System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting an address, the number of households, a desired food cost, a food ingredient concept, self-cooking capability, a target weight, and a refrigerator inventory from a user; means for acquiring information on nearby stores or online stores based on the address; means for generating an optimal food ingredient list and recipe based on the input information and the acquired store information; means for proposing the most economical or convenient purchase place based on the food ingredient list; and means for calculating a calorie intake based on the target weight and providing appropriate calorie advice.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's world, efficiently managing food expenses, which account for a large portion of a household's living expenses, is an important challenge for many families. However, each household has different conditions (address, number of household members, budget, food preferences, refrigerator inventory, ability to cook at home, etc.), and creating a meal plan while taking these into account is extremely time-consuming and laborious. It is also difficult to find economical sources of ingredients while managing calorie intake and target weight. Conventional systems lack a means to comprehensively manage these individual factors and automatically provide optimal meal plans, making it difficult to manage living expenses. [Means for solving the problem]

[0005] The present invention provides a system that provides optimal meal plans based on information entered by the user, such as address, number of household members, desired food costs, ingredient concepts, ability to cook at home, target weight, and refrigerator inventory. The system obtains information on the nearest store or online store in the user's area and, based on this information, suggests economical and convenient purchasing locations.

[0006] The system also analyzes the information and generates optimal recipes and ingredient lists based on refrigerator inventory. It also includes a function to calculate calorie intake based on the user's target weight and provide appropriate calorie advice. This system enables users to efficiently manage their household food budget and maintain a healthy diet.

[0007] "Address" refers to the detailed location of the area where the user lives, and is information that the system uses to obtain information about local supermarkets and online stores.

[0008] "Number of households" refers to the number of people living together in the same household, and is the basis information for the system to generate appropriate amounts of ingredients and recipes.

[0009] The "desired food budget" indicates the upper limit of the food budget that the user wishes to spend per month or per day, and is an important criterion when the system suggests economical shopping destinations and ingredient lists.

[0010] "Ingredient concept" refers to the ingredients and cooking style desired by the user, and is information that allows the system to select a recipe that suits the user's preferences.

[0011] "Ability to cook at home" indicates whether the user has the ability or motivation to cook at home, and is information that influences the system's selection of recipes that can be cooked at home or simple cooking methods.

[0012] "Target weight" refers to the weight that the user wishes to achieve, and is information that serves as a reference for the system to manage calorie intake.

[0013] "Refrigerator inventory" refers to a list of ingredients currently stored in the user's refrigerator, and is information that allows the system to suggest recipes that make effective use of existing ingredients.

[0014] "Store information" refers to the location, products, and price information of supermarkets and online stores in the user's area, and is information used by the system to suggest the best place to purchase. [Brief explanation of the drawings]

[0015]

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[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The system of the present invention starts with the user inputting their address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, and then uses that information to suggest optimal daily meals and purchasing locations for each user. The program processing of the system of the present invention is explained below in natural language.

[0037] Initial Setup

[0038] User

[0039] First, the user logs into the system and enters their address, number of household members (e.g., 2 people), desired food budget (30,000 yen per month or 1,000 yen per day), food concept (mainly Japanese food), whether they can cook at home (possible), target weight (60 kg), and refrigerator inventory (e.g., rice, miso, chicken, etc.).

[0040] server

[0041] The server then stores the information provided by the user in a database.

[0042] The server obtains information on nearby supermarkets and online stores based on the user's address, as well as price information on ingredients sold at each store.

[0043] Ingredient and recipe recommendations

[0044] server

[0045] The input information is analyzed and a recipe that prioritizes the use of the refrigerator's inventory is searched for. For example, if there is rice and chicken, the recipe for "Teriyaki Chicken" is selected.

[0046] The ingredient concept is centered around Japanese cuisine and cooking at home is possible, so suitable Japanese recipes will be recommended.

[0047] Terminal

[0048] The recommended recipes are displayed on the user's device. For example, if a teriyaki chicken recipe is recommended, the cooking instructions and details of the ingredients are displayed.

[0049] Suggestions for where to buy ingredients

[0050] server

[0051] Based on the recommended recipe, a list of ingredients that are not in the user's refrigerator is created. For example, if it turns out that soy sauce, sugar, and ginger are not in the refrigerator, a purchase list for these items is generated.

[0052] Next, the system selects the most economical store for each ingredient based on price information from the nearest supermarket or online store and suggests it to the user.

[0053] Terminal

[0054] The user's device displays a list of ingredients needed and recommended places to buy them. For example, the information provided may include "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[0055] Calorie intake and weight management

[0056] server

[0057] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. For example, if the target weight is 60 kg, calculate the daily calorie intake and check whether the recommended recipes fall within that range.

[0058] It will suggest calorie adjustments and alternatives as needed, for example, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[0059] Terminal

[0060] The user's device will display a healthy meal plan along with calculated calorie information, such as "Today's menu is 1500 kcal in total, which is a good balance for your calorie goal."

[0061] The present invention thereby automates a series of processes for users to efficiently manage their living expenses and lead a balanced diet, thereby providing full support to users in both food expenses and health management.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] Users log in to the system and enter their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory, allowing them to register their lifestyle and food preferences in the system.

[0065] Step 2:

[0066] The server stores the information provided by the user in a database, which is used for further analysis and recommendations.

[0067] SQL

[0068] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[0069] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[0070] Step 3:

[0071] The server obtains information about nearby supermarkets and online stores based on the user's address. This information is collected using APIs that reference the acquired store data.

[0072] Python

[0073] nearest_stores = get_nearest_stores(user_address)

[0074] store_prices = fetch_store_prices(nearest_stores)

[0075] Step 4:

[0076] The server analyzes the user's input information and searches for recipes that prioritize the use of existing refrigerator inventory. For example, if "rice" and "chicken" are in stock, the server searches for a recipe for "teriyaki chicken."

[0077] SQL

[0078] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept;

[0079] Step 5:

[0080] The server selects the most suitable recipe and sends the recommended recipe information to the user terminal. For example, a recipe for "Teriyaki Chicken" is provided, along with cooking instructions and details of the ingredients required.

[0081] Step 6:

[0082] The device displays the recommended recipes to the user, for example, providing a detailed visual recipe for teriyaki chicken.

[0083] HTML

[0084]

[0085] <h1>{{recommended_recipe.name}}< / h1>

[0086] {{recommended_recipe.ingredients}}

[0087] {{recommended_recipe.instructions}}

[0088]

[0089] Step 7:

[0090] The server generates a list of ingredients that are missing from the refrigerator based on the recommended recipe. For example, if soy sauce, sugar, or ginger are missing, the server adds these items to the list.

[0091] SQL

[0092] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[0093] Step 8:

[0094] The server lists the most economical places to purchase each ingredient and suggests them to the user, such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar at online store X."

[0095] Python

[0096] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[0097] Step 9:

[0098] The device displays a list of ingredients to purchase and recommended places to buy them to the user, organizing and presenting the information in a format that is visually easy for the user to understand.

[0099] HTML

[0100]

[0101] <h2>Recommended Shops< / h2>

[0102]

[0103] {% for item, shop in purchase_recommendations %}

[0104] {{item}} - Buy at {{shop}}

[0105] {% endfor %}

[0106]

[0107]

[0108] Step 10:

[0109] The server calculates the calories of the recommended recipes and compares them with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server analyzes the calorie information of the recipes based on the appropriate daily calorie intake.

[0110] Python

[0111] recipe_calories = calculate_calories(recommended_recipe)

[0112] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[0113] Step 11:

[0114] The server provides the user with advice on calorie management. For example, specific advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[0115] Python

[0116] if recipe_calories <= daily_calorie_needs:

[0117] calorie_advice = "This meal fits within your daily calorie needs."

[0118] else:

[0119] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[0120] Step 12:

[0121] The device displays the calculated calorie information and advice to the user, allowing them to follow a healthy eating plan.

[0122] HTML

[0123]

[0124] <h3>Calories: {{recipe_calories}}< / h3>

[0125] {{calorie_advice}}

[0126]

[0127] Through these steps, the system comprehensively supports users in managing food expenses, calorie intake, and maintaining a healthy diet.

[0128] Example 1

[0129] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0130] In today's busy lifestyles, it is difficult for many people to efficiently plan, purchase, and manage their health. This challenge is especially significant for users who want to maintain a balanced diet on a limited budget. Many users also want to avoid wasting ingredients they already have at home and shop economically by effectively utilizing nearby store information. To solve these problems, an automated meal planning and purchasing suggestion system tailored to the user's needs is needed.

[0131] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0132] In this invention, the server includes means for receiving input of a user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for acquiring information on nearby stores or online stores based on the address, means for generating an optimal ingredient list and recipe based on the input information and the acquired store information, means for suggesting the most economical or convenient purchasing source based on the generated ingredient list, means for calculating calorie intake based on the target weight and providing appropriate calorie advice, and means for visually displaying the recommended recipe and purchasing source information on the user terminal. This allows users to efficiently plan their ingredient purchases and maintain a healthy and balanced diet while shopping economically and without waste.

[0133] "User" refers to an individual or household using the system.

[0134] "Address" refers to geographic information of the place where the user resides.

[0135] "Number of households" refers to the number of people in the household to which the user belongs.

[0136] "Desired food budget" refers to the monthly or daily budget set by the user for meals.

[0137] "Ingredient concept" refers to a guideline for a specific food culture or cooking style that a user prefers, such as "mainly Japanese food."

[0138] "Self-cooking" refers to whether the user is able to cook at home.

[0139] "Target weight" refers to the weight that the user wants to achieve.

[0140] "Refrigerator inventory" refers to the types and quantities of ingredients currently in the user's refrigerator.

[0141] "Server" refers to the computer system that performs the central calculations and stores data for this system.

[0142] "Store information" refers to data about nearby stores or online stores obtained based on the user's address.

[0143] An "ingredient list" is a list of ingredients needed by the user, and is used for creating recipes and planning purchases.

[0144] A "recipe" refers to information that describes the steps and ingredients needed to prepare a dish.

[0145] "Purchasing locations" refers to stores and online stores suggested for users to purchase ingredients.

[0146] "Calories intake" refers to the amount of calories consumed by a user in a certain period of time.

[0147] "Calorie Advice" refers to advice based on recommended calorie intake for a user to achieve a weight goal.

[0148] "User terminal" refers to a device, such as a computer, smartphone, or tablet, that a user uses to access the system.

[0149] "Visually displaying" refers to presenting information in an easy-to-read format on the screen of a user terminal.

[0150] MODE FOR CARRYING OUT THE INVENTION

[0151] The system of the present invention proposes optimal daily cooking and food purchasing locations for users based on multiple pieces of information provided by the user. This system is composed of a combination of hardware and software, and a specific example is shown below.

[0152] Initial Setup

[0153] User

[0154] First, the user logs in to the system and enters the address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory information. Specifically, the following information is entered:

[0155] Address: Tokyo

[0156] Number of people in the household: 2

[0157] Desired food expenses: 30,000 yen per month

[0158] Ingredients concept: Japanese cuisine

[0159] Self-catering: Yes

[0160] Target weight: 60kg

[0161] Refrigerator inventory: rice, miso, chicken

[0162] Information storage and analysis

[0163] server

[0164] The server stores the information entered by the user in a database. The database used for this is a relational database such as MySQL (registered trademark) or PostgreSQL. Based on the stored information, the server collects information on nearby stores and online stores based on the user's address. This information is collected using web scraping technologies such as Python's BeautifulSoup and Scrapy.

[0165] Recipe Recommendations

[0166] server

[0167] Next, the server searches for recipes that prioritize the refrigerator inventory information provided by the user. For example, if there is rice and chicken in the refrigerator, a recipe such as "Teriyaki Chicken" will be selected. Also, since the ingredient concept is centered on Japanese cuisine, the server will recommend suitable recipes from among Japanese cuisine recipes.

[0168] Viewing Recipes

[0169] Terminal

[0170] The recommended recipes are displayed on the user's device. They are presented in a visually easy-to-understand format using HTML and JavaScript (registered trademark). For example, if a recipe for "teriyaki chicken" is recommended, the cooking instructions and details of the ingredients are displayed on the user's device.

[0171] Suggestions for where to buy ingredients

[0172] server

[0173] Based on the recommended recipe, the server creates a list of ingredients that the user does not have in their refrigerator. For example, if soy sauce, sugar, or ginger are missing, they are added to the shopping list. The server then suggests the most economical way to purchase the ingredients based on price information from the nearest supermarket or online store.

[0174] View shopping list

[0175] Terminal

[0176] The user's device will display a list of ingredients needed and recommended places to buy them. For example, it will show information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from an online store."

[0177] Calorie intake and weight management

[0178] server

[0179] The server calculates the calorie information of the recommended recipes and compares it with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server sets the daily calorie intake to 1800 kcal and checks whether the provided recipes fall within that range.

[0180] View calorie information and meal plans

[0181] Terminal

[0182] A healthy meal plan is displayed on the user's device along with calculated calorie information. For example, advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie goal of 1500 kcal" is shown.

[0183] Examples and prompts

[0184] As a concrete example, here is how the system operates based on the information above:

[0185] 1. Address: Tokyo

[0186] 2. Number of people in the household: 2

[0187] 3. Desired food expenses: 30,000 yen per month

[0188] 4. Ingredients concept: Japanese cuisine

[0189] 5. Self-catering: Yes

[0190] 6. Target weight: 60kg

[0191] 7. Refrigerator inventory: rice, miso paste, chicken

[0192] Based on this, the system makes recommendations such as:

[0193] Recommended recipe: Teriyaki Chicken

[0194] Shopping list: soy sauce, sugar, ginger

[0195] Where to buy: Soy sauce from your local supermarket, sugar from an online store

[0196] Prompt Sentence Examples

[0197] "Enter the user's address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory to display a list of recommended recipes and where to buy them."

[0198] As described above, the present invention is a comprehensive system that allows users to efficiently plan food purchasing, maintain a balanced diet, and manage their health.

[0199] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0200] Step 1: Enter your information

[0201] Input: The user enters their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory into the system.

[0202] Specific operation: The user logs in to a dedicated application or website using a smartphone or computer and enters the necessary information. For example, they enter information such as: living in Tokyo, household size: 2 people, desired food budget: 30,000 yen per month, mainly Japanese food, able to cook at home, target weight: 60 kg, and having rice, miso, and chicken in the refrigerator.

[0203] Output: The system receives user input.

[0204] Step 2: Store and analyze information

[0205] Input: Information entered by the user.

[0206] What it does: The server receives the information entered by the user and stores it in a database, using a relational database such as MySQL or PostgreSQL.

[0207] Output: Stored user information data. The server uses this data to:

[0208] Step 3: Gather information about nearby stores

[0209] Input: User's address information.

[0210] Specific operation: Based on the user's address, the server uses web scraping technology (e.g., Python's BeautifulSoup or Scrapy) to collect information on nearby supermarkets and online stores. For example, it collects price information for large supermarkets and online grocery stores in a specific area of ​​Tokyo.

[0211] Output: Collected nearby store and price information data.

[0212] Step 4: Find a recipe

[0213] Input: User's refrigerator inventory information, ingredient concept.

[0214] Specific operation: The server searches the recipe database for the corresponding recipe based on the input refrigerator inventory information. For example, if there is rice and chicken in the refrigerator, it searches for Japanese recipes that use these ingredients.

[0215] Output: A list of suitable recipes that were found.

[0216] Step 5: Recipe Selection

[0217] Input: Recipe search results.

[0218] Specific operation: The server recommends the best recipe based on the ingredient concept (e.g., mainly Japanese food). As a specific example, the recipe "Teriyaki Chicken" using chicken and rice is selected.

[0219] Output: Recommended recipe information.

[0220] Step 6: View the recipe

[0221] Input: Recommended recipe information.

[0222] What it does: The recommended recipe is displayed on the user's device. The recipe steps and ingredient details for "Teriyaki Chicken" are visually displayed on the screen using HTML and JavaScript.

[0223] Output: Recipe information displayed on the user's device.

[0224] Step 7: Make a list of ingredients you need

[0225] Input: Recommended recipe information, user's refrigerator inventory information.

[0226] Specific behavior: The server creates a list of ingredients that are missing from the user's refrigerator based on the recommended recipe. For example, if a teriyaki chicken recipe requires soy sauce, sugar, and ginger, but these are not in the refrigerator, the server adds them to the list.

[0227] Output: A list of ingredients needed.

[0228] Step 8: Propose a supplier

[0229] Input: List of ingredients needed, information on nearby stores.

[0230] Specific operation: The server selects the most economical and convenient place to purchase and suggests it to the user. For example, it suggests that the nearest supermarket is the cheapest place to buy soy sauce, and the online store is the cheapest place to buy sugar.

[0231] Output: Recommended vendor information.

[0232] Step 9: View your shopping list

[0233] Input: list of ingredients needed, recommended purchasing information.

[0234] Specific behavior: The recommended purchasing locations and a list of ingredients needed are displayed on the user's device. The user is given specific instructions, such as "Purchase soy sauce at the nearest supermarket and sugar at online store X."

[0235] Output: Shopping list information displayed on the user's device.

[0236] Step 10: Calculate calorie information

[0237] Input: Recommended recipe information, user's goal weight.

[0238] Specific operation: The server calculates the calorie information of the recommended recipe and compares it with the appropriate calorie schedule based on the user's target weight. For example, if the target weight is 60 kg, it sets the daily calorie intake to 1800 kcal and checks whether it falls within that range.

[0239] Output: Calorie count and calorie advice.

[0240] Step 11: View calorie information and meal plans

[0241] Input: Calorie count and calorie advice.

[0242] What it does: A healthy meal plan is displayed on the user's device along with calculated calorie information, and specific advice is given, such as "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie goal of 1500 kcal."

[0243] Output: Calorie information and meal plan displayed on user device.

[0244] As described above, this system provides comprehensive support for users to efficiently plan food purchases, maintain a balanced diet, and manage their health.

[0245] (Application example 1)

[0246] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0247] Conventional meal recommendation systems focus on supporting home cooking based on information entered by the user, but in real life, there are many situations where home cooking is not possible or people prefer to eat out. Furthermore, maintaining a healthy diet requires consideration of specific calorie intake and nutritional balance, but existing systems have difficulty providing comprehensive support for these. Therefore, there was a need for a system that could provide optimal meal recommendations not only for home cooking, but also for eating out or ordering food delivery.

[0248] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0249] In this invention, the server includes means for receiving input from the user of the user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for obtaining information on nearby stores or online stores, means for generating optimal ingredient lists and recipes, means for obtaining restaurant menus and recommending optimal menus, and means for arranging orders through affiliated food delivery services. This allows users to receive economical and healthy meal suggestions for a variety of eating habits, including not only cooking at home but also eating out and food delivery.

[0250] A "user" is an entity that uses this system, and is an individual or group that provides information such as address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory.

[0251] An "address" is information used to identify the location where a user resides, and is data necessary for procuring ingredients from nearby stores or online stores and using food delivery services.

[0252] "Number of households" indicates the number of people living at the same address, and is necessary to properly calculate recommended recipes and ingredient amounts.

[0253] "Desired food budget" is information indicating the budget that the user can spend on ingredients and meals, and is a standard value for suggesting economical ingredient lists and purchasing locations.

[0254] "Ingredient concept" is information that indicates the user's preferred eating style or cuisine genre, and is a criterion when selecting recommended recipes and menus.

[0255] "Ability to cook at home" is information that indicates the user's ability and willingness to cook at home, and is a criterion for determining whether or not a recommendation of a restaurant menu is necessary.

[0256] "Target weight" is information indicating the weight that the user wants to achieve, and is data necessary for calculating calorie intake and providing calorie advice.

[0257] "Refrigerator inventory" is information showing a list of ingredients that the user currently owns, and is data that serves as a basis for providing economical recipes that use inventory as much as possible.

[0258] "Store or online store information" refers to information about physical stores located near the user's address or places where ingredients can be purchased online, including price information and information about ingredients available.

[0259] The "optimal ingredient list" is a list of the most economical and nutritionally balanced ingredients based on information such as the user's desired food budget, ingredient concept, and whether or not they can cook at home.

[0260] A "recipe" is information that indicates the cooking steps and details of the ingredients required, generated based on information provided by the user.

[0261] The "dining out menu" is a list of recommended dishes for when the user is unable to cook at home or wishes to eat out, and is selected based on the user's nutritional balance and calorie goals.

[0262] A "food delivery service" is a service in which food is delivered to a user's address by an affiliated company or service provider, allowing users to easily enjoy restaurant menus in the comfort of their own home.

[0263] The "means for arranging an order" refers to a means for enabling a user to quickly and reliably order and use the restaurant menu selected by the user through a food delivery service.

[0264] This invention is a system that proposes optimal meals based on information provided by users to support their diverse dietary habits. This system is configured to accommodate not only users who cook at home, but also those who wish to eat out or use food delivery services.

[0265] System configuration

[0266] 1. User Device

[0267] Users access the system using a device such as a smartphone and enter information such as their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is necessary to make meal suggestions based on the user's specific needs and environment. User devices are built using a cross-platform development environment such as React Native.

[0268] 2. Server

[0269] The server plays a central role in storing the information collected from users in a database (MongoDB) and performing the following processes:

[0270] Information collection: Using Google (registered trademark) Maps API or similar, information on nearby stores or online stores based on the user's address is collected.

[0271] Recipe generation: Using a generative AI model (OpenAI® GPT-4®), an optimal recipe is generated based on the input information.

[0272] Ingredient list generation: Generates a list of ingredients needed based on a recipe and suggests economical and convenient places to buy them.

[0273] Calorie Calculation: Calculates calorie intake based on your target weight and provides appropriate calorie advice.

[0274] Dining menu recommendation: For users who wish to eat out, the app recommends the most suitable dining menu and arranges the order through a partner food delivery service.

[0275] Specific examples

[0276] For example, if a user enters the following information:

[0277] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[0278] Number of household members: 2

[0279] Desired food expenses: 30,000 yen per month

[0280] Ingredients concept: Mainly Japanese cuisine

[0281] Self-catering: Possible

[0282] Target weight: 60kg

[0283] Refrigerator inventory: rice, miso, chicken

[0284] With this information, the server does the following:

[0285] 1. Use the Google Maps API to get information about supermarkets and online stores around Shibuya Ward.

[0286] 2. Using a generative AI model (OpenAI GPT-4), generate recipes such as "Teriyaki Chicken" based on the inventory in the refrigerator.

[0287] 3. It creates a list of ingredients needed for the generated recipe and suggests the best places to buy them based on that list. For example, it suggests buying soy sauce at the nearest supermarket and sugar at an online store.

[0288] 4. Calculate calories and ensure the user meets the calorie goal. For example, calculate that one serving of teriyaki chicken is 500 kcal, and ensure that the user is within the calorie goal even if they eat it three times a day.

[0289] 5. If you can't cook or prefer to eat out, Google Maps will use its API to find nearby healthy restaurants and recommend dishes like a salmon and avocado salad bowl (500 kcal per serving). It will then arrange the order through a partner food delivery service.

[0290] This flow allows users to receive healthy and economical meal suggestions for both home cooking and eating out.

[0291] Example prompts

[0292] User Information:

[0293] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[0294] Number of people in the household: 2

[0295] Desired food expenses: 30,000 yen per month

[0296] Ingredients concept: Japanese cuisine

[0297] Self-catering: Yes

[0298] Target weight: 60kg

[0299] Refrigerator inventory: rice, miso, chicken

[0300] Based on this, please tell me a Japanese recipe that prioritizes using the stock in your refrigerator. Also, please provide the ingredients needed, where to buy them, and the associated calorie information.

[0301] This configuration provides comprehensive support for the user's eating habits, enabling them to maintain eating habits efficiently and economically.

[0302] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0303] Step 1:

[0304] A user logs in to the application using a smartphone. The user inputs information such as address, number of household members, desired food budget, ingredient concept, ability to cook at home, target weight, and refrigerator inventory. This input information provides basic parameters related to the user's eating habits.

[0305] Processing: The user launches the application, enters information, and presses the send button. The input information is sent from the terminal to the server.

[0306] Input: Address, number of households, desired food budget, food concept, whether you can cook at home, target weight, refrigerator inventory

[0307] Output: Input sent to the server

[0308] Step 2:

[0309] The server stores the received user input information in a database (MongoDB), which allows for centralized management of data required for subsequent processing.

[0310] Processing: The server parses the input information and stores it in a database.

[0311] Input: Information submitted by the user

[0312] Output: User information stored in the database

[0313] Step 3:

[0314] The server uses the Google Maps API to obtain information about nearby stores or online stores based on the user's address.

[0315] Processing: The server inputs the user's address into the Google Maps API and retrieves information about nearby stores.

[0316] Input: User's address

[0317] Output: Store or online store information

[0318] Step 4:

[0319] The server uses a generative AI model (OpenAI GPT-4) to generate an optimal recipe based on the input information and store information. This recipe prioritizes the use of the inventory in the user's refrigerator.

[0320] Processing: The server inputs the prompt sentences into the AI ​​model and generates the optimal recipe.

[0321] Input: User input information, store information

[0322] Output: The generated recipe

[0323] Step 5:

[0324] The server creates a list of ingredients required for the generated recipe and suggests the most economical and convenient place to buy them based on that list.

[0325] Processing: The server analyzes the recipe, creates a list of ingredients needed, and searches for where to purchase each ingredient.

[0326] Input: Generated recipe, store information

[0327] Output: Optimal ingredients list and purchasing information

[0328] Step 6:

[0329] The server calculates calorie intake based on the user's target weight and checks whether the target recipe is within the appropriate calorie range.

[0330] Processing: The server calculates the calorie information of the recipe and evaluates whether it is suitable for the target weight.

[0331] Input: Generated recipe, target weight

[0332] Output: Calorie intake information and calorie advice

[0333] Step 7:

[0334] If the user wants to eat out, the server uses the Google Maps API to retrieve the menus of nearby healthy restaurants and recommends the most suitable menu based on the user's nutritional balance and calorie goals.

[0335] Processing: The server searches for and recommends restaurant menus based on the user's preferences.

[0336] Input: User's preference, address, target weight

[0337] Output: Optimal dining out menu

[0338] Step 8:

[0339] The server will arrange to order the selected restaurant menu through an affiliated food delivery service.

[0340] Processing: The server sends the dining out menu selection results to the food delivery service API and arranges the order.

[0341] Input: Selected restaurant menu information

[0342] Output: Order placement completion information

[0343] Step 9:

[0344] The user terminal visually displays the recipe, ingredient list, supplier information, calorie intake information, restaurant menu, and order status received from the server.

[0345] Processing: The user terminal converts the received information into a display format and presents it visually to the user.

[0346] Input: Information sent from the server

[0347] Output: Information presented visually to the user

[0348] Through these steps, users can receive healthy and economical meal suggestions for both home cooking and eating out.

[0349] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0350] The system of the present invention provides the user with the optimal meal plan based on various input information from the user (address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, refrigerator inventory). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to recommend recipes and ingredients according to the user's emotional state, making the user's dining experience more personalized.

[0351] Initial Setup

[0352] User

[0353] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate an emotion engine to provide information about their current emotional state.

[0354] server

[0355] The server stores the information provided by the user in a database. Based on the address, it retrieves information about nearby supermarkets and online stores. It also collects information about the prices of ingredients at each store.

[0356] Emotion Recognition and Recipe Recommendation

[0357] Emotion Engine

[0358] The system recognizes the user's current emotions from their facial expressions and voice, and sends the emotional data to the server. For example, if the system recognizes that the user is feeling stressed, it will use that information to select ingredients and recipes.

[0359] server

[0360] The server searches for and selects the optimal recipe based on the entered refrigerator inventory data and the acquired emotional data. For example, if the user is feeling stressed, it will recommend dishes or teas that have a relaxing effect.

[0361] The server generates the selected recipe and a list of ingredients required and provides it to the user, giving priority to recipes that use ingredients already in the refrigerator.

[0362] Purchase recommendation

[0363] server

[0364] Based on the provided recipe, the system generates a list of ingredients that are not in the refrigerator. It identifies the most economical source of purchase for each ingredient and suggests it to the user. For example, it provides information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from online store X."

[0365] Based on information from the emotion engine, the system also recommends places to buy based on the user's emotions. For example, if the system recommends matcha to reduce stress, it will also recommend the best places to buy it.

[0366] Calorie and weight management

[0367] server

[0368] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. If the target weight is 60 kg, analyze the calorie information of the recipes based on the appropriate daily calorie intake.

[0369] It will suggest calorie adjustments and alternatives as needed, providing specific advice such as, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[0370] Terminal

[0371] Visually present users with recommended recipes and supplier information. Visually display detailed recipe instructions and ingredient information for recommended recipes, as well as multiple supplier information.

[0372] Based on the emotion recognition results of the emotion engine, the system also makes recommendations aimed at reducing stress and improving the user's mood. For example, the system might suggest, "You seem to be in the mood to relax a bit today. How about drinking some green tea?"

[0373] By displaying calculated calorie information and advice to users, users can follow a healthy meal plan and maintain a balanced diet.

[0374] Through these steps, the system supports the user's daily life by managing food expenses, calorie intake, and suggesting meals that are in line with their emotions, providing a more personalized dining experience. This allows the user to efficiently manage their living expenses and lead an appropriate dietary lifestyle according to their emotional state.

[0375] The processing flow will be explained below.

[0376] Step 1:

[0377] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate the emotion engine and provide their current emotional state.

[0378] Step 2:

[0379] The server stores the information provided by the user in a database, including address, number of household members, desired food budget, food concept, ability to cook at home, target weight, and refrigerator inventory.

[0380] SQL

[0381] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[0382] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[0383] Step 3:

[0384] The server retrieves information about nearby supermarkets and online stores based on the user's address, including the location, products, and prices of each store.

[0385] Python

[0386] nearest_stores = get_nearest_stores(user_address)

[0387] store_prices = fetch_store_prices(nearest_stores)

[0388] Step 4:

[0389] The emotion engine performs facial recognition or voice analysis of the user to analyze their current emotional state (e.g., stress, joy, sadness, etc.), and sends the results to the server.

[0390] Python

[0391] emotion_state = analyze_emotion(user_facial_expression)

[0392] send_emotion_data_to_server(emotion_state)

[0393] Step 5:

[0394] The server searches for the optimal recipe based on the user's emotional state, refrigerator inventory, and ingredient concept. For example, if the user is feeling stressed, it will prioritize dishes that are known to have a relaxing effect.

[0395] SQL

[0396] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept AND emotion_suitability = :emotion_state;

[0397] Step 6:

[0398] The server selects the most suitable recipe and sends its details (e.g., ingredients, cooking instructions) to the user terminal. For example, if "Teriyaki Chicken" is selected, the server provides the recipe details.

[0399] Python

[0400] recommended_recipe = select_best_recipe(available_recipes)

[0401] send_recipe_to_client(recommended_recipe)

[0402] Step 7:

[0403] The device visually displays details of the recommended recipe, including the ingredients list and cooking instructions.

[0404] HTML

[0405]

[0406] <h1>{{recommended_recipe.name}}< / h1>

[0407] {{recommended_recipe.ingredients}}

[0408] {{recommended_recipe.instructions}}

[0409]

[0410] Step 8:

[0411] The server generates a list of ingredients missing from the refrigerator based on the recommended recipe, including information identifying the most economical source for each ingredient.

[0412] SQL

[0413] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[0414] Step 9:

[0415] Based on the generated ingredient list, the server suggests the most economical and convenient place to buy ingredients, such as "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[0416] Python

[0417] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[0418] send_purchase_recommendations_to_client(purchase_recommendations)

[0419] Step 10:

[0420] The device displays a list of ingredients to be purchased and recommended places to purchase them to the user, allowing the user to shop efficiently.

[0421] HTML

[0422]

[0423] <h2>Recommended Shops< / h2>

[0424]

[0425] {% for item, shop in purchase_recommendations %}

[0426] {{item}} - Buy at {{shop}}

[0427] {% endfor %}

[0428]

[0429]

[0430] Step 11:

[0431] The server calculates the calories of the recommended recipe and checks it against the appropriate calorie amount based on the target weight. For example, if the target weight is 60 kg, the calorie information of the recipe is verified based on the appropriate calorie intake for that day.

[0432] Python

[0433] recipe_calories = calculate_calories(recommended_recipe)

[0434] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[0435] Step 12:

[0436] The server provides the user with advice on calorie management, such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[0437] Python

[0438] if recipe_calories <= daily_calorie_needs:

[0439] calorie_advice = "This meal fits within your daily calorie needs."

[0440] else:

[0441] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[0442] send_calorie_advice_to_client(calorie_advice)

[0443] Step 13:

[0444] The device visually displays calculated calorie information and advice, allowing users to follow a healthy eating plan.

[0445] HTML

[0446]

[0447] <h3>Calories: {{recipe_calories}}< / h3>

[0448] {{calorie_advice}}

[0449]

[0450] Through these steps, the system comprehensively supports users in managing their food expenses, calorie intake, and suggesting meals according to their emotions, allowing users to efficiently manage their living expenses and lead an appropriate diet according to their emotional state.

[0451] Example 2

[0452] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0453] Conventional meal plan suggestion systems make blanket suggestions without considering the user's basic information or current emotional state, making it difficult to provide personalized meal plans tailored to individual needs. Furthermore, because ingredients and recipes are not selected based on refrigerator inventory or the user's emotional state, there are problems with food waste and reduced user satisfaction. Furthermore, the number of potential suppliers is limited, making it difficult to make economical or convenient choices.

[0454] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of the user's address, number of households, desired cost, ingredient concept, ability to cook at home, target weight, and refrigerator inventory; means for acquiring information on nearby retailers or online stores based on the address; means for recognizing the user's emotional state by analyzing the user's facial expressions and voice; means for generating an optimal ingredient list and cooking method based on the input information, emotional state, and acquired retailer information; means for suggesting the most economical or convenient purchasing source based on the generated ingredient list; and means for calculating calorie intake based on the target weight and providing appropriate calorie advice. This makes it possible to provide a personalized meal plan tailored to the user's individual needs and current emotional state.

[0455] "User" refers to an individual who enters information into the system and receives a personalized meal plan.

[0456] "Address" refers to detailed information about the user's place of residence and is used to obtain information about nearby retailers and online stores.

[0457] "Number of households" refers to the number of people living in the user's household, and is information that affects meal plan portion sizes and food cost calculations.

[0458] "Desired spend" refers to the monthly or weekly budget that the user plans to spend on food.

[0459] "Ingredient concept" refers to the meal theme or ingredient characteristics desired by the user (e.g., healthy, low calorie, etc.).

[0460] "Ability to cook at home" refers to whether or not the user has the ability or desire to cook at home.

[0461] "Goal weight" refers to the weight the user wants to achieve, and is important information for calculating calories and creating meal plans.

[0462] "Refrigerator inventory" refers to a list of ingredients currently stored in the user's refrigerator.

[0463] "Store" refers to a physical store selling ingredients.

[0464] "Online Store" refers to an e-commerce site that sells products over the Internet.

[0465] "Emotional state" refers to the mood or psychological state of the user that is recognized based on facial expressions and voice data.

[0466] "Ingredient list" refers to a list of ingredients that the user needs to purchase.

[0467] "Recipe" refers to the steps or recipes for cooking using ingredients specified by the user.

[0468] "Purchasing point" refers to the retail store or online store where you purchase ingredients.

[0469] "Calories" refers to the amount of energy contained in an ingredient or dish and is used to calculate a meal plan relative to a user's weight goal.

[0470] The present invention relates to a system that proposes an optimal meal plan taking into account the user's input information and emotional state. The details of this system are described below.

[0471] User

[0472] The user logs into the system and enters their address, number of household members, desired cost, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is entered from the device the user uses (e.g., PC, smartphone, tablet). The user also activates the emotion engine and provides their current emotional state. At this time, emotions are detected using facial recognition and voice analysis. A specific example is shown below.

[0473] Examples:

[0474] The user enters the following information:

[0475] Address: Minato-ku, Tokyo

[0476] Number of people in the household: 2

[0477] Desired cost: 40,000 yen / month

[0478] Ingredients concept: Healthy food

[0479] Self-catering: Yes

[0480] Target weight: 60kg

[0481] Fridge stock: Chicken breast, broccoli, tofu

[0482] Next, the user's emotion engine is activated and recognizes that the user is feeling stressed.

[0483] server

[0484] The server stores the information provided by the user in a database. For example, it uses an SQL or NoSQL database to efficiently manage data. The server also accesses an API to obtain information about nearby retailers and online stores based on the user's address information. This involves large-scale data collection and analysis.

[0485] Furthermore, the server receives user emotional data and uses it to select ingredients and generate recipes. Emotion recognition uses image recognition technology (e.g., OpenCV) and natural language processing (e.g., Google Cloud's natural language API).

[0486] Examples:

[0487] The server uses the emotion data and refrigerator inventory data to suggest recipes such as:

[0488] "Healthy stir-fried chicken breast and broccoli"

[0489] Next, based on this recipe, a list of ingredients needed that are not in the refrigerator (e.g. olive oil, salt) is made.

[0490] Terminal

[0491] The device visually presents the information sent from the server to the user. Specifically, it displays recommended recipes, purchasing information, and calorie information. The user can confirm this information and proceed to purchase or execute the plan.

[0492] Examples:

[0493] The following information will be displayed on the terminal screen:

[0494] "New Recipe: Healthy Stir-fried Chicken Breast and Broccoli"

[0495] "Estimated calories: 500kcal per serving"

[0496] "Purchase information: Olive oil - nearest supermarket, Salt - Online Store Y"

[0497] Prompt Sentence Examples

[0498] Below are some example prompts to input to the generative AI model:

[0499] User-entered information:

[0500] Address: Minato-ku, Tokyo

[0501] Number of people in the household: 2

[0502] Desired cost: 40,000 yen / month

[0503] Ingredients concept: Healthy food

[0504] Self-catering: Yes

[0505] Target weight: 60kg

[0506] Fridge stock: Chicken breast, broccoli, tofu

[0507] Current emotional state: I'm stressed

[0508] Use this information to provide users with the perfect meal plan, and if they don't have the ingredients they need for a recipe in their fridge, provide them with information on where to buy them.

[0509] As described above, this system generates meal plans based on the user's input information and emotional state and provides them visually, thereby enabling personalized meal suggestions tailored to individual needs.

[0510] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0511] Step 1: User Input

[0512] User

[0513] Users log in to the system and enter their address, number of household members, desired cost, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory.

[0514] It also activates the emotion engine and provides the current emotional state.

[0515] input

[0516] Address, number of households, desired expenses, food concept, ability to cook at home, target weight, refrigerator inventory, emotional state

[0517] Specific actions

[0518] The user enters the necessary information into the device interface and clicks the "Send" button. The emotion engine uses a camera and microphone to collect facial and voice data.

[0519] output

[0520] The entered data is sent to the server.

[0521] Step 2: Storing and Retrieving Data

[0522] server

[0523] The server stores the information provided by the user in a database.

[0524] Obtain information on nearby retailers and online stores based on address information.

[0525] input

[0526] Input data submitted by the user

[0527] Specific actions

[0528] The server uses an SQL or NoSQL database to structure and store user information, and then uses an API to collect information from merchants.

[0529] output

[0530] User information stored in the database and price information obtained from retailers

[0531] Step 3: Emotion Recognition

[0532] Emotion Engine

[0533] It analyzes the user's facial expressions and voice data to recognize their current emotions.

[0534] The recognized emotion data is sent to the server.

[0535] input

[0536] Facial expression and voice data collected by cameras and microphones

[0537] Specific actions

[0538] The emotion engine analyzes emotions using image recognition technology (e.g., OpenCV) and natural language processing technology.

[0539] output

[0540] Recognized emotional state data is generated and transmitted to a server.

[0541] Step 4: Select and generate a recipe

[0542] server

[0543] Search and select the best recipes based on refrigerator inventory data and sentiment data.

[0544] Generate recipes along with ingredient lists.

[0545] input

[0546] Refrigerator inventory data, sentiment data, retailer information

[0547] Specific actions

[0548] It queries a large recipe database and selects recipes based on the user's emotional state. It applies a filtering algorithm to determine the best recipe.

[0549] output

[0550] Selected recipes and ingredient lists

[0551] Step 5: Recommend a supplier

[0552] server

[0553] Generate a list of ingredients that are not in the refrigerator and identify the most economical source of each ingredient.

[0554] It also makes recommendations on where to buy based on emotional data.

[0555] input

[0556] Recipes, ingredient lists, retailer information, emotional data

[0557] Specific actions

[0558] It uses cost calculation algorithms to select economical purchasing sources, and also suggests the best places to buy specific ingredients based on sentiment data.

[0559] output

[0560] Recommended Purchase List

[0561] Step 6: Counting and adjusting calories

[0562] server

[0563] Calculate the calorie information for recommended recipes and compare it with the appropriate calorie amount based on your target weight.

[0564] Suggest calorie adjustments or alternatives as needed.

[0565] input

[0566] Recipe data, target weight

[0567] Specific actions

[0568] It uses a calorie counting algorithm to calculate the calories in each recipe, calculates your daily calorie intake based on your target weight, and offers alternative suggestions if adjustments are needed.

[0569] output

[0570] Calorie calculation results and adjustment suggestions

[0571] Step 7: Visualizing the results

[0572] Terminal

[0573] To provide information from a server to a user visually.

[0574] View recipes, where to buy, and calorie information.

[0575] input

[0576] Recipes, ingredient lists, purchasing information, and calorie information sent from the server

[0577] Specific actions

[0578] The information is displayed on the device interface for the user to check, and the user can check the displayed information through the device and decide on the next action.

[0579] output

[0580] Information presented visually to the user

[0581] (Application example 2)

[0582] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0583] Currently, there are systems that provide personalized meal plans, but they do not adequately recommend ingredients and recipes that take into account the user's emotional state. Furthermore, there are no systems that reflect refrigerator inventory information and provide emotional personalization. Therefore, it is difficult to effectively provide meal suggestions that help users relax and maintain their health.

[0584] The specific processing 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 receiving input of the user's address, number of households, desired food expenses, ingredient concept, ability to cook at home, target weight, refrigerator inventory, and emotional state; means for acquiring information on nearby commercial facilities or electronic commerce sites based on the address; means for generating an optimal ingredient list and cooking method based on the input information and the acquired commercial facility information; means for suggesting the most economical or convenient purchasing source based on the generated ingredient list; means for calculating calorie intake based on the target weight and providing appropriate calorie advice; and means for recommending ingredients and recipes tailored to the user based on the emotional state. This makes it possible to provide a personalized meal plan that takes the user's emotional state into consideration.

[0585] An "address" is geographical information that indicates where a user lives.

[0586] "Number of households" is information indicating the number of people residing in a particular residence.

[0587] "Desired food expenses" is information indicating the amount of money the user wishes to spend on ingredients and meals.

[0588] "Ingredient concept" is information that indicates the theme or philosophy of the ingredients or dishes that the user likes.

[0589] "Ability to cook at home" is information indicating whether the user has the ability or motivation to cook for themselves.

[0590] "Target weight" is information indicating the weight that the user wishes to achieve.

[0591] "Refrigerator inventory" is information showing a list of ingredients currently stored in the user's refrigerator.

[0592] "Emotional state" is information that indicates the user's current psychological and emotional state.

[0593] "Commercial facility" means a store selling food and daily necessities.

[0594] "Electronic Venue" means an online store where goods can be purchased over the Internet.

[0595] The "optimal ingredient list" indicates a list of ingredients that are most suitable for the user's needs.

[0596] A "cooking method" is a recipe or procedure for cooking a dish using specific ingredients.

[0597] "Economical or convenient purchasing location" refers to the place where the user can purchase ingredients that offers the best cost performance or convenience.

[0598] "Intake of calories" refers to the total amount of energy that a user takes in within a certain period of time.

[0599] "Calorie advice" refers to advice on the recommended calorie intake to achieve the user's goal weight.

[0600] "Personalized meal plan" refers to a meal plan that is customized based on an individual user's personal information and emotional state.

[0601] The following describes an embodiment of the present invention.

[0602] System configuration

[0603] The system consists of a user's smartphone, a server, and a communication network via the Internet. The user's smartphone includes an emotion recognition engine, a voice recognition engine, and a data entry interface. The server includes a database management system, a recipe generation engine, a calorie calculation library, and a delivery API.

[0604] Hardware and Software

[0605] Smartphone: Uses OpenCV and dlib for facial expression recognition, and Google Cloud Speech-to-Text for voice recognition.

[0606] Server: We use MySQL as our database management system, with custom libraries for calorie calculation and recipe generation. Delivery information is obtained from a number of online APIs (e.g. UberEats and other delivery integration APIs).

[0607] Program processing overview

[0608] User Input

[0609] The user uses a smartphone to input information such as address, number of household members, desired food budget, ingredient concept, ability to cook at home, target weight, refrigerator inventory, and current emotional state. The emotional state is acquired using the smartphone's camera and voice interface. Facial expressions are analyzed using a facial recognition engine (e.g., OpenCV and dlib), and the voice data is converted into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text).

[0610] Data Processing and Recipe Generation

[0611] The server stores the received user information in a database. Based on the address, information on nearby commercial facilities and electronic trading locations is obtained via API. Next, the optimal ingredient list and cooking method is generated based on the input and obtained information. Specifically, it suggests ingredients that reduce stress and recipes that have a relaxing effect based on the user's emotional state. It also uses the inventory in the refrigerator to avoid the need to purchase unnecessary ingredients.

[0612] Economical purchasing suggestions

[0613] Based on the generated ingredient list, the server searches for the most economical or convenient source of purchase via API and suggests it to the user. For example, it compares whether the ingredients needed for a particular dish are cheaper at a nearby commercial facility or an online store, and provides the user with the optimal source of purchase.

[0614] Calorie Management and Calorie Advice

[0615] The server calculates the user's daily calorie intake based on their target weight, evaluates the calorie content of the suggested recipes, and, if necessary, provides the user with alternative recipes with adjusted calorie content or additional advice.

[0616] Specific examples

[0617] For example, if a user is feeling stressed at work and wants to relax during lunchtime, the system will suggest relaxing "ochazuke" (rice with green tea) or "relaxing tea" based on the user's emotional state, and provide information on the nearest commercial facility or online store where to purchase the ingredients needed for these. It will also provide calorie information and suggest balanced meals based on the user's target weight and current calorie intake.

[0618] Prompt Sentence Examples

[0619] "If a user is feeling stressed at work, suggest a relaxing dish. Or search for nearby delivery services and provide the best options."

[0620] In this way, the present invention is able to provide a personalized meal plan that takes into account the user's emotional state and daily needs.

[0621] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0622] Step 1: Enter your user information

[0623] The user uses a smartphone to input their address, household size, desired food budget, ingredient concept, whether they can cook at home, target weight, refrigerator inventory, and current emotional state. The input information is sent to the server through the smartphone's data input interface. This process collects the individual information and emotional state required for the system.

[0624] Input: User's address, number of household members, desired food budget, food concept, whether self-cooking is possible, target weight, refrigerator inventory, emotional state

[0625] Output: Sending information to the server

[0626] Step 2: Recognizing your emotional state

[0627] The device's camera and microphone are used to recognize the user's current emotional state from their facial expressions and voice. The device processes the facial expression data using an emotion recognition engine (e.g., OpenCV and dlib), converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text), and determines the emotion. The analysis results are sent to the server.

[0628] Input: User's facial expression data, voice data

[0629] Output: Judgment result of the user's emotional state

[0630] Step 3: Storing information in a database

[0631] The server stores the received user information in a database. A database management system (e.g., MySQL) is used to efficiently manage information such as user profiles, refrigerator inventory, and emotional states.

[0632] Input: User information (address, number of households, etc.), emotional state

[0633] Output: Save information to a database

[0634] Step 4: Obtain information on nearby commercial facilities

[0635] Based on the address, the server retrieves information about nearby commercial facilities and online stores via API, including information on the prices of ingredients at each store.

[0636] Input: User's address

[0637] Output: Information about commercial facilities and online stores

[0638] Step 5: Generate a recipe and ingredient list

[0639] The server generates an optimal ingredient list and recipe based on the input information and acquired commercial facility information, taking into account refrigerator inventory and emotional state, and selecting ingredients and recipes that have a relaxing effect according to the emotional state.

[0640] Input: User information, commercial facility information, emotional state

[0641] Output: Ingredient list and recipe

[0642] Step 6: Propose a supplier

[0643] Based on the generated list of ingredients, the server compares prices and delivery terms using delivery APIs (e.g., Uber Eats and other delivery integration APIs) to suggest the most economical or convenient shopping locations. Based on this information, the server suggests the most suitable shopping locations for the user.

[0644] Input: Ingredient list

[0645] Output: Buyer suggestions

[0646] Step 7: Calorie counting and advice

[0647] The server calculates calorie intake based on the user's target weight, evaluates the calorie information of the generated recipe, and provides the user with alternative recipes with adjusted calorie amounts or additional advice, if necessary.

[0648] Input: Recipe, Goal Weight

[0649] Output: Calorie calculation results, advice provided

[0650] Step 8: Provide visual information

[0651] The device visually presents recommended recipes and vendor information to the user, displaying detailed recipe steps, ingredient information, multiple vendor information, and calorie information through a visual interface.

[0652] Input: Recipe, supplier information, calorie calculation results

[0653] Output: A visual display to the user

[0654] Through these steps, users can efficiently receive meal plans tailored to their emotional state and lead a healthy and personalized diet.

[0655] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0656] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0657] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0658] [Second embodiment]

[0659] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0660] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0661] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0662] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0663] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0664] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0665] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0666] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0667] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0668] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0669] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0670] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0671] The system of the present invention starts with the user inputting their address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, and then uses that information to suggest optimal daily meals and purchasing locations for each user. The program processing of the system of the present invention is explained below in natural language.

[0672] Initial Setup

[0673] User

[0674] First, the user logs into the system and enters their address, number of household members (e.g., 2 people), desired food budget (30,000 yen per month or 1,000 yen per day), food concept (mainly Japanese food), whether they can cook at home (possible), target weight (60 kg), and refrigerator inventory (e.g., rice, miso, chicken, etc.).

[0675] server

[0676] The server then stores the information provided by the user in a database.

[0677] The server obtains information on nearby supermarkets and online stores based on the user's address, as well as price information on ingredients sold at each store.

[0678] Ingredient and recipe recommendations

[0679] server

[0680] The input information is analyzed and a recipe that prioritizes the use of the refrigerator's inventory is searched for. For example, if there is rice and chicken, the recipe for "Teriyaki Chicken" is selected.

[0681] The ingredient concept is centered around Japanese cuisine and cooking at home is possible, so suitable Japanese recipes will be recommended.

[0682] Terminal

[0683] The recommended recipes are displayed on the user's device. For example, if a teriyaki chicken recipe is recommended, the cooking instructions and details of the ingredients are displayed.

[0684] Suggestions for where to buy ingredients

[0685] server

[0686] Based on the recommended recipe, a list of ingredients that are not in the user's refrigerator is created. For example, if it turns out that soy sauce, sugar, and ginger are not in the refrigerator, a purchase list for these items is generated.

[0687] Next, the system selects the most economical store for each ingredient based on price information from the nearest supermarket or online store and suggests it to the user.

[0688] Terminal

[0689] The user's device displays a list of ingredients needed and recommended places to buy them. For example, the information provided may include "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[0690] Calorie intake and weight management

[0691] server

[0692] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. For example, if the target weight is 60 kg, calculate the daily calorie intake and check whether the recommended recipes fall within that range.

[0693] It will suggest calorie adjustments and alternatives as needed, for example, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[0694] Terminal

[0695] The user's device will display a healthy meal plan along with calculated calorie information, such as "Today's menu is 1500 kcal in total, which is a good balance for your calorie goal."

[0696] The present invention thereby automates a series of processes for users to efficiently manage their living expenses and lead a balanced diet, thereby providing full support to users in both food expenses and health management.

[0697] The processing flow will be explained below.

[0698] Step 1:

[0699] Users log in to the system and enter their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory, allowing them to register their lifestyle and food preferences in the system.

[0700] Step 2:

[0701] The server stores the information provided by the user in a database, which is used for further analysis and recommendations.

[0702] SQL

[0703] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[0704] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[0705] Step 3:

[0706] The server obtains information about nearby supermarkets and online stores based on the user's address. This information is collected using APIs that reference the acquired store data.

[0707] Python

[0708] nearest_stores = get_nearest_stores(user_address)

[0709] store_prices = fetch_store_prices(nearest_stores)

[0710] Step 4:

[0711] The server analyzes the user's input information and searches for recipes that prioritize the use of existing refrigerator inventory. For example, if "rice" and "chicken" are in stock, the server searches for a recipe for "teriyaki chicken."

[0712] SQL

[0713] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept;

[0714] Step 5:

[0715] The server selects the most suitable recipe and sends the recommended recipe information to the user terminal. For example, a recipe for "Teriyaki Chicken" is provided, along with cooking instructions and details of the ingredients required.

[0716] Step 6:

[0717] The device displays the recommended recipes to the user, for example, providing a detailed visual recipe for teriyaki chicken.

[0718] HTML

[0719]

[0720] <h1>{{recommended_recipe.name}}< / h1>

[0721] {{recommended_recipe.ingredients}}

[0722] {{recommended_recipe.instructions}}

[0723]

[0724] Step 7:

[0725] The server generates a list of ingredients that are missing from the refrigerator based on the recommended recipe. For example, if soy sauce, sugar, or ginger are missing, the server adds these items to the list.

[0726] SQL

[0727] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[0728] Step 8:

[0729] The server lists the most economical places to purchase each ingredient and suggests them to the user, such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar at online store X."

[0730] Python

[0731] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[0732] Step 9:

[0733] The device displays a list of ingredients to purchase and recommended places to buy them to the user, organizing and presenting the information in a format that is visually easy for the user to understand.

[0734] HTML

[0735]

[0736] <h2>Recommended Shops< / h2>

[0737]

[0738] {% for item, shop in purchase_recommendations %}

[0739] {{item}} - Buy at {{shop}}

[0740] {% endfor %}

[0741]

[0742]

[0743] Step 10:

[0744] The server calculates the calories of the recommended recipes and compares them with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server analyzes the calorie information of the recipes based on the appropriate daily calorie intake.

[0745] Python

[0746] recipe_calories = calculate_calories(recommended_recipe)

[0747] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[0748] Step 11:

[0749] The server provides the user with advice on calorie management. For example, specific advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[0750] Python

[0751] if recipe_calories <= daily_calorie_needs:

[0752] calorie_advice = "This meal fits within your daily calorie needs."

[0753] else:

[0754] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[0755] Step 12:

[0756] The device displays the calculated calorie information and advice to the user, allowing them to follow a healthy eating plan.

[0757] HTML

[0758]

[0759] <h3>Calories: {{recipe_calories}}< / h3>

[0760] {{calorie_advice}}

[0761]

[0762] Through these steps, the system comprehensively supports users in managing food expenses, calorie intake, and maintaining a healthy diet.

[0763] Example 1

[0764] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0765] In today's busy lifestyles, it is difficult for many people to efficiently plan, purchase, and manage their health. This challenge is especially significant for users who want to maintain a balanced diet on a limited budget. Many users also want to avoid wasting ingredients they already have at home and shop economically by effectively utilizing nearby store information. To solve these problems, an automated meal planning and purchasing suggestion system tailored to the user's needs is needed.

[0766] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0767] In this invention, the server includes means for receiving input of a user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for acquiring information on nearby stores or online stores based on the address, means for generating an optimal ingredient list and recipe based on the input information and the acquired store information, means for suggesting the most economical or convenient purchasing source based on the generated ingredient list, means for calculating calorie intake based on the target weight and providing appropriate calorie advice, and means for visually displaying the recommended recipe and purchasing source information on the user terminal. This allows users to efficiently plan their ingredient purchases and maintain a healthy and balanced diet while shopping economically and without waste.

[0768] "User" refers to an individual or household using the system.

[0769] "Address" refers to geographic information of the place where the user resides.

[0770] "Number of households" refers to the number of people in the household to which the user belongs.

[0771] "Desired food budget" refers to the monthly or daily budget set by the user for meals.

[0772] "Ingredient concept" refers to a guideline for a specific food culture or cooking style that a user prefers, such as "mainly Japanese food."

[0773] "Self-cooking" refers to whether the user is able to cook at home.

[0774] "Target weight" refers to the weight that the user wants to achieve.

[0775] "Refrigerator inventory" refers to the types and quantities of ingredients currently in the user's refrigerator.

[0776] "Server" refers to the computer system that performs the central calculations and stores data for this system.

[0777] "Store information" refers to data about nearby stores or online stores obtained based on the user's address.

[0778] An "ingredient list" is a list of ingredients needed by the user, and is used for creating recipes and planning purchases.

[0779] A "recipe" refers to information that describes the steps and ingredients needed to prepare a dish.

[0780] "Purchasing locations" refers to stores and online stores suggested for users to purchase ingredients.

[0781] "Calories intake" refers to the amount of calories consumed by a user in a certain period of time.

[0782] "Calorie Advice" refers to advice based on recommended calorie intake for a user to achieve a weight goal.

[0783] "User terminal" refers to a device, such as a computer, smartphone, or tablet, that a user uses to access the system.

[0784] "Visually displaying" refers to presenting information in an easy-to-read format on the screen of a user terminal.

[0785] MODE FOR CARRYING OUT THE INVENTION

[0786] The system of the present invention proposes optimal daily cooking and food purchasing locations for users based on multiple pieces of information provided by the user. This system is composed of a combination of hardware and software, and a specific example is shown below.

[0787] Initial Setup

[0788] User

[0789] First, the user logs in to the system and enters the address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory information. Specifically, the following information is entered:

[0790] Address: Tokyo

[0791] Number of people in the household: 2

[0792] Desired food expenses: 30,000 yen per month

[0793] Ingredients concept: Japanese cuisine

[0794] Self-catering: Yes

[0795] Target weight: 60kg

[0796] Refrigerator inventory: rice, miso, chicken

[0797] Information storage and analysis

[0798] server

[0799] The server stores the information entered by the user in a database. The database used for this is a relational database such as MySQL or PostgreSQL. Based on the stored information, the server collects information about nearby stores and online stores based on the user's address. This information is collected using web scraping technologies such as Python's BeautifulSoup and Scrapy.

[0800] Recipe Recommendations

[0801] server

[0802] Next, the server searches for recipes that prioritize the refrigerator inventory information provided by the user. For example, if there is rice and chicken in the refrigerator, a recipe such as "Teriyaki Chicken" will be selected. Also, since the ingredient concept is centered on Japanese cuisine, the server will recommend suitable recipes from among Japanese cuisine recipes.

[0803] Viewing Recipes

[0804] Terminal

[0805] The recommended recipes are displayed on the user's device. They are presented in a visually easy-to-understand format using HTML and JavaScript. For example, if a recipe for "teriyaki chicken" is recommended, the cooking instructions and details of the ingredients are displayed on the user's device.

[0806] Suggestions for where to buy ingredients

[0807] server

[0808] Based on the recommended recipe, the server creates a list of ingredients that the user does not have in their refrigerator. For example, if soy sauce, sugar, or ginger are missing, they are added to the shopping list. The server then suggests the most economical way to purchase the ingredients based on price information from the nearest supermarket or online store.

[0809] View shopping list

[0810] Terminal

[0811] The user's device will display a list of ingredients needed and recommended places to buy them. For example, it will show information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from an online store."

[0812] Calorie intake and weight management

[0813] server

[0814] The server calculates the calorie information of the recommended recipes and compares it with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server sets the daily calorie intake to 1800 kcal and checks whether the provided recipes fall within that range.

[0815] View calorie information and meal plans

[0816] Terminal

[0817] A healthy meal plan is displayed on the user's device along with calculated calorie information. For example, advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie goal of 1500 kcal" is shown.

[0818] Examples and prompts

[0819] As a concrete example, here is how the system operates based on the information above:

[0820] 1. Address: Tokyo

[0821] 2. Number of people in the household: 2

[0822] 3. Desired food expenses: 30,000 yen per month

[0823] 4. Ingredients concept: Japanese cuisine

[0824] 5. Self-catering: Yes

[0825] 6. Target weight: 60kg

[0826] 7. Refrigerator inventory: rice, miso paste, chicken

[0827] Based on this, the system makes recommendations such as:

[0828] Recommended recipe: Teriyaki Chicken

[0829] Shopping list: soy sauce, sugar, ginger

[0830] Where to buy: Soy sauce from your local supermarket, sugar from an online store

[0831] Prompt Sentence Examples

[0832] "Enter the user's address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory to display a list of recommended recipes and where to buy them."

[0833] As described above, the present invention is a comprehensive system that allows users to efficiently plan food purchasing, maintain a balanced diet, and manage their health.

[0834] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0835] Step 1: Enter your information

[0836] Input: The user enters their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory into the system.

[0837] Specific operation: The user logs in to a dedicated application or website using a smartphone or computer and enters the necessary information. For example, they enter information such as: living in Tokyo, household size: 2 people, desired food budget: 30,000 yen per month, mainly Japanese food, able to cook at home, target weight: 60 kg, and having rice, miso, and chicken in the refrigerator.

[0838] Output: The system receives user input.

[0839] Step 2: Store and analyze information

[0840] Input: Information entered by the user.

[0841] What it does: The server receives the information entered by the user and stores it in a database, using a relational database such as MySQL or PostgreSQL.

[0842] Output: Stored user information data. The server uses this data to:

[0843] Step 3: Gather information about nearby stores

[0844] Input: User's address information.

[0845] Specific operation: Based on the user's address, the server uses web scraping technology (e.g., Python's BeautifulSoup or Scrapy) to collect information on nearby supermarkets and online stores. For example, it collects price information for large supermarkets and online grocery stores in a specific area of ​​Tokyo.

[0846] Output: Collected nearby store and price information data.

[0847] Step 4: Find a recipe

[0848] Input: User's refrigerator inventory information, ingredient concept.

[0849] Specific operation: The server searches the recipe database for the corresponding recipe based on the input refrigerator inventory information. For example, if there is rice and chicken in the refrigerator, it searches for Japanese recipes that use these ingredients.

[0850] Output: A list of suitable recipes that were found.

[0851] Step 5: Recipe Selection

[0852] Input: Recipe search results.

[0853] Specific operation: The server recommends the best recipe based on the ingredient concept (e.g., mainly Japanese food). As a specific example, the recipe "Teriyaki Chicken" using chicken and rice is selected.

[0854] Output: Recommended recipe information.

[0855] Step 6: View the recipe

[0856] Input: Recommended recipe information.

[0857] What it does: The recommended recipe is displayed on the user's device. The recipe steps and ingredient details for "Teriyaki Chicken" are visually displayed on the screen using HTML and JavaScript.

[0858] Output: Recipe information displayed on the user's device.

[0859] Step 7: Make a list of ingredients you need

[0860] Input: Recommended recipe information, user's refrigerator inventory information.

[0861] Specific behavior: The server creates a list of ingredients that are missing from the user's refrigerator based on the recommended recipe. For example, if a teriyaki chicken recipe requires soy sauce, sugar, and ginger, but these are not in the refrigerator, the server adds them to the list.

[0862] Output: A list of ingredients needed.

[0863] Step 8: Propose a supplier

[0864] Input: List of ingredients needed, information on nearby stores.

[0865] Specific operation: The server selects the most economical and convenient place to purchase and suggests it to the user. For example, it suggests that the nearest supermarket is the cheapest place to buy soy sauce, and the online store is the cheapest place to buy sugar.

[0866] Output: Recommended vendor information.

[0867] Step 9: View your shopping list

[0868] Input: list of ingredients needed, recommended purchasing information.

[0869] Specific behavior: The recommended purchasing locations and a list of ingredients needed are displayed on the user's device. The user is given specific instructions, such as "Purchase soy sauce at the nearest supermarket and sugar at online store X."

[0870] Output: Shopping list information displayed on the user's device.

[0871] Step 10: Calculate calorie information

[0872] Input: Recommended recipe information, user's goal weight.

[0873] Specific operation: The server calculates the calorie information of the recommended recipe and compares it with the appropriate calorie schedule based on the user's target weight. For example, if the target weight is 60 kg, it sets the daily calorie intake to 1800 kcal and checks whether it falls within that range.

[0874] Output: Calorie count and calorie advice.

[0875] Step 11: View calorie information and meal plans

[0876] Input: Calorie count and calorie advice.

[0877] What it does: A healthy meal plan is displayed on the user's device along with calculated calorie information, and specific advice is given, such as "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie goal of 1500 kcal."

[0878] Output: Calorie information and meal plan displayed on user device.

[0879] As described above, this system provides comprehensive support for users to efficiently plan food purchases, maintain a balanced diet, and manage their health.

[0880] (Application example 1)

[0881] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0882] Conventional meal recommendation systems focus on supporting home cooking based on information entered by the user, but in real life, there are many situations where home cooking is not possible or people prefer to eat out. Furthermore, maintaining a healthy diet requires consideration of specific calorie intake and nutritional balance, but existing systems have difficulty providing comprehensive support for these. Therefore, there was a need for a system that could provide optimal meal recommendations not only for home cooking, but also for eating out or ordering food delivery.

[0883] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0884] In this invention, the server includes means for receiving input from the user of the user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for obtaining information on nearby stores or online stores, means for generating optimal ingredient lists and recipes, means for obtaining restaurant menus and recommending optimal menus, and means for arranging orders through affiliated food delivery services. This allows users to receive economical and healthy meal suggestions for a variety of eating habits, including not only cooking at home but also eating out and food delivery.

[0885] A "user" is an entity that uses this system, and is an individual or group that provides information such as address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory.

[0886] An "address" is information used to identify the location where a user resides, and is data necessary for procuring ingredients from nearby stores or online stores and using food delivery services.

[0887] "Number of households" indicates the number of people living at the same address, and is necessary to properly calculate recommended recipes and ingredient amounts.

[0888] "Desired food budget" is information indicating the budget that the user can spend on ingredients and meals, and is a standard value for suggesting economical ingredient lists and purchasing locations.

[0889] "Ingredient concept" is information that indicates the user's preferred eating style or cuisine genre, and is a criterion when selecting recommended recipes and menus.

[0890] "Ability to cook at home" is information that indicates the user's ability and willingness to cook at home, and is a criterion for determining whether or not a recommendation of a restaurant menu is necessary.

[0891] "Target weight" is information indicating the weight that the user wants to achieve, and is data necessary for calculating calorie intake and providing calorie advice.

[0892] "Refrigerator inventory" is information showing a list of ingredients that the user currently owns, and is data that serves as a basis for providing economical recipes that use inventory as much as possible.

[0893] "Store or online store information" refers to information about physical stores located near the user's address or places where ingredients can be purchased online, including price information and information about ingredients available.

[0894] The "optimal ingredient list" is a list of the most economical and nutritionally balanced ingredients based on information such as the user's desired food budget, ingredient concept, and whether or not they can cook at home.

[0895] A "recipe" is information that indicates the cooking steps and details of the ingredients required, generated based on information provided by the user.

[0896] The "dining out menu" is a list of recommended dishes for when the user is unable to cook at home or wishes to eat out, and is selected based on the user's nutritional balance and calorie goals.

[0897] A "food delivery service" is a service in which food is delivered to a user's address by an affiliated company or service provider, allowing users to easily enjoy restaurant menus in the comfort of their own home.

[0898] The "means for arranging an order" refers to a means for enabling a user to quickly and reliably order and use the restaurant menu selected by the user through a food delivery service.

[0899] This invention is a system that proposes optimal meals based on information provided by users to support their diverse dietary habits. This system is configured to accommodate not only users who cook at home, but also those who wish to eat out or use food delivery services.

[0900] System configuration

[0901] 1. User Device

[0902] Users access the system using a device such as a smartphone and enter information such as their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is necessary to make meal suggestions based on the user's specific needs and environment. User devices are built using a cross-platform development environment such as React Native.

[0903] 2. Server

[0904] The server plays a central role in storing the information collected from users in a database (MongoDB) and performing the following processes:

[0905] Information collection: Using Google Maps API, etc., we collect information about nearby stores or online stores based on the user's address.

[0906] Recipe generation: Using a generative AI model (OpenAI GPT-4), the optimal recipe is generated based on the input information.

[0907] Ingredient list generation: Generates a list of ingredients needed based on a recipe and suggests economical and convenient places to buy them.

[0908] Calorie Calculation: Calculates calorie intake based on your target weight and provides appropriate calorie advice.

[0909] Dining menu recommendation: For users who wish to eat out, the app recommends the most suitable dining menu and arranges the order through a partner food delivery service.

[0910] Specific examples

[0911] For example, if a user enters the following information:

[0912] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[0913] Number of household members: 2

[0914] Desired food expenses: 30,000 yen per month

[0915] Ingredients concept: Mainly Japanese cuisine

[0916] Self-catering: Possible

[0917] Target weight: 60kg

[0918] Refrigerator inventory: rice, miso, chicken

[0919] With this information, the server does the following:

[0920] 1. Use the Google Maps API to get information about supermarkets and online stores around Shibuya Ward.

[0921] 2. Using a generative AI model (OpenAI GPT-4), generate recipes such as "Teriyaki Chicken" based on the inventory in the refrigerator.

[0922] 3. It creates a list of ingredients needed for the generated recipe and suggests the best places to buy them based on that list. For example, it suggests buying soy sauce at the nearest supermarket and sugar at an online store.

[0923] 4. Calculate calories and ensure the user meets the calorie goal. For example, calculate that one serving of teriyaki chicken is 500 kcal, and ensure that the user is within the calorie goal even if they eat it three times a day.

[0924] 5. If you can't cook or prefer to eat out, Google Maps will use its API to find nearby healthy restaurants and recommend dishes like a salmon and avocado salad bowl (500 kcal per serving). It will then arrange the order through a partner food delivery service.

[0925] This flow allows users to receive healthy and economical meal suggestions for both home cooking and eating out.

[0926] Example prompts

[0927] User Information:

[0928] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[0929] Number of people in the household: 2

[0930] Desired food expenses: 30,000 yen per month

[0931] Ingredients concept: Japanese cuisine

[0932] Self-catering: Yes

[0933] Target weight: 60kg

[0934] Refrigerator inventory: rice, miso, chicken

[0935] Based on this, please tell me a Japanese recipe that prioritizes using the stock in your refrigerator. Also, please provide the ingredients needed, where to buy them, and the associated calorie information.

[0936] This configuration provides comprehensive support for the user's eating habits, enabling them to maintain eating habits efficiently and economically.

[0937] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0938] Step 1:

[0939] A user logs in to the application using a smartphone. The user inputs information such as address, number of household members, desired food budget, ingredient concept, ability to cook at home, target weight, and refrigerator inventory. This input information provides basic parameters related to the user's eating habits.

[0940] Processing: The user launches the application, enters information, and presses the send button. The input information is sent from the terminal to the server.

[0941] Input: Address, number of households, desired food budget, food concept, whether you can cook at home, target weight, refrigerator inventory

[0942] Output: Input sent to the server

[0943] Step 2:

[0944] The server stores the received user input information in a database (MongoDB), which allows for centralized management of data required for subsequent processing.

[0945] Processing: The server parses the input information and stores it in a database.

[0946] Input: Information submitted by the user

[0947] Output: User information stored in the database

[0948] Step 3:

[0949] The server uses the Google Maps API to obtain information about nearby stores or online stores based on the user's address.

[0950] Processing: The server inputs the user's address into the Google Maps API and retrieves information about nearby stores.

[0951] Input: User's address

[0952] Output: Store or online store information

[0953] Step 4:

[0954] The server uses a generative AI model (OpenAI GPT-4) to generate an optimal recipe based on the input information and store information. This recipe prioritizes the use of the inventory in the user's refrigerator.

[0955] Processing: The server inputs the prompt sentences into the AI ​​model and generates the optimal recipe.

[0956] Input: User input information, store information

[0957] Output: The generated recipe

[0958] Step 5:

[0959] The server creates a list of ingredients required for the generated recipe and suggests the most economical and convenient place to buy them based on that list.

[0960] Processing: The server analyzes the recipe, creates a list of ingredients needed, and searches for where to purchase each ingredient.

[0961] Input: Generated recipe, store information

[0962] Output: Optimal ingredients list and purchasing information

[0963] Step 6:

[0964] The server calculates calorie intake based on the user's target weight and checks whether the target recipe is within the appropriate calorie range.

[0965] Processing: The server calculates the calorie information of the recipe and evaluates whether it is suitable for the target weight.

[0966] Input: Generated recipe, target weight

[0967] Output: Calorie intake information and calorie advice

[0968] Step 7:

[0969] If the user wants to eat out, the server uses the Google Maps API to retrieve the menus of nearby healthy restaurants and recommends the most suitable menu based on the user's nutritional balance and calorie goals.

[0970] Processing: The server searches for and recommends restaurant menus based on the user's preferences.

[0971] Input: User's preference, address, target weight

[0972] Output: Optimal dining out menu

[0973] Step 8:

[0974] The server will arrange to order the selected restaurant menu through an affiliated food delivery service.

[0975] Processing: The server sends the dining out menu selection results to the food delivery service API and arranges the order.

[0976] Input: Selected restaurant menu information

[0977] Output: Order placement completion information

[0978] Step 9:

[0979] The user terminal visually displays the recipe, ingredient list, supplier information, calorie intake information, restaurant menu, and order status received from the server.

[0980] Processing: The user terminal converts the received information into a display format and presents it visually to the user.

[0981] Input: Information sent from the server

[0982] Output: Information presented visually to the user

[0983] Through these steps, users can receive healthy and economical meal suggestions for both home cooking and eating out.

[0984] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0985] The system of the present invention provides the user with the optimal meal plan based on various input information from the user (address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, refrigerator inventory). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to recommend recipes and ingredients according to the user's emotional state, making the user's dining experience more personalized.

[0986] Initial Setup

[0987] User

[0988] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate an emotion engine to provide information about their current emotional state.

[0989] server

[0990] The server stores the information provided by the user in a database. Based on the address, it retrieves information about nearby supermarkets and online stores. It also collects information about the prices of ingredients at each store.

[0991] Emotion Recognition and Recipe Recommendation

[0992] Emotion Engine

[0993] The system recognizes the user's current emotions from their facial expressions and voice, and sends the emotional data to the server. For example, if the system recognizes that the user is feeling stressed, it will use that information to select ingredients and recipes.

[0994] server

[0995] The server searches for and selects the optimal recipe based on the entered refrigerator inventory data and the acquired emotional data. For example, if the user is feeling stressed, it will recommend dishes or teas that have a relaxing effect.

[0996] The server generates the selected recipe and a list of ingredients required and provides it to the user, giving priority to recipes that use ingredients already in the refrigerator.

[0997] Purchase recommendation

[0998] server

[0999] Based on the provided recipe, the system generates a list of ingredients that are not in the refrigerator. It identifies the most economical source of purchase for each ingredient and suggests it to the user. For example, it provides information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from online store X."

[1000] Based on information from the emotion engine, the system also recommends places to buy based on the user's emotions. For example, if the system recommends matcha to reduce stress, it will also recommend the best places to buy it.

[1001] Calorie and weight management

[1002] server

[1003] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. If the target weight is 60 kg, analyze the calorie information of the recipes based on the appropriate daily calorie intake.

[1004] It will suggest calorie adjustments and alternatives as needed, providing specific advice such as, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[1005] Terminal

[1006] Visually present users with recommended recipes and supplier information. Visually display detailed recipe instructions and ingredient information for recommended recipes, as well as multiple supplier information.

[1007] Based on the emotion recognition results of the emotion engine, the system also makes recommendations aimed at reducing stress and improving the user's mood. For example, the system might suggest, "You seem to be in the mood to relax a bit today. How about drinking some green tea?"

[1008] By displaying calculated calorie information and advice to users, users can follow a healthy meal plan and maintain a balanced diet.

[1009] Through these steps, the system supports the user's daily life by managing food expenses, calorie intake, and suggesting meals that are in line with their emotions, providing a more personalized dining experience. This allows the user to efficiently manage their living expenses and lead an appropriate dietary lifestyle according to their emotional state.

[1010] The processing flow will be explained below.

[1011] Step 1:

[1012] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate the emotion engine and provide their current emotional state.

[1013] Step 2:

[1014] The server stores the information provided by the user in a database, including address, number of household members, desired food budget, food concept, ability to cook at home, target weight, and refrigerator inventory.

[1015] SQL

[1016] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[1017] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[1018] Step 3:

[1019] The server retrieves information about nearby supermarkets and online stores based on the user's address, including the location, products, and prices of each store.

[1020] Python

[1021] nearest_stores = get_nearest_stores(user_address)

[1022] store_prices = fetch_store_prices(nearest_stores)

[1023] Step 4:

[1024] The emotion engine performs facial recognition or voice analysis of the user to analyze their current emotional state (e.g., stress, joy, sadness, etc.), and sends the results to the server.

[1025] Python

[1026] emotion_state = analyze_emotion(user_facial_expression)

[1027] send_emotion_data_to_server(emotion_state)

[1028] Step 5:

[1029] The server searches for the optimal recipe based on the user's emotional state, refrigerator inventory, and ingredient concept. For example, if the user is feeling stressed, it will prioritize dishes that are known to have a relaxing effect.

[1030] SQL

[1031] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept AND emotion_suitability = :emotion_state;

[1032] Step 6:

[1033] The server selects the most suitable recipe and sends its details (e.g., ingredients, cooking instructions) to the user terminal. For example, if "Teriyaki Chicken" is selected, the server provides the recipe details.

[1034] Python

[1035] recommended_recipe = select_best_recipe(available_recipes)

[1036] send_recipe_to_client(recommended_recipe)

[1037] Step 7:

[1038] The device visually displays details of the recommended recipe, including the ingredients list and cooking instructions.

[1039] HTML

[1040]

[1041] <h1>{{recommended_recipe.name}}< / h1>

[1042] {{recommended_recipe.ingredients}}

[1043] {{recommended_recipe.instructions}}

[1044]

[1045] Step 8:

[1046] The server generates a list of ingredients missing from the refrigerator based on the recommended recipe, including information identifying the most economical source for each ingredient.

[1047] SQL

[1048] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[1049] Step 9:

[1050] Based on the generated ingredient list, the server suggests the most economical and convenient place to buy ingredients, such as "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[1051] Python

[1052] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[1053] send_purchase_recommendations_to_client(purchase_recommendations)

[1054] Step 10:

[1055] The device displays a list of ingredients to be purchased and recommended places to purchase them to the user, allowing the user to shop efficiently.

[1056] HTML

[1057]

[1058] <h2>Recommended Shops< / h2>

[1059]

[1060] {% for item, shop in purchase_recommendations %}

[1061] {{item}} - Buy at {{shop}}

[1062] {% endfor %}

[1063]

[1064]

[1065] Step 11:

[1066] The server calculates the calories of the recommended recipe and checks it against the appropriate calorie amount based on the target weight. For example, if the target weight is 60 kg, the calorie information of the recipe is verified based on the appropriate calorie intake for that day.

[1067] Python

[1068] recipe_calories = calculate_calories(recommended_recipe)

[1069] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[1070] Step 12:

[1071] The server provides the user with advice on calorie management, such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[1072] Python

[1073] if recipe_calories <= daily_calorie_needs:

[1074] calorie_advice = "This meal fits within your daily calorie needs."

[1075] else:

[1076] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[1077] send_calorie_advice_to_client(calorie_advice)

[1078] Step 13:

[1079] The device visually displays calculated calorie information and advice, allowing users to follow a healthy eating plan.

[1080] HTML

[1081]

[1082] <h3>Calories: {{recipe_calories}}< / h3>

[1083] {{calorie_advice}}

[1084]

[1085] Through these steps, the system comprehensively supports users in managing their food expenses, calorie intake, and suggesting meals according to their emotions, allowing users to efficiently manage their living expenses and lead an appropriate diet according to their emotional state.

[1086] Example 2

[1087] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1088] Conventional meal plan suggestion systems make blanket suggestions without considering the user's basic information or current emotional state, making it difficult to provide personalized meal plans tailored to individual needs. Furthermore, because ingredients and recipes are not selected based on refrigerator inventory or the user's emotional state, there are problems with food waste and reduced user satisfaction. Furthermore, the number of potential suppliers is limited, making it difficult to make economical or convenient choices.

[1089] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of the user's address, number of households, desired cost, ingredient concept, ability to cook at home, target weight, and refrigerator inventory; means for acquiring information on nearby retailers or online stores based on the address; means for recognizing the user's emotional state by analyzing the user's facial expressions and voice; means for generating an optimal ingredient list and cooking method based on the input information, emotional state, and acquired retailer information; means for suggesting the most economical or convenient purchasing source based on the generated ingredient list; and means for calculating calorie intake based on the target weight and providing appropriate calorie advice. This makes it possible to provide a personalized meal plan tailored to the user's individual needs and current emotional state.

[1090] "User" refers to an individual who enters information into the system and receives a personalized meal plan.

[1091] "Address" refers to detailed information about the user's place of residence and is used to obtain information about nearby retailers and online stores.

[1092] "Number of households" refers to the number of people living in the user's household, and is information that affects meal plan portion sizes and food cost calculations.

[1093] "Desired spend" refers to the monthly or weekly budget that the user plans to spend on food.

[1094] "Ingredient concept" refers to the meal theme or ingredient characteristics desired by the user (e.g., healthy, low calorie, etc.).

[1095] "Ability to cook at home" refers to whether or not the user has the ability or desire to cook at home.

[1096] "Goal weight" refers to the weight the user wants to achieve, and is important information for calculating calories and creating meal plans.

[1097] "Refrigerator inventory" refers to a list of ingredients currently stored in the user's refrigerator.

[1098] "Store" refers to a physical store selling ingredients.

[1099] "Online Store" refers to an e-commerce site that sells products over the Internet.

[1100] "Emotional state" refers to the mood or psychological state of the user that is recognized based on facial expressions and voice data.

[1101] "Ingredient list" refers to a list of ingredients that the user needs to purchase.

[1102] "Recipe" refers to the steps or recipes for cooking using ingredients specified by the user.

[1103] "Purchasing point" refers to the retail store or online store where you purchase ingredients.

[1104] "Calories" refers to the amount of energy contained in an ingredient or dish and is used to calculate a meal plan relative to a user's weight goal.

[1105] The present invention relates to a system that proposes an optimal meal plan taking into account the user's input information and emotional state. The details of this system are described below.

[1106] User

[1107] The user logs into the system and enters their address, number of household members, desired cost, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is entered from the device the user uses (e.g., PC, smartphone, tablet). The user also activates the emotion engine and provides their current emotional state. At this time, emotions are detected using facial recognition and voice analysis. A specific example is shown below.

[1108] Examples:

[1109] The user enters the following information:

[1110] Address: Minato-ku, Tokyo

[1111] Number of people in the household: 2

[1112] Desired cost: 40,000 yen / month

[1113] Ingredients concept: Healthy food

[1114] Self-catering: Yes

[1115] Target weight: 60kg

[1116] Fridge stock: Chicken breast, broccoli, tofu

[1117] Next, the user's emotion engine is activated and recognizes that the user is feeling stressed.

[1118] server

[1119] The server stores the information provided by the user in a database. For example, it uses an SQL or NoSQL database to efficiently manage data. The server also accesses an API to obtain information about nearby retailers and online stores based on the user's address information. This involves large-scale data collection and analysis.

[1120] Furthermore, the server receives user emotional data and uses it to select ingredients and generate recipes. Emotion recognition uses image recognition technology (e.g., OpenCV) and natural language processing (e.g., Google Cloud's natural language API).

[1121] Examples:

[1122] The server uses the emotion data and refrigerator inventory data to suggest recipes such as:

[1123] "Healthy stir-fried chicken breast and broccoli"

[1124] Next, based on this recipe, a list of ingredients needed that are not in the refrigerator (e.g. olive oil, salt) is made.

[1125] Terminal

[1126] The device visually presents the information sent from the server to the user. Specifically, it displays recommended recipes, purchasing information, and calorie information. The user can confirm this information and proceed to purchase or execute the plan.

[1127] Examples:

[1128] The following information will be displayed on the terminal screen:

[1129] "New Recipe: Healthy Stir-fried Chicken Breast and Broccoli"

[1130] "Estimated calories: 500kcal per serving"

[1131] "Purchase information: Olive oil - nearest supermarket, Salt - Online Store Y"

[1132] Prompt Sentence Examples

[1133] Below are some example prompts to input to the generative AI model:

[1134] User-entered information:

[1135] Address: Minato-ku, Tokyo

[1136] Number of people in the household: 2

[1137] Desired cost: 40,000 yen / month

[1138] Ingredients concept: Healthy food

[1139] Self-catering: Yes

[1140] Target weight: 60kg

[1141] Fridge stock: Chicken breast, broccoli, tofu

[1142] Current emotional state: I'm stressed

[1143] Use this information to provide users with the perfect meal plan, and if they don't have the ingredients they need for a recipe in their fridge, provide them with information on where to buy them.

[1144] As described above, this system generates meal plans based on the user's input information and emotional state and provides them visually, thereby enabling personalized meal suggestions tailored to individual needs.

[1145] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1146] Step 1: User Input

[1147] User

[1148] Users log in to the system and enter their address, number of household members, desired cost, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory.

[1149] It also activates the emotion engine and provides the current emotional state.

[1150] input

[1151] Address, number of households, desired expenses, food concept, ability to cook at home, target weight, refrigerator inventory, emotional state

[1152] Specific actions

[1153] The user enters the necessary information into the device interface and clicks the "Send" button. The emotion engine uses a camera and microphone to collect facial and voice data.

[1154] output

[1155] The entered data is sent to the server.

[1156] Step 2: Storing and Retrieving Data

[1157] server

[1158] The server stores the information provided by the user in a database.

[1159] Obtain information on nearby retailers and online stores based on address information.

[1160] input

[1161] Input data submitted by the user

[1162] Specific actions

[1163] The server uses an SQL or NoSQL database to structure and store user information, and then uses an API to collect information from merchants.

[1164] output

[1165] User information stored in the database and price information obtained from retailers

[1166] Step 3: Emotion Recognition

[1167] Emotion Engine

[1168] It analyzes the user's facial expressions and voice data to recognize their current emotions.

[1169] The recognized emotion data is sent to the server.

[1170] input

[1171] Facial expression and voice data collected by cameras and microphones

[1172] Specific actions

[1173] The emotion engine analyzes emotions using image recognition technology (e.g., OpenCV) and natural language processing technology.

[1174] output

[1175] Recognized emotional state data is generated and transmitted to a server.

[1176] Step 4: Select and generate a recipe

[1177] server

[1178] Search and select the best recipes based on refrigerator inventory data and sentiment data.

[1179] Generate recipes along with ingredient lists.

[1180] input

[1181] Refrigerator inventory data, sentiment data, retailer information

[1182] Specific actions

[1183] It queries a large recipe database and selects recipes based on the user's emotional state. It applies a filtering algorithm to determine the best recipe.

[1184] output

[1185] Selected recipes and ingredient lists

[1186] Step 5: Recommend a supplier

[1187] server

[1188] Generate a list of ingredients that are not in the refrigerator and identify the most economical source of each ingredient.

[1189] It also makes recommendations on where to buy based on emotional data.

[1190] input

[1191] Recipes, ingredient lists, retailer information, emotional data

[1192] Specific actions

[1193] It uses cost calculation algorithms to select economical purchasing sources, and also suggests the best places to buy specific ingredients based on sentiment data.

[1194] output

[1195] Recommended Purchase List

[1196] Step 6: Counting and adjusting calories

[1197] server

[1198] Calculate the calorie information for recommended recipes and compare it with the appropriate calorie amount based on your target weight.

[1199] Suggest calorie adjustments or alternatives as needed.

[1200] input

[1201] Recipe data, target weight

[1202] Specific actions

[1203] It uses a calorie counting algorithm to calculate the calories in each recipe, calculates your daily calorie intake based on your target weight, and offers alternative suggestions if adjustments are needed.

[1204] output

[1205] Calorie calculation results and adjustment suggestions

[1206] Step 7: Visualizing the results

[1207] Terminal

[1208] To provide information from a server to a user visually.

[1209] View recipes, where to buy, and calorie information.

[1210] input

[1211] Recipes, ingredient lists, purchasing information, and calorie information sent from the server

[1212] Specific actions

[1213] The information is displayed on the device interface for the user to check, and the user can check the displayed information through the device and decide on the next action.

[1214] output

[1215] Information presented visually to the user

[1216] (Application example 2)

[1217] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1218] Currently, there are systems that provide personalized meal plans, but they do not adequately recommend ingredients and recipes that take into account the user's emotional state. Furthermore, there are no systems that reflect refrigerator inventory information and provide emotional personalization. Therefore, it is difficult to effectively provide meal suggestions that help users relax and maintain their health.

[1219] The specific processing 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 receiving input of the user's address, number of households, desired food expenses, ingredient concept, ability to cook at home, target weight, refrigerator inventory, and emotional state; means for acquiring information on nearby commercial facilities or electronic commerce sites based on the address; means for generating an optimal ingredient list and cooking method based on the input information and the acquired commercial facility information; means for suggesting the most economical or convenient purchasing source based on the generated ingredient list; means for calculating calorie intake based on the target weight and providing appropriate calorie advice; and means for recommending ingredients and recipes tailored to the user based on the emotional state. This makes it possible to provide a personalized meal plan that takes the user's emotional state into consideration.

[1220] An "address" is geographical information that indicates where a user lives.

[1221] "Number of households" is information indicating the number of people residing in a particular residence.

[1222] "Desired food expenses" is information indicating the amount of money the user wishes to spend on ingredients and meals.

[1223] "Ingredient concept" is information that indicates the theme or philosophy of the ingredients or dishes that the user likes.

[1224] "Ability to cook at home" is information indicating whether the user has the ability or motivation to cook for themselves.

[1225] "Target weight" is information indicating the weight that the user wishes to achieve.

[1226] "Refrigerator inventory" is information showing a list of ingredients currently stored in the user's refrigerator.

[1227] "Emotional state" is information that indicates the user's current psychological and emotional state.

[1228] "Commercial facility" means a store selling food and daily necessities.

[1229] "Electronic Venue" means an online store where goods can be purchased over the Internet.

[1230] The "optimal ingredient list" indicates a list of ingredients that are most suitable for the user's needs.

[1231] A "cooking method" is a recipe or procedure for cooking a dish using specific ingredients.

[1232] "Economical or convenient purchasing location" refers to the place where the user can purchase ingredients that offers the best cost performance or convenience.

[1233] "Intake of calories" refers to the total amount of energy that a user takes in within a certain period of time.

[1234] "Calorie advice" refers to advice on the recommended calorie intake to achieve the user's goal weight.

[1235] "Personalized meal plan" refers to a meal plan that is customized based on an individual user's personal information and emotional state.

[1236] The following describes an embodiment of the present invention.

[1237] System configuration

[1238] The system consists of a user's smartphone, a server, and a communication network via the Internet. The user's smartphone includes an emotion recognition engine, a voice recognition engine, and a data entry interface. The server includes a database management system, a recipe generation engine, a calorie calculation library, and a delivery API.

[1239] Hardware and Software

[1240] Smartphone: Uses OpenCV and dlib for facial expression recognition, and Google Cloud Speech-to-Text for voice recognition.

[1241] Server: We use MySQL as our database management system, with custom libraries for calorie calculation and recipe generation. Delivery information is obtained from a number of online APIs (e.g. UberEats and other delivery integration APIs).

[1242] Program processing overview

[1243] User Input

[1244] The user uses a smartphone to input information such as address, number of household members, desired food budget, ingredient concept, ability to cook at home, target weight, refrigerator inventory, and current emotional state. The emotional state is acquired using the smartphone's camera and voice interface. Facial expressions are analyzed using a facial recognition engine (e.g., OpenCV and dlib), and the voice data is converted into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text).

[1245] Data Processing and Recipe Generation

[1246] The server stores the received user information in a database. Based on the address, information on nearby commercial facilities and electronic trading locations is obtained via API. Next, the optimal ingredient list and cooking method is generated based on the input and obtained information. Specifically, it suggests ingredients that reduce stress and recipes that have a relaxing effect based on the user's emotional state. It also uses the inventory in the refrigerator to avoid the need to purchase unnecessary ingredients.

[1247] Economical purchasing suggestions

[1248] Based on the generated ingredient list, the server searches for the most economical or convenient source of purchase via API and suggests it to the user. For example, it compares whether the ingredients needed for a particular dish are cheaper at a nearby commercial facility or an online store, and provides the user with the optimal source of purchase.

[1249] Calorie Management and Calorie Advice

[1250] The server calculates the user's daily calorie intake based on their target weight, evaluates the calorie content of the suggested recipes, and, if necessary, provides the user with alternative recipes with adjusted calorie content or additional advice.

[1251] Specific examples

[1252] For example, if a user is feeling stressed at work and wants to relax during lunchtime, the system will suggest relaxing "ochazuke" (rice with green tea) or "relaxing tea" based on the user's emotional state, and provide information on the nearest commercial facility or online store where to purchase the ingredients needed for these. It will also provide calorie information and suggest balanced meals based on the user's target weight and current calorie intake.

[1253] Prompt Sentence Examples

[1254] "If a user is feeling stressed at work, suggest a relaxing dish. Or search for nearby delivery services and provide the best options."

[1255] In this way, the present invention is able to provide a personalized meal plan that takes into account the user's emotional state and daily needs.

[1256] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1257] Step 1: Enter your user information

[1258] The user uses a smartphone to input their address, household size, desired food budget, ingredient concept, whether they can cook at home, target weight, refrigerator inventory, and current emotional state. The input information is sent to the server through the smartphone's data input interface. This process collects the individual information and emotional state required for the system.

[1259] Input: User's address, number of household members, desired food budget, food concept, whether self-cooking is possible, target weight, refrigerator inventory, emotional state

[1260] Output: Sending information to the server

[1261] Step 2: Recognizing your emotional state

[1262] The device's camera and microphone are used to recognize the user's current emotional state from their facial expressions and voice. The device processes the facial expression data using an emotion recognition engine (e.g., OpenCV and dlib), converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text), and determines the emotion. The analysis results are sent to the server.

[1263] Input: User's facial expression data, voice data

[1264] Output: Judgment result of the user's emotional state

[1265] Step 3: Storing information in a database

[1266] The server stores the received user information in a database. A database management system (e.g., MySQL) is used to efficiently manage information such as user profiles, refrigerator inventory, and emotional states.

[1267] Input: User information (address, number of households, etc.), emotional state

[1268] Output: Save information to a database

[1269] Step 4: Obtain information on nearby commercial facilities

[1270] Based on the address, the server retrieves information about nearby commercial facilities and online stores via API, including information on the prices of ingredients at each store.

[1271] Input: User's address

[1272] Output: Information about commercial facilities and online stores

[1273] Step 5: Generate a recipe and ingredient list

[1274] The server generates an optimal ingredient list and recipe based on the input information and acquired commercial facility information, taking into account refrigerator inventory and emotional state, and selecting ingredients and recipes that have a relaxing effect according to the emotional state.

[1275] Input: User information, commercial facility information, emotional state

[1276] Output: Ingredient list and recipe

[1277] Step 6: Propose a supplier

[1278] Based on the generated list of ingredients, the server compares prices and delivery terms using delivery APIs (e.g., Uber Eats and other delivery integration APIs) to suggest the most economical or convenient shopping locations. Based on this information, the server suggests the most suitable shopping locations for the user.

[1279] Input: Ingredient list

[1280] Output: Buyer suggestions

[1281] Step 7: Calorie counting and advice

[1282] The server calculates calorie intake based on the user's target weight, evaluates the calorie information of the generated recipe, and provides the user with alternative recipes with adjusted calorie amounts or additional advice, if necessary.

[1283] Input: Recipe, Goal Weight

[1284] Output: Calorie calculation results, advice provided

[1285] Step 8: Provide visual information

[1286] The device visually presents recommended recipes and vendor information to the user, displaying detailed recipe steps, ingredient information, multiple vendor information, and calorie information through a visual interface.

[1287] Input: Recipe, supplier information, calorie calculation results

[1288] Output: A visual display to the user

[1289] Through these steps, users can efficiently receive meal plans tailored to their emotional state and lead a healthy and personalized diet.

[1290] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1291] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1292] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1293] [Third embodiment]

[1294] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1295] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1296] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1297] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1298] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1299] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1300] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1301] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1302] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1303] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1304] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1305] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1306] The system of the present invention starts with the user inputting their address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, and then uses that information to suggest optimal daily meals and purchasing locations for each user. The program processing of the system of the present invention is explained below in natural language.

[1307] Initial Setup

[1308] User

[1309] First, the user logs into the system and enters their address, number of household members (e.g., 2 people), desired food budget (30,000 yen per month or 1,000 yen per day), food concept (mainly Japanese food), whether they can cook at home (possible), target weight (60 kg), and refrigerator inventory (e.g., rice, miso, chicken, etc.).

[1310] server

[1311] The server then stores the information provided by the user in a database.

[1312] The server obtains information on nearby supermarkets and online stores based on the user's address, as well as price information on ingredients sold at each store.

[1313] Ingredient and recipe recommendations

[1314] server

[1315] The input information is analyzed and a recipe that prioritizes the use of the refrigerator's inventory is searched for. For example, if there is rice and chicken, the recipe for "Teriyaki Chicken" is selected.

[1316] The ingredient concept is centered around Japanese cuisine and cooking at home is possible, so suitable Japanese recipes will be recommended.

[1317] Terminal

[1318] The recommended recipes are displayed on the user's device. For example, if a teriyaki chicken recipe is recommended, the cooking instructions and details of the ingredients are displayed.

[1319] Suggestions for where to buy ingredients

[1320] server

[1321] Based on the recommended recipe, a list of ingredients that are not in the user's refrigerator is created. For example, if it turns out that soy sauce, sugar, and ginger are not in the refrigerator, a purchase list for these items is generated.

[1322] Next, the system selects the most economical store for each ingredient based on price information from the nearest supermarket or online store and suggests it to the user.

[1323] Terminal

[1324] The user's device displays a list of ingredients needed and recommended places to buy them. For example, the information provided may include "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[1325] Calorie intake and weight management

[1326] server

[1327] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. For example, if the target weight is 60 kg, calculate the daily calorie intake and check whether the recommended recipes fall within that range.

[1328] It will suggest calorie adjustments and alternatives as needed, for example, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[1329] Terminal

[1330] The user's device will display a healthy meal plan along with calculated calorie information, such as "Today's menu is 1500 kcal in total, which is a good balance for your calorie goal."

[1331] The present invention thereby automates a series of processes for users to efficiently manage their living expenses and lead a balanced diet, thereby providing full support to users in both food expenses and health management.

[1332] The processing flow will be explained below.

[1333] Step 1:

[1334] Users log in to the system and enter their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory, allowing them to register their lifestyle and food preferences in the system.

[1335] Step 2:

[1336] The server stores the information provided by the user in a database, which is used for further analysis and recommendations.

[1337] SQL

[1338] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[1339] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[1340] Step 3:

[1341] The server obtains information about nearby supermarkets and online stores based on the user's address. This information is collected using APIs that reference the acquired store data.

[1342] Python

[1343] nearest_stores = get_nearest_stores(user_address)

[1344] store_prices = fetch_store_prices(nearest_stores)

[1345] Step 4:

[1346] The server analyzes the user's input information and searches for recipes that prioritize the use of existing refrigerator inventory. For example, if "rice" and "chicken" are in stock, the server searches for a recipe for "teriyaki chicken."

[1347] SQL

[1348] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept;

[1349] Step 5:

[1350] The server selects the most suitable recipe and sends the recommended recipe information to the user terminal. For example, a recipe for "Teriyaki Chicken" is provided, along with cooking instructions and details of the ingredients required.

[1351] Step 6:

[1352] The device displays the recommended recipes to the user, for example, providing a detailed visual recipe for teriyaki chicken.

[1353] HTML

[1354]

[1355] <h1>{{recommended_recipe.name}}< / h1>

[1356] {{recommended_recipe.ingredients}}

[1357] {{recommended_recipe.instructions}}

[1358]

[1359] Step 7:

[1360] The server generates a list of ingredients that are missing from the refrigerator based on the recommended recipe. For example, if soy sauce, sugar, or ginger are missing, the server adds these items to the list.

[1361] SQL

[1362] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[1363] Step 8:

[1364] The server lists the most economical places to purchase each ingredient and suggests them to the user, such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar at online store X."

[1365] Python

[1366] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[1367] Step 9:

[1368] The device displays a list of ingredients to purchase and recommended places to buy them to the user, organizing and presenting the information in a format that is visually easy for the user to understand.

[1369] HTML

[1370]

[1371] <h2>Recommended Shops< / h2>

[1372]

[1373] {% for item, shop in purchase_recommendations %}

[1374] {{item}} - Buy at {{shop}}

[1375] {% endfor %}

[1376]

[1377]

[1378] Step 10:

[1379] The server calculates the calories of the recommended recipes and compares them with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server analyzes the calorie information of the recipes based on the appropriate daily calorie intake.

[1380] Python

[1381] recipe_calories = calculate_calories(recommended_recipe)

[1382] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[1383] Step 11:

[1384] The server provides the user with advice on calorie management. For example, specific advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[1385] Python

[1386] if recipe_calories <= daily_calorie_needs:

[1387] calorie_advice = "This meal fits within your daily calorie needs."

[1388] else:

[1389] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[1390] Step 12:

[1391] The device displays the calculated calorie information and advice to the user, allowing them to follow a healthy eating plan.

[1392] HTML

[1393]

[1394] <h3>Calories: {{recipe_calories}}< / h3>

[1395] {{calorie_advice}}

[1396]

[1397] Through these steps, the system comprehensively supports users in managing food expenses, calorie intake, and maintaining a healthy diet.

[1398] Example 1

[1399] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1400] In today's busy lifestyles, it is difficult for many people to efficiently plan, purchase, and manage their health. This challenge is especially significant for users who want to maintain a balanced diet on a limited budget. Many users also want to avoid wasting ingredients they already have at home and shop economically by effectively utilizing nearby store information. To solve these problems, an automated meal planning and purchasing suggestion system tailored to the user's needs is needed.

[1401] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1402] In this invention, the server includes means for receiving input of a user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for acquiring information on nearby stores or online stores based on the address, means for generating an optimal ingredient list and recipe based on the input information and the acquired store information, means for suggesting the most economical or convenient purchasing source based on the generated ingredient list, means for calculating calorie intake based on the target weight and providing appropriate calorie advice, and means for visually displaying the recommended recipe and purchasing source information on the user terminal. This allows users to efficiently plan their ingredient purchases and maintain a healthy and balanced diet while shopping economically and without waste.

[1403] "User" refers to an individual or household using the system.

[1404] "Address" refers to geographic information of the place where the user resides.

[1405] "Number of households" refers to the number of people in the household to which the user belongs.

[1406] "Desired food budget" refers to the monthly or daily budget set by the user for meals.

[1407] "Ingredient concept" refers to a guideline for a specific food culture or cooking style that a user prefers, such as "mainly Japanese food."

[1408] "Self-cooking" refers to whether the user is able to cook at home.

[1409] "Target weight" refers to the weight that the user wants to achieve.

[1410] "Refrigerator inventory" refers to the types and quantities of ingredients currently in the user's refrigerator.

[1411] "Server" refers to the computer system that performs the central calculations and stores data for this system.

[1412] "Store information" refers to data about nearby stores or online stores obtained based on the user's address.

[1413] An "ingredient list" is a list of ingredients needed by the user, and is used for creating recipes and planning purchases.

[1414] A "recipe" refers to information that describes the steps and ingredients needed to prepare a dish.

[1415] "Purchasing locations" refers to stores and online stores suggested for users to purchase ingredients.

[1416] "Calories intake" refers to the amount of calories consumed by a user in a certain period of time.

[1417] "Calorie Advice" refers to advice based on recommended calorie intake for a user to achieve a weight goal.

[1418] "User terminal" refers to a device, such as a computer, smartphone, or tablet, that a user uses to access the system.

[1419] "Visually displaying" refers to presenting information in an easy-to-read format on the screen of a user terminal.

[1420] MODE FOR CARRYING OUT THE INVENTION

[1421] The system of the present invention proposes optimal daily cooking and food purchasing locations for users based on multiple pieces of information provided by the user. This system is composed of a combination of hardware and software, and a specific example is shown below.

[1422] Initial Setup

[1423] User

[1424] First, the user logs in to the system and enters the address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory information. Specifically, the following information is entered:

[1425] Address: Tokyo

[1426] Number of people in the household: 2

[1427] Desired food expenses: 30,000 yen per month

[1428] Ingredients concept: Japanese cuisine

[1429] Self-catering: Yes

[1430] Target weight: 60kg

[1431] Refrigerator inventory: rice, miso, chicken

[1432] Information storage and analysis

[1433] server

[1434] The server stores the information entered by the user in a database. The database used for this is a relational database such as MySQL or PostgreSQL. Based on the stored information, the server collects information about nearby stores and online stores based on the user's address. This information is collected using web scraping technologies such as Python's BeautifulSoup and Scrapy.

[1435] Recipe Recommendations

[1436] server

[1437] Next, the server searches for recipes that prioritize the refrigerator inventory information provided by the user. For example, if there is rice and chicken in the refrigerator, a recipe such as "Teriyaki Chicken" will be selected. Also, since the ingredient concept is centered on Japanese cuisine, the server will recommend suitable recipes from among Japanese cuisine recipes.

[1438] Viewing Recipes

[1439] Terminal

[1440] The recommended recipes are displayed on the user's device. They are presented in a visually easy-to-understand format using HTML and JavaScript. For example, if a recipe for "teriyaki chicken" is recommended, the cooking instructions and details of the ingredients are displayed on the user's device.

[1441] Suggestions for where to buy ingredients

[1442] server

[1443] Based on the recommended recipe, the server creates a list of ingredients that the user does not have in their refrigerator. For example, if soy sauce, sugar, or ginger are missing, they are added to the shopping list. The server then suggests the most economical way to purchase the ingredients based on price information from the nearest supermarket or online store.

[1444] View shopping list

[1445] Terminal

[1446] The user's device will display a list of ingredients needed and recommended places to buy them. For example, it will show information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from an online store."

[1447] Calorie intake and weight management

[1448] server

[1449] The server calculates the calorie information of the recommended recipes and compares it with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server sets the daily calorie intake to 1800 kcal and checks whether the provided recipes fall within that range.

[1450] View calorie information and meal plans

[1451] Terminal

[1452] A healthy meal plan is displayed on the user's device along with calculated calorie information. For example, advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie goal of 1500 kcal" is shown.

[1453] Examples and prompts

[1454] As a concrete example, here is how the system operates based on the information above:

[1455] 1. Address: Tokyo

[1456] 2. Number of people in the household: 2

[1457] 3. Desired food expenses: 30,000 yen per month

[1458] 4. Ingredients concept: Japanese cuisine

[1459] 5. Self-catering: Yes

[1460] 6. Target weight: 60kg

[1461] 7. Refrigerator inventory: rice, miso paste, chicken

[1462] Based on this, the system makes recommendations such as:

[1463] Recommended recipe: Teriyaki Chicken

[1464] Shopping list: soy sauce, sugar, ginger

[1465] Where to buy: Soy sauce from your local supermarket, sugar from an online store

[1466] Prompt Sentence Examples

[1467] "Enter the user's address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory to display a list of recommended recipes and where to buy them."

[1468] As described above, the present invention is a comprehensive system that allows users to efficiently plan food purchasing, maintain a balanced diet, and manage their health.

[1469] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1470] Step 1: Enter your information

[1471] Input: The user enters their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory into the system.

[1472] Specific operation: The user logs in to a dedicated application or website using a smartphone or computer and enters the necessary information. For example, they enter information such as: living in Tokyo, household size: 2 people, desired food budget: 30,000 yen per month, mainly Japanese food, able to cook at home, target weight: 60 kg, and having rice, miso, and chicken in the refrigerator.

[1473] Output: The system receives user input.

[1474] Step 2: Store and analyze information

[1475] Input: Information entered by the user.

[1476] What it does: The server receives the information entered by the user and stores it in a database, using a relational database such as MySQL or PostgreSQL.

[1477] Output: Stored user information data. The server uses this data to:

[1478] Step 3: Gather information about nearby stores

[1479] Input: User's address information.

[1480] Specific operation: Based on the user's address, the server uses web scraping technology (e.g., Python's BeautifulSoup or Scrapy) to collect information on nearby supermarkets and online stores. For example, it collects price information for large supermarkets and online grocery stores in a specific area of ​​Tokyo.

[1481] Output: Collected nearby store and price information data.

[1482] Step 4: Find a recipe

[1483] Input: User's refrigerator inventory information, ingredient concept.

[1484] Specific operation: The server searches the recipe database for the corresponding recipe based on the input refrigerator inventory information. For example, if there is rice and chicken in the refrigerator, it searches for Japanese recipes that use these ingredients.

[1485] Output: A list of suitable recipes that were found.

[1486] Step 5: Recipe Selection

[1487] Input: Recipe search results.

[1488] Specific operation: The server recommends the best recipe based on the ingredient concept (e.g., mainly Japanese food). As a specific example, the recipe "Teriyaki Chicken" using chicken and rice is selected.

[1489] Output: Recommended recipe information.

[1490] Step 6: View the recipe

[1491] Input: Recommended recipe information.

[1492] What it does: The recommended recipe is displayed on the user's device. The recipe steps and ingredient details for "Teriyaki Chicken" are visually displayed on the screen using HTML and JavaScript.

[1493] Output: Recipe information displayed on the user's device.

[1494] Step 7: Make a list of ingredients you need

[1495] Input: Recommended recipe information, user's refrigerator inventory information.

[1496] Specific behavior: The server creates a list of ingredients that are missing from the user's refrigerator based on the recommended recipe. For example, if a teriyaki chicken recipe requires soy sauce, sugar, and ginger, but these are not in the refrigerator, the server adds them to the list.

[1497] Output: A list of ingredients needed.

[1498] Step 8: Propose a supplier

[1499] Input: List of ingredients needed, information on nearby stores.

[1500] Specific operation: The server selects the most economical and convenient place to purchase and suggests it to the user. For example, it suggests that the nearest supermarket is the cheapest place to buy soy sauce, and the online store is the cheapest place to buy sugar.

[1501] Output: Recommended vendor information.

[1502] Step 9: View your shopping list

[1503] Input: list of ingredients needed, recommended purchasing information.

[1504] Specific behavior: The recommended purchasing locations and a list of ingredients needed are displayed on the user's device. The user is given specific instructions, such as "Purchase soy sauce at the nearest supermarket and sugar at online store X."

[1505] Output: Shopping list information displayed on the user's device.

[1506] Step 10: Calculate calorie information

[1507] Input: Recommended recipe information, user's goal weight.

[1508] Specific operation: The server calculates the calorie information of the recommended recipe and compares it with the appropriate calorie schedule based on the user's target weight. For example, if the target weight is 60 kg, it sets the daily calorie intake to 1800 kcal and checks whether it falls within that range.

[1509] Output: Calorie count and calorie advice.

[1510] Step 11: View calorie information and meal plans

[1511] Input: Calorie count and calorie advice.

[1512] What it does: A healthy meal plan is displayed on the user's device along with calculated calorie information, and specific advice is given, such as "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie goal of 1500 kcal."

[1513] Output: Calorie information and meal plan displayed on user device.

[1514] As described above, this system provides comprehensive support for users to efficiently plan food purchases, maintain a balanced diet, and manage their health.

[1515] (Application example 1)

[1516] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1517] Conventional meal recommendation systems focus on supporting home cooking based on information entered by the user, but in real life, there are many situations where home cooking is not possible or people prefer to eat out. Furthermore, maintaining a healthy diet requires consideration of specific calorie intake and nutritional balance, but existing systems have difficulty providing comprehensive support for these. Therefore, there was a need for a system that could provide optimal meal recommendations not only for home cooking, but also for eating out or ordering food delivery.

[1518] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1519] In this invention, the server includes means for receiving input from the user of the user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for obtaining information on nearby stores or online stores, means for generating optimal ingredient lists and recipes, means for obtaining restaurant menus and recommending optimal menus, and means for arranging orders through affiliated food delivery services. This allows users to receive economical and healthy meal suggestions for a variety of eating habits, including not only cooking at home but also eating out and food delivery.

[1520] A "user" is an entity that uses this system, and is an individual or group that provides information such as address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory.

[1521] An "address" is information used to identify the location where a user resides, and is data necessary for procuring ingredients from nearby stores or online stores and using food delivery services.

[1522] "Number of households" indicates the number of people living at the same address, and is necessary to properly calculate recommended recipes and ingredient amounts.

[1523] "Desired food budget" is information indicating the budget that the user can spend on ingredients and meals, and is a standard value for suggesting economical ingredient lists and purchasing locations.

[1524] "Ingredient concept" is information that indicates the user's preferred eating style or cuisine genre, and is a criterion when selecting recommended recipes and menus.

[1525] "Ability to cook at home" is information that indicates the user's ability and willingness to cook at home, and is a criterion for determining whether or not a recommendation of a restaurant menu is necessary.

[1526] "Target weight" is information indicating the weight that the user wants to achieve, and is data necessary for calculating calorie intake and providing calorie advice.

[1527] "Refrigerator inventory" is information showing a list of ingredients that the user currently owns, and is data that serves as a basis for providing economical recipes that use inventory as much as possible.

[1528] "Store or online store information" refers to information about physical stores located near the user's address or places where ingredients can be purchased online, including price information and information about ingredients available.

[1529] The "optimal ingredient list" is a list of the most economical and nutritionally balanced ingredients based on information such as the user's desired food budget, ingredient concept, and whether or not they can cook at home.

[1530] A "recipe" is information that indicates the cooking steps and details of the ingredients required, generated based on information provided by the user.

[1531] The "dining out menu" is a list of recommended dishes for when the user is unable to cook at home or wishes to eat out, and is selected based on the user's nutritional balance and calorie goals.

[1532] A "food delivery service" is a service in which food is delivered to a user's address by an affiliated company or service provider, allowing users to easily enjoy restaurant menus in the comfort of their own home.

[1533] The "means for arranging an order" refers to a means for enabling a user to quickly and reliably order and use the restaurant menu selected by the user through a food delivery service.

[1534] This invention is a system that proposes optimal meals based on information provided by users to support their diverse dietary habits. This system is configured to accommodate not only users who cook at home, but also those who wish to eat out or use food delivery services.

[1535] System configuration

[1536] 1. User Device

[1537] Users access the system using a device such as a smartphone and enter information such as their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is necessary to make meal suggestions based on the user's specific needs and environment. User devices are built using a cross-platform development environment such as React Native.

[1538] 2. Server

[1539] The server plays a central role in storing the information collected from users in a database (MongoDB) and performing the following processes:

[1540] Information collection: Using Google Maps API, etc., we collect information about nearby stores or online stores based on the user's address.

[1541] Recipe generation: Using a generative AI model (OpenAI GPT-4), the optimal recipe is generated based on the input information.

[1542] Ingredient list generation: Generates a list of ingredients needed based on a recipe and suggests economical and convenient places to buy them.

[1543] Calorie Calculation: Calculates calorie intake based on your target weight and provides appropriate calorie advice.

[1544] Dining menu recommendation: For users who wish to eat out, the app recommends the most suitable dining menu and arranges the order through a partner food delivery service.

[1545] Specific examples

[1546] For example, if a user enters the following information:

[1547] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[1548] Number of household members: 2

[1549] Desired food expenses: 30,000 yen per month

[1550] Ingredients concept: Mainly Japanese cuisine

[1551] Self-catering: Possible

[1552] Target weight: 60kg

[1553] Refrigerator inventory: rice, miso, chicken

[1554] With this information, the server does the following:

[1555] 1. Use the Google Maps API to get information about supermarkets and online stores around Shibuya Ward.

[1556] 2. Using a generative AI model (OpenAI GPT-4), generate recipes such as "Teriyaki Chicken" based on the inventory in the refrigerator.

[1557] 3. It creates a list of ingredients needed for the generated recipe and suggests the best places to buy them based on that list. For example, it suggests buying soy sauce at the nearest supermarket and sugar at an online store.

[1558] 4. Calculate calories and ensure the user meets the calorie goal. For example, calculate that one serving of teriyaki chicken is 500 kcal, and ensure that the user is within the calorie goal even if they eat it three times a day.

[1559] 5. If you can't cook or prefer to eat out, Google Maps will use its API to find nearby healthy restaurants and recommend dishes like a salmon and avocado salad bowl (500 kcal per serving). It will then arrange the order through a partner food delivery service.

[1560] This flow allows users to receive healthy and economical meal suggestions for both home cooking and eating out.

[1561] Example prompts

[1562] User Information:

[1563] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[1564] Number of people in the household: 2

[1565] Desired food expenses: 30,000 yen per month

[1566] Ingredients concept: Japanese cuisine

[1567] Self-catering: Yes

[1568] Target weight: 60kg

[1569] Refrigerator inventory: rice, miso, chicken

[1570] Based on this, please tell me a Japanese recipe that prioritizes using the stock in your refrigerator. Also, please provide the ingredients needed, where to buy them, and the associated calorie information.

[1571] This configuration provides comprehensive support for the user's eating habits, enabling them to maintain eating habits efficiently and economically.

[1572] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1573] Step 1:

[1574] A user logs in to the application using a smartphone. The user inputs information such as address, number of household members, desired food budget, ingredient concept, ability to cook at home, target weight, and refrigerator inventory. This input information provides basic parameters related to the user's eating habits.

[1575] Processing: The user launches the application, enters information, and presses the send button. The input information is sent from the terminal to the server.

[1576] Input: Address, number of households, desired food budget, food concept, whether you can cook at home, target weight, refrigerator inventory

[1577] Output: Input sent to the server

[1578] Step 2:

[1579] The server stores the received user input information in a database (MongoDB), which allows for centralized management of data required for subsequent processing.

[1580] Processing: The server parses the input information and stores it in a database.

[1581] Input: Information submitted by the user

[1582] Output: User information stored in the database

[1583] Step 3:

[1584] The server uses the Google Maps API to obtain information about nearby stores or online stores based on the user's address.

[1585] Processing: The server inputs the user's address into the Google Maps API and retrieves information about nearby stores.

[1586] Input: User's address

[1587] Output: Store or online store information

[1588] Step 4:

[1589] The server uses a generative AI model (OpenAI GPT-4) to generate an optimal recipe based on the input information and store information. This recipe prioritizes the use of the inventory in the user's refrigerator.

[1590] Processing: The server inputs the prompt sentences into the AI ​​model and generates the optimal recipe.

[1591] Input: User input information, store information

[1592] Output: The generated recipe

[1593] Step 5:

[1594] The server creates a list of ingredients required for the generated recipe and suggests the most economical and convenient place to buy them based on that list.

[1595] Processing: The server analyzes the recipe, creates a list of ingredients needed, and searches for where to purchase each ingredient.

[1596] Input: Generated recipe, store information

[1597] Output: Optimal ingredients list and purchasing information

[1598] Step 6:

[1599] The server calculates calorie intake based on the user's target weight and checks whether the target recipe is within the appropriate calorie range.

[1600] Processing: The server calculates the calorie information of the recipe and evaluates whether it is suitable for the target weight.

[1601] Input: Generated recipe, target weight

[1602] Output: Calorie intake information and calorie advice

[1603] Step 7:

[1604] If the user wants to eat out, the server uses the Google Maps API to retrieve the menus of nearby healthy restaurants and recommends the most suitable menu based on the user's nutritional balance and calorie goals.

[1605] Processing: The server searches for and recommends restaurant menus based on the user's preferences.

[1606] Input: User's preference, address, target weight

[1607] Output: Optimal dining out menu

[1608] Step 8:

[1609] The server will arrange to order the selected restaurant menu through an affiliated food delivery service.

[1610] Processing: The server sends the dining out menu selection results to the food delivery service API and arranges the order.

[1611] Input: Selected restaurant menu information

[1612] Output: Order placement completion information

[1613] Step 9:

[1614] The user terminal visually displays the recipe, ingredient list, supplier information, calorie intake information, restaurant menu, and order status received from the server.

[1615] Processing: The user terminal converts the received information into a display format and presents it visually to the user.

[1616] Input: Information sent from the server

[1617] Output: Information presented visually to the user

[1618] Through these steps, users can receive healthy and economical meal suggestions for both home cooking and eating out.

[1619] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1620] The system of the present invention provides the user with the optimal meal plan based on various input information from the user (address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, refrigerator inventory). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to recommend recipes and ingredients according to the user's emotional state, making the user's dining experience more personalized.

[1621] Initial Setup

[1622] User

[1623] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate an emotion engine to provide information about their current emotional state.

[1624] server

[1625] The server stores the information provided by the user in a database. Based on the address, it retrieves information about nearby supermarkets and online stores. It also collects information about the prices of ingredients at each store.

[1626] Emotion Recognition and Recipe Recommendation

[1627] Emotion Engine

[1628] The system recognizes the user's current emotions from their facial expressions and voice, and sends the emotional data to the server. For example, if the system recognizes that the user is feeling stressed, it will use that information to select ingredients and recipes.

[1629] server

[1630] The server searches for and selects the optimal recipe based on the entered refrigerator inventory data and the acquired emotional data. For example, if the user is feeling stressed, it will recommend dishes or teas that have a relaxing effect.

[1631] The server generates the selected recipe and a list of ingredients required and provides it to the user, giving priority to recipes that use ingredients already in the refrigerator.

[1632] Purchase recommendation

[1633] server

[1634] Based on the provided recipe, the system generates a list of ingredients that are not in the refrigerator. It identifies the most economical source of purchase for each ingredient and suggests it to the user. For example, it provides information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from online store X."

[1635] Based on information from the emotion engine, the system also recommends places to buy based on the user's emotions. For example, if the system recommends matcha to reduce stress, it will also recommend the best places to buy it.

[1636] Calorie and weight management

[1637] server

[1638] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. If the target weight is 60 kg, analyze the calorie information of the recipes based on the appropriate daily calorie intake.

[1639] It will suggest calorie adjustments and alternatives as needed, providing specific advice such as, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[1640] Terminal

[1641] Visually present users with recommended recipes and supplier information. Visually display detailed recipe instructions and ingredient information for recommended recipes, as well as multiple supplier information.

[1642] Based on the emotion recognition results of the emotion engine, the system also makes recommendations aimed at reducing stress and improving the user's mood. For example, the system might suggest, "You seem to be in the mood to relax a bit today. How about drinking some green tea?"

[1643] By displaying calculated calorie information and advice to users, users can follow a healthy meal plan and maintain a balanced diet.

[1644] Through these steps, the system supports the user's daily life by managing food expenses, calorie intake, and suggesting meals that are in line with their emotions, providing a more personalized dining experience. This allows the user to efficiently manage their living expenses and lead an appropriate dietary lifestyle according to their emotional state.

[1645] The processing flow will be explained below.

[1646] Step 1:

[1647] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate the emotion engine and provide their current emotional state.

[1648] Step 2:

[1649] The server stores the information provided by the user in a database, including address, number of household members, desired food budget, food concept, ability to cook at home, target weight, and refrigerator inventory.

[1650] SQL

[1651] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[1652] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[1653] Step 3:

[1654] The server retrieves information about nearby supermarkets and online stores based on the user's address, including the location, products, and prices of each store.

[1655] Python

[1656] nearest_stores = get_nearest_stores(user_address)

[1657] store_prices = fetch_store_prices(nearest_stores)

[1658] Step 4:

[1659] The emotion engine performs facial recognition or voice analysis of the user to analyze their current emotional state (e.g., stress, joy, sadness, etc.), and sends the results to the server.

[1660] Python

[1661] emotion_state = analyze_emotion(user_facial_expression)

[1662] send_emotion_data_to_server(emotion_state)

[1663] Step 5:

[1664] The server searches for the optimal recipe based on the user's emotional state, refrigerator inventory, and ingredient concept. For example, if the user is feeling stressed, it will prioritize dishes that are known to have a relaxing effect.

[1665] SQL

[1666] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept AND emotion_suitability = :emotion_state;

[1667] Step 6:

[1668] The server selects the most suitable recipe and sends its details (e.g., ingredients, cooking instructions) to the user terminal. For example, if "Teriyaki Chicken" is selected, the server provides the recipe details.

[1669] Python

[1670] recommended_recipe = select_best_recipe(available_recipes)

[1671] send_recipe_to_client(recommended_recipe)

[1672] Step 7:

[1673] The device visually displays details of the recommended recipe, including the ingredients list and cooking instructions.

[1674] HTML

[1675]

[1676] <h1>{{recommended_recipe.name}} < / h1>

[1677] {{recommended_recipe.ingredients}}

[1678] {{recommended_recipe.instructions}}

[1679]

[1680] Step 8:

[1681] The server generates a list of ingredients missing from the refrigerator based on the recommended recipe, including information identifying the most economical source for each ingredient.

[1682] SQL

[1683] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[1684] Step 9:

[1685] Based on the generated ingredient list, the server suggests the most economical and convenient place to buy ingredients, such as "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[1686] Python

[1687] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[1688] send_purchase_recommendations_to_client(purchase_recommendations)

[1689] Step 10:

[1690] The device displays a list of ingredients to be purchased and recommended places to purchase them to the user, allowing the user to shop efficiently.

[1691] HTML

[1692]

[1693] <h2> Recommended Shops < / h2>

[1694]

[1695] {% for item, shop in purchase_recommendations %}

[1696] {{item}} - Buy at {{shop}}

[1697] {% endfor %}

[1698]

[1699]

[1700] Step 11:

[1701] The server calculates the calories of the recommended recipe and checks it against the appropriate calorie amount based on the target weight. For example, if the target weight is 60 kg, the calorie information of the recipe is verified based on the appropriate calorie intake for that day.

[1702] Python

[1703] recipe_calories = calculate_calories(recommended_recipe)

[1704] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[1705] Step 12:

[1706] The server provides the user with advice on calorie management, such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[1707] Python

[1708] if recipe_calories <= daily_calorie_needs:

[1709] calorie_advice = "This meal fits within your daily calorie needs."

[1710] else:

[1711] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[1712] send_calorie_advice_to_client(calorie_advice)

[1713] Step 13:

[1714] The device visually displays calculated calorie information and advice, allowing users to follow a healthy eating plan.

[1715] HTML

[1716]

[1717] <h3> Calories: {{recipe_calories}} < / h3>

[1718] {{calorie_advice}}

[1719]

[1720] Through these steps, the system comprehensively supports users in managing their food expenses, calorie intake, and suggesting meals according to their emotions, allowing users to efficiently manage their living expenses and lead an appropriate diet according to their emotional state.

[1721] Example 2

[1722] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1723] Conventional meal plan suggestion systems make blanket suggestions without considering the user's basic information or current emotional state, making it difficult to provide personalized meal plans tailored to individual needs. Furthermore, because ingredients and recipes are not selected based on refrigerator inventory or the user's emotional state, there are problems with food waste and reduced user satisfaction. Furthermore, the number of potential suppliers is limited, making it difficult to make economical or convenient choices.

[1724] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of the user's address, number of households, desired cost, ingredient concept, ability to cook at home, target weight, and refrigerator inventory; means for acquiring information on nearby retailers or online stores based on the address; means for recognizing the user's emotional state by analyzing the user's facial expressions and voice; means for generating an optimal ingredient list and cooking method based on the input information, emotional state, and acquired retailer information; means for suggesting the most economical or convenient purchasing source based on the generated ingredient list; and means for calculating calorie intake based on the target weight and providing appropriate calorie advice. This makes it possible to provide a personalized meal plan tailored to the user's individual needs and current emotional state.

[1725] "User" refers to an individual who enters information into the system and receives a personalized meal plan.

[1726] "Address" refers to detailed information about the user's place of residence and is used to obtain information about nearby retailers and online stores.

[1727] "Number of households" refers to the number of people living in the user's household, and is information that affects meal plan portion sizes and food cost calculations.

[1728] "Desired spend" refers to the monthly or weekly budget that the user plans to spend on food.

[1729] "Ingredient concept" refers to the meal theme or ingredient characteristics desired by the user (e.g., healthy, low calorie, etc.).

[1730] "Ability to cook at home" refers to whether or not the user has the ability or desire to cook at home.

[1731] "Goal weight" refers to the weight the user wants to achieve, and is important information for calculating calories and creating meal plans.

[1732] "Refrigerator inventory" refers to a list of ingredients currently stored in the user's refrigerator.

[1733] "Store" refers to a physical store selling ingredients.

[1734] "Online Store" refers to an e-commerce site that sells products over the Internet.

[1735] "Emotional state" refers to the mood or psychological state of the user that is recognized based on facial expressions and voice data.

[1736] "Ingredient list" refers to a list of ingredients that the user needs to purchase.

[1737] "Recipe" refers to the steps or recipes for cooking using ingredients specified by the user.

[1738] "Purchasing point" refers to the retail store or online store where you purchase ingredients.

[1739] "Calories" refers to the amount of energy contained in an ingredient or dish and is used to calculate a meal plan relative to a user's weight goal.

[1740] The present invention relates to a system that proposes an optimal meal plan taking into account the user's input information and emotional state. The details of this system are described below.

[1741] User

[1742] The user logs into the system and enters their address, number of household members, desired cost, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is entered from the device the user uses (e.g., PC, smartphone, tablet). The user also activates the emotion engine and provides their current emotional state. At this time, emotions are detected using facial recognition and voice analysis. A specific example is shown below.

[1743] Examples:

[1744] The user enters the following information:

[1745] Address: Minato-ku, Tokyo

[1746] Number of people in the household: 2

[1747] Desired cost: 40,000 yen / month

[1748] Ingredients concept: Healthy food

[1749] Self-catering: Yes

[1750] Target weight: 60kg

[1751] Fridge stock: Chicken breast, broccoli, tofu

[1752] Next, the user's emotion engine is activated and recognizes that the user is feeling stressed.

[1753] server

[1754] The server stores the information provided by the user in a database. For example, it uses an SQL or NoSQL database to efficiently manage data. The server also accesses an API to obtain information about nearby retailers and online stores based on the user's address information. This involves large-scale data collection and analysis.

[1755] Furthermore, the server receives user emotional data and uses it to select ingredients and generate recipes. Emotion recognition uses image recognition technology (e.g., OpenCV) and natural language processing (e.g., Google Cloud's natural language API).

[1756] Examples:

[1757] The server uses the emotion data and refrigerator inventory data to suggest recipes such as:

[1758] "Healthy stir-fried chicken breast and broccoli"

[1759] Next, based on this recipe, a list of ingredients needed that are not in the refrigerator (e.g. olive oil, salt) is made.

[1760] Terminal

[1761] The device visually presents the information sent from the server to the user. Specifically, it displays recommended recipes, purchasing information, and calorie information. The user can confirm this information and proceed to purchase or execute the plan.

[1762] Examples:

[1763] The following information will be displayed on the terminal screen:

[1764] "New Recipe: Healthy Stir-fried Chicken Breast and Broccoli"

[1765] "Estimated calories: 500kcal per serving"

[1766] "Purchase information: Olive oil - nearest supermarket, Salt - Online Store Y"

[1767] Prompt Sentence Examples

[1768] Below are some example prompts to input to the generative AI model:

[1769] User-entered information:

[1770] Address: Minato-ku, Tokyo

[1771] Number of people in the household: 2

[1772] Desired cost: 40,000 yen / month

[1773] Ingredients concept: Healthy food

[1774] Self-catering: Yes

[1775] Target weight: 60kg

[1776] Fridge stock: Chicken breast, broccoli, tofu

[1777] Current emotional state: I'm stressed

[1778] Use this information to provide users with the perfect meal plan, and if they don't have the ingredients they need for a recipe in their fridge, provide them with information on where to buy them.

[1779] As described above, this system generates meal plans based on the user's input information and emotional state and provides them visually, thereby enabling personalized meal suggestions tailored to individual needs.

[1780] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1781] Step 1: User Input

[1782] User

[1783] Users log in to the system and enter their address, number of household members, desired cost, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory.

[1784] It also activates the emotion engine and provides the current emotional state.

[1785] input

[1786] Address, number of households, desired expenses, food concept, ability to cook at home, target weight, refrigerator inventory, emotional state

[1787] Specific actions

[1788] The user enters the necessary information into the device interface and clicks the "Send" button. The emotion engine uses a camera and microphone to collect facial and voice data.

[1789] output

[1790] The entered data is sent to the server.

[1791] Step 2: Storing and Retrieving Data

[1792] server

[1793] The server stores the information provided by the user in a database.

[1794] Obtain information on nearby retailers and online stores based on address information.

[1795] input

[1796] Input data submitted by the user

[1797] Specific actions

[1798] The server uses an SQL or NoSQL database to structure and store user information, and then uses an API to collect information from merchants.

[1799] output

[1800] User information stored in the database and price information obtained from retailers

[1801] Step 3: Emotion Recognition

[1802] Emotion Engine

[1803] It analyzes the user's facial expressions and voice data to recognize their current emotions.

[1804] The recognized emotion data is sent to the server.

[1805] input

[1806] Facial expression and voice data collected by cameras and microphones

[1807] Specific actions

[1808] The emotion engine analyzes emotions using image recognition technology (e.g., OpenCV) and natural language processing technology.

[1809] output

[1810] Recognized emotional state data is generated and transmitted to a server.

[1811] Step 4: Select and generate a recipe

[1812] server

[1813] Search and select the best recipes based on refrigerator inventory data and sentiment data.

[1814] Generate recipes along with ingredient lists.

[1815] input

[1816] Refrigerator inventory data, sentiment data, retailer information

[1817] Specific actions

[1818] It queries a large recipe database and selects recipes based on the user's emotional state. It applies a filtering algorithm to determine the best recipe.

[1819] output

[1820] Selected recipes and ingredient lists

[1821] Step 5: Recommend a supplier

[1822] server

[1823] Generate a list of ingredients that are not in the refrigerator and identify the most economical source of each ingredient.

[1824] It also makes recommendations on where to buy based on emotional data.

[1825] input

[1826] Recipes, ingredient lists, retailer information, emotional data

[1827] Specific actions

[1828] It uses cost calculation algorithms to select economical purchasing sources, and also suggests the best places to buy specific ingredients based on sentiment data.

[1829] output

[1830] Recommended Purchase List

[1831] Step 6: Counting and adjusting calories

[1832] server

[1833] Calculate the calorie information for recommended recipes and compare it with the appropriate calorie amount based on your target weight.

[1834] Suggest calorie adjustments or alternatives as needed.

[1835] input

[1836] Recipe data, target weight

[1837] Specific actions

[1838] It uses a calorie counting algorithm to calculate the calories in each recipe, calculates your daily calorie intake based on your target weight, and offers alternative suggestions if adjustments are needed.

[1839] output

[1840] Calorie calculation results and adjustment suggestions

[1841] Step 7: Visualizing the results

[1842] Terminal

[1843] To provide information from a server to a user visually.

[1844] View recipes, where to buy, and calorie information.

[1845] input

[1846] Recipes, ingredient lists, purchasing information, and calorie information sent from the server

[1847] Specific actions

[1848] The information is displayed on the device interface for the user to check, and the user can check the displayed information through the device and decide on the next action.

[1849] output

[1850] Information presented visually to the user

[1851] (Application example 2)

[1852] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1853] Currently, there are systems that provide personalized meal plans, but they do not adequately recommend ingredients and recipes that take into account the user's emotional state. Furthermore, there are no systems that reflect refrigerator inventory information and provide emotional personalization. Therefore, it is difficult to effectively provide meal suggestions that help users relax and maintain their health.

[1854] The specific processing 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 receiving input of the user's address, number of households, desired food expenses, ingredient concept, ability to cook at home, target weight, refrigerator inventory, and emotional state; means for acquiring information on nearby commercial facilities or electronic commerce sites based on the address; means for generating an optimal ingredient list and cooking method based on the input information and the acquired commercial facility information; means for suggesting the most economical or convenient purchasing source based on the generated ingredient list; means for calculating calorie intake based on the target weight and providing appropriate calorie advice; and means for recommending ingredients and recipes tailored to the user based on the emotional state. This makes it possible to provide a personalized meal plan that takes the user's emotional state into consideration.

[1855] An "address" is geographical information that indicates where a user lives.

[1856] "Number of households" is information indicating the number of people residing in a particular residence.

[1857] "Desired food expenses" is information indicating the amount of money the user wishes to spend on ingredients and meals.

[1858] "Ingredient concept" is information that indicates the theme or philosophy of the ingredients or dishes that the user likes.

[1859] "Ability to cook at home" is information indicating whether the user has the ability or motivation to cook for themselves.

[1860] "Target weight" is information indicating the weight that the user wishes to achieve.

[1861] "Refrigerator inventory" is information showing a list of ingredients currently stored in the user's refrigerator.

[1862] "Emotional state" is information that indicates the user's current psychological and emotional state.

[1863] "Commercial facility" means a store selling food and daily necessities.

[1864] "Electronic Venue" means an online store where goods can be purchased over the Internet.

[1865] The "optimal ingredient list" indicates a list of ingredients that are most suitable for the user's needs.

[1866] A "cooking method" is a recipe or procedure for cooking a dish using specific ingredients.

[1867] "Economical or convenient purchasing location" refers to the place where the user can purchase ingredients that offers the best cost performance or convenience.

[1868] "Intake of calories" refers to the total amount of energy that a user takes in within a certain period of time.

[1869] "Calorie advice" refers to advice on the recommended calorie intake to achieve the user's goal weight.

[1870] "Personalized meal plan" refers to a meal plan that is customized based on an individual user's personal information and emotional state.

[1871] The following describes an embodiment of the present invention.

[1872] System configuration

[1873] The system consists of a user's smartphone, a server, and a communication network via the Internet. The user's smartphone includes an emotion recognition engine, a voice recognition engine, and a data entry interface. The server includes a database management system, a recipe generation engine, a calorie calculation library, and a delivery API.

[1874] Hardware and Software

[1875] Smartphone: Uses OpenCV and dlib for facial expression recognition, and Google Cloud Speech-to-Text for voice recognition.

[1876] Server: We use MySQL as our database management system, with custom libraries for calorie calculation and recipe generation. Delivery information is obtained from a number of online APIs (e.g. UberEats and other delivery integration APIs).

[1877] Program processing overview

[1878] User Input

[1879] The user uses a smartphone to input information such as address, number of household members, desired food budget, ingredient concept, ability to cook at home, target weight, refrigerator inventory, and current emotional state. The emotional state is acquired using the smartphone's camera and voice interface. Facial expressions are analyzed using a facial recognition engine (e.g., OpenCV and dlib), and the voice data is converted into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text).

[1880] Data Processing and Recipe Generation

[1881] The server stores the received user information in a database. Based on the address, information on nearby commercial facilities and electronic trading locations is obtained via API. Next, the optimal ingredient list and cooking method is generated based on the input and obtained information. Specifically, it suggests ingredients that reduce stress and recipes that have a relaxing effect based on the user's emotional state. It also uses the inventory in the refrigerator to avoid the need to purchase unnecessary ingredients.

[1882] Economical purchasing suggestions

[1883] Based on the generated ingredient list, the server searches for the most economical or convenient source of purchase via API and suggests it to the user. For example, it compares whether the ingredients needed for a particular dish are cheaper at a nearby commercial facility or an online store, and provides the user with the optimal source of purchase.

[1884] Calorie Management and Calorie Advice

[1885] The server calculates the user's daily calorie intake based on their target weight, evaluates the calorie content of the suggested recipes, and, if necessary, provides the user with alternative recipes with adjusted calorie content or additional advice.

[1886] Specific examples

[1887] For example, if a user is feeling stressed at work and wants to relax during lunchtime, the system will suggest relaxing "ochazuke" (rice with green tea) or "relaxing tea" based on the user's emotional state, and provide information on the nearest commercial facility or online store where to purchase the ingredients needed for these. It will also provide calorie information and suggest balanced meals based on the user's target weight and current calorie intake.

[1888] Prompt Sentence Examples

[1889] "If a user is feeling stressed at work, suggest a relaxing dish. Or search for nearby delivery services and provide the best options."

[1890] In this way, the present invention is able to provide a personalized meal plan that takes into account the user's emotional state and daily needs.

[1891] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1892] Step 1: Enter your user information

[1893] The user uses a smartphone to input their address, household size, desired food budget, ingredient concept, whether they can cook at home, target weight, refrigerator inventory, and current emotional state. The input information is sent to the server through the smartphone's data input interface. This process collects the individual information and emotional state required for the system.

[1894] Input: User's address, number of household members, desired food budget, food concept, whether self-cooking is possible, target weight, refrigerator inventory, emotional state

[1895] Output: Sending information to the server

[1896] Step 2: Recognizing your emotional state

[1897] The device's camera and microphone are used to recognize the user's current emotional state from their facial expressions and voice. The device processes the facial expression data using an emotion recognition engine (e.g., OpenCV and dlib), converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text), and determines the emotion. The analysis results are sent to the server.

[1898] Input: User's facial expression data, voice data

[1899] Output: Judgment result of the user's emotional state

[1900] Step 3: Storing information in a database

[1901] The server stores the received user information in a database. A database management system (e.g., MySQL) is used to efficiently manage information such as user profiles, refrigerator inventory, and emotional states.

[1902] Input: User information (address, number of households, etc.), emotional state

[1903] Output: Save information to a database

[1904] Step 4: Obtain information on nearby commercial facilities

[1905] Based on the address, the server retrieves information about nearby commercial facilities and online stores via API, including information on the prices of ingredients at each store.

[1906] Input: User's address

[1907] Output: Information about commercial facilities and online stores

[1908] Step 5: Generate a recipe and ingredient list

[1909] The server generates an optimal ingredient list and recipe based on the input information and acquired commercial facility information, taking into account refrigerator inventory and emotional state, and selecting ingredients and recipes that have a relaxing effect according to the emotional state.

[1910] Input: User information, commercial facility information, emotional state

[1911] Output: Ingredient list and recipe

[1912] Step 6: Propose a supplier

[1913] Based on the generated list of ingredients, the server compares prices and delivery terms using delivery APIs (e.g., Uber Eats and other delivery integration APIs) to suggest the most economical or convenient shopping locations. Based on this information, the server suggests the most suitable shopping locations for the user.

[1914] Input: Ingredient list

[1915] Output: Buyer suggestions

[1916] Step 7: Calorie counting and advice

[1917] The server calculates calorie intake based on the user's target weight, evaluates the calorie information of the generated recipe, and provides the user with alternative recipes with adjusted calorie amounts or additional advice, if necessary.

[1918] Input: Recipe, Goal Weight

[1919] Output: Calorie calculation results, advice provided

[1920] Step 8: Provide visual information

[1921] The device visually presents recommended recipes and vendor information to the user, displaying detailed recipe steps, ingredient information, multiple vendor information, and calorie information through a visual interface.

[1922] Input: Recipe, supplier information, calorie calculation results

[1923] Output: A visual display to the user

[1924] Through these steps, users can efficiently receive meal plans tailored to their emotional state and lead a healthy and personalized diet.

[1925] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1926] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1927] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1928] [Fourth embodiment]

[1929] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1930] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1931] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1932] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1933] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1934] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1935] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1936] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1937] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1938] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1939] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1940] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1941] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1942] The system of the present invention starts with the user inputting their address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, and then uses that information to suggest optimal daily meals and purchasing locations for each user. The program processing of the system of the present invention is explained below in natural language.

[1943] Initial Setup

[1944] User

[1945] First, the user logs into the system and enters their address, number of household members (e.g., 2 people), desired food budget (30,000 yen per month or 1,000 yen per day), food concept (mainly Japanese food), whether they can cook at home (possible), target weight (60 kg), and refrigerator inventory (e.g., rice, miso, chicken, etc.).

[1946] server

[1947] The server then stores the information provided by the user in a database.

[1948] The server obtains information on nearby supermarkets and online stores based on the user's address, as well as price information on ingredients sold at each store.

[1949] Ingredient and recipe recommendations

[1950] server

[1951] The input information is analyzed and a recipe that prioritizes the use of the refrigerator's inventory is searched for. For example, if there is rice and chicken, the recipe for "Teriyaki Chicken" is selected.

[1952] The ingredient concept is centered around Japanese cuisine and cooking at home is possible, so suitable Japanese recipes will be recommended.

[1953] Terminal

[1954] The recommended recipes are displayed on the user's device. For example, if a teriyaki chicken recipe is recommended, the cooking instructions and details of the ingredients are displayed.

[1955] Suggestions for where to buy ingredients

[1956] server

[1957] Based on the recommended recipe, a list of ingredients that are not in the user's refrigerator is created. For example, if it turns out that soy sauce, sugar, and ginger are not in the refrigerator, a purchase list for these items is generated.

[1958] Next, the system selects the most economical store for each ingredient based on price information from the nearest supermarket or online store and suggests it to the user.

[1959] Terminal

[1960] The user's device displays a list of ingredients needed and recommended places to buy them. For example, the information provided may include "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[1961] Calorie intake and weight management

[1962] server

[1963] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. For example, if the target weight is 60 kg, calculate the daily calorie intake and check whether the recommended recipes fall within that range.

[1964] It will suggest calorie adjustments and alternatives as needed, for example, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[1965] Terminal

[1966] The user's device will display a healthy meal plan along with calculated calorie information, such as "Today's menu is 1500 kcal in total, which is a good balance for your calorie goal."

[1967] The present invention thereby automates a series of processes for users to efficiently manage their living expenses and lead a balanced diet, thereby providing full support to users in both food expenses and health management.

[1968] The processing flow will be explained below.

[1969] Step 1:

[1970] Users log in to the system and enter their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory, allowing them to register their lifestyle and food preferences in the system.

[1971] Step 2:

[1972] The server stores the information provided by the user in a database, which is used for further analysis and recommendations.

[1973] SQL

[1974] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[1975] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[1976] Step 3:

[1977] The server obtains information about nearby supermarkets and online stores based on the user's address. This information is collected using APIs that reference the acquired store data.

[1978] Python

[1979] nearest_stores = get_nearest_stores(user_address)

[1980] store_prices = fetch_store_prices(nearest_stores)

[1981] Step 4:

[1982] The server analyzes the user's input information and searches for recipes that prioritize the use of existing refrigerator inventory. For example, if "rice" and "chicken" are in stock, the server searches for a recipe for "teriyaki chicken."

[1983] SQL

[1984] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept;

[1985] Step 5:

[1986] The server selects the most suitable recipe and sends the recommended recipe information to the user terminal. For example, a recipe for "Teriyaki Chicken" is provided, along with cooking instructions and details of the ingredients required.

[1987] Step 6:

[1988] The device displays the recommended recipes to the user, for example, providing a detailed visual recipe for teriyaki chicken.

[1989] HTML

[1990]

[1991] <h1> {{recommended_recipe.name}} < / h1>

[1992] {{recommended_recipe.ingredients}}

[1993] {{recommended_recipe.instructions}}

[1994]

[1995] Step 7:

[1996] The server generates a list of ingredients that are missing from the refrigerator based on the recommended recipe. For example, if soy sauce, sugar, or ginger are missing, the server adds these items to the list.

[1997] SQL

[1998] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[1999] Step 8:

[2000] The server lists the most economical places to purchase each ingredient and suggests them to the user, such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar at online store X."

[2001] Python

[2002] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[2003] Step 9:

[2004] The device displays a list of ingredients to purchase and recommended places to buy them to the user, organizing and presenting the information in a format that is visually easy for the user to understand.

[2005] HTML

[2006]

[2007] <h2> Recommended Shops < / h2>

[2008]

[2009] {% for item, shop in purchase_recommendations %}

[2010] {{item}} - Buy at {{shop}}

[2011] {% endfor %}

[2012]

[2013]

[2014] Step 10:

[2015] The server calculates the calories of the recommended recipes and compares them with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server analyzes the calorie information of the recipes based on the appropriate daily calorie intake.

[2016] Python

[2017] recipe_calories = calculate_calories(recommended_recipe)

[2018] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[2019] Step 11:

[2020] The server provides the user with advice on calorie management. For example, specific advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[2021] Python

[2022] if recipe_calories <= daily_calorie_needs:

[2023] calorie_advice = "This meal fits within your daily calorie needs."

[2024] else:

[2025] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[2026] Step 12:

[2027] The device displays the calculated calorie information and advice to the user, allowing them to follow a healthy eating plan.

[2028] HTML

[2029]

[2030] <h3> Calories: {{recipe_calories}} < / h3>

[2031] {{calorie_advice}}

[2032]

[2033] Through these steps, the system comprehensively supports users in managing food expenses, calorie intake, and maintaining a healthy diet.

[2034] Example 1

[2035] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2036] In today's busy lifestyles, it is difficult for many people to efficiently plan, purchase, and manage their health. This challenge is especially significant for users who want to maintain a balanced diet on a limited budget. Many users also want to avoid wasting ingredients they already have at home and shop economically by effectively utilizing nearby store information. To solve these problems, an automated meal planning and purchasing suggestion system tailored to the user's needs is needed.

[2037] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2038] In this invention, the server includes means for receiving input of a user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for acquiring information on nearby stores or online stores based on the address, means for generating an optimal ingredient list and recipe based on the input information and the acquired store information, means for suggesting the most economical or convenient purchasing source based on the generated ingredient list, means for calculating calorie intake based on the target weight and providing appropriate calorie advice, and means for visually displaying the recommended recipe and purchasing source information on the user terminal. This allows users to efficiently plan their ingredient purchases and maintain a healthy and balanced diet while shopping economically and without waste.

[2039] "User" refers to an individual or household using the system.

[2040] "Address" refers to geographic information of the place where the user resides.

[2041] "Number of households" refers to the number of people in the household to which the user belongs.

[2042] "Desired food budget" refers to the monthly or daily budget set by the user for meals.

[2043] "Ingredient concept" refers to a guideline for a specific food culture or cooking style that a user prefers, such as "mainly Japanese food."

[2044] "Self-cooking" refers to whether the user is able to cook at home.

[2045] "Target weight" refers to the weight that the user wants to achieve.

[2046] "Refrigerator inventory" refers to the types and quantities of ingredients currently in the user's refrigerator.

[2047] "Server" refers to the computer system that performs the central calculations and stores data for this system.

[2048] "Store information" refers to data about nearby stores or online stores obtained based on the user's address.

[2049] An "ingredient list" is a list of ingredients needed by the user, and is used for creating recipes and planning purchases.

[2050] A "recipe" refers to information that describes the steps and ingredients needed to prepare a dish.

[2051] "Purchasing locations" refers to stores and online stores suggested for users to purchase ingredients.

[2052] "Calories intake" refers to the amount of calories consumed by a user in a certain period of time.

[2053] "Calorie Advice" refers to advice based on recommended calorie intake for a user to achieve a weight goal.

[2054] "User terminal" refers to a device, such as a computer, smartphone, or tablet, that a user uses to access the system.

[2055] "Visually displaying" refers to presenting information in an easy-to-read format on the screen of a user terminal.

[2056] MODE FOR CARRYING OUT THE INVENTION

[2057] The system of the present invention proposes optimal daily cooking and food purchasing locations for users based on multiple pieces of information provided by the user. This system is composed of a combination of hardware and software, and a specific example is shown below.

[2058] Initial Setup

[2059] User

[2060] First, the user logs in to the system and enters the address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory information. Specifically, the following information is entered:

[2061] Address: Tokyo

[2062] Number of people in the household: 2

[2063] Desired food expenses: 30,000 yen per month

[2064] Ingredients concept: Japanese cuisine

[2065] Self-catering: Yes

[2066] Target weight: 60kg

[2067] Refrigerator inventory: rice, miso, chicken

[2068] Information storage and analysis

[2069] server

[2070] The server stores the information entered by the user in a database. The database used for this is a relational database such as MySQL or PostgreSQL. Based on the stored information, the server collects information about nearby stores and online stores based on the user's address. This information is collected using web scraping technologies such as Python's BeautifulSoup and Scrapy.

[2071] Recipe Recommendations

[2072] server

[2073] Next, the server searches for recipes that prioritize the refrigerator inventory information provided by the user. For example, if there is rice and chicken in the refrigerator, a recipe such as "Teriyaki Chicken" will be selected. Also, since the ingredient concept is centered on Japanese cuisine, the server will recommend suitable recipes from among Japanese cuisine recipes.

[2074] Viewing Recipes

[2075] Terminal

[2076] The recommended recipes are displayed on the user's device. They are presented in a visually easy-to-understand format using HTML and JavaScript. For example, if a recipe for "teriyaki chicken" is recommended, the cooking instructions and details of the ingredients are displayed on the user's device.

[2077] Suggestions for where to buy ingredients

[2078] server

[2079] Based on the recommended recipe, the server creates a list of ingredients that the user does not have in their refrigerator. For example, if soy sauce, sugar, or ginger are missing, they are added to the shopping list. The server then suggests the most economical way to purchase the ingredients based on price information from the nearest supermarket or online store.

[2080] View shopping list

[2081] Terminal

[2082] The user's device will display a list of ingredients needed and recommended places to buy them. For example, it will show information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from an online store."

[2083] Calorie intake and weight management

[2084] server

[2085] The server calculates the calorie information of the recommended recipes and compares it with the appropriate calorie intake based on the user's target weight. For example, if the target weight is 60 kg, the server sets the daily calorie intake to 1800 kcal and checks whether the provided recipes fall within that range.

[2086] View calorie information and meal plans

[2087] Terminal

[2088] A healthy meal plan is displayed on the user's device along with calculated calorie information. For example, advice such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie goal of 1500 kcal" is shown.

[2089] Examples and prompts

[2090] As a concrete example, here is how the system operates based on the information above:

[2091] 1. Address: Tokyo

[2092] 2. Number of people in the household: 2

[2093] 3. Desired food expenses: 30,000 yen per month

[2094] 4. Ingredients concept: Japanese cuisine

[2095] 5. Self-catering: Yes

[2096] 6. Target weight: 60kg

[2097] 7. Refrigerator inventory: rice, miso paste, chicken

[2098] Based on this, the system makes recommendations such as:

[2099] Recommended recipe: Teriyaki Chicken

[2100] Shopping list: soy sauce, sugar, ginger

[2101] Where to buy: Soy sauce from your local supermarket, sugar from an online store

[2102] Prompt Sentence Examples

[2103] "Enter the user's address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory to display a list of recommended recipes and where to buy them."

[2104] As described above, the present invention is a comprehensive system that allows users to efficiently plan food purchasing, maintain a balanced diet, and manage their health.

[2105] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2106] Step 1: Enter your information

[2107] Input: The user enters their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory into the system.

[2108] Specific operation: The user logs in to a dedicated application or website using a smartphone or computer and enters the necessary information. For example, they enter information such as: living in Tokyo, household size: 2 people, desired food budget: 30,000 yen per month, mainly Japanese food, able to cook at home, target weight: 60 kg, and having rice, miso, and chicken in the refrigerator.

[2109] Output: The system receives user input.

[2110] Step 2: Store and analyze information

[2111] Input: Information entered by the user.

[2112] What it does: The server receives the information entered by the user and stores it in a database, using a relational database such as MySQL or PostgreSQL.

[2113] Output: Stored user information data. The server uses this data to:

[2114] Step 3: Gather information about nearby stores

[2115] Input: User's address information.

[2116] Specific operation: Based on the user's address, the server uses web scraping technology (e.g., Python's BeautifulSoup or Scrapy) to collect information on nearby supermarkets and online stores. For example, it collects price information for large supermarkets and online grocery stores in a specific area of ​​Tokyo.

[2117] Output: Collected nearby store and price information data.

[2118] Step 4: Find a recipe

[2119] Input: User's refrigerator inventory information, ingredient concept.

[2120] Specific operation: The server searches the recipe database for the corresponding recipe based on the input refrigerator inventory information. For example, if there is rice and chicken in the refrigerator, it searches for Japanese recipes that use these ingredients.

[2121] Output: A list of suitable recipes that were found.

[2122] Step 5: Recipe Selection

[2123] Input: Recipe search results.

[2124] Specific operation: The server recommends the best recipe based on the ingredient concept (e.g., mainly Japanese food). As a specific example, the recipe "Teriyaki Chicken" using chicken and rice is selected.

[2125] Output: Recommended recipe information.

[2126] Step 6: View the recipe

[2127] Input: Recommended recipe information.

[2128] What it does: The recommended recipe is displayed on the user's device. The recipe steps and ingredient details for "Teriyaki Chicken" are visually displayed on the screen using HTML and JavaScript.

[2129] Output: Recipe information displayed on the user's device.

[2130] Step 7: Make a list of ingredients you need

[2131] Input: Recommended recipe information, user's refrigerator inventory information.

[2132] Specific behavior: The server creates a list of ingredients that are missing from the user's refrigerator based on the recommended recipe. For example, if a teriyaki chicken recipe requires soy sauce, sugar, and ginger, but these are not in the refrigerator, the server adds them to the list.

[2133] Output: A list of ingredients needed.

[2134] Step 8: Propose a supplier

[2135] Input: List of ingredients needed, information on nearby stores.

[2136] Specific operation: The server selects the most economical and convenient place to purchase and suggests it to the user. For example, it suggests that the nearest supermarket is the cheapest place to buy soy sauce, and the online store is the cheapest place to buy sugar.

[2137] Output: Recommended vendor information.

[2138] Step 9: View your shopping list

[2139] Input: list of ingredients needed, recommended purchasing information.

[2140] Specific behavior: The recommended purchasing locations and a list of ingredients needed are displayed on the user's device. The user is given specific instructions, such as "Purchase soy sauce at the nearest supermarket and sugar at online store X."

[2141] Output: Shopping list information displayed on the user's device.

[2142] Step 10: Calculate calorie information

[2143] Input: Recommended recipe information, user's goal weight.

[2144] Specific operation: The server calculates the calorie information of the recommended recipe and compares it with the appropriate calorie schedule based on the user's target weight. For example, if the target weight is 60 kg, it sets the daily calorie intake to 1800 kcal and checks whether it falls within that range.

[2145] Output: Calorie count and calorie advice.

[2146] Step 11: View calorie information and meal plans

[2147] Input: Calorie count and calorie advice.

[2148] What it does: A healthy meal plan is displayed on the user's device along with calculated calorie information, and specific advice is given, such as "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie goal of 1500 kcal."

[2149] Output: Calorie information and meal plan displayed on user device.

[2150] As described above, this system provides comprehensive support for users to efficiently plan food purchases, maintain a balanced diet, and manage their health.

[2151] (Application example 1)

[2152] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2153] Conventional meal recommendation systems focus on supporting home cooking based on information entered by the user, but in real life, there are many situations where home cooking is not possible or people prefer to eat out. Furthermore, maintaining a healthy diet requires consideration of specific calorie intake and nutritional balance, but existing systems have difficulty providing comprehensive support for these. Therefore, there was a need for a system that could provide optimal meal recommendations not only for home cooking, but also for eating out or ordering food delivery.

[2154] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2155] In this invention, the server includes means for receiving input from the user of the user's address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory, means for obtaining information on nearby stores or online stores, means for generating optimal ingredient lists and recipes, means for obtaining restaurant menus and recommending optimal menus, and means for arranging orders through affiliated food delivery services. This allows users to receive economical and healthy meal suggestions for a variety of eating habits, including not only cooking at home but also eating out and food delivery.

[2156] A "user" is an entity that uses this system, and is an individual or group that provides information such as address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, and refrigerator inventory.

[2157] An "address" is information used to identify the location where a user resides, and is data necessary for procuring ingredients from nearby stores or online stores and using food delivery services.

[2158] "Number of households" indicates the number of people living at the same address, and is necessary to properly calculate recommended recipes and ingredient amounts.

[2159] "Desired food budget" is information indicating the budget that the user can spend on ingredients and meals, and is a standard value for suggesting economical ingredient lists and purchasing locations.

[2160] "Ingredient concept" is information that indicates the user's preferred eating style or cuisine genre, and is a criterion when selecting recommended recipes and menus.

[2161] "Ability to cook at home" is information that indicates the user's ability and willingness to cook at home, and is a criterion for determining whether or not a recommendation of a restaurant menu is necessary.

[2162] "Target weight" is information indicating the weight that the user wants to achieve, and is data necessary for calculating calorie intake and providing calorie advice.

[2163] "Refrigerator inventory" is information showing a list of ingredients that the user currently owns, and is data that serves as a basis for providing economical recipes that use inventory as much as possible.

[2164] "Store or online store information" refers to information about physical stores located near the user's address or places where ingredients can be purchased online, including price information and information about ingredients available.

[2165] The "optimal ingredient list" is a list of the most economical and nutritionally balanced ingredients based on information such as the user's desired food budget, ingredient concept, and whether or not they can cook at home.

[2166] A "recipe" is information that indicates the cooking steps and details of the ingredients required, generated based on information provided by the user.

[2167] The "dining out menu" is a list of recommended dishes for when the user is unable to cook at home or wishes to eat out, and is selected based on the user's nutritional balance and calorie goals.

[2168] A "food delivery service" is a service in which food is delivered to a user's address by an affiliated company or service provider, allowing users to easily enjoy restaurant menus in the comfort of their own home.

[2169] The "means for arranging an order" refers to a means for enabling a user to quickly and reliably order and use the restaurant menu selected by the user through a food delivery service.

[2170] This invention is a system that proposes optimal meals based on information provided by users to support their diverse dietary habits. This system is configured to accommodate not only users who cook at home, but also those who wish to eat out or use food delivery services.

[2171] System configuration

[2172] 1. User Device

[2173] Users access the system using a device such as a smartphone and enter information such as their address, number of household members, desired food budget, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is necessary to make meal suggestions based on the user's specific needs and environment. User devices are built using a cross-platform development environment such as React Native.

[2174] 2. Server

[2175] The server plays a central role in storing the information collected from users in a database (MongoDB) and performing the following processes:

[2176] Information collection: Using Google Maps API, etc., we collect information about nearby stores or online stores based on the user's address.

[2177] Recipe generation: Using a generative AI model (OpenAI GPT-4), the optimal recipe is generated based on the input information.

[2178] Ingredient list generation: Generates a list of ingredients needed based on a recipe and suggests economical and convenient places to buy them.

[2179] Calorie Calculation: Calculates calorie intake based on your target weight and provides appropriate calorie advice.

[2180] Dining menu recommendation: For users who wish to eat out, the app recommends the most suitable dining menu and arranges the order through a partner food delivery service.

[2181] Specific examples

[2182] For example, if a user enters the following information:

[2183] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[2184] Number of household members: 2

[2185] Desired food expenses: 30,000 yen per month

[2186] Ingredients concept: Mainly Japanese cuisine

[2187] Self-catering: Possible

[2188] Target weight: 60kg

[2189] Refrigerator inventory: rice, miso, chicken

[2190] With this information, the server does the following:

[2191] 1. Use the Google Maps API to get information about supermarkets and online stores around Shibuya Ward.

[2192] 2. Using a generative AI model (OpenAI GPT-4), generate recipes such as "Teriyaki Chicken" based on the inventory in the refrigerator.

[2193] 3. It creates a list of ingredients needed for the generated recipe and suggests the best places to buy them based on that list. For example, it suggests buying soy sauce at the nearest supermarket and sugar at an online store.

[2194] 4. Calculate calories and ensure the user meets the calorie goal. For example, calculate that one serving of teriyaki chicken is 500 kcal, and ensure that the user is within the calorie goal even if they eat it three times a day.

[2195] 5. If you can't cook or prefer to eat out, Google Maps will use its API to find nearby healthy restaurants and recommend dishes like a salmon and avocado salad bowl (500 kcal per serving). It will then arrange the order through a partner food delivery service.

[2196] This flow allows users to receive healthy and economical meal suggestions for both home cooking and eating out.

[2197] Example prompts

[2198] User Information:

[2199] Address: 1-2-3 Dogenzaka, Shibuya-ku, Tokyo

[2200] Number of people in the household: 2

[2201] Desired food expenses: 30,000 yen per month

[2202] Ingredients concept: Japanese cuisine

[2203] Self-catering: Yes

[2204] Target weight: 60kg

[2205] Refrigerator inventory: rice, miso, chicken

[2206] Based on this, please tell me a Japanese recipe that prioritizes using the stock in your refrigerator. Also, please provide the ingredients needed, where to buy them, and the associated calorie information.

[2207] This configuration provides comprehensive support for the user's eating habits, enabling them to maintain eating habits efficiently and economically.

[2208] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2209] Step 1:

[2210] A user logs in to the application using a smartphone. The user inputs information such as address, number of household members, desired food budget, ingredient concept, ability to cook at home, target weight, and refrigerator inventory. This input information provides basic parameters related to the user's eating habits.

[2211] Processing: The user launches the application, enters information, and presses the send button. The input information is sent from the terminal to the server.

[2212] Input: Address, number of households, desired food budget, food concept, whether you can cook at home, target weight, refrigerator inventory

[2213] Output: Input sent to the server

[2214] Step 2:

[2215] The server stores the received user input information in a database (MongoDB), which allows for centralized management of data required for subsequent processing.

[2216] Processing: The server parses the input information and stores it in a database.

[2217] Input: Information submitted by the user

[2218] Output: User information stored in the database

[2219] Step 3:

[2220] The server uses the Google Maps API to obtain information about nearby stores or online stores based on the user's address.

[2221] Processing: The server inputs the user's address into the Google Maps API and retrieves information about nearby stores.

[2222] Input: User's address

[2223] Output: Store or online store information

[2224] Step 4:

[2225] The server uses a generative AI model (OpenAI GPT-4) to generate an optimal recipe based on the input information and store information. This recipe prioritizes the use of the inventory in the user's refrigerator.

[2226] Processing: The server inputs the prompt sentences into the AI ​​model and generates the optimal recipe.

[2227] Input: User input information, store information

[2228] Output: The generated recipe

[2229] Step 5:

[2230] The server creates a list of ingredients required for the generated recipe and suggests the most economical and convenient place to buy them based on that list.

[2231] Processing: The server analyzes the recipe, creates a list of ingredients needed, and searches for where to purchase each ingredient.

[2232] Input: Generated recipe, store information

[2233] Output: Optimal ingredients list and purchasing information

[2234] Step 6:

[2235] The server calculates calorie intake based on the user's target weight and checks whether the target recipe is within the appropriate calorie range.

[2236] Processing: The server calculates the calorie information of the recipe and evaluates whether it is suitable for the target weight.

[2237] Input: Generated recipe, target weight

[2238] Output: Calorie intake information and calorie advice

[2239] Step 7:

[2240] If the user wants to eat out, the server uses the Google Maps API to retrieve the menus of nearby healthy restaurants and recommends the most suitable menu based on the user's nutritional balance and calorie goals.

[2241] Processing: The server searches for and recommends restaurant menus based on the user's preferences.

[2242] Input: User's preference, address, target weight

[2243] Output: Optimal dining out menu

[2244] Step 8:

[2245] The server will arrange to order the selected restaurant menu through an affiliated food delivery service.

[2246] Processing: The server sends the dining out menu selection results to the food delivery service API and arranges the order.

[2247] Input: Selected restaurant menu information

[2248] Output: Order placement completion information

[2249] Step 9:

[2250] The user terminal visually displays the recipe, ingredient list, supplier information, calorie intake information, restaurant menu, and order status received from the server.

[2251] Processing: The user terminal converts the received information into a display format and presents it visually to the user.

[2252] Input: Information sent from the server

[2253] Output: Information presented visually to the user

[2254] Through these steps, users can receive healthy and economical meal suggestions for both home cooking and eating out.

[2255] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2256] The system of the present invention provides the user with the optimal meal plan based on various input information from the user (address, number of household members, desired food expenses, ingredient concept, ability to cook at home, target weight, refrigerator inventory). Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to recommend recipes and ingredients according to the user's emotional state, making the user's dining experience more personalized.

[2257] Initial Setup

[2258] User

[2259] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate an emotion engine to provide information about their current emotional state.

[2260] server

[2261] The server stores the information provided by the user in a database. Based on the address, it retrieves information about nearby supermarkets and online stores. It also collects information about the prices of ingredients at each store.

[2262] Emotion Recognition and Recipe Recommendation

[2263] Emotion Engine

[2264] The system recognizes the user's current emotions from their facial expressions and voice, and sends the emotional data to the server. For example, if the system recognizes that the user is feeling stressed, it will use that information to select ingredients and recipes.

[2265] server

[2266] The server searches for and selects the optimal recipe based on the entered refrigerator inventory data and the acquired emotional data. For example, if the user is feeling stressed, it will recommend dishes or teas that have a relaxing effect.

[2267] The server generates the selected recipe and a list of ingredients required and provides it to the user, giving priority to recipes that use ingredients already in the refrigerator.

[2268] Purchase recommendation

[2269] server

[2270] Based on the provided recipe, the system generates a list of ingredients that are not in the refrigerator. It identifies the most economical source of purchase for each ingredient and suggests it to the user. For example, it provides information such as "Purchase soy sauce at the nearest supermarket" or "Purchase sugar from online store X."

[2271] Based on information from the emotion engine, the system also recommends places to buy based on the user's emotions. For example, if the system recommends matcha to reduce stress, it will also recommend the best places to buy it.

[2272] Calorie and weight management

[2273] server

[2274] Calculate the calorie information of the recommended recipes and compare the appropriate calorie amount based on the user's target weight. If the target weight is 60 kg, analyze the calorie information of the recipes based on the appropriate daily calorie intake.

[2275] It will suggest calorie adjustments and alternatives as needed, providing specific advice such as, "This dish is 500 kcal per serving, so even if you eat it three times a day, you'll still be within your calorie target."

[2276] Terminal

[2277] Visually present users with recommended recipes and supplier information. Visually display detailed recipe instructions and ingredient information for recommended recipes, as well as multiple supplier information.

[2278] Based on the emotion recognition results of the emotion engine, the system also makes recommendations aimed at reducing stress and improving the user's mood. For example, the system might suggest, "You seem to be in the mood to relax a bit today. How about drinking some green tea?"

[2279] By displaying calculated calorie information and advice to users, users can follow a healthy meal plan and maintain a balanced diet.

[2280] Through these steps, the system supports the user's daily life by managing food expenses, calorie intake, and suggesting meals that are in line with their emotions, providing a more personalized dining experience. This allows the user to efficiently manage their living expenses and lead an appropriate dietary lifestyle according to their emotional state.

[2281] The processing flow will be explained below.

[2282] Step 1:

[2283] Users log in to the system and input their address, number of household members, desired food budget, food concept, whether they can cook at home, target weight, and refrigerator inventory. They also activate the emotion engine and provide their current emotional state.

[2284] Step 2:

[2285] The server stores the information provided by the user in a database, including address, number of household members, desired food budget, food concept, ability to cook at home, target weight, and refrigerator inventory.

[2286] SQL

[2287] INSERT INTO user_data (user_id, address, household_size, monthly_budget, food_concept, can_cook, target_weight, fridge_contents)

[2288] VALUES (:user_id, :address, :household_size, :monthly_budget, :food_concept, :can_cook, :target_weight, :fridge_contents);

[2289] Step 3:

[2290] The server retrieves information about nearby supermarkets and online stores based on the user's address, including the location, products, and prices of each store.

[2291] Python

[2292] nearest_stores = get_nearest_stores(user_address)

[2293] store_prices = fetch_store_prices(nearest_stores)

[2294] Step 4:

[2295] The emotion engine performs facial recognition or voice analysis of the user to analyze their current emotional state (e.g., stress, joy, sadness, etc.), and sends the results to the server.

[2296] Python

[2297] emotion_state = analyze_emotion(user_facial_expression)

[2298] send_emotion_data_to_server(emotion_state)

[2299] Step 5:

[2300] The server searches for the optimal recipe based on the user's emotional state, refrigerator inventory, and ingredient concept. For example, if the user is feeling stressed, it will prioritize dishes that are known to have a relaxing effect.

[2301] SQL

[2302] SELECT FROM recipes WHERE ingredients IN (SELECT item FROM fridge_contents WHERE user_id = :user_id) AND food_concept = :food_concept AND emotion_suitability = :emotion_state;

[2303] Step 6:

[2304] The server selects the most suitable recipe and sends its details (e.g., ingredients, cooking instructions) to the user terminal. For example, if "Teriyaki Chicken" is selected, the server provides the recipe details.

[2305] Python

[2306] recommended_recipe = select_best_recipe(available_recipes)

[2307] send_recipe_to_client(recommended_recipe)

[2308] Step 7:

[2309] The device visually displays details of the recommended recipe, including the ingredients list and cooking instructions.

[2310] HTML

[2311]

[2312] <h1> {{recommended_recipe.name}} < / h1>

[2313] {{recommended_recipe.ingredients}}

[2314] {{recommended_recipe.instructions}}

[2315]

[2316] Step 8:

[2317] The server generates a list of ingredients missing from the refrigerator based on the recommended recipe, including information identifying the most economical source for each ingredient.

[2318] SQL

[2319] SELECT item FROM recipeingredients WHERE recipe_id = :recipe_id AND item NOT IN (SELECT item FROM fridge_contents WHERE user_id = :user_id);

[2320] Step 9:

[2321] Based on the generated ingredient list, the server suggests the most economical and convenient place to buy ingredients, such as "purchase soy sauce at the nearest supermarket" or "purchase sugar from online store X."

[2322] Python

[2323] purchase_recommendations = get_best_purchase_options(needed_items, store_prices)

[2324] send_purchase_recommendations_to_client(purchase_recommendations)

[2325] Step 10:

[2326] The device displays a list of ingredients to be purchased and recommended places to purchase them to the user, allowing the user to shop efficiently.

[2327] HTML

[2328]

[2329] <h2> Recommended Shops < / h2>

[2330]

[2331] {% for item, shop in purchase_recommendations %}

[2332] {{item}} - Buy at {{shop}}

[2333] {% endfor %}

[2334]

[2335]

[2336] Step 11:

[2337] The server calculates the calories of the recommended recipe and checks it against the appropriate calorie amount based on the target weight. For example, if the target weight is 60 kg, the calorie information of the recipe is verified based on the appropriate calorie intake for that day.

[2338] Python

[2339] recipe_calories = calculate_calories(recommended_recipe)

[2340] daily_calorie_needs = calculate_daily_needs(user_target_weight, user_activity_level)

[2341] Step 12:

[2342] The server provides the user with advice on calorie management, such as "This dish has 500 kcal per serving, so even if you eat it three times a day, you will still be within your calorie target."

[2343] Python

[2344] if recipe_calories <= daily_calorie_needs:

[2345] calorie_advice = "This meal fits within your daily calorie needs."

[2346] else:

[2347] calorie_advice = "Consider reducing portion size or choosing a lower-calorie alternative."

[2348] send_calorie_advice_to_client(calorie_advice)

[2349] Step 13:

[2350] The device visually displays calculated calorie information and advice, allowing users to follow a healthy eating plan.

[2351] HTML

[2352]

[2353] <h3> Calories: {{recipe_calories}} < / h3>

[2354] {{calorie_advice}}

[2355]

[2356] Through these steps, the system comprehensively supports users in managing their food expenses, calorie intake, and suggesting meals according to their emotions, allowing users to efficiently manage their living expenses and lead an appropriate diet according to their emotional state.

[2357] Example 2

[2358] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2359] Conventional meal plan suggestion systems make blanket suggestions without considering the user's basic information or current emotional state, making it difficult to provide personalized meal plans tailored to individual needs. Furthermore, because ingredients and recipes are not selected based on refrigerator inventory or the user's emotional state, there are problems with food waste and reduced user satisfaction. Furthermore, the number of potential suppliers is limited, making it difficult to make economical or convenient choices.

[2360] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input of the user's address, number of households, desired cost, ingredient concept, ability to cook at home, target weight, and refrigerator inventory; means for acquiring information on nearby retailers or online stores based on the address; means for recognizing the user's emotional state by analyzing the user's facial expressions and voice; means for generating an optimal ingredient list and cooking method based on the input information, emotional state, and acquired retailer information; means for suggesting the most economical or convenient purchasing source based on the generated ingredient list; and means for calculating calorie intake based on the target weight and providing appropriate calorie advice. This makes it possible to provide a personalized meal plan tailored to the user's individual needs and current emotional state.

[2361] "User" refers to an individual who enters information into the system and receives a personalized meal plan.

[2362] "Address" refers to detailed information about the user's place of residence and is used to obtain information about nearby retailers and online stores.

[2363] "Number of households" refers to the number of people living in the user's household, and is information that affects meal plan portion sizes and food cost calculations.

[2364] "Desired spend" refers to the monthly or weekly budget that the user plans to spend on food.

[2365] "Ingredient concept" refers to the meal theme or ingredient characteristics desired by the user (e.g., healthy, low calorie, etc.).

[2366] "Ability to cook at home" refers to whether or not the user has the ability or desire to cook at home.

[2367] "Goal weight" refers to the weight the user wants to achieve, and is important information for calculating calories and creating meal plans.

[2368] "Refrigerator inventory" refers to a list of ingredients currently stored in the user's refrigerator.

[2369] "Store" refers to a physical store selling ingredients.

[2370] "Online Store" refers to an e-commerce site that sells products over the Internet.

[2371] "Emotional state" refers to the mood or psychological state of the user that is recognized based on facial expressions and voice data.

[2372] "Ingredient list" refers to a list of ingredients that the user needs to purchase.

[2373] "Recipe" refers to the steps or recipes for cooking using ingredients specified by the user.

[2374] "Purchasing point" refers to the retail store or online store where you purchase ingredients.

[2375] "Calories" refers to the amount of energy contained in an ingredient or dish and is used to calculate a meal plan relative to a user's weight goal.

[2376] The present invention relates to a system that proposes an optimal meal plan taking into account the user's input information and emotional state. The details of this system are described below.

[2377] User

[2378] The user logs into the system and enters their address, number of household members, desired cost, ingredient concept, whether they can cook at home, target weight, and refrigerator inventory. This information is entered from the device the user uses (e.g., PC, smartphone, tablet). The user also activates the emotion engine and provides their current emotional state. At this time, emotions are detected using facial recognition and voice analysis. A specific example is shown below.

[2379] Examples:

[2380] The user enters the following information:

[2381] Address: Minato-ku, Tokyo

[2382] Number of people in the household: 2

[2383] Desired cost: 40,000 yen / month

[2384] Ingredients concept: Healthy food

[2385] Self-catering: Yes

[2386] Target weight: 60kg

[2387] Fridge stock: Chicken breast, broccoli, tofu

[2388] Next, the user's emotion engine is activated and recognizes that the user is feeling stressed.

[2389] server

[2390] The server stores the information provided by the user in a database. For example, it uses an SQL or NoSQL database to efficiently manage data. The server also accesses an API to obtain information about nearby retailers and online stores based on the user's address information. This involves large-scale data collection and analysis.

[2391] Furthermore, the server receives user emotional data and uses it to select ingredients and generate recipes. Emotion recognition uses image recognition technology (e.g., OpenCV) and natural language processing (e.g., Google Cloud's natural language API).

[2392] Examples:

[2393] The server uses the emotion data and refrigerator inventory data to suggest recipes such as:

[2394] "Healthy stir-fried chicken breast and broccoli"

[2395] Next, based on this recipe, a list of ingredients needed that are not in the refrigerator (e.g. olive oil, salt) is made.

[2396] Terminal

[2397] The device visually presents the information sent from the server to the user. Specifically, it displays recommended recipes, purchasing information, and calorie information. The user can confirm this information and proceed to purchase or execute the plan.

[2398] Examples:

[2399] The following information will be displayed on the terminal screen:

[2400] "New Recipe: Healthy Stir-fried Chicken Breast and Broccoli"

[2401] "Estimated calories: 500kcal per serving"

[2402] "Purchase information: Olive oil - nearest supermarket, Salt - Online Store Y"

[2403] Prompt Sentence Examples

[2404] Below are some example prompts to input to the generative AI model:

[2405] User-entered information:

[2406] Address: Minato-ku, Tokyo

[2407] Number of people in the household: 2

[2408] Desired cost: 40,000 yen / month

[2409] Ingredients concept: Healthy food

[2410] Self-catering: Yes

[2411] Target weight: 60kg

[2412] Fridge stock: Chicken breast, broccoli, tofu

[2413] Current emotional state: I'm stressed

[2414] Use this information to provide users with the perfect meal plan, and if they don't have the ingredients they need for a recipe in their fridge, provide them with information on where to buy them.

[2415] As described above, this system generates meal plans based on the user's input information and emotional state and provides them visually, thereby enabling personalized me...

Claims

1. A means for users to input their address, number of household members, desired food expenses, food concept, whether they can cook at home, target weight, and refrigerator inventory; A means for acquiring information on nearby stores or online stores based on the address; A means for generating an optimal ingredient list and recipe based on the input information and the acquired store information; A means for suggesting the most economical or convenient place to purchase ingredients based on the generated ingredient list; The system includes a means for calculating calorie intake based on the target weight and providing appropriate calorie advice.

2. 2. The system according to claim 1, further comprising means for selecting a recipe that uses ingredients already in the refrigerator with priority based on the input refrigerator inventory information.

3. The system of claim 1 further comprising means for visually presenting recommended recipes and purchasing information to the user.

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