

[1108] The following is an example of a prompt message for a generative AI model:

[1109] "We are designing a system to reduce food waste in homes and businesses. We're considering a user who is a housewife with a dairy allergy and who buys a lot of vegetables. Please design a process that suggests the most suitable foods and recipes for this user."

[1110] 4. Order Confirmation and Delivery

[1111] Once the user reviews the suggested food items and recipes and confirms their order, the server processes the order data and provides it to the distributor. The server also generates a confirmation email and sends it to the user's email address. The distributor prepares the food based on the order data received from the server and delivers it to the user's address.

[1112] 5. Notification of delivery completion

[1113] Upon completion of delivery, the distributor updates the status through the system, and the server generates and sends a delivery completion notification to the user. The user can then receive the delivery completion notification on their device.

[1114] As described above, this system efficiently collects and manages food data and suggests optimal foods and recipes to users, thereby reducing food waste in households and businesses and providing benefits to consumers, producers, and distributors alike.

[1115] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1116] Step 1:

[1117] Users access the system from their home devices (smartphones or PCs) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. The entered data is sent to the server when the user presses the "Submit" button. The server validates the received input data and saves it to the database in the appropriate format. As output, a unique user ID is generated for the user, and a registration confirmation screen is displayed on the device.

[1118] Step 2:

[1119] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server by pressing the "Submit" button. The server validates the received food data and adds it to the database in the appropriate format. As output, the food list is updated and the correct data is reflected on the management screen.

[1120] Step 3:

[1121] The user logs into the system using their device and requests suggestions. The server queries the user's past purchase history, allergy information, and food preferences, and sends this information to a generative AI model. The generative AI model processes this data and selects the most suitable foods and recipes. As output, the server sends a list of selected foods and recipes to the user's device, allowing the user to review the suggestion list.

[1122] Step 4:

[1123] The user reviews the suggested food items and recipes and presses the "Confirm Order" button on their terminal. The order data is sent to the server. The server validates the order data, performs the necessary processing, and provides it to the distributor. As output, the server generates a confirmation email and sends it to the user's email address, and the distributor is provided with the necessary order information.

[1124] Step 5:

[1125] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are then delivered to the user's address. Specifically, the distributor's logistics system takes in the order data and calculates the optimal delivery route. As an output, the delivery schedule is finalized, and the user is notified of the delivery date.

[1126] Step 6:

[1127] The user receives the delivered food and cooks it using the recipe. Upon completion of delivery, the distributor sends a delivery completion status to the server. The server receives this information, generates a delivery completion notification, and sends it to the user's terminal. As output, the user receives the delivery completion notification, and the system records that all processing is complete.

[1128] (Application Example 1)

[1129] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1130] Existing food delivery systems lack effective means to reduce food waste, and are particularly hesitant to utilize foods with short shelf lives or those that do not meet specifications. Furthermore, they are insufficient in optimizing delivery based on user allergy information and preferences. In addition, the delivery system for ordered foods lacks efficiency, compromising user convenience. To address these challenges, more advanced information processing and the use of smart devices are necessary.

[1131] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1132] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. This makes it possible to reduce food waste and improve user convenience.

[1133] A "user" is an individual or legal entity that uses the system to request and order food and recipes.

[1134] "Basic information" refers to information such as the user's name, address, contact information, allergy information, preferred foods, and past purchase history.

[1135] "Food data" refers to information such as the type, quantity, expiration date, and price of food products provided by producers and distributors.

[1136] The "suggestion method" refers to a system function that selects the most suitable food and recipe based on user information and presents them to the user.

[1137] "Ordering method" refers to a system function that allows users to select selected food items and recipes and confirm their order.

[1138] "Delivery method" refers to the service or function used to deliver ordered food items to the address specified by the user.

[1139] A "smart device" is a device that connects to the internet and provides or retrieves information, such as a smartphone, smart glasses, a head-mounted display, or a robot.

[1140] A "database" is a recording device or a system that includes a recording device for organizing and managing information.

[1141] "Reducing food waste" refers to reducing the amount of food that is wasted by offering and delivering food that is nearing its expiration date or that does not meet standard specifications to customers.

[1142] "User information" refers to information that includes basic information and additional information provided by smart devices.

[1143] The system for realizing this invention includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, means for acquiring food data and recipe information using a smart device, and means for providing food and recipe information to the user using that data. Specific embodiments are described below.

[1144] User registration and information gathering

[1145] Users access the system from a home device (e.g., a smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form. Once this information is submitted, the server receives the data and stores it in a database.

[1146] Food data collection

[1147] Producers and distributors access the system through a management screen and input data on products with short shelf lives or off-spec vegetables and fruits. This includes the type of food, quantity, expiration date, and price. The data is sent to the server and added to the database.

[1148] Food and recipe suggestions

[1149] Users log in to the system from their devices and request suggestions. The server selects the most suitable foods and recipes based on the user's past purchase history, allergy information, and food preferences. The list of selected foods and recipes is sent to the user's device for review. For example, a user with a dairy allergy who buys a lot of vegetables might be suggested a dairy-free "sweet potato vegan curry."

[1150] Order Confirmation

[1151] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which provides the order data to the distributor. The user receives an order confirmation email.

[1152] Food delivery and pickup

[1153] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's address, and the user receives the delivered food. The user receives a delivery completion notification on their device.

[1154] Use of smart devices

[1155] This system efficiently acquires and provides food data and recipe information by utilizing smart devices. These include smartphones, smart glasses, head-mounted displays, and robots. These devices perform functions such as acquiring additional user information, presenting suggestions, and even processing orders.

[1156] Prompt statements as concrete examples

[1157] "User Profile: Name: Taro Yamada, Address: Minato-ku, Tokyo, Contact: 090-1234-5678, Allergies: Dairy, Favorite Foods: Vegetables. Past Purchase History: Cabbage, Sweet Potatoes. Available Food List: Non-standard Cabbage, Non-standard Sweet Potatoes. Suggested Recipes: Can be cooked without using dairy. Please generate suggested recipes."

[1158] In this way, the system of the present invention realizes a process that utilizes the user's basic information and food data to propose, order, and deliver optimal food and recipes. This is expected to reduce food waste and improve user convenience.

[1159] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1160] Step 1:

[1161] Users access the system from their home devices (smartphones or PCs) and enter basic information (name, address, contact information, allergy information, food preferences, and past purchase history). The entered data is sent to the server and stored in the database. The input here is the user's basic information, and the output is data to which a user ID is assigned.

[1162] Step 2:

[1163] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. The data is sent to the server and added to the database. The input here is detailed product data, and the output is organized and managed food data.

[1164] Step 3:

[1165] The user logs into the system from their device and requests suggestions. The server uses the user's past purchase history, allergy information, and food preferences to select the most suitable foods and recipes using an AI model. A list of selected foods and recipes is sent to the user's device. The inputs here are user profile information and food data, and the output is a list of suggested foods and recipes.

[1166] Step 4:

[1167] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order data is sent to the server, which provides the order details to the distributor. The server generates an order confirmation email and sends it to the user's email address. The input here is the user's selected data, and the output is the confirmed order data and confirmation email.

[1168] Step 5:

[1169] The distributor receives order data from the server and prepares the necessary food items. The prepared food items are delivered to the user's address. Upon completion of delivery, the server generates a delivery completion notification and sends it to the user's terminal. The input here is the order data, and the output is the delivered food items and the delivery completion notification.

[1170] Step 6:

[1171] Smart devices (smartphones, smart glasses, head-mounted displays, robots, etc.) acquire and present user information and suggestions. Additional user information is acquired, and suggestions are effectively displayed to the user. The input here is data acquired by the smart device, and the output is optimal food and recipe information provided to the user.

[1172] The above describes the specific operation of each program processing step in the system that implements the application example.

[1173] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1174] This invention is a system that reduces food waste in homes and businesses, allowing consumers, producers, and distributors to all benefit. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, and means for delivering the ordered food. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to suggest food and recipes that respond to the user's emotions.

[1175] Overall system flow

[1176] 1. User registration and information gathering

[1177] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form.

[1178] When a user submits this information, the server receives the input data and stores it in the database. The system assigns a unique user ID to each user and uses it to manage future transactions.

[1179] 2. Food data collection

[1180] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits.

[1181] This data is sent to the server and added to the database. The server organizes and manages the collected data and uses it to generate a list of foods to provide to users.

[1182] 3. Emotion recognition by an emotion engine

[1183] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using cameras and microphones.

[1184] The emotion engine analyzes this data and recognizes the emotions the user is currently feeling (e.g., stress, joy, excitement, etc.).

[1185] 4. Food and recipe suggestions

[1186] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and sentiment data obtained from the sentiment engine.

[1187] A list of selected foods and recipes is sent to the user's device. The user can view the suggested list on their device screen.

[1188] For example, if the emotion engine detects that a user is experiencing work-related stress, the server will suggest a recipe using ingredients with relaxing properties (e.g., herbal tea and a refreshing salad). Also, if the user lives alone and leads a busy life, the server will prioritize suggesting easy-to-prepare foods.

[1189] 5. Confirm your order

[1190] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor.

[1191] Once a user's order is confirmed, the server generates a confirmation email and sends it to the user's email address.

[1192] 6. Food delivery and pickup

[1193] The distributor receives order data from the server and prepares the necessary food items. The food items are then delivered to the user's address.

[1194] Users can receive the delivered food and enjoy cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[1195] In this way, the system of the present invention efficiently collects and manages food data and emotional data, and reduces food waste in households by suggesting the most suitable foods and recipes for the user. Furthermore, by providing suggestions that respond to the user's emotions, it offers a more personalized service and improves the user experience.

[1196] The following describes the processing flow.

[1197] Step 1:

[1198] Users access the Ecolicious website or app and fill out a new registration form with their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[1199] Step 2:

[1200] When a user submits their basic information, the server receives this information and stores it in a database. The server assigns a unique user ID to each user and uses it to manage future transactions.

[1201] Step 3:

[1202] Producers and distributors access the management screen and enter information (type, quantity, expiration date, price, etc.) about foods with short shelf lives or vegetables and fruits that do not meet specifications.

[1203] Step 4:

[1204] Food information entered by producers and distributors is sent to the server, which adds, organizes, and manages it in a database. This generates a list of food products to be offered to users.

[1205] Step 5:

[1206] Users log in to the system using their devices and request food and recipe suggestions.

[1207] Step 6:

[1208] The user answers interactive questions to provide emotional data, or their facial expressions and voice tone are analyzed using a camera and microphone. The emotion engine then generates the user's emotional data.

[1209] Step 7:

[1210] The emotion engine generates emotional data, which the server receives and combines with the user's purchase history, allergy information, and food preferences to select the most suitable foods and recipes.

[1211] Step 8:

[1212] The server sends a list of selected foods and recipes to the user's device. The user reviews the suggestions, selects their favorite foods and recipes, and confirms their order.

[1213] Step 9:

[1214] Once the user confirms their order, the server receives the order details and automatically sends the order data to the distributor. The server then generates an order confirmation email and sends it to the user's email address.

[1215] Step 10:

[1216] The distributor receives order data from the server, prepares the necessary food items, and delivers them to the address specified by the user.

[1217] Step 11:

[1218] The user receives the delivered food and enjoys cooking it according to the set recipe. After delivery is complete, the server generates a delivery completion notification and sends it to the user's device.

[1219] As a concrete example, consider a situation where a user is busy and stressed. The emotion engine recognizes this stress, and the server suggests a recipe for a relaxing herbal tea and a light snack. Furthermore, if the user has a dairy allergy, that information is also taken into consideration in the suggestions. This allows the user to receive foods and recipes that are best suited to their situation, reducing food waste while simultaneously improving the user experience.

[1220] (Example 2)

[1221] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1222] Food waste has become a significant social problem in both households and businesses. In particular, poor management of expiration dates and food waste are contributing factors. Furthermore, consumers face the challenge of selecting foods and recipes that suit their health and emotional needs. Traditional systems lack mechanisms for users to select foods and recipes based on their emotions, resulting in a lack of personalized suggestions and making it difficult to increase user satisfaction.

[1223] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1224] In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for the user to select and order food and recipes, means for delivering the ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes the user's emotions. This makes it possible to suggest personalized food and recipes that are tailored to the user's individual health condition and emotions.

[1225] A "user" is an individual or legal entity that utilizes the system and is the entity that provides basic information, food preferences, emotional data, and so on.

[1226] "Basic information" refers to data entered by the user, such as name, address, contact information, allergy information, food preferences, and past purchase history.

[1227] "Food data" refers to information such as the type, quantity, expiration date, and price of food products entered by producers and distributors.

[1228] "Means of suggestion" refers to the methods and processes by which the server selects and suggests the most suitable food and recipes based on the user's basic information and sentiment data.

[1229] "Method of ordering" refers to the method or process by which users review suggested food items and recipes and confirm their orders through the system.

[1230] "Means of delivery" refers to the methods and processes by which distributors prepare food based on order data from a server and deliver it to the user's address.

[1231] An "emotion engine" refers to a technology that collects and analyzes emotional data using interactive questions, cameras, microphones, etc., in order to recognize the user's emotions.

[1232] A "database" is a collection of information managed by a server, and refers to a system for organizing and storing basic user information and food data.

[1233] "Personalized suggestions" refer to food and recipe suggestions that are customized based on the user's individual health status, emotions, preferences, and other factors.

[1234] This invention is a system that reduces food waste in homes and businesses, bringing benefits to consumers, producers, and distributors alike. The system includes means for users to input basic information, means for collecting food data, means for suggesting food and recipes based on user information, means for users to select and order food and recipes, means for delivering ordered food, and means for suggesting food and recipes by combining an emotion engine that recognizes user emotions.

[1235] System Overview

[1236] User registration and information gathering

[1237] Users access the system from their home devices (e.g., smartphones or PCs) and enter their name, address, contact information, allergy information, food preferences, past purchase history, etc., into a new registration form. This information is then sent to the server, and a unique ID is generated for each user. For example, users may enter information on how to reduce stress into the registration form. This data is received by the server and stored in a database.

[1238] Food data collection

[1239] Producers and distributors access the system from a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to the server, where it is organized and stored in a database. The server lists the food data and manages it so that users can select from it.

[1240] Emotion recognition by an emotion engine

[1241] The system collects emotional data by having users answer interactive questions through their devices and by analyzing their facial expressions and voice tone using the camera and microphone. An emotion engine analyzes this data to recognize the emotions the user is currently feeling (stress, joy, excitement, etc.). This makes it possible to understand the user's real-time emotional state.

[1242] Food and recipe suggestions

[1243] When a user logs into the system and requests food and recipe suggestions, the server selects the most suitable foods and recipes based on the user's purchase history, allergy information, food preferences, and emotional data. The selected list is sent to the user's device, where the user can visually review the suggestions. For example, if the emotional engine detects that the user is stressed at work, the server will suggest a recipe using ingredients with relaxing effects (e.g., herbal tea and a refreshing salad).

[1244] User orders and food delivery

[1245] The user reviews the suggested food items and recipes and confirms their order by pressing the order button. The order details are sent to the server, which processes the order data and provides it to the distributor. The distributor receives the order data from the server, prepares the necessary food items, and delivers them to the user's address. After receiving the food items, the user enjoys cooking using the recipes. Upon completion of delivery, the server generates a notification and sends it to the user's device.

[1246] This allows the entire system to work together, enabling efficient reduction of food waste while individually personalizing each user's diet.

[1247] Example prompt statements

[1248] "Based on the basic information registered by the user, use an emotion engine to recognize the user's current emotions and generate food and recipe suggestions that correspond to those emotions. For example, if the user is feeling stressed, the goal is to suggest foods and recipes that have a relaxing effect."

[1249] Thus, advanced, personalized food recommendation systems that integrate with an emotion engine are expected to make a significant contribution to reducing food waste in homes and businesses.

[1250] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1251] Step 1: User registration and information gathering

[1252] Users access the system using a home device (smartphone or PC) and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history into a new registration form.

[1253] Input: Basic information entered by the user.

[1254] The device sends this information to the server.

[1255] The server stores the received information in a database and assigns a unique user ID to each user.

[1256] Output: User information and a unique user ID stored in the database.

[1257] Step 2: Food data collection

[1258] Producers and distributors access the system using management terminals and input food data (type, quantity, expiration date, price, etc.).

[1259] Input: Food data entered by producers and distributors.

[1260] The device sends this information to the server.

[1261] The server adds the received information to the database and organizes it while maintaining consistency with existing data.

[1262] Output: Food data added or updated in the database.

[1263] Step 3: Emotion recognition by the emotion engine

[1264] Users can answer interactive questions through their devices and have their facial expressions and voice tone analyzed using the camera and microphone.

[1265] Input: User response data, camera video, microphone audio.

[1266] The device sends this information to the server.

[1267] The server uses an emotion engine to analyze the received data and recognize the user's emotional state.

[1268] Output: User emotional state data (e.g., stress, joy, excitement).

[1269] Step 4: Food and recipe suggestions

[1270] Users log in to the system using their devices and request food and recipe suggestions.

[1271] Input: User login information, suggestion request.

[1272] The terminal sends a request to the server.

[1273] The server analyzes the user's purchase history, allergy information, food preferences, and emotional data to select the most suitable foods and recipes.

[1274] Output: A list of selected foods and recipes.

[1275] The server sends the selection results to the user's terminal.

[1276] Step 5: Confirm your order

[1277] The user reviews the suggested food items and recipes on their device and confirms their order by pressing the order button.

[1278] Input: Food and recipe selected by the user.

[1279] The terminal sends the order data to the server.

[1280] The server receives the order data and records it in the database.

[1281] The server performs processing to provide order data to distributors.

[1282] Output: Order confirmation notification, order data transmitted to distributors.

[1283] The server generates a confirmation email and sends it to the user's email address.

[1284] Step 6: Food delivery and pickup

[1285] The distributor prepares the food based on the order data received from the server.

[1286] Input: Order data received from the server.

[1287] Distributors deliver food products to users' addresses.

[1288] Output: Delivered food.

[1289] Users receive food and enjoy cooking using the recipes.

[1290] The server generates a delivery completion notification and sends it to the user's device.

[1291] (Application Example 2)

[1292] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1293] Traditional food delivery systems primarily suggested food items and recipes based on the user's basic information and past transaction history. However, these systems did not consider the user's emotions, meaning the suggestions offered were sometimes unsuitable for the user's current mood or situation. This resulted in a poor user experience and hindered the effective reduction of food waste.

[1294] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input basic information, means for collecting food data, means for suggesting food and recipes based on the user's information, means for collecting user emotion data using a camera and microphone, means for suggesting food and recipes based on the user's emotion data, and means for notifying the user when delivery is complete. This makes it possible to suggest optimal food and recipes according to the user's emotions, improving the user experience and reducing food waste.

[1295] "Means for users to input basic information" refers to technical means that provide an interface for users to input information such as their name, address, contact information, allergy information, food preferences, past purchase history, etc.

[1296] "Means of collecting food data" refers to technical means for producers and distributors to input data on products with short shelf lives or substandard vegetables and fruits, and to manage and store this data.

[1297] "Means for suggesting food and recipes based on user information" refers to technical means for selecting and suggesting the most suitable food and recipes based on the user's basic information and past purchase history that has been collected.

[1298] "Means for users to select and order food and recipes" refers to technical means that provide an interface for users to review a list of suggested food and recipes, make selections, and confirm their orders.

[1299] "Means of delivering ordered food" refers to the technical means by which a distributor prepares the food ordered by a user and delivers it to the user's address.

[1300] "Means for collecting user emotional data using a camera and microphone" refers to technical means that use a camera and microphone to collect emotional data in order to analyze the user's facial expressions and tone of voice.

[1301] "Means for suggesting food and recipes based on user emotional data" refers to technical means for analyzing collected emotional data and suggesting food and recipes that are best suited to the user's current emotional state.

[1302] "Means of notifying the user upon completion of delivery" refers to technical means of sending a notification to the user's device when the food has been delivered, informing them of the completion of the delivery.

[1303] This invention provides a food delivery system that analyzes user emotions and suggests appropriate food items and recipes. This system consists of the following main hardware and software components.

[1304] First, users access the system using a home device such as a smartphone and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This information is stored in RDS (Relational Database Service) on Amazon Web Services (AWS).

[1305] Next, food data is entered by producers and distributors. This food data is stored in an AWS DynamoDB database and includes information such as type, quantity, expiration date, and price. This allows the system to organize and manage up-to-date food information.

[1306] Furthermore, this system includes an emotion engine that uses the smartphone's camera and microphone to collect the user's facial expressions and voice tone, thereby obtaining emotion data. This data is processed in real time on AWS Lambda and the OpenAI GPT-4 API is used to analyze the user's emotions.

[1307] When a user logs into the system and requests food and recipe suggestions, the server first accesses the user's basic information and sentiment data. Based on this, it uses a GPT-4 model to select and suggest the most suitable foods and recipes. Specifically, it inputs prompt statements like the following into the generating AI model:

[1308] User information: {Name: Tanaka, Allergy: Nuts, Favorite food: Fish, Stress level: High}

[1309] Emotional data: {stress}

[1310] Please generate the suggested recipe.

[1311] The generated list of food items and recipes is sent to the user's device. The user reviews this list, selects the food items and recipes as needed, and confirms the order. The order data is sent to the distributor using AWS SNS (Simple Notification Service), and the appropriate food items are prepared and delivered to the user's address. Once delivery is complete, the server sends a notification to the user's device informing them that the delivery is complete.

[1312] In this way, by utilizing user sentiment data to suggest food and recipes and providing optimal delivery services, it is possible to create a better user experience and contribute to reducing food waste.

[1313] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1314] Step 1:

[1315] Users access the system using their devices and enter basic information such as their name, address, contact information, allergy information, food preferences, and past purchase history. This input data is sent to a server, which extracts important information from the received data and stores it in Amazon Web Services (AWS) RDS (Relational Database Service). This allows the data to be managed based on the user's unique identification code.

[1316] Step 2:

[1317] Producers and distributors access the system through a management screen and input data (type, quantity, expiration date, price, etc.) on products with short shelf lives or off-spec vegetables and fruits. This data is sent to a server, which adds, organizes, and manages the received data in an AWS DynamoDB database. This ensures that the latest food information is always updated and used to generate food lists for users.

[1318] Step 3:

[1319] The user interacts with the device to answer interactive questions and uses the camera and microphone to collect facial expressions and voice tone. The server sends this input data to AWS Lambda, where it performs sentiment analysis using the OpenAI GPT-4 API. This process identifies the emotions the user is currently experiencing (e.g., stress, joy, excitement), and this data is stored on the server.

[1320] Step 4:

[1321] The user logs into the system and requests food and recipe suggestions. The server selects the most suitable foods and recipes based on the user's basic information, allergy information, food preferences, past purchase history, and sentiment data. This selection uses a generative AI model powered by the OpenAI GPT-4 API, which generates prompt messages like the following:

[1322] User information: {Name: User X, Allergies: Nuts, Favorite food: Fish, Stress level: High}

[1323] Emotional data: {stress}

[1324] Please generate the suggested recipe.

[1325] A list of generated foods and recipes is sent from the server to the user's terminal.

[1326] Step 5:

[1327] The user reviews a list of suggested foods and recipes and selects them as needed. Once the user confirms their selection, the data is sent to the server and notified to the distributor via AWS SNS (Simple Notification Service).

[1328] Step 6:

[1329] The distributor receives order data from the server and prepares the necessary food items. The food is delivered to the user's registered address. Once delivery is complete, the server generates a delivery completion notification and sends it to the user's device. This allows the user to check the delivery progress in real time.

[1330] Through these steps, personalized food and recipe suggestions and deliveries are realized by leveraging user sentiment data.

[1331] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1332] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1333] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1334] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1335] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1336] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1337] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1338] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1339] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1340] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1341] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1342] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1343] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1344] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1345] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1346] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1347] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1348] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1349] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1350] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1351] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1352] The following is further disclosed regarding the embodiments described above.

[1353] (Claim 1)

[1354] A means for users to input basic information,

[1355] Means of collecting food data,

[1356] A means of suggesting food and recipes based on user information,

[1357] A means for users to select and order food and recipes,

[1358] The means of delivering the ordered food,

[1359] A system that includes this.

[1360] (Claim 2)

[1361] The system according to claim 1, comprising means for suggesting optimal foods and recipes based on allergy information and food preferences registered by the user.

[1362] (Claim 3)

[1363] The system according to claim 1, comprising means for managing a food database and organizing and managing newly added food data.

[1364] "Example 1"

[1365] (Claim 1)

[1366] A means for users to input basic information,

[1367] Means of collecting food data,

[1368] A means of suggesting food and recipes based on user information,

[1369] A means for users to select and order food and recipes,

[1370] The means of delivering the ordered food,

[1371] A means of receiving data entered by a user, saving it to a database, and assigning a unique ID to each user,

[1372] A means for organizing and managing food data entered by producers and distributors, and generating a list to provide to users,

[1373] A method for selecting and suggesting optimal foods and recipes to users based on their past purchase history, allergy information, and food preferences.

[1374] A means of receiving and processing user orders and providing them to distributors,

[1375] A means of generating and sending a notification to the user upon completion of delivery,

[1376] A system that includes this.

[1377] (Claim 2)

[1378] The system according to claim 1, comprising means for generating a confirmation email using user registration information and sending it to the user's email address.

[1379] (Claim 3)

[1380] The system according to claim 1, comprising means for sending generated suggestions to a user and allowing the user to view the suggested food and recipe list from their device.

[1381] "Application Example 1"

[1382] (Claim 1)

[1383] A means for users to input basic information,

[1384] Means of collecting food data,

[1385] A means of suggesting food and recipes based on user information,

[1386] A means for users to select and order food and recipes,

[1387] The means of delivering the ordered food,

[1388] A means of acquiring food data and recipe information using a smart device,

[1389] A means of providing users with food and recipe information using that data,

[1390] A system that includes this.

[1391] (Claim 2)

[1392] The system according to claim 1, which includes means for suggesting optimal foods and recipes based on allergy information and food preferences registered by the user, and further optimizes the suggested content by combining it with information obtained from a smart device.

[1393] (Claim 3)

[1394] The system according to claim 1, which manages a food database, has means for organizing and managing newly added food data, and optimizes food recommendations and delivery in conjunction with user information from smart devices.

[1395] "Example 2 of combining an emotion engine"

[1396] (Claim 1)

[1397] A means for users to input basic information,

[1398] Means of collecting food data,

[1399] A means of suggesting food and recipes based on user information,

[1400] A means for users to select and order food and recipes,

[1401] The means of delivering the ordered food,

[1402] A means of suggesting food and recipes by combining an emotion engine that recognizes the user's emotions,

[1403] A system that includes this.

[1404] (Claim 2)

[1405] The system according to claim 1, comprising means for suggesting optimal foods and recipes based on allergy information and food preferences registered by the user.

[1406] (Claim 3)

[1407] The system according to claim 1, comprising means for managing a food database and organizing and managing newly added food data.

[1408] "Application example 2 when combining with an emotional engine"

[1409] (Claim 1)

[1410] A means for users to input basic information,

[1411] Means of collecting food data,

[1412] A means of suggesting food and recipes based on user information,

[1413] A means for users to select and order food and recipes,

[1414] The means of delivering the ordered food,

[1415] A means of collecting user emotion data using a camera and microphone,

[1416] A means of suggesting food and recipes based on user sentiment data,

[1417] A means of notifying the user when delivery is complete,

[1418] A system that includes this.

[1419] (Claim 2)

[1420] The system according to claim 1, comprising means for suggesting optimal foods and recipes based on allergy information and food preferences registered by the user.

[1421] (Claim 3)

[1422] The system according to claim 1, comprising means for managing a food database and organizing and managing newly added food data. [Explanation of Symbols]

[1423] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input basic information, Means of collecting food data, A means of suggesting food and recipes based on user information, A means for users to select and order food and recipes, The means of delivering the ordered food, A system that includes this.

2. The system according to claim 1, comprising means for suggesting optimal foods and recipes based on allergy information and food preferences registered by the user.

3. The system according to claim 1, comprising means for managing a food database and organizing and managing newly added food data.

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