System

Abstract

A system is provided.SOLUTION: The system includes a means for acquiring weather data, a means for collecting data of a social networking service, a means for generating a recommended recipe based on the collected data, a means for displaying the generated recipe and a necessary food list, and a means for generating a purchase link of an online supermarket.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, the importance of dietary education has increased with the rise in health consciousness. However, it remains difficult for consumers to easily select appropriate ingredients and eat a balanced diet. Furthermore, there is a lack of recipe selection based on climate and season, and recipes that reflect trendy cooking information on social networking services (SNS). As a result, consumers must expend a great deal of effort to gather information, select appropriate recipes, and purchase ingredients. Therefore, the objective of this invention is to provide a system that efficiently recommends appropriate recipes to consumers based on climate data and SNS trend information, and supports them in purchasing ingredients. [Means for solving the problem]

[0005] The present invention is a system having the following configuration.

[0006] First, the system is equipped with a means for acquiring climate data, which allows it to collect information such as current temperature, humidity, and weather. It is also equipped with a means for collecting data from social networking services, which allows it to obtain information on food-related trends. Next, it is equipped with a means for generating recipes optimized for consumers based on this collected data. The generated recipes and the list of ingredients required for them are visually provided to the user through a display means. Furthermore, it is equipped with a means for generating purchasing links for online supermarkets, which allows consumers to efficiently and quickly purchase the ingredients they need. This configuration makes it possible to promote a healthy and balanced diet that takes into account the climate and the latest trends.

[0007] "Climate data" refers to data that refers to information about current weather conditions, such as temperature, humidity, and weather.

[0008] A "social networking service" is an online service that allows users to exchange information and form communities over the Internet.

[0009] "Means of collecting data" refers to the functions and methods for obtaining the required information from climate data and social networking services.

[0010] "Recommended recipes" are information that refer to cooking methods suggested to users based on collected data.

[0011] "Generating means" refers to the method or process used to evaluate and analyze the collected data and produce a specific result (in this case, a recipe).

[0012] "Display means" refers to a function or device for showing the generated recipe and the list of ingredients to the user.

[0013] An "online supermarket" refers to a retailer that sells food and daily necessities over the Internet.

[0014] A "purchase link" refers to a URL or hyperlink that a user clicks on to go to a web page where they can purchase a particular product. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[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] This invention is a system that utilizes weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and also supports food ingredient purchasing at online supermarkets.

[0037] Server Roles

[0038] The server acts as the core of the system through the following steps:

[0039] 1. Obtaining climate data:

[0040] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0041] 2. Social Media Data Collection:

[0042] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0043] 3. Generate the recipe:

[0044] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[0045] 4. Generate a purchase link:

[0046] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. Specifically, it sends the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[0047] Device Role

[0048] The terminal provides an interface for users to view recipes and make purchases.

[0049] 1. Get and display recipes:

[0050] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[0051] 2. View Purchase Links:

[0052] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[0053] User Roles

[0054] The user operates the terminal to purchase ingredients based on the provided recipe.

[0055] 1. Check the recipe:

[0056] The user browses the recipe and ingredient list provided on the device.

[0057] 2. Click on the purchase link and purchase the ingredients:

[0058] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[0059] Specific examples

[0060] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click on the purchase link displayed to purchase the ingredients on the online supermarket site.

[0061] The present invention allows users to efficiently practice a healthy and balanced diet that takes into account the weather and the latest trends.

[0062] The processing flow will be explained below.

[0063] Step 1: Collect data

[0064] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0065] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0066] Step 2: Analyze the data and select a recipe

[0067] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information.

[0068] The server searches for the corresponding recipe in its internal database, for example by executing the SQL query "SELECT FROM recipes WHERE type='cold' AND category='salad'".

[0069] Step 3: Generate the recipe and ingredient list

[0070] The server generates a list of ingredients required for the selected recipe.

[0071] The server sends the generated recipe and ingredient list to the terminal.

[0072] Step 4: View the recipe

[0073] The terminal displays the recipe and the list of ingredients received from the server to the user.

[0074] For example, the recipe name of "Cold Summer Salad" and the required ingredients (lettuce, tomato, cucumber, dressing, etc.) are visually presented to the user.

[0075] Step 5: Generate Purchasing Links

[0076] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, send the list of ingredients via "POST https: / / supermarketapi.com / cart / add".

[0077] The server receives the purchase link returned from the online supermarket.

[0078] Step 6: View purchasing links

[0079] The terminal displays the purchase link received from the server to the user.

[0080] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[0081] Step 7: Buy ingredients

[0082] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[0083] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[0084] By following these steps, users can easily obtain recipes that reflect the weather and trends, and efficiently purchase the ingredients they need.

[0085] Example 1

[0086] 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."

[0087] Modern consumers face challenges in quickly finding appropriate recipes in response to changes in climate and lifestyles. They also lack the means to efficiently select the latest trendy and healthy meals and easily purchase the ingredients. Conventional systems have limited capabilities for utilizing climate data and information from social networking services, making it difficult to provide users with optimal recipes and convenient purchasing methods. Given this background, there is a demand for a system that allows users to easily find optimal recipes based on climate and social trends and easily purchase the ingredients online.

[0088] 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.

[0089] In this invention, the server includes means for acquiring weather data, means for collecting information from social networking services, means for generating recommended recipes based on the collected information, means for displaying the generated recipes and lists of ingredients required, and means for generating purchasing links to online grocery stores, thereby enabling users to easily find optimal recipes based on weather and trend information and quickly purchase the ingredients.

[0090] "Climate data" is information about meteorological conditions such as current temperature, humidity, and weather.

[0091] A "social networking service" is an online platform where users share information and communicate.

[0092] "Means of collecting information" are the functions and processes used to obtain the required information from a particular data source.

[0093] A "means for generating recommended recipes" is a method or algorithm for analyzing collected data and selecting the most suitable recipe for the user based on that data.

[0094] An "ingredient list" is a list of ingredients or items needed to execute a particular recipe.

[0095] An "online grocer" is a retailer or platform that sells food and related products over the internet.

[0096] A "means for generating purchase links" is a method or process for creating a URL or link that allows a particular product or ingredient to be added to a shopping cart at an online grocery store.

[0097] The present invention is a system that utilizes weather data and information from social networking services (SNS) to provide consumers with suitable recipes and also supports ingredient purchasing at online grocery stores.

[0098] Server Roles

[0099] The server functions as the core of the system using the following software and hardware: Weather API, SNS platform API, and online supermarket API.

[0100] Obtaining climate data

[0101] The server obtains climate data such as the current temperature, humidity, and weather by sending a request to WeatherAPI. For example, by sending a request such as "GET https: / / weatherapi.com / current?location=Tokyo", the current weather conditions for Tokyo are obtained. This data is stored in a database on the server.

[0102] Social media data collection

[0103] The server uses the API of the social media platform to collect current trending posts related to the food category. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food" to obtain trending information related to food. The collected data is analyzed, and the necessary information is stored in a database.

[0104] Recipe Generation

[0105] The server analyzes the acquired weather and social media data to select the best recipe for the user. This analysis is performed using a generative AI model. For example, based on the collected data, it may recommend cold dishes or menus using trending ingredients. The selected recipes are extracted from the recipe information stored in the internal database and displayed.

[0106] Generate Purchasing Links

[0107] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients required for the selected recipe. Specifically, the server sends the ingredient list via the request "POST https: / / supermarketapi.com / cart / add" and generates a purchase link. This link is also saved in the server's database.

[0108] Device Role

[0109] The terminal provides an interface for the user to view recipes and purchase ingredients.

[0110] Retrieving and displaying recipes

[0111] The device sends a request to the server based on the user's current status and location. For example, it sends a request like "GET https: / / myapp.com / recommendations?location=Tokyo" to retrieve the optimal recipe and ingredient list from the server. The received information is then displayed to the user.

[0112] View Purchasing Links

[0113] The device displays the purchase link received from the server to the user, and when the user clicks the link, they are taken to the online grocery store's website where they can easily purchase the ingredients they need.

[0114] User Roles

[0115] The user operates the terminal to purchase ingredients based on the provided recipe.

[0116] Check the recipe

[0117] The user checks the recipe and ingredient list provided on the terminal.

[0118] Click on the purchase link and purchase the material

[0119] The user clicks on the purchase link, which takes them to the online grocery store's website, where they can proceed to purchase the ingredients they need.

[0120] Specific examples

[0121] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from a weather data API. It also collects information about trending topics related to "salad" from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who then clicks on a purchase link to purchase the ingredients on an online grocery store's website.

[0122] Example prompts for generative AI models

[0123] "Please suggest suitable recipes based on current weather data and trending food information on social media. For example, what recipes would be good for a summer day in Tokyo (30 degrees, sunny)?"

[0124] With this invention, users can easily receive recipe suggestions that take into account the weather and the latest trends, and can quickly purchase the ingredients.

[0125] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0126] Step 1: Obtaining climate data

[0127] The server sends an HTTP request to WeatherAPI. Specifically, it uses the request "GET https: / / weatherapi.com / current?location=Tokyo". This request allows the server to obtain data such as the current temperature, humidity, and weather in JSON format. The obtained data is stored in an internal database.

[0128] Input: Current location information (e.g. Tokyo)

[0129] Output: Weather data such as temperature, humidity, and weather conditions (JSON format)

[0130] Step 2: Collect social media data

[0131] The server accesses the social media platform API and collects trending posts in the food category. For example, it uses the request "GET https: / / snsapi.com / trending?category=food". This request allows the server to obtain information about food-related topics that are currently trending. The obtained data is then analyzed and stored in a database.

[0132] Input: Request URL (e.g., food-related trends)

[0133] Output: Trending food data (JSON format)

[0134] Step 3: Generate the recipe

[0135] The server analyzes the acquired weather and social media data. It uses a generative AI model to analyze and select the optimal recipe for the user. It extracts an appropriate menu item, such as a "cold summer salad," from the recipe information stored in the database. It creates the selected recipe and a list of required ingredients and stores them in the database.

[0136] Input: Weather data, trending food data

[0137] Output: Recommended recipe, ingredients list

[0138] Step 4: Generate Purchasing Links

[0139] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. For example, the list of ingredients is sent via a request such as "POST https: / / supermarketapi.com / cart / add." The purchase link is generated and saved in the database.

[0140] Input: Materials list

[0141] Output: Purchasing Link

[0142] Step 5: Retrieve and display the recipe

[0143] The device sends an HTTP request to the server based on the user's current status and location information. For example, by sending a request such as "GET https: / / myapp.com / recommendations?location=Tokyo", the device obtains the optimal recipe and ingredient list from the server. The device then displays the received recipe and ingredient list to the user.

[0144] Input: current state and location of the user

[0145] Output: Recommended recipe, ingredients list

[0146] Step 6: View purchasing links

[0147] The terminal displays the purchase link received from the server to the user, who, when clicking the link, is directed to the online grocery store's website where the required ingredients are automatically added to the cart.

[0148] Input: Purchasing Link

[0149] Output: Online grocery store URL

[0150] Step 7: Check the recipe

[0151] The user can check the recipe and ingredient list displayed on the device, and can also check the details of the recipe, cooking steps, and required ingredients.

[0152] Input: Recommended recipe, ingredient list

[0153] Output: Recipe confirmation information

[0154] Step 8: Click on the purchase link and purchase the material

[0155] By clicking the purchase link displayed on the device, the user is taken to the online grocery store's website, where they can check the ingredients automatically added to their online supermarket cart and complete the purchase.

[0156] Input: Purchasing Link

[0157] Output: Online grocery store purchase page

[0158] (Application example 1)

[0159] 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."

[0160] The objective of this invention is to utilize weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and enable them to quickly order food not only from online supermarkets but also from food delivery services. This allows users to easily enjoy food that is suited to the weather and trends, improving the quality of their diet.

[0161] 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.

[0162] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for generating recommended recipes based on the collected data, means for displaying the generated recipes and a list of necessary ingredients, and means for generating an ordering link for a food delivery service, thereby enabling the user to receive suggested dishes that match the weather and trends and to quickly order them on the spot.

[0163] "Climate Data" is information about environmental conditions in a particular area, such as current temperature, humidity, and weather.

[0164] "Social networking service data" refers to user posts and trending information collected from online platforms.

[0165] "Recommended recipes" are cooking recipes generated based on collected weather data and data from social networking services.

[0166] The "ingredient list" is a list of ingredients required based on the recommended recipe.

[0167] An "online supermarket" is a service that allows you to purchase food and other products online.

[0168] A "purchase link" is a URL link that allows users to directly purchase the specified ingredients or dishes.

[0169] A "food delivery service" is a service that delivers food ordered by a user to their home or a designated location.

[0170] "Order Link" means a URL link for ordering food through a food delivery service.

[0171] The present invention relates to a system that utilizes weather data and data from social networking services (SNS) to provide consumers with suitable recipes and also supports food ordering via food delivery services.

[0172] Server Roles

[0173] 1. Obtaining climate data

[0174] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0175] 2. Collecting social media data

[0176] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0177] 3. Recipe Generation

[0178] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[0179] 4. Generate an order link

[0180] The server uses the food delivery service's API to generate an order link for the selected dish. Specifically, it sends a request to "POST https: / / deliveryapi.com / order / add" and sends the information about the selected dish.

[0181] Device Role

[0182] 1. Get and display recipes

[0183] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[0184] 2. Display of order link

[0185] The terminal displays the order link received from the server to the user, and the user can click the link to move to the food delivery service site and order the corresponding food.

[0186] User Roles

[0187] 1. Check the recipe

[0188] The user browses the recipe and ingredient list provided on the device.

[0189] 2. Click on the order link and order your food

[0190] The user clicks on the order link, goes to the food delivery service's website, and orders the food.

[0191] Specific examples

[0192] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click the displayed order link to order the food via a food delivery service.

[0193] This system allows users to easily enjoy cooking that takes into account the weather and the latest trends.

[0194] Prompt Sentence Examples

[0195] On a summer day in Tokyo when the weather is sunny and the temperature is 30 degrees, if the dish going viral on social media is a salad, what recipe would be appropriate?

[0196] (Hardware and software used)

[0197] Hardware: Servers, smartphones

[0198] Software: Python, Requests module, Weather API, SNS API, Food Delivery API

[0199] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0200] Step 1:

[0201] The server sends a request to the climate data API to obtain information such as the current temperature, humidity, and weather. The input is the user's location information, and the output is the current climate information for that location. The specific operation is to send an HTTP GET request to the API endpoint and extract the required data from the response.

[0202] Step 2:

[0203] The server accesses the API of a social networking service and collects the most recent buzzworthy food-related posts. The input is API authentication information and category information, and the output is trending food-related post data. Specifically, it sends an HTTP GET request to the API and extracts the necessary food trend information from the returned data.

[0204] Step 3:

[0205] The server analyzes the weather data acquired in step 1 and the social media data collected in step 2, and selects the optimal recipe for the user based on this information. The input is weather data and social media data, and the output is a recommended recipe and a list of required ingredients. The specific operation is to use an internal algorithm to select the optimal recipe and generate a list of required ingredients based on it.

[0206] Step 4:

[0207] The server generates an order link using the food delivery service's API based on the generated recommended recipe and list of ingredients. The input is the recommended recipe and list of ingredients, and the output is the order link. Specifically, it sends an HTTP POST request to the food delivery service's API to obtain the order link.

[0208] Step 5:

[0209] The device requests a recipe from the server based on the user's current conditions, and displays the recipe and ingredient list received from the server to the user. The input is the user's location information and other condition information, and the output is a recommended recipe and ingredient list. The specific operation is to send an HTTP GET request to the server and display the returned data on the device.

[0210] Step 6:

[0211] The terminal displays the order link received from the server to the user, and allows the user to click the link to go to the food delivery service's website and order the corresponding food. The input is the order link from the server, and the output is the user going to the food delivery service and ordering the food. The specific operation is to provide a user interface for clicking the order link.

[0212] Step 7:

[0213] The user views the recipe and ingredient list provided on the device, clicks the order link to go to the food delivery service's website, and places an order. The input is the recipe, ingredient list, and order link displayed on the device, and the output is the order being confirmed. The specific operation is for the user to click the order link on the device to complete the ordering process.

[0214] 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.

[0215] This invention is a system that uses weather data, data from social networking services (SNS), and an emotion engine that recognizes user emotions to provide consumers with optimal recipes and support ingredient purchasing at online supermarkets.

[0216] Server Roles

[0217] The server acts as the core of the system through the following steps:

[0218] 1. Obtaining climate data:

[0219] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0220] 2. Social Media Data Collection:

[0221] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0222] 3. Collecting Emotional Data:

[0223] The server uses an emotion engine to analyze the user's facial expressions, voice, and text input to recognize the user's current emotion, and this emotion data is reflected in the recipe recommendations.

[0224] 4. Generate the recipe:

[0225] The server generates the optimal recipe for the user based on the collected weather data, social media data, and emotional data.

[0226] For example, if a user is "feeling stressed," it will recommend recipes using herbs that have a relaxing effect.

[0227] 5. Generate a purchase link:

[0228] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" to send the list of ingredients.

[0229] Device Role

[0230] The terminal provides an interface for users to view recipes and make purchases.

[0231] 1. Recognizing and transmitting emotions:

[0232] The device uses the user's facial recognition camera, microphone, and keyboard input to perform analysis using an emotion engine, and the analysis results are sent to a server.

[0233] 2. Get and display recipes:

[0234] The terminal displays the recipe and the list of ingredients received from the server to the user.

[0235] For example, the recipe name of "Relaxing Herbal Tea" and the required ingredients (chamomile, peppermint, etc.) are visually presented to the user.

[0236] 3. View Purchase Links:

[0237] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[0238] User Roles

[0239] The user operates the terminal to purchase ingredients based on the provided recipe.

[0240] 1. Check the recipe:

[0241] The user browses the recipe and ingredient list provided on the device.

[0242] 2. Click on the purchase link and purchase the ingredients:

[0243] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[0244] Specific examples

[0245] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "smoothies" are trending from social media data. Furthermore, the emotion engine determines that the user is "feeling stressed." Based on this, the server selects a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link provided to purchase the ingredients on an online supermarket website.

[0246] The present invention allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and to efficiently purchase the ingredients they need.

[0247] The processing flow will be explained below.

[0248] Step 1: Collect climate data

[0249] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0250] Step 2: Collect social media data

[0251] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0252] Step 3: Collecting emotion data

[0253] The device uses the user's facial expressions, voice, and text input to analyze using an emotion engine and recognize the user's current emotions.

[0254] For example, the device uses a camera to capture the user's facial expressions, which are then analyzed by the emotion engine. It also uses a microphone to analyze the tone of the voice.

[0255] Step 4: Sending emotion data

[0256] The device transmits the recognized user emotion data to the server.

[0257] For example, send emotion data to the server with a "POST https: / / myapp.com / emotion" request.

[0258] Step 5: Generate the recipe

[0259] The server analyzes the collected weather data, social media data, and sentiment data, and generates the optimal recipe for the user based on this.

[0260] For example, if the temperature is 30 degrees and the day is sunny, cold food would be appropriate, and if "smoothies" are trending on social media and the user is perceived as "feeling stressed," the app will suggest a relaxing herbal tea.

[0261] Step 6: Generate the recipe and ingredient list

[0262] The server generates the selected recipe and ingredient list and sends them to the terminal.

[0263] For example, generate data containing a recipe for "cold herbal tea" and the ingredients needed (chamomile, peppermint, etc.).

[0264] Step 7: View the recipe

[0265] The terminal displays the recipe and the list of ingredients received from the server to the user.

[0266] For example, a recipe for "cold herbal tea" can be visually presented to the user, including a photo, instructions, and a list of ingredients needed.

[0267] Step 8: Generate Purchasing Links

[0268] The server uses the online supermarket's API to generate a purchase link based on the ingredients list. For example, it sends the ingredients list to "POST https: / / supermarketapi.com / cart / add".

[0269] The server receives the purchase link returned from the online supermarket.

[0270] Step 9: View Purchasing Links

[0271] The terminal displays the purchase link received from the server to the user.

[0272] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[0273] Step 10: Buy ingredients

[0274] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[0275] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[0276] By following these steps, users can easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[0277] Example 2

[0278] 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."

[0279] Today's busy consumers find it difficult to efficiently purchase ingredients and find suitable recipes in their daily lives. Furthermore, there are currently no recipe recommendation systems that take into account factors such as weather, trends, and user emotions, and there is a need for a method to utilize this information in an integrated manner. The present invention aims to solve these problems by providing a system that offers optimal recipes to users and supports ingredient purchasing.

[0280] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0281] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for recognizing a user's emotions using an emotion engine, means for generating recommended recipes based on the collected data and the recognized emotions, means for displaying the generated recipes and a list of necessary ingredients, and means for generating purchasing links to online supermarkets. This allows users to easily obtain optimal recipes that take into account the weather, trends, and emotions, and efficiently purchase the necessary ingredients.

[0282] "Climate data" refers to information about the weather, such as current temperature, humidity, and weather.

[0283] "Social networking service data" refers to information about food-related content and trends posted on social media platforms.

[0284] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, and text input to recognize the user's current emotions.

[0285] A "recommended recipe" is a cooking recipe that is optimal for the user and is generated based on weather data, data from social networking services, and the user's emotional data.

[0286] The "ingredient list" is a list of ingredients needed to prepare a dish based on the recommended recipe.

[0287] An "online supermarket" is a supermarket that sells ingredients and food online.

[0288] A "purchase link" is a link on the online supermarket site that allows direct access to a shopping cart containing the ingredients you need.

[0289] This system integrates weather data, data from social networking services, and user sentiment data to provide optimal recipes to consumers and support food purchasing in online supermarkets. The system consists of a server and a terminal.

[0290] Server Roles

[0291] The server serves as the core of the system and performs the following functions:

[0292] 1. Obtaining climate data:

[0293] The server uses the weather data API to collect information such as the current temperature, humidity, and weather. Specifically, it sends a request such as "GET https: / / weatherapi.com / current?location=Tokyo" and analyzes the returned data. This weather data is used for subsequent processing.

[0294] 2. Social Media Data Collection:

[0295] The server uses the API of the social media platform to collect recent trending food-related posts. For example, it sends a request like "GET https: / / snsapi.com / trending?category=food" to retrieve data on popular dishes. The social media data, along with weather data, is used to generate recipes.

[0296] 3. Collecting Emotional Data:

[0297] The server uses an emotion engine to recognize emotions from the user's facial expressions, voice, and text input. Emotional data is captured as "stress," "relaxation," "joy," etc., and is reflected in the creation of recipes.

[0298] 4. Generate the recipe:

[0299] The server combines the collected weather, social media, and emotional data to generate recipes tailored to the user. For example, if a user is feeling stressed, it will recommend recipes using herbs that have a relaxing effect. It will generate a recipe such as "Relaxing Herbal Tea" and list the ingredients needed.

[0300] 5. Generate a purchase link:

[0301] The server uses the online supermarket's API to generate a list of the ingredients needed and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" and generates a purchase link by sending the ingredient list. The link is sent to the device, and the user can click it to go to the online supermarket's website and purchase the ingredients.

[0302] Device Role

[0303] The terminal provides an interface for users to view recipes and make purchases.

[0304] 1. Recognizing and transmitting emotions:

[0305] The device uses a facial recognition camera, microphone, and keyboard input to analyze the user's emotions and sends the results to a server.

[0306] 2. Get and display recipes:

[0307] The device displays the recipe and the list of ingredients received from the server to the user. Specifically, the device visually presents the recipe name, such as "Relaxing Herbal Tea," and the ingredients required (chamomile, peppermint, etc.).

[0308] 3. View Purchase Links:

[0309] The terminal displays the purchase link received from the server, and the user can click on the link to go to the online supermarket site and purchase the necessary ingredients.

[0310] User Roles

[0311] The user operates the terminal to purchase ingredients based on the provided recipe.

[0312] 1. Check the recipe:

[0313] The user browses the recipe and ingredient list provided on the device.

[0314] 2. Click on the purchase link and purchase the ingredients:

[0315] The user clicks on the purchase link and is taken to the online supermarket site to purchase the necessary ingredients.

[0316] Specific examples

[0317] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and gathers information about the popularity of "smoothies" from social media data. The emotion engine then determines that the user is "feeling stressed." Based on this information, the server generates a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link to purchase the ingredients on the online supermarket site.

[0318] Prompt Sentence Examples

[0319] "Based on current weather data for Tokyo, please tell us some recipes for cold drinks that are perfect for weather over 25 degrees that have been trending on social media recently. Also, please include examples of recipes that would be perfect for when users are feeling relaxed."

[0320] This system allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[0321] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0322] Step 1:

[0323] Input: The server sends a request from the Climate Data API.

[0324] How it works: The server executes the request "GET https: / / weatherapi.com / current?location=Tokyo" to get the current temperature, humidity, and weather information.

[0325] Output: The server retrieves climate data such as temperature (30 degrees), humidity (70%), and weather (sunny).

[0326] Step 2:

[0327] Input: The server collects data from the API of the social networking platform.

[0328] How it works: The server executes the request "GET https: / / snsapi.com / trending?category=food" to collect data on the most recent trending food-related posts.

[0329] Output: The server gets information about trending foods such as "smoothies," "pasta," and "salads."

[0330] Step 3:

[0331] Input: The server sends the user's data to the emotion engine.

[0332] Operation: The server inputs facial expression data, voice data, and text input sent from the device into the emotion engine and analyzes the user's emotions.

[0333] Output: The server receives emotion data such as "stress," "relaxation," and "joy."

[0334] Step 4:

[0335] Input: The server integrates climate data, social media data, and sentiment data.

[0336] How it works: The server uses this data to generate the optimal recipe for the user. For example, if the weather is "30 degrees, sunny," the social media trend is "smoothie," and the emotion is "stress," it generates a recipe for "relaxing herbal tea."

[0337] Output: The server will list the generated recipe (Relaxing Herbal Tea) and the ingredients it requires (chamomile, peppermint, etc.).

[0338] Step 5:

[0339] Input: The server sends the generated ingredient list to the online supermarket API.

[0340] What happens: The server executes the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[0341] Output: The server receives a purchase link from the online supermarket.

[0342] Step 6:

[0343] Input: The terminal displays the data received from the server.

[0344] Operation: The device displays the recipe received from the server, a list of the ingredients needed, and a link to purchase the recipe. Specifically, the device displays the recipe name for "Relaxing Herbal Tea" and the ingredients needed (chamomile, peppermint, etc.).

[0345] Output: The terminal provides visual information to the user.

[0346] Step 7:

[0347] Input: The user sees the recipe and ingredients list on their device.

[0348] How it works: A user uses a device to view a provided recipe and ingredient list.

[0349] Output: The user checks the ingredients needed and makes a purchasing decision.

[0350] Step 8:

[0351] Input: User clicks on a purchase link on their device.

[0352] Operation: The device will redirect the user to an online supermarket website based on the purchase link they clicked, where they can purchase ingredients.

[0353] Output: The user adds ingredients to the online supermarket cart and completes the purchase.

[0354] This process allows users to obtain optimal recipes based on the weather, trends, and emotions, and efficiently purchase the ingredients they need.

[0355] (Application example 2)

[0356] 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."

[0357] Modern consumers often don't have time to prepare meals due to their busy daily lives. Food preferences change depending on the season, weather, and personal emotions, making it difficult to instantly find the right recipe that reflects these preferences. Furthermore, the process of purchasing ingredients can be time-consuming, creating a demand for reducing the effort required for meal preparation.

[0358] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0359] In this invention, the server includes means for acquiring weather data, means for collecting data from electronic communication platforms, means for generating recommended recipes based on the collected data, means for adjusting the recommended recipes based on the collected emotion data using an emotion engine that recognizes the user's emotions, means for displaying the generated recipes and a list of required ingredients, and means for generating purchasing links to online stores. This allows users to easily obtain optimal recipes based on weather conditions, social network trends, and personal emotions, and then efficiently purchase the required ingredients online.

[0360] "Climate data" is information about environmental conditions such as current temperature, humidity, and weather.

[0361] An "electronic communication platform" is a service that allows users to interact and share information over the Internet.

[0362] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, text input, etc. to recognize the user's emotions.

[0363] A "recommended recipe" is a suggestion of how to cook a dish that is deemed best for the user based on collected information.

[0364] An "online store" is a platform for selling products over the Internet.

[0365] A "purchase link" is a URL that a user can click to access an online store and purchase a specific product.

[0366] The system of the invention integrates user sentiment, weather data, and trends from social networking services to support optimal recipe suggestions and online ingredient purchasing. The main components of the system are a server, a user terminal, and a network interface.

[0367] First, the server collects current weather information (temperature, humidity, weather) using a climate data acquisition method. It uses a climate data API to obtain the necessary information and updates it in real time. This information is collected using existing climate data providers, such as the OpenWeatherMap API.

[0368] Next, we use the APIs of electronic communication platforms, such as Twitter API and Instagram API, to gather the latest food-related trend information. This allows us to understand what is currently trending and what food-related posts are popular.

[0369] The server also uses an emotion engine to recognize the user's emotions. It uses the smartphone's camera and microphone to capture the user's facial expressions and voice to collect emotion data. This analysis utilizes emotion recognition technologies such as Google Cloud Vision API and Amazon Rekognition.

[0370] Based on the collected weather data, social media data, and emotion data, a generative AI model (e.g., GPT-4 (registered trademark)) is used to generate optimal recipes. These recipes are suggested to users based on prompt statements such as, "The user's emotion is stress, the current weather is 30 degrees and sunny, and the latest trend is smoothies. Please suggest the optimal recipe taking these into consideration."

[0371] A list of ingredients is created along with the recipe. The server then generates a purchase link from an online store based on this list. For example, the server can automatically create a purchase link for ingredients using an online store API such as Amazon MWS or Rakuten Market API.

[0372] The user device visually displays the generated recipe, ingredient list, and purchase link to the user. Users can view the recipe through the smartphone app and click the purchase link to go directly to the online store and easily purchase the necessary ingredients.

[0373] This system allows users to quickly find the best recipes based on weather conditions, social network trends, and their own emotions, and then efficiently purchase ingredients online.

[0374] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0375] Step 1:

[0376] The server acquires current weather information using the climate data acquisition means.

[0377] Input: User's location information

[0378] Data processing: Send a request to the climate data API to get the current temperature, humidity, and weather information

[0379] Output: Temperature, humidity, weather information

[0380] Specific behavior: Using the OpenWeatherMap API, make a request such as "GET https: / / api.openweathermap.org / data / 2.5 / weather?q=Tokyo&appid=your_api_key".

[0381] Step 2:

[0382] The server collects data for the electronic communication platform.

[0383] Enter: Food-related trending categories

[0384] Data processing: Send a request to the API of a social media platform to collect the latest food-related posts.

[0385] Output: Food-related trend information

[0386] What it does: Uses the Twitter API to make a request like "GET https: / / api.twitter.com / 2 / tweets / search / recent?query=food_trend".

[0387] Step 3:

[0388] The server uses an emotion engine to collect user emotion data.

[0389] Input: User facial expression video, audio data

[0390] Data processing: Send this data to the emotion recognition API to analyze emotions.

[0391] Output: Emotion data (e.g., stress, excitement, etc.)

[0392] What it does: Uses the Google Cloud Vision API to analyze a video or image and get an output such as "Emotion: Stress".

[0393] Step 4:

[0394] The server generates recommended recipes based on collected weather data, social media data, and emotional data.

[0395] Input: Climate data, social media data, sentiment data

[0396] Data processing: Input prompts into the generative AI model to generate optimal recipes

[0397] Output: Recommended recipes

[0398] Specific behavior: Send a prompt to a generative AI model such as GPT-4, such as "The user's emotion is stress, the current weather is 30 degrees and sunny, and the latest trend is smoothies. Please suggest the best recipe taking this into consideration."

[0399] Step 5:

[0400] The server generates a list of ingredients and a purchasing link based on the generated recipe.

[0401] Input: Recommended recipe

[0402] Data processing: Using the API of an online store, generate a purchase link based on the ingredients list

[0403] Output: Purchase link (URL)

[0404] Specific operation: Using the Amazon MWS API, make a request such as "POST https: / / api.example.com / cart / add" to obtain a purchase link.

[0405] Step 6:

[0406] The terminal visually displays the generated recipe, ingredient list, and purchase link to the user.

[0407] Input: Recommended recipe, purchase link

[0408] Data processing: Visual display through GUI

[0409] Output: Recipe information and links displayed to the user

[0410] What it does: The smartphone app displays the recipe name for "Relaxing Herbal Tea," along with the ingredients needed (e.g., chamomile, peppermint), and a link to purchase the recipe to the user.

[0411] Step 7:

[0412] Users click on the purchase link from their device and purchase the necessary ingredients from the online store.

[0413] Enter: Purchasing Link

[0414] Data processing: Open the link via your smartphone browser and access the online store

[0415] Output: Screen to complete the purchase process

[0416] What happens: When a user clicks on the purchase link, they are taken to the online store's website, where they can add the ingredients they need to their cart and complete the purchase.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] [Second embodiment]

[0421] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0422] 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.

[0423] 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).

[0424] 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.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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."

[0433] This invention is a system that utilizes weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and also supports food ingredient purchasing at online supermarkets.

[0434] Server Roles

[0435] The server acts as the core of the system through the following steps:

[0436] 1. Obtaining climate data:

[0437] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0438] 2. Social Media Data Collection:

[0439] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0440] 3. Generate the recipe:

[0441] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[0442] 4. Generate a purchase link:

[0443] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. Specifically, it sends the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[0444] Device Role

[0445] The terminal provides an interface for users to view recipes and make purchases.

[0446] 1. Get and display recipes:

[0447] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[0448] 2. View Purchase Links:

[0449] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[0450] User Roles

[0451] The user operates the terminal to purchase ingredients based on the provided recipe.

[0452] 1. Check the recipe:

[0453] The user browses the recipe and ingredient list provided on the device.

[0454] 2. Click on the purchase link and purchase the ingredients:

[0455] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[0456] Specific examples

[0457] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click on the purchase link displayed to purchase the ingredients on the online supermarket site.

[0458] The present invention allows users to efficiently practice a healthy and balanced diet that takes into account the weather and the latest trends.

[0459] The processing flow will be explained below.

[0460] Step 1: Collect data

[0461] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0462] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0463] Step 2: Analyze the data and select a recipe

[0464] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information.

[0465] The server searches for the corresponding recipe in its internal database, for example by executing the SQL query "SELECT FROM recipes WHERE type='cold' AND category='salad'".

[0466] Step 3: Generate the recipe and ingredient list

[0467] The server generates a list of ingredients required for the selected recipe.

[0468] The server sends the generated recipe and ingredient list to the terminal.

[0469] Step 4: View the recipe

[0470] The terminal displays the recipe and the list of ingredients received from the server to the user.

[0471] For example, the recipe name of "Cold Summer Salad" and the required ingredients (lettuce, tomato, cucumber, dressing, etc.) are visually presented to the user.

[0472] Step 5: Generate Purchasing Links

[0473] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, send the list of ingredients via "POST https: / / supermarketapi.com / cart / add".

[0474] The server receives the purchase link returned from the online supermarket.

[0475] Step 6: View purchasing links

[0476] The terminal displays the purchase link received from the server to the user.

[0477] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[0478] Step 7: Buy ingredients

[0479] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[0480] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[0481] By following these steps, users can easily obtain recipes that reflect the weather and trends, and efficiently purchase the ingredients they need.

[0482] Example 1

[0483] 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."

[0484] Modern consumers face challenges in quickly finding appropriate recipes in response to changes in climate and lifestyles. They also lack the means to efficiently select the latest trendy and healthy meals and easily purchase the ingredients. Conventional systems have limited capabilities for utilizing climate data and information from social networking services, making it difficult to provide users with optimal recipes and convenient purchasing methods. Given this background, there is a demand for a system that allows users to easily find optimal recipes based on climate and social trends and easily purchase the ingredients online.

[0485] 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.

[0486] In this invention, the server includes means for acquiring weather data, means for collecting information from social networking services, means for generating recommended recipes based on the collected information, means for displaying the generated recipes and lists of ingredients required, and means for generating purchasing links to online grocery stores, thereby enabling users to easily find optimal recipes based on weather and trend information and quickly purchase the ingredients.

[0487] "Climate data" is information about meteorological conditions such as current temperature, humidity, and weather.

[0488] A "social networking service" is an online platform where users share information and communicate.

[0489] "Means of collecting information" are the functions and processes used to obtain the required information from a particular data source.

[0490] A "means for generating recommended recipes" is a method or algorithm for analyzing collected data and selecting the most suitable recipe for the user based on that data.

[0491] An "ingredient list" is a list of ingredients or items needed to execute a particular recipe.

[0492] An "online grocer" is a retailer or platform that sells food and related products over the internet.

[0493] A "means for generating purchase links" is a method or process for creating a URL or link that allows a particular product or ingredient to be added to a shopping cart at an online grocery store.

[0494] The present invention is a system that utilizes weather data and information from social networking services (SNS) to provide consumers with suitable recipes and also supports ingredient purchasing at online grocery stores.

[0495] Server Roles

[0496] The server functions as the core of the system using the following software and hardware: Weather API, SNS platform API, and online supermarket API.

[0497] Obtaining climate data

[0498] The server obtains climate data such as the current temperature, humidity, and weather by sending a request to WeatherAPI. For example, by sending a request such as "GET https: / / weatherapi.com / current?location=Tokyo", the current weather conditions for Tokyo are obtained. This data is stored in a database on the server.

[0499] Social media data collection

[0500] The server uses the API of the social media platform to collect current trending posts related to the food category. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food" to obtain trending information related to food. The collected data is analyzed, and the necessary information is stored in a database.

[0501] Recipe Generation

[0502] The server analyzes the acquired weather and social media data to select the best recipe for the user. This analysis is performed using a generative AI model. For example, based on the collected data, it may recommend cold dishes or menus using trending ingredients. The selected recipes are extracted from the recipe information stored in the internal database and displayed.

[0503] Generate Purchasing Links

[0504] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients required for the selected recipe. Specifically, the server sends the ingredient list via the request "POST https: / / supermarketapi.com / cart / add" and generates a purchase link. This link is also saved in the server's database.

[0505] Device Role

[0506] The terminal provides an interface for the user to view recipes and purchase ingredients.

[0507] Retrieving and displaying recipes

[0508] The device sends a request to the server based on the user's current status and location. For example, it sends a request like "GET https: / / myapp.com / recommendations?location=Tokyo" to retrieve the optimal recipe and ingredient list from the server. The received information is then displayed to the user.

[0509] View Purchasing Links

[0510] The device displays the purchase link received from the server to the user, and when the user clicks the link, they are taken to the online grocery store's website where they can easily purchase the ingredients they need.

[0511] User Roles

[0512] The user operates the terminal to purchase ingredients based on the provided recipe.

[0513] Check the recipe

[0514] The user checks the recipe and ingredient list provided on the terminal.

[0515] Click on the purchase link and purchase the material

[0516] The user clicks on the purchase link, which takes them to the online grocery store's website, where they can proceed to purchase the ingredients they need.

[0517] Specific examples

[0518] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from a weather data API. It also collects information about trending topics related to "salad" from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who then clicks on a purchase link to purchase the ingredients on an online grocery store's website.

[0519] Example prompts for generative AI models

[0520] "Please suggest suitable recipes based on current weather data and trending food information on social media. For example, what recipes would be good for a summer day in Tokyo (30 degrees, sunny)?"

[0521] With this invention, users can easily receive recipe suggestions that take into account the weather and the latest trends, and can quickly purchase the ingredients.

[0522] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0523] Step 1: Obtaining climate data

[0524] The server sends an HTTP request to WeatherAPI. Specifically, it uses the request "GET https: / / weatherapi.com / current?location=Tokyo". This request allows the server to obtain data such as the current temperature, humidity, and weather in JSON format. The obtained data is stored in an internal database.

[0525] Input: Current location information (e.g. Tokyo)

[0526] Output: Weather data such as temperature, humidity, and weather conditions (JSON format)

[0527] Step 2: Collect social media data

[0528] The server accesses the social media platform API and collects trending posts in the food category. For example, it uses the request "GET https: / / snsapi.com / trending?category=food". This request allows the server to obtain information about food-related topics that are currently trending. The obtained data is then analyzed and stored in a database.

[0529] Input: Request URL (e.g., food-related trends)

[0530] Output: Trending food data (JSON format)

[0531] Step 3: Generate the recipe

[0532] The server analyzes the acquired weather and social media data. It uses a generative AI model to analyze and select the optimal recipe for the user. It extracts an appropriate menu item, such as a "cold summer salad," from the recipe information stored in the database. It creates the selected recipe and a list of required ingredients and stores them in the database.

[0533] Input: Weather data, trending food data

[0534] Output: Recommended recipe, ingredients list

[0535] Step 4: Generate Purchasing Links

[0536] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. For example, the list of ingredients is sent via a request such as "POST https: / / supermarketapi.com / cart / add." The purchase link is generated and saved in the database.

[0537] Input: Materials list

[0538] Output: Purchasing Link

[0539] Step 5: Retrieve and display the recipe

[0540] The device sends an HTTP request to the server based on the user's current status and location information. For example, by sending a request such as "GET https: / / myapp.com / recommendations?location=Tokyo", the device obtains the optimal recipe and ingredient list from the server. The device then displays the received recipe and ingredient list to the user.

[0541] Input: current state and location of the user

[0542] Output: Recommended recipe, ingredients list

[0543] Step 6: View purchasing links

[0544] The terminal displays the purchase link received from the server to the user, who, when clicking the link, is directed to the online grocery store's website where the required ingredients are automatically added to the cart.

[0545] Input: Purchasing Link

[0546] Output: Online grocery store URL

[0547] Step 7: Check the recipe

[0548] The user can check the recipe and ingredient list displayed on the device, and can also check the details of the recipe, cooking steps, and required ingredients.

[0549] Input: Recommended recipe, ingredient list

[0550] Output: Recipe confirmation information

[0551] Step 8: Click on the purchase link and purchase the material

[0552] By clicking the purchase link displayed on the device, the user is taken to the online grocery store's website, where they can check the ingredients automatically added to their online supermarket cart and complete the purchase.

[0553] Input: Purchasing Link

[0554] Output: Online grocery store purchase page

[0555] (Application example 1)

[0556] 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."

[0557] The objective of this invention is to utilize weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and enable them to quickly order food not only from online supermarkets but also from food delivery services. This allows users to easily enjoy food that is suited to the weather and trends, improving the quality of their diet.

[0558] 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.

[0559] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for generating recommended recipes based on the collected data, means for displaying the generated recipes and a list of necessary ingredients, and means for generating an ordering link for a food delivery service, thereby enabling the user to receive suggested dishes that match the weather and trends and to quickly order them on the spot.

[0560] "Climate Data" is information about environmental conditions in a particular area, such as current temperature, humidity, and weather.

[0561] "Social networking service data" refers to user posts and trending information collected from online platforms.

[0562] "Recommended recipes" are cooking recipes generated based on collected weather data and data from social networking services.

[0563] The "ingredient list" is a list of ingredients required based on the recommended recipe.

[0564] An "online supermarket" is a service that allows you to purchase food and other products online.

[0565] A "purchase link" is a URL link that allows users to directly purchase the specified ingredients or dishes.

[0566] A "food delivery service" is a service that delivers food ordered by a user to their home or a designated location.

[0567] "Order Link" means a URL link for ordering food through a food delivery service.

[0568] The present invention relates to a system that utilizes weather data and data from social networking services (SNS) to provide consumers with suitable recipes and also supports food ordering via food delivery services.

[0569] Server Roles

[0570] 1. Obtaining climate data

[0571] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0572] 2. Collecting social media data

[0573] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0574] 3. Recipe Generation

[0575] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[0576] 4. Generate an order link

[0577] The server uses the food delivery service's API to generate an order link for the selected dish. Specifically, it sends a request to "POST https: / / deliveryapi.com / order / add" and sends the information about the selected dish.

[0578] Device Role

[0579] 1. Get and display recipes

[0580] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[0581] 2. Display of order link

[0582] The terminal displays the order link received from the server to the user, and the user can click the link to move to the food delivery service site and order the corresponding food.

[0583] User Roles

[0584] 1. Check the recipe

[0585] The user browses the recipe and ingredient list provided on the device.

[0586] 2. Click on the order link and order your food

[0587] The user clicks on the order link, goes to the food delivery service's website, and orders the food.

[0588] Specific examples

[0589] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click the displayed order link to order the food via a food delivery service.

[0590] This system allows users to easily enjoy cooking that takes into account the weather and the latest trends.

[0591] Prompt Sentence Examples

[0592] On a summer day in Tokyo when the weather is sunny and the temperature is 30 degrees, if the dish going viral on social media is a salad, what recipe would be appropriate?

[0593] (Hardware and software used)

[0594] Hardware: Servers, smartphones

[0595] Software: Python, Requests module, Weather API, SNS API, Food Delivery API

[0596] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0597] Step 1:

[0598] The server sends a request to the climate data API to obtain information such as the current temperature, humidity, and weather. The input is the user's location information, and the output is the current climate information for that location. The specific operation is to send an HTTP GET request to the API endpoint and extract the required data from the response.

[0599] Step 2:

[0600] The server accesses the API of a social networking service and collects the most recent buzzworthy food-related posts. The input is API authentication information and category information, and the output is trending food-related post data. Specifically, it sends an HTTP GET request to the API and extracts the necessary food trend information from the returned data.

[0601] Step 3:

[0602] The server analyzes the weather data acquired in step 1 and the social media data collected in step 2, and selects the optimal recipe for the user based on this information. The input is weather data and social media data, and the output is a recommended recipe and a list of required ingredients. The specific operation is to use an internal algorithm to select the optimal recipe and generate a list of required ingredients based on it.

[0603] Step 4:

[0604] The server generates an order link using the food delivery service's API based on the generated recommended recipe and list of ingredients. The input is the recommended recipe and list of ingredients, and the output is the order link. Specifically, it sends an HTTP POST request to the food delivery service's API to obtain the order link.

[0605] Step 5:

[0606] The device requests a recipe from the server based on the user's current conditions, and displays the recipe and ingredient list received from the server to the user. The input is the user's location information and other condition information, and the output is a recommended recipe and ingredient list. The specific operation is to send an HTTP GET request to the server and display the returned data on the device.

[0607] Step 6:

[0608] The terminal displays the order link received from the server to the user, and allows the user to click the link to go to the food delivery service's website and order the corresponding food. The input is the order link from the server, and the output is the user going to the food delivery service and ordering the food. The specific operation is to provide a user interface for clicking the order link.

[0609] Step 7:

[0610] The user views the recipe and ingredient list provided on the device, clicks the order link to go to the food delivery service's website, and places an order. The input is the recipe, ingredient list, and order link displayed on the device, and the output is the order being confirmed. The specific operation is for the user to click the order link on the device to complete the ordering process.

[0611] 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.

[0612] This invention is a system that uses weather data, data from social networking services (SNS), and an emotion engine that recognizes user emotions to provide consumers with optimal recipes and support ingredient purchasing at online supermarkets.

[0613] Server Roles

[0614] The server acts as the core of the system through the following steps:

[0615] 1. Obtaining climate data:

[0616] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0617] 2. Social Media Data Collection:

[0618] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0619] 3. Collecting Emotional Data:

[0620] The server uses an emotion engine to analyze the user's facial expressions, voice, and text input to recognize the user's current emotion, and this emotion data is reflected in the recipe recommendations.

[0621] 4. Generate the recipe:

[0622] The server generates the optimal recipe for the user based on the collected weather data, social media data, and emotional data.

[0623] For example, if a user is "feeling stressed," it will recommend recipes using herbs that have a relaxing effect.

[0624] 5. Generate a purchase link:

[0625] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" to send the list of ingredients.

[0626] Device Role

[0627] The terminal provides an interface for users to view recipes and make purchases.

[0628] 1. Recognizing and transmitting emotions:

[0629] The device uses the user's facial recognition camera, microphone, and keyboard input to perform analysis using an emotion engine, and the analysis results are sent to a server.

[0630] 2. Get and display recipes:

[0631] The terminal displays the recipe and the list of ingredients received from the server to the user.

[0632] For example, the recipe name of "Relaxing Herbal Tea" and the required ingredients (chamomile, peppermint, etc.) are visually presented to the user.

[0633] 3. View Purchase Links:

[0634] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[0635] User Roles

[0636] The user operates the terminal to purchase ingredients based on the provided recipe.

[0637] 1. Check the recipe:

[0638] The user browses the recipe and ingredient list provided on the device.

[0639] 2. Click on the purchase link and purchase the ingredients:

[0640] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[0641] Specific examples

[0642] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "smoothies" are trending from social media data. Furthermore, the emotion engine determines that the user is "feeling stressed." Based on this, the server selects a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link provided to purchase the ingredients on an online supermarket website.

[0643] The present invention allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and to efficiently purchase the ingredients they need.

[0644] The processing flow will be explained below.

[0645] Step 1: Collect climate data

[0646] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0647] Step 2: Collect social media data

[0648] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0649] Step 3: Collecting emotion data

[0650] The device uses the user's facial expressions, voice, and text input to analyze using an emotion engine and recognize the user's current emotions.

[0651] For example, the device uses a camera to capture the user's facial expressions, which are then analyzed by the emotion engine. It also uses a microphone to analyze the tone of the voice.

[0652] Step 4: Sending emotion data

[0653] The device transmits the recognized user emotion data to the server.

[0654] For example, send emotion data to the server with a "POST https: / / myapp.com / emotion" request.

[0655] Step 5: Generate the recipe

[0656] The server analyzes the collected weather data, social media data, and sentiment data, and generates the optimal recipe for the user based on this.

[0657] For example, if the temperature is 30 degrees and the day is sunny, cold food would be appropriate, and if "smoothies" are trending on social media and the user is perceived as "feeling stressed," the app will suggest a relaxing herbal tea.

[0658] Step 6: Generate the recipe and ingredient list

[0659] The server generates the selected recipe and ingredient list and sends them to the terminal.

[0660] For example, generate data containing a recipe for "cold herbal tea" and the ingredients needed (chamomile, peppermint, etc.).

[0661] Step 7: View the recipe

[0662] The terminal displays the recipe and the list of ingredients received from the server to the user.

[0663] For example, a recipe for "cold herbal tea" can be visually presented to the user, including a photo, instructions, and a list of ingredients needed.

[0664] Step 8: Generate Purchasing Links

[0665] The server uses the online supermarket's API to generate a purchase link based on the ingredients list. For example, it sends the ingredients list to "POST https: / / supermarketapi.com / cart / add".

[0666] The server receives the purchase link returned from the online supermarket.

[0667] Step 9: View Purchasing Links

[0668] The terminal displays the purchase link received from the server to the user.

[0669] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[0670] Step 10: Buy ingredients

[0671] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[0672] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[0673] By following these steps, users can easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[0674] Example 2

[0675] 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."

[0676] Today's busy consumers find it difficult to efficiently purchase ingredients and find suitable recipes in their daily lives. Furthermore, there are currently no recipe recommendation systems that take into account factors such as weather, trends, and user emotions, and there is a need for a method to utilize this information in an integrated manner. The present invention aims to solve these problems by providing a system that offers optimal recipes to users and supports ingredient purchasing.

[0677] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0678] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for recognizing a user's emotions using an emotion engine, means for generating recommended recipes based on the collected data and the recognized emotions, means for displaying the generated recipes and a list of necessary ingredients, and means for generating purchasing links to online supermarkets. This allows users to easily obtain optimal recipes that take into account the weather, trends, and emotions, and efficiently purchase the necessary ingredients.

[0679] "Climate data" refers to information about the weather, such as current temperature, humidity, and weather.

[0680] "Social networking service data" refers to information about food-related content and trends posted on social media platforms.

[0681] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, and text input to recognize the user's current emotions.

[0682] A "recommended recipe" is a cooking recipe that is optimal for the user and is generated based on weather data, data from social networking services, and the user's emotional data.

[0683] The "ingredient list" is a list of ingredients needed to prepare a dish based on the recommended recipe.

[0684] An "online supermarket" is a supermarket that sells ingredients and food online.

[0685] A "purchase link" is a link on the online supermarket site that allows direct access to a shopping cart containing the ingredients you need.

[0686] This system integrates weather data, data from social networking services, and user sentiment data to provide optimal recipes to consumers and support food purchasing in online supermarkets. The system consists of a server and a terminal.

[0687] Server Roles

[0688] The server serves as the core of the system and performs the following functions:

[0689] 1. Obtaining climate data:

[0690] The server uses the weather data API to collect information such as the current temperature, humidity, and weather. Specifically, it sends a request such as "GET https: / / weatherapi.com / current?location=Tokyo" and analyzes the returned data. This weather data is used for subsequent processing.

[0691] 2. Social Media Data Collection:

[0692] The server uses the API of the social media platform to collect recent trending food-related posts. For example, it sends a request like "GET https: / / snsapi.com / trending?category=food" to retrieve data on popular dishes. The social media data, along with weather data, is used to generate recipes.

[0693] 3. Collecting Emotional Data:

[0694] The server uses an emotion engine to recognize emotions from the user's facial expressions, voice, and text input. Emotional data is captured as "stress," "relaxation," "joy," etc., and is reflected in the creation of recipes.

[0695] 4. Generate the recipe:

[0696] The server combines the collected weather, social media, and emotional data to generate recipes tailored to the user. For example, if a user is feeling stressed, it will recommend recipes using herbs that have a relaxing effect. It will generate a recipe such as "Relaxing Herbal Tea" and list the ingredients needed.

[0697] 5. Generate a purchase link:

[0698] The server uses the online supermarket's API to generate a list of the ingredients needed and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" and generates a purchase link by sending the ingredient list. The link is sent to the device, and the user can click it to go to the online supermarket's website and purchase the ingredients.

[0699] Device Role

[0700] The terminal provides an interface for users to view recipes and make purchases.

[0701] 1. Recognizing and transmitting emotions:

[0702] The device uses a facial recognition camera, microphone, and keyboard input to analyze the user's emotions and sends the results to a server.

[0703] 2. Get and display recipes:

[0704] The device displays the recipe and the list of ingredients received from the server to the user. Specifically, the device visually presents the recipe name, such as "Relaxing Herbal Tea," and the ingredients required (chamomile, peppermint, etc.).

[0705] 3. View Purchase Links:

[0706] The terminal displays the purchase link received from the server, and the user can click on the link to go to the online supermarket site and purchase the necessary ingredients.

[0707] User Roles

[0708] The user operates the terminal to purchase ingredients based on the provided recipe.

[0709] 1. Check the recipe:

[0710] The user browses the recipe and ingredient list provided on the device.

[0711] 2. Click on the purchase link and purchase the ingredients:

[0712] The user clicks on the purchase link and is taken to the online supermarket site to purchase the necessary ingredients.

[0713] Specific examples

[0714] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and gathers information about the popularity of "smoothies" from social media data. The emotion engine then determines that the user is "feeling stressed." Based on this information, the server generates a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link to purchase the ingredients on the online supermarket site.

[0715] Prompt Sentence Examples

[0716] "Based on current weather data for Tokyo, please tell us some recipes for cold drinks that are perfect for weather over 25 degrees that have been trending on social media recently. Also, please include examples of recipes that would be perfect for when users are feeling relaxed."

[0717] This system allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[0718] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0719] Step 1:

[0720] Input: The server sends a request from the Climate Data API.

[0721] How it works: The server executes the request "GET https: / / weatherapi.com / current?location=Tokyo" to get the current temperature, humidity, and weather information.

[0722] Output: The server retrieves climate data such as temperature (30 degrees), humidity (70%), and weather (sunny).

[0723] Step 2:

[0724] Input: The server collects data from the API of the social networking platform.

[0725] How it works: The server executes the request "GET https: / / snsapi.com / trending?category=food" to collect data on the most recent trending food-related posts.

[0726] Output: The server gets information about trending foods such as "smoothies," "pasta," and "salads."

[0727] Step 3:

[0728] Input: The server sends the user's data to the emotion engine.

[0729] Operation: The server inputs facial expression data, voice data, and text input sent from the device into the emotion engine and analyzes the user's emotions.

[0730] Output: The server receives emotion data such as "stress," "relaxation," and "joy."

[0731] Step 4:

[0732] Input: The server integrates climate data, social media data, and sentiment data.

[0733] How it works: The server uses this data to generate the optimal recipe for the user. For example, if the weather is "30 degrees, sunny," the social media trend is "smoothie," and the emotion is "stress," it generates a recipe for "relaxing herbal tea."

[0734] Output: The server will list the generated recipe (Relaxing Herbal Tea) and the ingredients it requires (chamomile, peppermint, etc.).

[0735] Step 5:

[0736] Input: The server sends the generated ingredient list to the online supermarket API.

[0737] What happens: The server executes the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[0738] Output: The server receives a purchase link from the online supermarket.

[0739] Step 6:

[0740] Input: The terminal displays the data received from the server.

[0741] Operation: The device displays the recipe received from the server, a list of the ingredients needed, and a link to purchase the recipe. Specifically, the device displays the recipe name for "Relaxing Herbal Tea" and the ingredients needed (chamomile, peppermint, etc.).

[0742] Output: The terminal provides visual information to the user.

[0743] Step 7:

[0744] Input: The user sees the recipe and ingredients list on their device.

[0745] How it works: A user uses a device to view a provided recipe and ingredient list.

[0746] Output: The user checks the ingredients needed and makes a purchasing decision.

[0747] Step 8:

[0748] Input: User clicks on a purchase link on their device.

[0749] Operation: The device will redirect the user to an online supermarket website based on the purchase link they clicked, where they can purchase ingredients.

[0750] Output: The user adds ingredients to the online supermarket cart and completes the purchase.

[0751] This process allows users to obtain optimal recipes based on the weather, trends, and emotions, and efficiently purchase the ingredients they need.

[0752] (Application example 2)

[0753] 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."

[0754] Modern consumers often don't have time to prepare meals due to their busy daily lives. Food preferences change depending on the season, weather, and personal emotions, making it difficult to instantly find the right recipe that reflects these preferences. Furthermore, the process of purchasing ingredients can be time-consuming, creating a demand for reducing the effort required for meal preparation.

[0755] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0756] In this invention, the server includes means for acquiring weather data, means for collecting data from electronic communication platforms, means for generating recommended recipes based on the collected data, means for adjusting the recommended recipes based on the collected emotion data using an emotion engine that recognizes the user's emotions, means for displaying the generated recipes and a list of required ingredients, and means for generating purchasing links to online stores. This allows users to easily obtain optimal recipes based on weather conditions, social network trends, and personal emotions, and then efficiently purchase the required ingredients online.

[0757] "Climate data" is information about environmental conditions such as current temperature, humidity, and weather.

[0758] An "electronic communication platform" is a service that allows users to interact and share information over the Internet.

[0759] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, text input, etc. to recognize the user's emotions.

[0760] A "recommended recipe" is a suggestion of how to cook a dish that is deemed best for the user based on collected information.

[0761] An "online store" is a platform for selling products over the Internet.

[0762] A "purchase link" is a URL that a user can click to access an online store and purchase a specific product.

[0763] The system of the invention integrates user sentiment, weather data, and trends from social networking services to support optimal recipe suggestions and online ingredient purchasing. The main components of the system are a server, a user terminal, and a network interface.

[0764] First, the server collects current weather information (temperature, humidity, weather) using a climate data acquisition method. It uses a climate data API to obtain the necessary information and updates it in real time. This information is collected using existing climate data providers, such as the OpenWeatherMap API.

[0765] Next, we use the APIs of electronic communication platforms, such as Twitter API and Instagram API, to gather the latest food-related trend information. This allows us to understand what is currently trending and what food-related posts are popular.

[0766] The server also uses an emotion engine to recognize the user's emotions. It uses the smartphone's camera and microphone to capture the user's facial expressions and voice, and collects emotion data. This analysis utilizes emotion recognition technologies such as Google Cloud Vision API and Amazon Rekognition.

[0767] Based on the collected weather, social media, and emotion data, a generative AI model (e.g., GPT-4) is used to generate optimal recipes. These recipes are suggested to users based on prompt statements such as, "The user's emotion is stress, the current weather is 30 degrees, sunny, and the latest trend is smoothies. Please suggest the optimal recipe taking these into consideration."

[0768] A list of ingredients is created along with the recipe. The server then generates a purchase link from an online store based on this list. For example, the server can automatically create a purchase link for ingredients using an online store API such as Amazon MWS or Rakuten Market API.

[0769] The user device visually displays the generated recipe, ingredient list, and purchase link to the user. Users can view the recipe through the smartphone app and click the purchase link to go directly to the online store and easily purchase the necessary ingredients.

[0770] This system allows users to quickly find the best recipes based on weather conditions, social network trends, and their own emotions, and then efficiently purchase ingredients online.

[0771] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0772] Step 1:

[0773] The server acquires current weather information using the climate data acquisition means.

[0774] Input: User's location information

[0775] Data processing: Send a request to the climate data API to get the current temperature, humidity, and weather information

[0776] Output: Temperature, humidity, weather information

[0777] Specific behavior: Using the OpenWeatherMap API, make a request such as "GET https: / / api.openweathermap.org / data / 2.5 / weather?q=Tokyo&appid=your_api_key".

[0778] Step 2:

[0779] The server collects data for the electronic communication platform.

[0780] Enter: Food-related trending categories

[0781] Data processing: Send a request to the API of a social media platform to collect the latest food-related posts.

[0782] Output: Food-related trend information

[0783] What it does: Uses the Twitter API to make a request like "GET https: / / api.twitter.com / 2 / tweets / search / recent?query=food_trend".

[0784] Step 3:

[0785] The server uses an emotion engine to collect user emotion data.

[0786] Input: User facial expression video, audio data

[0787] Data processing: Send this data to the emotion recognition API to analyze emotions.

[0788] Output: Emotion data (e.g., stress, excitement, etc.)

[0789] What it does: Uses the Google Cloud Vision API to analyze a video or image and get an output such as "Emotion: Stress".

[0790] Step 4:

[0791] The server generates recommended recipes based on collected weather data, social media data, and emotional data.

[0792] Input: Climate data, social media data, sentiment data

[0793] Data processing: Input prompts into the generative AI model to generate optimal recipes

[0794] Output: Recommended recipes

[0795] Specific behavior: Send a prompt to a generative AI model such as GPT-4, such as "The user's emotion is stress, the current weather is 30 degrees and sunny, and the latest trend is smoothies. Please suggest the best recipe taking this into consideration."

[0796] Step 5:

[0797] The server generates a list of ingredients and a purchasing link based on the generated recipe.

[0798] Input: Recommended recipe

[0799] Data processing: Using the API of an online store, generate a purchase link based on the ingredients list

[0800] Output: Purchase link (URL)

[0801] Specific operation: Using the Amazon MWS API, make a request such as "POST https: / / api.example.com / cart / add" to obtain a purchase link.

[0802] Step 6:

[0803] The terminal visually displays the generated recipe, ingredient list, and purchase link to the user.

[0804] Input: Recommended recipe, purchase link

[0805] Data processing: Visual display through GUI

[0806] Output: Recipe information and links displayed to the user

[0807] What it does: The smartphone app displays the recipe name for "Relaxing Herbal Tea," along with the ingredients needed (e.g., chamomile, peppermint), and a link to purchase the recipe to the user.

[0808] Step 7:

[0809] Users click on the purchase link from their device and purchase the necessary ingredients from the online store.

[0810] Enter: Purchasing Link

[0811] Data processing: Open the link via your smartphone browser and access the online store

[0812] Output: Screen to complete the purchase process

[0813] What happens: When a user clicks on the purchase link, they are taken to the online store's website, where they can add the ingredients they need to their cart and complete the purchase.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] [Third embodiment]

[0818] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0819] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0820] 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).

[0821] 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.

[0822] 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.

[0823] 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).

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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."

[0830] This invention is a system that utilizes weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and also supports food ingredient purchasing at online supermarkets.

[0831] Server Roles

[0832] The server acts as the core of the system through the following steps:

[0833] 1. Obtaining climate data:

[0834] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0835] 2. Social Media Data Collection:

[0836] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0837] 3. Generate the recipe:

[0838] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[0839] 4. Generate a purchase link:

[0840] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. Specifically, it sends the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[0841] Device Role

[0842] The terminal provides an interface for users to view recipes and make purchases.

[0843] 1. Get and display recipes:

[0844] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[0845] 2. View Purchase Links:

[0846] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[0847] User Roles

[0848] The user operates the terminal to purchase ingredients based on the provided recipe.

[0849] 1. Check the recipe:

[0850] The user browses the recipe and ingredient list provided on the device.

[0851] 2. Click on the purchase link and purchase the ingredients:

[0852] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[0853] Specific examples

[0854] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click on the purchase link displayed to purchase the ingredients on the online supermarket site.

[0855] The present invention allows users to efficiently practice a healthy and balanced diet that takes into account the weather and the latest trends.

[0856] The processing flow will be explained below.

[0857] Step 1: Collect data

[0858] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0859] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0860] Step 2: Analyze the data and select a recipe

[0861] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information.

[0862] The server searches for the corresponding recipe in its internal database, for example by executing the SQL query "SELECT FROM recipes WHERE type='cold' AND category='salad'".

[0863] Step 3: Generate the recipe and ingredient list

[0864] The server generates a list of ingredients required for the selected recipe.

[0865] The server sends the generated recipe and ingredient list to the terminal.

[0866] Step 4: View the recipe

[0867] The terminal displays the recipe and the list of ingredients received from the server to the user.

[0868] For example, the recipe name of "Cold Summer Salad" and the required ingredients (lettuce, tomato, cucumber, dressing, etc.) are visually presented to the user.

[0869] Step 5: Generate Purchasing Links

[0870] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, send the list of ingredients via "POST https: / / supermarketapi.com / cart / add".

[0871] The server receives the purchase link returned from the online supermarket.

[0872] Step 6: View purchasing links

[0873] The terminal displays the purchase link received from the server to the user.

[0874] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[0875] Step 7: Buy ingredients

[0876] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[0877] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[0878] By following these steps, users can easily obtain recipes that reflect the weather and trends, and efficiently purchase the ingredients they need.

[0879] Example 1

[0880] 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."

[0881] Modern consumers face challenges in quickly finding appropriate recipes in response to changes in climate and lifestyles. They also lack the means to efficiently select the latest trendy and healthy meals and easily purchase the ingredients. Conventional systems have limited capabilities for utilizing climate data and information from social networking services, making it difficult to provide users with optimal recipes and convenient purchasing methods. Given this background, there is a demand for a system that allows users to easily find optimal recipes based on climate and social trends and easily purchase the ingredients online.

[0882] 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.

[0883] In this invention, the server includes means for acquiring weather data, means for collecting information from social networking services, means for generating recommended recipes based on the collected information, means for displaying the generated recipes and lists of ingredients required, and means for generating purchasing links to online grocery stores, thereby enabling users to easily find optimal recipes based on weather and trend information and quickly purchase the ingredients.

[0884] "Climate data" is information about meteorological conditions such as current temperature, humidity, and weather.

[0885] A "social networking service" is an online platform where users share information and communicate.

[0886] "Means of collecting information" are the functions and processes used to obtain the required information from a particular data source.

[0887] A "means for generating recommended recipes" is a method or algorithm for analyzing collected data and selecting the most suitable recipe for the user based on that data.

[0888] An "ingredient list" is a list of ingredients or items needed to execute a particular recipe.

[0889] An "online grocer" is a retailer or platform that sells food and related products over the internet.

[0890] A "means for generating purchase links" is a method or process for creating a URL or link that allows a particular product or ingredient to be added to a shopping cart at an online grocery store.

[0891] The present invention is a system that utilizes weather data and information from social networking services (SNS) to provide consumers with suitable recipes and also supports ingredient purchasing at online grocery stores.

[0892] Server Roles

[0893] The server functions as the core of the system using the following software and hardware: Weather API, SNS platform API, and online supermarket API.

[0894] Obtaining climate data

[0895] The server obtains climate data such as the current temperature, humidity, and weather by sending a request to WeatherAPI. For example, by sending a request such as "GET https: / / weatherapi.com / current?location=Tokyo", the current weather conditions for Tokyo are obtained. This data is stored in a database on the server.

[0896] Social media data collection

[0897] The server uses the API of the social media platform to collect current trending posts related to the food category. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food" to obtain trending information related to food. The collected data is analyzed, and the necessary information is stored in a database.

[0898] Recipe Generation

[0899] The server analyzes the acquired weather and social media data to select the best recipe for the user. This analysis is performed using a generative AI model. For example, based on the collected data, it may recommend cold dishes or menus using trending ingredients. The selected recipes are extracted from the recipe information stored in the internal database and displayed.

[0900] Generate Purchasing Links

[0901] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients required for the selected recipe. Specifically, the server sends the ingredient list via the request "POST https: / / supermarketapi.com / cart / add" and generates a purchase link. This link is also saved in the server's database.

[0902] Device Role

[0903] The terminal provides an interface for the user to view recipes and purchase ingredients.

[0904] Retrieving and displaying recipes

[0905] The device sends a request to the server based on the user's current status and location. For example, it sends a request like "GET https: / / myapp.com / recommendations?location=Tokyo" to retrieve the optimal recipe and ingredient list from the server. The received information is then displayed to the user.

[0906] View Purchasing Links

[0907] The device displays the purchase link received from the server to the user, and when the user clicks the link, they are taken to the online grocery store's website where they can easily purchase the ingredients they need.

[0908] User Roles

[0909] The user operates the terminal to purchase ingredients based on the provided recipe.

[0910] Check the recipe

[0911] The user checks the recipe and ingredient list provided on the terminal.

[0912] Click on the purchase link and purchase the material

[0913] The user clicks on the purchase link, which takes them to the online grocery store's website, where they can proceed to purchase the ingredients they need.

[0914] Specific examples

[0915] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from a weather data API. It also collects information about trending topics related to "salad" from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who then clicks on a purchase link to purchase the ingredients on an online grocery store's website.

[0916] Example prompts for generative AI models

[0917] "Please suggest suitable recipes based on current weather data and trending food information on social media. For example, what recipes would be good for a summer day in Tokyo (30 degrees, sunny)?"

[0918] With this invention, users can easily receive recipe suggestions that take into account the weather and the latest trends, and can quickly purchase the ingredients.

[0919] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0920] Step 1: Obtaining climate data

[0921] The server sends an HTTP request to WeatherAPI. Specifically, it uses the request "GET https: / / weatherapi.com / current?location=Tokyo". This request allows the server to obtain data such as the current temperature, humidity, and weather in JSON format. The obtained data is stored in an internal database.

[0922] Input: Current location information (e.g. Tokyo)

[0923] Output: Weather data such as temperature, humidity, and weather conditions (JSON format)

[0924] Step 2: Collect social media data

[0925] The server accesses the social media platform API and collects trending posts in the food category. For example, it uses the request "GET https: / / snsapi.com / trending?category=food". This request allows the server to obtain information about food-related topics that are currently trending. The obtained data is then analyzed and stored in a database.

[0926] Input: Request URL (e.g., food-related trends)

[0927] Output: Trending food data (JSON format)

[0928] Step 3: Generate the recipe

[0929] The server analyzes the acquired weather and social media data. It uses a generative AI model to analyze and select the optimal recipe for the user. It extracts an appropriate menu item, such as a "cold summer salad," from the recipe information stored in the database. It creates the selected recipe and a list of required ingredients and stores them in the database.

[0930] Input: Weather data, trending food data

[0931] Output: Recommended recipe, ingredients list

[0932] Step 4: Generate Purchasing Links

[0933] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. For example, the list of ingredients is sent via a request such as "POST https: / / supermarketapi.com / cart / add." The purchase link is generated and saved in the database.

[0934] Input: Materials list

[0935] Output: Purchasing Link

[0936] Step 5: Retrieve and display the recipe

[0937] The device sends an HTTP request to the server based on the user's current status and location information. For example, by sending a request such as "GET https: / / myapp.com / recommendations?location=Tokyo", the device obtains the optimal recipe and ingredient list from the server. The device then displays the received recipe and ingredient list to the user.

[0938] Input: current state and location of the user

[0939] Output: Recommended recipe, ingredients list

[0940] Step 6: View purchasing links

[0941] The terminal displays the purchase link received from the server to the user, who, when clicking the link, is directed to the online grocery store's website where the required ingredients are automatically added to the cart.

[0942] Input: Purchasing Link

[0943] Output: Online grocery store URL

[0944] Step 7: Check the recipe

[0945] The user can check the recipe and ingredient list displayed on the device, and can also check the details of the recipe, cooking steps, and required ingredients.

[0946] Input: Recommended recipe, ingredient list

[0947] Output: Recipe confirmation information

[0948] Step 8: Click on the purchase link and purchase the material

[0949] By clicking the purchase link displayed on the device, the user is taken to the online grocery store's website, where they can check the ingredients automatically added to their online supermarket cart and complete the purchase.

[0950] Input: Purchasing Link

[0951] Output: Online grocery store purchase page

[0952] (Application example 1)

[0953] 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."

[0954] The objective of this invention is to utilize weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and enable them to quickly order food not only from online supermarkets but also from food delivery services. This allows users to easily enjoy food that is suited to the weather and trends, improving the quality of their diet.

[0955] 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.

[0956] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for generating recommended recipes based on the collected data, means for displaying the generated recipes and a list of necessary ingredients, and means for generating an ordering link for a food delivery service, thereby enabling the user to receive suggested dishes that match the weather and trends and to quickly order them on the spot.

[0957] "Climate Data" is information about environmental conditions in a particular area, such as current temperature, humidity, and weather.

[0958] "Social networking service data" refers to user posts and trending information collected from online platforms.

[0959] "Recommended recipes" are cooking recipes generated based on collected weather data and data from social networking services.

[0960] The "ingredient list" is a list of ingredients required based on the recommended recipe.

[0961] An "online supermarket" is a service that allows you to purchase food and other products online.

[0962] A "purchase link" is a URL link that allows users to directly purchase the specified ingredients or dishes.

[0963] A "food delivery service" is a service that delivers food ordered by a user to their home or a designated location.

[0964] "Order Link" means a URL link for ordering food through a food delivery service.

[0965] The present invention relates to a system that utilizes weather data and data from social networking services (SNS) to provide consumers with suitable recipes and also supports food ordering via food delivery services.

[0966] Server Roles

[0967] 1. Obtaining climate data

[0968] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[0969] 2. Collecting social media data

[0970] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[0971] 3. Recipe Generation

[0972] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[0973] 4. Generate an order link

[0974] The server uses the food delivery service's API to generate an order link for the selected dish. Specifically, it sends a request to "POST https: / / deliveryapi.com / order / add" and sends the information about the selected dish.

[0975] Device Role

[0976] 1. Get and display recipes

[0977] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[0978] 2. Display of order link

[0979] The terminal displays the order link received from the server to the user, and the user can click the link to move to the food delivery service site and order the corresponding food.

[0980] User Roles

[0981] 1. Check the recipe

[0982] The user browses the recipe and ingredient list provided on the device.

[0983] 2. Click on the order link and order your food

[0984] The user clicks on the order link, goes to the food delivery service's website, and orders the food.

[0985] Specific examples

[0986] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click the displayed order link to order the food via a food delivery service.

[0987] This system allows users to easily enjoy cooking that takes into account the weather and the latest trends.

[0988] Prompt Sentence Examples

[0989] On a summer day in Tokyo when the weather is sunny and the temperature is 30 degrees, if the dish going viral on social media is a salad, what recipe would be appropriate?

[0990] (Hardware and software used)

[0991] Hardware: Servers, smartphones

[0992] Software: Python, Requests module, Weather API, SNS API, Food Delivery API

[0993] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0994] Step 1:

[0995] The server sends a request to the climate data API to obtain information such as the current temperature, humidity, and weather. The input is the user's location information, and the output is the current climate information for that location. The specific operation is to send an HTTP GET request to the API endpoint and extract the required data from the response.

[0996] Step 2:

[0997] The server accesses the API of a social networking service and collects the most recent buzzworthy food-related posts. The input is API authentication information and category information, and the output is trending food-related post data. Specifically, it sends an HTTP GET request to the API and extracts the necessary food trend information from the returned data.

[0998] Step 3:

[0999] The server analyzes the weather data acquired in step 1 and the social media data collected in step 2, and selects the optimal recipe for the user based on this information. The input is weather data and social media data, and the output is a recommended recipe and a list of required ingredients. The specific operation is to use an internal algorithm to select the optimal recipe and generate a list of required ingredients based on it.

[1000] Step 4:

[1001] The server generates an order link using the food delivery service's API based on the generated recommended recipe and list of ingredients. The input is the recommended recipe and list of ingredients, and the output is the order link. Specifically, it sends an HTTP POST request to the food delivery service's API to obtain the order link.

[1002] Step 5:

[1003] The device requests a recipe from the server based on the user's current conditions, and displays the recipe and ingredient list received from the server to the user. The input is the user's location information and other condition information, and the output is a recommended recipe and ingredient list. The specific operation is to send an HTTP GET request to the server and display the returned data on the device.

[1004] Step 6:

[1005] The terminal displays the order link received from the server to the user, and allows the user to click the link to go to the food delivery service's website and order the corresponding food. The input is the order link from the server, and the output is the user going to the food delivery service and ordering the food. The specific operation is to provide a user interface for clicking the order link.

[1006] Step 7:

[1007] The user views the recipe and ingredient list provided on the device, clicks the order link to go to the food delivery service's website, and places an order. The input is the recipe, ingredient list, and order link displayed on the device, and the output is the order being confirmed. The specific operation is for the user to click the order link on the device to complete the ordering process.

[1008] 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.

[1009] This invention is a system that uses weather data, data from social networking services (SNS), and an emotion engine that recognizes user emotions to provide consumers with optimal recipes and support ingredient purchasing at online supermarkets.

[1010] Server Roles

[1011] The server acts as the core of the system through the following steps:

[1012] 1. Obtaining climate data:

[1013] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[1014] 2. Social Media Data Collection:

[1015] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[1016] 3. Collecting Emotional Data:

[1017] The server uses an emotion engine to analyze the user's facial expressions, voice, and text input to recognize the user's current emotion, and this emotion data is reflected in the recipe recommendations.

[1018] 4. Generate the recipe:

[1019] The server generates the optimal recipe for the user based on the collected weather data, social media data, and emotional data.

[1020] For example, if a user is "feeling stressed," it will recommend recipes using herbs that have a relaxing effect.

[1021] 5. Generate a purchase link:

[1022] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" to send the list of ingredients.

[1023] Device Role

[1024] The terminal provides an interface for users to view recipes and make purchases.

[1025] 1. Recognizing and transmitting emotions:

[1026] The device uses the user's facial recognition camera, microphone, and keyboard input to perform analysis using an emotion engine, and the analysis results are sent to a server.

[1027] 2. Get and display recipes:

[1028] The terminal displays the recipe and the list of ingredients received from the server to the user.

[1029] For example, the recipe name of "Relaxing Herbal Tea" and the required ingredients (chamomile, peppermint, etc.) are visually presented to the user.

[1030] 3. View Purchase Links:

[1031] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[1032] User Roles

[1033] The user operates the terminal to purchase ingredients based on the provided recipe.

[1034] 1. Check the recipe:

[1035] The user browses the recipe and ingredient list provided on the device.

[1036] 2. Click on the purchase link and purchase the ingredients:

[1037] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[1038] Specific examples

[1039] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "smoothies" are trending from social media data. Furthermore, the emotion engine determines that the user is "feeling stressed." Based on this, the server selects a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link provided to purchase the ingredients on an online supermarket website.

[1040] The present invention allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and to efficiently purchase the ingredients they need.

[1041] The processing flow will be explained below.

[1042] Step 1: Collect climate data

[1043] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[1044] Step 2: Collect social media data

[1045] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[1046] Step 3: Collecting emotion data

[1047] The device uses the user's facial expressions, voice, and text input to analyze using an emotion engine and recognize the user's current emotions.

[1048] For example, the device uses a camera to capture the user's facial expressions, which are then analyzed by the emotion engine. It also uses a microphone to analyze the tone of the voice.

[1049] Step 4: Sending emotion data

[1050] The device transmits the recognized user emotion data to the server.

[1051] For example, send emotion data to the server with a "POST https: / / myapp.com / emotion" request.

[1052] Step 5: Generate the recipe

[1053] The server analyzes the collected weather data, social media data, and sentiment data, and generates the optimal recipe for the user based on this.

[1054] For example, if the temperature is 30 degrees and the day is sunny, cold food would be appropriate, and if "smoothies" are trending on social media and the user is perceived as "feeling stressed," the app will suggest a relaxing herbal tea.

[1055] Step 6: Generate the recipe and ingredient list

[1056] The server generates the selected recipe and ingredient list and sends them to the terminal.

[1057] For example, generate data containing a recipe for "cold herbal tea" and the ingredients needed (chamomile, peppermint, etc.).

[1058] Step 7: View the recipe

[1059] The terminal displays the recipe and the list of ingredients received from the server to the user.

[1060] For example, a recipe for "cold herbal tea" can be visually presented to the user, including a photo, instructions, and a list of ingredients needed.

[1061] Step 8: Generate Purchasing Links

[1062] The server uses the online supermarket's API to generate a purchase link based on the ingredients list. For example, it sends the ingredients list to "POST https: / / supermarketapi.com / cart / add".

[1063] The server receives the purchase link returned from the online supermarket.

[1064] Step 9: View Purchasing Links

[1065] The terminal displays the purchase link received from the server to the user.

[1066] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[1067] Step 10: Buy ingredients

[1068] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[1069] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[1070] By following these steps, users can easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[1071] Example 2

[1072] 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."

[1073] Today's busy consumers find it difficult to efficiently purchase ingredients and find suitable recipes in their daily lives. Furthermore, there are currently no recipe recommendation systems that take into account factors such as weather, trends, and user emotions, and there is a need for a method to utilize this information in an integrated manner. The present invention aims to solve these problems by providing a system that offers optimal recipes to users and supports ingredient purchasing.

[1074] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1075] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for recognizing a user's emotions using an emotion engine, means for generating recommended recipes based on the collected data and the recognized emotions, means for displaying the generated recipes and a list of necessary ingredients, and means for generating purchasing links to online supermarkets. This allows users to easily obtain optimal recipes that take into account the weather, trends, and emotions, and efficiently purchase the necessary ingredients.

[1076] "Climate data" refers to information about the weather, such as current temperature, humidity, and weather.

[1077] "Social networking service data" refers to information about food-related content and trends posted on social media platforms.

[1078] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, and text input to recognize the user's current emotions.

[1079] A "recommended recipe" is a cooking recipe that is optimal for the user and is generated based on weather data, data from social networking services, and the user's emotional data.

[1080] The "ingredient list" is a list of ingredients needed to prepare a dish based on the recommended recipe.

[1081] An "online supermarket" is a supermarket that sells ingredients and food online.

[1082] A "purchase link" is a link on the online supermarket site that allows direct access to a shopping cart containing the ingredients you need.

[1083] This system integrates weather data, data from social networking services, and user sentiment data to provide optimal recipes to consumers and support food purchasing in online supermarkets. The system consists of a server and a terminal.

[1084] Server Roles

[1085] The server serves as the core of the system and performs the following functions:

[1086] 1. Obtaining climate data:

[1087] The server uses the weather data API to collect information such as the current temperature, humidity, and weather. Specifically, it sends a request such as "GET https: / / weatherapi.com / current?location=Tokyo" and analyzes the returned data. This weather data is used for subsequent processing.

[1088] 2. Social Media Data Collection:

[1089] The server uses the API of the social media platform to collect recent trending food-related posts. For example, it sends a request like "GET https: / / snsapi.com / trending?category=food" to retrieve data on popular dishes. The social media data, along with weather data, is used to generate recipes.

[1090] 3. Collecting Emotional Data:

[1091] The server uses an emotion engine to recognize emotions from the user's facial expressions, voice, and text input. Emotional data is captured as "stress," "relaxation," "joy," etc., and is reflected in the creation of recipes.

[1092] 4. Generate the recipe:

[1093] The server combines the collected weather, social media, and emotional data to generate recipes tailored to the user. For example, if a user is feeling stressed, it will recommend recipes using herbs that have a relaxing effect. It will generate a recipe such as "Relaxing Herbal Tea" and list the ingredients needed.

[1094] 5. Generate a purchase link:

[1095] The server uses the online supermarket's API to generate a list of the ingredients needed and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" and generates a purchase link by sending the ingredient list. The link is sent to the device, and the user can click it to go to the online supermarket's website and purchase the ingredients.

[1096] Device Role

[1097] The terminal provides an interface for users to view recipes and make purchases.

[1098] 1. Recognizing and transmitting emotions:

[1099] The device uses a facial recognition camera, microphone, and keyboard input to analyze the user's emotions and sends the results to a server.

[1100] 2. Get and display recipes:

[1101] The device displays the recipe and the list of ingredients received from the server to the user. Specifically, the device visually presents the recipe name, such as "Relaxing Herbal Tea," and the ingredients required (chamomile, peppermint, etc.).

[1102] 3. View Purchase Links:

[1103] The terminal displays the purchase link received from the server, and the user can click on the link to go to the online supermarket site and purchase the necessary ingredients.

[1104] User Roles

[1105] The user operates the terminal to purchase ingredients based on the provided recipe.

[1106] 1. Check the recipe:

[1107] The user browses the recipe and ingredient list provided on the device.

[1108] 2. Click on the purchase link and purchase the ingredients:

[1109] The user clicks on the purchase link and is taken to the online supermarket site to purchase the necessary ingredients.

[1110] Specific examples

[1111] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and gathers information about the popularity of "smoothies" from social media data. The emotion engine then determines that the user is "feeling stressed." Based on this information, the server generates a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link to purchase the ingredients on the online supermarket site.

[1112] Prompt Sentence Examples

[1113] "Based on current weather data for Tokyo, please tell us some recipes for cold drinks that are perfect for weather over 25 degrees that have been trending on social media recently. Also, please include examples of recipes that would be perfect for when users are feeling relaxed."

[1114] This system allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[1115] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1116] Step 1:

[1117] Input: The server sends a request from the Climate Data API.

[1118] How it works: The server executes the request "GET https: / / weatherapi.com / current?location=Tokyo" to get the current temperature, humidity, and weather information.

[1119] Output: The server retrieves climate data such as temperature (30 degrees), humidity (70%), and weather (sunny).

[1120] Step 2:

[1121] Input: The server collects data from the API of the social networking platform.

[1122] How it works: The server executes the request "GET https: / / snsapi.com / trending?category=food" to collect data on the most recent trending food-related posts.

[1123] Output: The server gets information about trending foods such as "smoothies," "pasta," and "salads."

[1124] Step 3:

[1125] Input: The server sends the user's data to the emotion engine.

[1126] Operation: The server inputs facial expression data, voice data, and text input sent from the device into the emotion engine and analyzes the user's emotions.

[1127] Output: The server receives emotion data such as "stress," "relaxation," and "joy."

[1128] Step 4:

[1129] Input: The server integrates climate data, social media data, and sentiment data.

[1130] How it works: The server uses this data to generate the optimal recipe for the user. For example, if the weather is "30 degrees, sunny," the social media trend is "smoothie," and the emotion is "stress," it generates a recipe for "relaxing herbal tea."

[1131] Output: The server will list the generated recipe (Relaxing Herbal Tea) and the ingredients it requires (chamomile, peppermint, etc.).

[1132] Step 5:

[1133] Input: The server sends the generated ingredient list to the online supermarket API.

[1134] What happens: The server executes the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[1135] Output: The server receives a purchase link from the online supermarket.

[1136] Step 6:

[1137] Input: The terminal displays the data received from the server.

[1138] Operation: The device displays the recipe received from the server, a list of the ingredients needed, and a link to purchase the recipe. Specifically, the device displays the recipe name for "Relaxing Herbal Tea" and the ingredients needed (chamomile, peppermint, etc.).

[1139] Output: The terminal provides visual information to the user.

[1140] Step 7:

[1141] Input: The user sees the recipe and ingredients list on their device.

[1142] How it works: A user uses a device to view a provided recipe and ingredient list.

[1143] Output: The user checks the ingredients needed and makes a purchasing decision.

[1144] Step 8:

[1145] Input: User clicks on a purchase link on their device.

[1146] Operation: The device will redirect the user to an online supermarket website based on the purchase link they clicked, where they can purchase ingredients.

[1147] Output: The user adds ingredients to the online supermarket cart and completes the purchase.

[1148] This process allows users to obtain optimal recipes based on the weather, trends, and emotions, and efficiently purchase the ingredients they need.

[1149] (Application example 2)

[1150] 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."

[1151] Modern consumers often don't have time to prepare meals due to their busy daily lives. Food preferences change depending on the season, weather, and personal emotions, making it difficult to instantly find the right recipe that reflects these preferences. Furthermore, the process of purchasing ingredients can be time-consuming, creating a demand for reducing the effort required for meal preparation.

[1152] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1153] In this invention, the server includes means for acquiring weather data, means for collecting data from electronic communication platforms, means for generating recommended recipes based on the collected data, means for adjusting the recommended recipes based on the collected emotion data using an emotion engine that recognizes the user's emotions, means for displaying the generated recipes and a list of required ingredients, and means for generating purchasing links to online stores. This allows users to easily obtain optimal recipes based on weather conditions, social network trends, and personal emotions, and then efficiently purchase the required ingredients online.

[1154] "Climate data" is information about environmental conditions such as current temperature, humidity, and weather.

[1155] An "electronic communication platform" is a service that allows users to interact and share information over the Internet.

[1156] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, text input, etc. to recognize the user's emotions.

[1157] A "recommended recipe" is a suggestion of how to cook a dish that is deemed best for the user based on collected information.

[1158] An "online store" is a platform for selling products over the Internet.

[1159] A "purchase link" is a URL that a user can click to access an online store and purchase a specific product.

[1160] The system of the invention integrates user sentiment, weather data, and trends from social networking services to support optimal recipe suggestions and online ingredient purchasing. The main components of the system are a server, a user terminal, and a network interface.

[1161] First, the server collects current weather information (temperature, humidity, weather) using a climate data acquisition method. It uses a climate data API to obtain the necessary information and updates it in real time. This information is collected using existing climate data providers, such as the OpenWeatherMap API.

[1162] Next, we use the APIs of electronic communication platforms, such as Twitter API and Instagram API, to gather the latest food-related trend information. This allows us to understand what is currently trending and what food-related posts are popular.

[1163] The server also uses an emotion engine to recognize the user's emotions. It uses the smartphone's camera and microphone to capture the user's facial expressions and voice, and collects emotion data. This analysis utilizes emotion recognition technologies such as Google Cloud Vision API and Amazon Rekognition.

[1164] Based on the collected weather, social media, and emotion data, a generative AI model (e.g., GPT-4) is used to generate optimal recipes. These recipes are suggested to users based on prompt statements such as, "The user's emotion is stress, the current weather is 30 degrees, sunny, and the latest trend is smoothies. Please suggest the optimal recipe taking these into consideration."

[1165] A list of ingredients is created along with the recipe. The server then generates a purchase link from an online store based on this list. For example, the server can automatically create a purchase link for ingredients using an online store API such as Amazon MWS or Rakuten Market API.

[1166] The user device visually displays the generated recipe, ingredient list, and purchase link to the user. Users can view the recipe through the smartphone app and click the purchase link to go directly to the online store and easily purchase the necessary ingredients.

[1167] This system allows users to quickly find the best recipes based on weather conditions, social network trends, and their own emotions, and then efficiently purchase ingredients online.

[1168] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1169] Step 1:

[1170] The server acquires current weather information using the climate data acquisition means.

[1171] Input: User's location information

[1172] Data processing: Send a request to the climate data API to get the current temperature, humidity, and weather information

[1173] Output: Temperature, humidity, weather information

[1174] Specific behavior: Using the OpenWeatherMap API, make a request such as "GET https: / / api.openweathermap.org / data / 2.5 / weather?q=Tokyo&appid=your_api_key".

[1175] Step 2:

[1176] The server collects data for the electronic communication platform.

[1177] Enter: Food-related trending categories

[1178] Data processing: Send a request to the API of a social media platform to collect the latest food-related posts.

[1179] Output: Food-related trend information

[1180] What it does: Uses the Twitter API to make a request like "GET https: / / api.twitter.com / 2 / tweets / search / recent?query=food_trend".

[1181] Step 3:

[1182] The server uses an emotion engine to collect user emotion data.

[1183] Input: User facial expression video, audio data

[1184] Data processing: Send this data to the emotion recognition API to analyze emotions.

[1185] Output: Emotion data (e.g., stress, excitement, etc.)

[1186] What it does: Uses the Google Cloud Vision API to analyze a video or image and get an output such as "Emotion: Stress".

[1187] Step 4:

[1188] The server generates recommended recipes based on collected weather data, social media data, and emotional data.

[1189] Input: Climate data, social media data, sentiment data

[1190] Data processing: Input prompts into the generative AI model to generate optimal recipes

[1191] Output: Recommended recipes

[1192] Specific behavior: Send a prompt to a generative AI model such as GPT-4, such as "The user's emotion is stress, the current weather is 30 degrees and sunny, and the latest trend is smoothies. Please suggest the best recipe taking this into consideration."

[1193] Step 5:

[1194] The server generates a list of ingredients and a purchasing link based on the generated recipe.

[1195] Input: Recommended recipe

[1196] Data processing: Using the API of an online store, generate a purchase link based on the ingredients list

[1197] Output: Purchase link (URL)

[1198] Specific operation: Using the Amazon MWS API, make a request such as "POST https: / / api.example.com / cart / add" to obtain a purchase link.

[1199] Step 6:

[1200] The terminal visually displays the generated recipe, ingredient list, and purchase link to the user.

[1201] Input: Recommended recipe, purchase link

[1202] Data processing: Visual display through GUI

[1203] Output: Recipe information and links displayed to the user

[1204] What it does: The smartphone app displays the recipe name for "Relaxing Herbal Tea," along with the ingredients needed (e.g., chamomile, peppermint), and a link to purchase the recipe to the user.

[1205] Step 7:

[1206] Users click on the purchase link from their device and purchase the necessary ingredients from the online store.

[1207] Enter: Purchasing Link

[1208] Data processing: Open the link via your smartphone browser and access the online store

[1209] Output: Screen to complete the purchase process

[1210] What happens: When a user clicks on the purchase link, they are taken to the online store's website, where they can add the ingredients they need to their cart and complete the purchase.

[1211] 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.

[1212] 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.

[1213] 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.

[1214] [Fourth embodiment]

[1215] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1216] 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.

[1217] 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).

[1218] 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.

[1219] 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.

[1220] 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).

[1221] 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.

[1222] 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.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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."

[1228] This invention is a system that utilizes weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and also supports food ingredient purchasing at online supermarkets.

[1229] Server Roles

[1230] The server acts as the core of the system through the following steps:

[1231] 1. Obtaining climate data:

[1232] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[1233] 2. Social Media Data Collection:

[1234] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[1235] 3. Generate the recipe:

[1236] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[1237] 4. Generate a purchase link:

[1238] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. Specifically, it sends the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[1239] Device Role

[1240] The terminal provides an interface for users to view recipes and make purchases.

[1241] 1. Get and display recipes:

[1242] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[1243] 2. View Purchase Links:

[1244] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[1245] User Roles

[1246] The user operates the terminal to purchase ingredients based on the provided recipe.

[1247] 1. Check the recipe:

[1248] The user browses the recipe and ingredient list provided on the device.

[1249] 2. Click on the purchase link and purchase the ingredients:

[1250] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[1251] Specific examples

[1252] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click on the purchase link displayed to purchase the ingredients on the online supermarket site.

[1253] The present invention allows users to efficiently practice a healthy and balanced diet that takes into account the weather and the latest trends.

[1254] The processing flow will be explained below.

[1255] Step 1: Collect data

[1256] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[1257] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[1258] Step 2: Analyze the data and select a recipe

[1259] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information.

[1260] The server searches for the corresponding recipe in its internal database, for example by executing the SQL query "SELECT FROM recipes WHERE type='cold' AND category='salad'".

[1261] Step 3: Generate the recipe and ingredient list

[1262] The server generates a list of ingredients required for the selected recipe.

[1263] The server sends the generated recipe and ingredient list to the terminal.

[1264] Step 4: View the recipe

[1265] The terminal displays the recipe and the list of ingredients received from the server to the user.

[1266] For example, the recipe name of "Cold Summer Salad" and the required ingredients (lettuce, tomato, cucumber, dressing, etc.) are visually presented to the user.

[1267] Step 5: Generate Purchasing Links

[1268] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, send the list of ingredients via "POST https: / / supermarketapi.com / cart / add".

[1269] The server receives the purchase link returned from the online supermarket.

[1270] Step 6: View purchasing links

[1271] The terminal displays the purchase link received from the server to the user.

[1272] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[1273] Step 7: Buy ingredients

[1274] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[1275] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[1276] By following these steps, users can easily obtain recipes that reflect the weather and trends, and efficiently purchase the ingredients they need.

[1277] Example 1

[1278] 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."

[1279] Modern consumers face challenges in quickly finding appropriate recipes in response to changes in climate and lifestyles. They also lack the means to efficiently select the latest trendy and healthy meals and easily purchase the ingredients. Conventional systems have limited capabilities for utilizing climate data and information from social networking services, making it difficult to provide users with optimal recipes and convenient purchasing methods. Given this background, there is a demand for a system that allows users to easily find optimal recipes based on climate and social trends and easily purchase the ingredients online.

[1280] 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.

[1281] In this invention, the server includes means for acquiring weather data, means for collecting information from social networking services, means for generating recommended recipes based on the collected information, means for displaying the generated recipes and lists of ingredients required, and means for generating purchasing links to online grocery stores, thereby enabling users to easily find optimal recipes based on weather and trend information and quickly purchase the ingredients.

[1282] "Climate data" is information about meteorological conditions such as current temperature, humidity, and weather.

[1283] A "social networking service" is an online platform where users share information and communicate.

[1284] "Means of collecting information" are the functions and processes used to obtain the required information from a particular data source.

[1285] A "means for generating recommended recipes" is a method or algorithm for analyzing collected data and selecting the most suitable recipe for the user based on that data.

[1286] An "ingredient list" is a list of ingredients or items needed to execute a particular recipe.

[1287] An "online grocer" is a retailer or platform that sells food and related products over the internet.

[1288] A "means for generating purchase links" is a method or process for creating a URL or link that allows a particular product or ingredient to be added to a shopping cart at an online grocery store.

[1289] The present invention is a system that utilizes weather data and information from social networking services (SNS) to provide consumers with suitable recipes and also supports ingredient purchasing at online grocery stores.

[1290] Server Roles

[1291] The server functions as the core of the system using the following software and hardware: Weather API, SNS platform API, and online supermarket API.

[1292] Obtaining climate data

[1293] The server obtains climate data such as the current temperature, humidity, and weather by sending a request to WeatherAPI. For example, by sending a request such as "GET https: / / weatherapi.com / current?location=Tokyo", the current weather conditions for Tokyo are obtained. This data is stored in a database on the server.

[1294] Social media data collection

[1295] The server uses the API of the social media platform to collect current trending posts related to the food category. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food" to obtain trending information related to food. The collected data is analyzed, and the necessary information is stored in a database.

[1296] Recipe Generation

[1297] The server analyzes the acquired weather and social media data to select the best recipe for the user. This analysis is performed using a generative AI model. For example, based on the collected data, it may recommend cold dishes or menus using trending ingredients. The selected recipes are extracted from the recipe information stored in the internal database and displayed.

[1298] Generate Purchasing Links

[1299] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients required for the selected recipe. Specifically, the server sends the ingredient list via the request "POST https: / / supermarketapi.com / cart / add" and generates a purchase link. This link is also saved in the server's database.

[1300] Device Role

[1301] The terminal provides an interface for the user to view recipes and purchase ingredients.

[1302] Retrieving and displaying recipes

[1303] The device sends a request to the server based on the user's current status and location. For example, it sends a request like "GET https: / / myapp.com / recommendations?location=Tokyo" to retrieve the optimal recipe and ingredient list from the server. The received information is then displayed to the user.

[1304] View Purchasing Links

[1305] The device displays the purchase link received from the server to the user, and when the user clicks the link, they are taken to the online grocery store's website where they can easily purchase the ingredients they need.

[1306] User Roles

[1307] The user operates the terminal to purchase ingredients based on the provided recipe.

[1308] Check the recipe

[1309] The user checks the recipe and ingredient list provided on the terminal.

[1310] Click on the purchase link and purchase the material

[1311] The user clicks on the purchase link, which takes them to the online grocery store's website, where they can proceed to purchase the ingredients they need.

[1312] Specific examples

[1313] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from a weather data API. It also collects information about trending topics related to "salad" from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who then clicks on a purchase link to purchase the ingredients on an online grocery store's website.

[1314] Example prompts for generative AI models

[1315] "Please suggest suitable recipes based on current weather data and trending food information on social media. For example, what recipes would be good for a summer day in Tokyo (30 degrees, sunny)?"

[1316] With this invention, users can easily receive recipe suggestions that take into account the weather and the latest trends, and can quickly purchase the ingredients.

[1317] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1318] Step 1: Obtaining climate data

[1319] The server sends an HTTP request to WeatherAPI. Specifically, it uses the request "GET https: / / weatherapi.com / current?location=Tokyo". This request allows the server to obtain data such as the current temperature, humidity, and weather in JSON format. The obtained data is stored in an internal database.

[1320] Input: Current location information (e.g. Tokyo)

[1321] Output: Weather data such as temperature, humidity, and weather conditions (JSON format)

[1322] Step 2: Collect social media data

[1323] The server accesses the social media platform API and collects trending posts in the food category. For example, it uses the request "GET https: / / snsapi.com / trending?category=food". This request allows the server to obtain information about food-related topics that are currently trending. The obtained data is then analyzed and stored in a database.

[1324] Input: Request URL (e.g., food-related trends)

[1325] Output: Trending food data (JSON format)

[1326] Step 3: Generate the recipe

[1327] The server analyzes the acquired weather and social media data. It uses a generative AI model to analyze and select the optimal recipe for the user. It extracts an appropriate menu item, such as a "cold summer salad," from the recipe information stored in the database. It creates the selected recipe and a list of required ingredients and stores them in the database.

[1328] Input: Weather data, trending food data

[1329] Output: Recommended recipe, ingredients list

[1330] Step 4: Generate Purchasing Links

[1331] The server uses the online supermarket's API to generate a purchase link based on the list of ingredients needed. For example, the list of ingredients is sent via a request such as "POST https: / / supermarketapi.com / cart / add." The purchase link is generated and saved in the database.

[1332] Input: Materials list

[1333] Output: Purchasing Link

[1334] Step 5: Retrieve and display the recipe

[1335] The device sends an HTTP request to the server based on the user's current status and location information. For example, by sending a request such as "GET https: / / myapp.com / recommendations?location=Tokyo", the device obtains the optimal recipe and ingredient list from the server. The device then displays the received recipe and ingredient list to the user.

[1336] Input: current state and location of the user

[1337] Output: Recommended recipe, ingredients list

[1338] Step 6: View purchasing links

[1339] The terminal displays the purchase link received from the server to the user, who, when clicking the link, is directed to the online grocery store's website where the required ingredients are automatically added to the cart.

[1340] Input: Purchasing Link

[1341] Output: Online grocery store URL

[1342] Step 7: Check the recipe

[1343] The user can check the recipe and ingredient list displayed on the device, and can also check the details of the recipe, cooking steps, and required ingredients.

[1344] Input: Recommended recipe, ingredient list

[1345] Output: Recipe confirmation information

[1346] Step 8: Click on the purchase link and purchase the material

[1347] By clicking the purchase link displayed on the device, the user is taken to the online grocery store's website, where they can check the ingredients automatically added to their online supermarket cart and complete the purchase.

[1348] Input: Purchasing Link

[1349] Output: Online grocery store purchase page

[1350] (Application example 1)

[1351] 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."

[1352] The objective of this invention is to utilize weather data and data from social networking services (SNS) to provide consumers with appropriate recipes and enable them to quickly order food not only from online supermarkets but also from food delivery services. This allows users to easily enjoy food that is suited to the weather and trends, improving the quality of their diet.

[1353] 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.

[1354] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for generating recommended recipes based on the collected data, means for displaying the generated recipes and a list of necessary ingredients, and means for generating an ordering link for a food delivery service, thereby enabling the user to receive suggested dishes that match the weather and trends and to quickly order them on the spot.

[1355] "Climate Data" is information about environmental conditions in a particular area, such as current temperature, humidity, and weather.

[1356] "Social networking service data" refers to user posts and trending information collected from online platforms.

[1357] "Recommended recipes" are cooking recipes generated based on collected weather data and data from social networking services.

[1358] The "ingredient list" is a list of ingredients required based on the recommended recipe.

[1359] An "online supermarket" is a service that allows you to purchase food and other products online.

[1360] A "purchase link" is a URL link that allows users to directly purchase the specified ingredients or dishes.

[1361] A "food delivery service" is a service that delivers food ordered by a user to their home or a designated location.

[1362] "Order Link" means a URL link for ordering food through a food delivery service.

[1363] The present invention relates to a system that utilizes weather data and data from social networking services (SNS) to provide consumers with suitable recipes and also supports food ordering via food delivery services.

[1364] Server Roles

[1365] 1. Obtaining climate data

[1366] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[1367] 2. Collecting social media data

[1368] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[1369] 3. Recipe Generation

[1370] The server analyzes the collected weather and social media data and selects the best recipe for the user based on this information. The selected recipe is extracted from the recipe information stored in the internal database.

[1371] 4. Generate an order link

[1372] The server uses the food delivery service's API to generate an order link for the selected dish. Specifically, it sends a request to "POST https: / / deliveryapi.com / order / add" and sends the information about the selected dish.

[1373] Device Role

[1374] 1. Get and display recipes

[1375] The device requests a recipe based on the user's current preferences from the server and displays the recipe and ingredient list received from the server to the user. For example, the request is "GET https: / / myapp.com / recommendations?location=Tokyo".

[1376] 2. Display of order link

[1377] The terminal displays the order link received from the server to the user, and the user can click the link to move to the food delivery service site and order the corresponding food.

[1378] User Roles

[1379] 1. Check the recipe

[1380] The user browses the recipe and ingredient list provided on the device.

[1381] 2. Click on the order link and order your food

[1382] The user clicks on the order link, goes to the food delivery service's website, and orders the food.

[1383] Specific examples

[1384] For example, if a user requests a recipe for a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "salad" is trending from social media data. Based on this information, the server selects a recipe for a "cold summer salad" and lists the necessary ingredients (lettuce, tomato, cucumber, dressing, etc.). The device displays this information to the user, who can click the displayed order link to order the food via a food delivery service.

[1385] This system allows users to easily enjoy cooking that takes into account the weather and the latest trends.

[1386] Prompt Sentence Examples

[1387] On a summer day in Tokyo when the weather is sunny and the temperature is 30 degrees, if the dish going viral on social media is a salad, what recipe would be appropriate?

[1388] (Hardware and software used)

[1389] Hardware: Servers, smartphones

[1390] Software: Python, Requests module, Weather API, SNS API, Food Delivery API

[1391] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1392] Step 1:

[1393] The server sends a request to the climate data API to obtain information such as the current temperature, humidity, and weather. The input is the user's location information, and the output is the current climate information for that location. The specific operation is to send an HTTP GET request to the API endpoint and extract the required data from the response.

[1394] Step 2:

[1395] The server accesses the API of a social networking service and collects the most recent buzzworthy food-related posts. The input is API authentication information and category information, and the output is trending food-related post data. Specifically, it sends an HTTP GET request to the API and extracts the necessary food trend information from the returned data.

[1396] Step 3:

[1397] The server analyzes the weather data acquired in step 1 and the social media data collected in step 2, and selects the optimal recipe for the user based on this information. The input is weather data and social media data, and the output is a recommended recipe and a list of required ingredients. The specific operation is to use an internal algorithm to select the optimal recipe and generate a list of required ingredients based on it.

[1398] Step 4:

[1399] The server generates an order link using the food delivery service's API based on the generated recommended recipe and list of ingredients. The input is the recommended recipe and list of ingredients, and the output is the order link. Specifically, it sends an HTTP POST request to the food delivery service's API to obtain the order link.

[1400] Step 5:

[1401] The device requests a recipe from the server based on the user's current conditions, and displays the recipe and ingredient list received from the server to the user. The input is the user's location information and other condition information, and the output is a recommended recipe and ingredient list. The specific operation is to send an HTTP GET request to the server and display the returned data on the device.

[1402] Step 6:

[1403] The terminal displays the order link received from the server to the user, and allows the user to click the link to go to the food delivery service's website and order the corresponding food. The input is the order link from the server, and the output is the user going to the food delivery service and ordering the food. The specific operation is to provide a user interface for clicking the order link.

[1404] Step 7:

[1405] The user views the recipe and ingredient list provided on the device, clicks the order link to go to the food delivery service's website, and places an order. The input is the recipe, ingredient list, and order link displayed on the device, and the output is the order being confirmed. The specific operation is for the user to click the order link on the device to complete the ordering process.

[1406] 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.

[1407] This invention is a system that uses weather data, data from social networking services (SNS), and an emotion engine that recognizes user emotions to provide consumers with optimal recipes and support ingredient purchasing at online supermarkets.

[1408] Server Roles

[1409] The server acts as the core of the system through the following steps:

[1410] 1. Obtaining climate data:

[1411] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[1412] 2. Social Media Data Collection:

[1413] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[1414] 3. Collecting Emotional Data:

[1415] The server uses an emotion engine to analyze the user's facial expressions, voice, and text input to recognize the user's current emotion, and this emotion data is reflected in the recipe recommendations.

[1416] 4. Generate the recipe:

[1417] The server generates the optimal recipe for the user based on the collected weather data, social media data, and emotional data.

[1418] For example, if a user is "feeling stressed," it will recommend recipes using herbs that have a relaxing effect.

[1419] 5. Generate a purchase link:

[1420] The server uses the online supermarket's API to generate a list of ingredients and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" to send the list of ingredients.

[1421] Device Role

[1422] The terminal provides an interface for users to view recipes and make purchases.

[1423] 1. Recognizing and transmitting emotions:

[1424] The device uses the user's facial recognition camera, microphone, and keyboard input to perform analysis using an emotion engine, and the analysis results are sent to a server.

[1425] 2. Get and display recipes:

[1426] The terminal displays the recipe and the list of ingredients received from the server to the user.

[1427] For example, the recipe name of "Relaxing Herbal Tea" and the required ingredients (chamomile, peppermint, etc.) are visually presented to the user.

[1428] 3. View Purchase Links:

[1429] The terminal displays the purchase link received from the server to the user, and the user can click the link to go to the online supermarket site and purchase the necessary ingredients.

[1430] User Roles

[1431] The user operates the terminal to purchase ingredients based on the provided recipe.

[1432] 1. Check the recipe:

[1433] The user browses the recipe and ingredient list provided on the device.

[1434] 2. Click on the purchase link and purchase the ingredients:

[1435] The user clicks on the purchase link, goes to the online supermarket site and purchases the ingredients they need.

[1436] Specific examples

[1437] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and information that "smoothies" are trending from social media data. Furthermore, the emotion engine determines that the user is "feeling stressed." Based on this, the server selects a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link provided to purchase the ingredients on an online supermarket website.

[1438] The present invention allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and to efficiently purchase the ingredients they need.

[1439] The processing flow will be explained below.

[1440] Step 1: Collect climate data

[1441] The server sends a request to the weather data API to get information such as the current temperature, humidity, and weather. For example, the request is "GET https: / / weatherapi.com / current?location=Tokyo".

[1442] Step 2: Collect social media data

[1443] The server accesses the API of the social media platform and collects the most recent trending food-related posts. For example, it sends a request such as "GET https: / / snsapi.com / trending?category=food".

[1444] Step 3: Collecting emotion data

[1445] The device uses the user's facial expressions, voice, and text input to analyze using an emotion engine and recognize the user's current emotions.

[1446] For example, the device uses a camera to capture the user's facial expressions, which are then analyzed by the emotion engine. It also uses a microphone to analyze the tone of the voice.

[1447] Step 4: Sending emotion data

[1448] The device transmits the recognized user emotion data to the server.

[1449] For example, send emotion data to the server with a "POST https: / / myapp.com / emotion" request.

[1450] Step 5: Generate the recipe

[1451] The server analyzes the collected weather data, social media data, and sentiment data, and generates the optimal recipe for the user based on this.

[1452] For example, if the temperature is 30 degrees and the day is sunny, cold food would be appropriate, and if "smoothies" are trending on social media and the user is perceived as "feeling stressed," the app will suggest a relaxing herbal tea.

[1453] Step 6: Generate the recipe and ingredient list

[1454] The server generates the selected recipe and ingredient list and sends them to the terminal.

[1455] For example, generate data containing a recipe for "cold herbal tea" and the ingredients needed (chamomile, peppermint, etc.).

[1456] Step 7: View the recipe

[1457] The terminal displays the recipe and the list of ingredients received from the server to the user.

[1458] For example, a recipe for "cold herbal tea" can be visually presented to the user, including a photo, instructions, and a list of ingredients needed.

[1459] Step 8: Generate Purchasing Links

[1460] The server uses the online supermarket's API to generate a purchase link based on the ingredients list. For example, it sends the ingredients list to "POST https: / / supermarketapi.com / cart / add".

[1461] The server receives the purchase link returned from the online supermarket.

[1462] Step 9: View Purchasing Links

[1463] The terminal displays the purchase link received from the server to the user.

[1464] For example, show the user "Purchase link: https: / / supermarket.com / cart?id=12345".

[1465] Step 10: Buy ingredients

[1466] The user clicks on the purchase link displayed on the device and is taken to the online supermarket site.

[1467] Users check the list of ingredients they need on the online supermarket website and complete the purchasing process.

[1468] By following these steps, users can easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[1469] Example 2

[1470] 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."

[1471] Today's busy consumers find it difficult to efficiently purchase ingredients and find suitable recipes in their daily lives. Furthermore, there are currently no recipe recommendation systems that take into account factors such as weather, trends, and user emotions, and there is a need for a method to utilize this information in an integrated manner. The present invention aims to solve these problems by providing a system that offers optimal recipes to users and supports ingredient purchasing.

[1472] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1473] In this invention, the server includes means for acquiring weather data, means for collecting data from social networking services, means for recognizing a user's emotions using an emotion engine, means for generating recommended recipes based on the collected data and the recognized emotions, means for displaying the generated recipes and a list of necessary ingredients, and means for generating purchasing links to online supermarkets. This allows users to easily obtain optimal recipes that take into account the weather, trends, and emotions, and efficiently purchase the necessary ingredients.

[1474] "Climate data" refers to information about the weather, such as current temperature, humidity, and weather.

[1475] "Social networking service data" refers to information about food-related content and trends posted on social media platforms.

[1476] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, and text input to recognize the user's current emotions.

[1477] A "recommended recipe" is a cooking recipe that is optimal for the user and is generated based on weather data, data from social networking services, and the user's emotional data.

[1478] The "ingredient list" is a list of ingredients needed to prepare a dish based on the recommended recipe.

[1479] An "online supermarket" is a supermarket that sells ingredients and food online.

[1480] A "purchase link" is a link on the online supermarket site that allows direct access to a shopping cart containing the ingredients you need.

[1481] This system integrates weather data, data from social networking services, and user sentiment data to provide optimal recipes to consumers and support food purchasing in online supermarkets. The system consists of a server and a terminal.

[1482] Server Roles

[1483] The server serves as the core of the system and performs the following functions:

[1484] 1. Obtaining climate data:

[1485] The server uses the weather data API to collect information such as the current temperature, humidity, and weather. Specifically, it sends a request such as "GET https: / / weatherapi.com / current?location=Tokyo" and analyzes the returned data. This weather data is used for subsequent processing.

[1486] 2. Social Media Data Collection:

[1487] The server uses the API of the social media platform to collect recent trending food-related posts. For example, it sends a request like "GET https: / / snsapi.com / trending?category=food" to retrieve data on popular dishes. The social media data, along with weather data, is used to generate recipes.

[1488] 3. Collecting Emotional Data:

[1489] The server uses an emotion engine to recognize emotions from the user's facial expressions, voice, and text input. Emotional data is captured as "stress," "relaxation," "joy," etc., and is reflected in the creation of recipes.

[1490] 4. Generate the recipe:

[1491] The server combines the collected weather, social media, and emotional data to generate recipes tailored to the user. For example, if a user is feeling stressed, it will recommend recipes using herbs that have a relaxing effect. It will generate a recipe such as "Relaxing Herbal Tea" and list the ingredients needed.

[1492] 5. Generate a purchase link:

[1493] The server uses the online supermarket's API to generate a list of the ingredients needed and a purchase link. For example, it sends a request such as "POST https: / / supermarketapi.com / cart / add" and generates a purchase link by sending the ingredient list. The link is sent to the device, and the user can click it to go to the online supermarket's website and purchase the ingredients.

[1494] Device Role

[1495] The terminal provides an interface for users to view recipes and make purchases.

[1496] 1. Recognizing and transmitting emotions:

[1497] The device uses a facial recognition camera, microphone, and keyboard input to analyze the user's emotions and sends the results to a server.

[1498] 2. Get and display recipes:

[1499] The device displays the recipe and the list of ingredients received from the server to the user. Specifically, the device visually presents the recipe name, such as "Relaxing Herbal Tea," and the ingredients required (chamomile, peppermint, etc.).

[1500] 3. View Purchase Links:

[1501] The terminal displays the purchase link received from the server, and the user can click on the link to go to the online supermarket site and purchase the necessary ingredients.

[1502] User Roles

[1503] The user operates the terminal to purchase ingredients based on the provided recipe.

[1504] 1. Check the recipe:

[1505] The user browses the recipe and ingredient list provided on the device.

[1506] 2. Click on the purchase link and purchase the ingredients:

[1507] The user clicks on the purchase link and is taken to the online supermarket site to purchase the necessary ingredients.

[1508] Specific examples

[1509] For example, if a user is recognized as feeling stressed on a summer day in Tokyo, the server retrieves information such as "30 degrees, sunny" from the weather data API and gathers information about the popularity of "smoothies" from social media data. The emotion engine then determines that the user is "feeling stressed." Based on this information, the server generates a recipe for "relaxing herbal tea" and lists the necessary ingredients (chamomile, peppermint, etc.). The device displays this information to the user, who can then click on the purchase link to purchase the ingredients on the online supermarket site.

[1510] Prompt Sentence Examples

[1511] "Based on current weather data for Tokyo, please tell us some recipes for cold drinks that are perfect for weather over 25 degrees that have been trending on social media recently. Also, please include examples of recipes that would be perfect for when users are feeling relaxed."

[1512] This system allows users to easily obtain recipes that reflect the weather, trends, and even their own emotions, and efficiently purchase the ingredients they need.

[1513] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1514] Step 1:

[1515] Input: The server sends a request from the Climate Data API.

[1516] How it works: The server executes the request "GET https: / / weatherapi.com / current?location=Tokyo" to get the current temperature, humidity, and weather information.

[1517] Output: The server retrieves climate data such as temperature (30 degrees), humidity (70%), and weather (sunny).

[1518] Step 2:

[1519] Input: The server collects data from the API of the social networking platform.

[1520] How it works: The server executes the request "GET https: / / snsapi.com / trending?category=food" to collect data on the most recent trending food-related posts.

[1521] Output: The server gets information about trending foods such as "smoothies," "pasta," and "salads."

[1522] Step 3:

[1523] Input: The server sends the user's data to the emotion engine.

[1524] Operation: The server inputs facial expression data, voice data, and text input sent from the device into the emotion engine and analyzes the user's emotions.

[1525] Output: The server receives emotion data such as "stress," "relaxation," and "joy."

[1526] Step 4:

[1527] Input: The server integrates climate data, social media data, and sentiment data.

[1528] How it works: The server uses this data to generate the optimal recipe for the user. For example, if the weather is "30 degrees, sunny," the social media trend is "smoothie," and the emotion is "stress," it generates a recipe for "relaxing herbal tea."

[1529] Output: The server will list the generated recipe (Relaxing Herbal Tea) and the ingredients it requires (chamomile, peppermint, etc.).

[1530] Step 5:

[1531] Input: The server sends the generated ingredient list to the online supermarket API.

[1532] What happens: The server executes the request "POST https: / / supermarketapi.com / cart / add" and sends the list of ingredients.

[1533] Output: The server receives a purchase link from the online supermarket.

[1534] Step 6:

[1535] Input: The terminal displays the data received from the server.

[1536] Operation: The device displays the recipe received from the server, a list of the ingredients needed, and a link to purchase the recipe. Specifically, the device displays the recipe name for "Relaxing Herbal Tea" and the ingredients needed (chamomile, peppermint, etc.).

[1537] Output: The terminal provides visual information to the user.

[1538] Step 7:

[1539] Input: The user sees the recipe and ingredients list on their device.

[1540] How it works: A user uses a device to view a provided recipe and ingredient list.

[1541] Output: The user checks the ingredients needed and makes a purchasing decision.

[1542] Step 8:

[1543] Input: User clicks on a purchase link on their device.

[1544] Operation: The device will redirect the user to an online supermarket website based on the purchase link they clicked, where they can purchase ingredients.

[1545] Output: The user adds ingredients to the online supermarket cart and completes the purchase.

[1546] This process allows users to obtain optimal recipes based on the weather, trends, and emotions, and efficiently purchase the ingredients they need.

[1547] (Application example 2)

[1548] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1549] Modern consumers often don't have time to prepare meals due to their busy daily lives. Food preferences change depending on the season, weather, and personal emotions, making it difficult to instantly find the right recipe that reflects these preferences. Furthermore, the process of purchasing ingredients can be time-consuming, creating a demand for reducing the effort required for meal preparation.

[1550] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1551] In this invention, the server includes means for acquiring weather data, means for collecting data from electronic communication platforms, means for generating recommended recipes based on the collected data, means for adjusting the recommended recipes based on the collected emotion data using an emotion engine that recognizes the user's emotions, means for displaying the generated recipes and a list of required ingredients, and means for generating purchasing links to online stores. This allows users to easily obtain optimal recipes based on weather conditions, social network trends, and personal emotions, and then efficiently purchase the required ingredients online.

[1552] "Climate data" is information about environmental conditions such as current temperature, humidity, and weather.

[1553] An "electronic communication platform" is a service that allows users to interact and share information over the Internet.

[1554] An "emotion engine" is a technology that analyzes a user's facial expressions, voice, text input, etc. to recognize the user's emotions.

[1555] A "recommended recipe" is a suggestion of how to cook a dish that is deemed best for the user based on collected information.

[1556] An "online store" is a platform for selling products over the Internet.

[1557] A "purchase link" is a URL that a user can click to access an online store and purchase a specific product.

[1558] The system of the invention integrates user sentiment, weather data, and trends from social networking services to support optimal recipe suggestions and online ingredient purchasing. The main components of the system are a server, a user terminal, and a network interface.

[1559] First, the server collects current weather information (temperature, humidity, weather) using a climate data acquisition method. It uses a climate data API to obtain the necessary information and updates it in real time. This information is collected using existing climate data providers, such as the OpenWeatherMap API.

[1560] Next, we use the APIs of electronic communication platforms, such as Twitter API and Instagram API, to gather the latest food-related trend information. This allows us to understand what is currently trending and what food-related posts are popular.

[1561] The server also uses an emotion engine to recognize the user's emotions. It uses the smartphone's camera and microphone to capture the user's facial expressions and voice, and collects emotion data. This analysis utilizes emotion recognition technologies such as Google Cloud Vision API and Amazon Rekognition.

[1562] Based on the collected weather, social media, and emotion data, a generative AI model (e.g., GPT-4) is used to generate optimal recipes. These recipes are suggested to users based on prompt statements such as, "The user's emotion is stress, the current weather is 30 degrees, sunny, and the latest trend is smoothies. Please suggest the optimal recipe taking these into consideration."

[1563] A list of ingredients is created along with the recipe. The server then generates a purchase link from an online store based on this list. For example, the server can automatically create a purchase link for ingredients using an online store API such as Amazon MWS or Rakuten Market API.

[1564] The user device visually displays the generated recipe, ingredient list, and purchase link to the user. Users can view the recipe through the smartphone app and click the purchase link to go directly to the online store and easily purchase the necessary ingredients.

[1565] This system allows users to quickly find the best recipes based on weather conditions, social network trends, and their own emotions, and then efficiently purchase ingredients online.

[1566] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1567] Step 1:

[1568] The server acquires current weather information using the climate data acquisition means.

[1569] Input: User's location information

[1570] Data processing: Send a request to the climate data API to get the current temperature, humidity, and weather information

[1571] Output: Temperature, humidity, weather information

[1572] Specific behavior: Using the OpenWeatherMap API, make a request such as "GET https: / / api.openweathermap.org / data / 2.5 / weather?q=Tokyo&appid=your_api_key".

[1573] Step 2:

[1574] The server collects data for the electronic communication platform.

[1575] Enter: Food-related trending categories

[1576] Data processing: Send a request to the API of a social media platform to collect the latest food-related posts.

[1577] Output: Food-related trend information

[1578] What it does: Uses the Twitter API to make a request like "GET https: / / api.twitter.com / 2 / tweets / search / recent?query=food_trend".

[1579] Step 3:

[1580] The server uses an emotion engine to collect user emotion data.

[1581] Input: User facial expression video, audio data

[1582] Data processing: Send this data to the emotion recognition API to analyze emotions.

[1583] Output: Emotion data (e.g., stress, excitement, etc.)

[1584] What it does: Uses the Google Cloud Vision API to analyze a video or image and get an output such as "Emotion: Stress".

[1585] Step 4:

[1586] The server generates recommended recipes based on collected weather data, social media data, and emotional data.

[1587] Input: Climate data, social media data, sentiment data

[1588] Data processing: Input prompts into the generative AI model to generate optimal recipes

[1589] Output: Recommended recipes

[1590] Specific behavior: Send a prompt to a generative AI model such as GPT-4, such as "The user's emotion is stress, the current weather is 30 degrees and sunny, and the latest trend is smoothies. Please suggest the best recipe taking this into consideration."

[1591] Step 5:

[1592] The server generates a list of ingredients and a purchasing link based on the generated recipe.

[1593] Input: Recommended recipe

[1594] Data processing: Using the API of an online store, generate a purchase link based on the ingredients list

[1595] Output: Purchase link (URL)

[1596] Specific operation: Using the Amazon MWS API, make a request such as "POST https: / / api.example.com / cart / add" to obtain a purchase link.

[1597] Step 6:

[1598] The terminal visually displays the generated recipe, ingredient list, and purchase link to the user.

[1599] Input: Recommended recipe, purchase link

[1600] Data processing: Visual display through GUI

[1601] Output: Recipe information and links displayed to the user

[1602] What it does: The smartphone app displays the recipe name for "Relaxing Herbal Tea," along with the ingredients needed (e.g., chamomile, peppermint), and a link to purchase the recipe to the user.

[1603] Step 7:

[1604] Users click on the purchase link from their device and purchase the necessary ingredients from the online store.

[1605] Enter: Purchasing Link

[1606] Data processing: Open the link via your smartphone browser and access the online store

[1607] Output: Screen to complete the purchase process

[1608] What happens: When a user clicks on the purchase link, they are taken to the online store's website, where they can add the ingredients they need to their cart and complete the purchase.

[1609] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1610] 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.

[1611] 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 robot 414.

[1612] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1613] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1614] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1615] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1616] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1617] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1618] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1619] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1620] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1621] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1622] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1623] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1624] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1625] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1626] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1627] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1628] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1629] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1630] The following is further disclosed regarding the above embodiment.

[1631] (Claim 1)

[1632] a means for obtaining climate data;

[1633] A means of collecting data from social networking services;

[1634] A means for generating recommended recipes based on the collected data;

[1635] a means for displaying the generated recipe and a list of ingredients required;

[1636] A means for generating a purchasing link for an online supermarket;

[1637] A system including:

[1638] (Claim 2)

[1639] 10. The system of claim 1, wherein the collected climate data includes current temperature, humidity, and weather.

[1640] (Claim 3)

[1641] 2. The system according to claim 1, wherein the data collection means of the social networking service collects trends in food-related posts.

[1642] "Example 1"

[1643] (Claim 1)

[1644] a means for obtaining climate data;

[1645] A means of collecting information from social networking services;

[1646] A means for generating recommended recipes based on the collected information;

[1647] a means for displaying the generated recipe and a list of required ingredients;

[1648] a means for generating a purchasing link for an online grocery store;

[1649] A system including:

[1650] (Claim 2)

[1651] 10. The system of claim 1, wherein the collected climate data includes current temperature, humidity, and weather.

[1652] (Claim 3)

[1653] 2. The system according to claim 1, wherein the information gathering means of the social networking service gathers trends in food-related posts.

[1654] "Application Example 1"

[1655] (Claim 1)

[1656] a means for obtaining climate data;

[1657] A means of collecting data from social networking services;

[1658] A means for generating recommended recipes based on the collected data;

[1659] a means for displaying the generated recipe and a list of ingredients required;

[1660] means for generating an ordering link for a food delivery service;

[1661] A system including:

[1662] (Claim 2)

[1663] 10. The system of claim 1, wherein the collected climate data includes current temperature, humidity, and weather.

[1664] (Claim 3)

[1665] 2. The system according to claim 1, wherein the data collection means of the social networking service collects trends in food-related posts.

[1666] "Example 2: Combining Emotion Engines"

[1667] (Claim 1)

[1668] a means for obtaining climate data;

[1669] A means of collecting data from social networking services;

[1670] means for recognizing a user's emotion using an emotion engine;

[1671] A means for generating recommended recipes based on the collected data and the recognized emotions;

[1672] a means for displaying the generated recipe and a list of ingredients required;

[1673] A means for generating a purchasing link for an online supermarket;

[1674] A system including:

[1675] (Claim 2)

[1676] 10. The system of claim 1, wherein the collected climate data includes current temperature, humidity, and weather.

[1677] (Claim 3)

[1678] 2. The system according to claim 1, wherein the data collection means of the social networking service collects trends in food-related posts.

[1679] "Application example 2 when combining emotion engines"

[1680] (Claim 1)

[1681] a means for obtaining climate data;

[1682] means of collecting data on electronic communication platforms;

[1683] A means for generating recommended recipes based on the collected data;

[1684] a means for adjusting the recommended recipes based on the collected emotion data using an emotion engine that recognizes the user's emotions;

[1685] a means for displaying the generated recipe and a list of ingredients required;

[1686] means for generating a purchase link for an online store;

[1687] A system including:

[1688] (Claim 2)

[1689] 10. The system of claim 1, wherein the collected climate data includes current temperature, humidity, and weather.

[1690] (Claim 3)

[1691] 10. The system of claim 1, wherein the data collection means of the electronic communication platform collects trends in food-related posts. [Explanation of symbols]

[1692] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for obtaining climate data; A means of collecting data from social networking services; A means for generating recommended recipes based on the collected data; a means for displaying the generated recipe and a list of ingredients required; A means for generating a purchasing link for an online supermarket; A system including:

2. 10. The system of claim 1, wherein the collected climate data includes current temperature, humidity, and weather.

3. 2. The system according to claim 1, wherein the data collection means of the social networking service collects trends in food-related posts.

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