System

Abstract

A system is provided.SOLUTION: This system includes a means for acquiring stock information in a refrigerator, a means for acquiring physical condition data based on the analysis of excrement, a means for generating a dinner menu on the basis of the acquired stock information and physical condition data, a means for calculating necessary foodstuffs on the basis of the generated menu, and a means for automatically purchasing the necessary foodstuffs.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 modern society, it is difficult to find time to plan and prepare daily meals in the midst of busy daily life. Many people, especially those living alone or with families, face the problem of "What should I eat today?" Health management is also important, and maintaining a healthy diet requires providing meals tailored to each individual's physical condition. However, there are limited means to solve all of these problems at once, which is a burden for many people. This invention solves these problems and provides a system that makes it easy to maintain a healthy diet even during busy daily lives. [Means for solving the problem]

[0005] The present invention is a system that includes a means for acquiring refrigerator inventory information, a means for acquiring health data based on an analysis of excrement, a means for generating a dinner menu based on the acquired inventory information and health data, a means for calculating the necessary ingredients based on the generated menu, and a means for automatically purchasing the necessary ingredients. The system transmits the refrigerator inventory information and health data from a toilet sensor to an AI engine, and determines an appropriate menu based on the response from the AI ​​engine. Furthermore, by automatically purchasing the necessary ingredients using an online store's API, users can prepare healthy meals without any hassle. In this way, users can easily maintain a healthy diet even in their busy daily lives.

[0006] "Refrigerator inventory information" is data about the types and quantities of food and ingredients in the refrigerator.

[0007] "Physical condition data based on analysis of excrement" is information about the user's health condition obtained by analyzing the characteristics of the user's excrement.

[0008] The "means for generating a dinner menu" is a process or system for proposing a dinner menu suitable for the user based on the acquired inventory information and physical condition data.

[0009] The "means for calculating the necessary ingredients" is a process or system for calculating the types and amounts of ingredients necessary for cooking based on the generated dinner menu.

[0010] "Means for automatically purchasing required ingredients" means a process or system that automatically purchases ingredients using an online store or other purchasing means when identified required ingredients are in short supply.

[0011] An "AI engine" is software or algorithm that uses artificial intelligence to analyze input data and generate appropriate menus.

[0012] An "online store API" is an interface for accessing online store functions via web services, retrieving and updating data, and performing product purchase operations.

[0013] "Toilet Sensor" means a device installed in a toilet that detects and analyzes the characteristics of a user's waste.

[0014] The "Refrigerator Inventory API" is an application programming interface for obtaining inventory data of food and ingredients in a refrigerator. [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] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, creates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[0037] Get refrigerator inventory information

[0038] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[0039] Obtaining health data based on excrement analysis

[0040] The server sends a request to the Toilet Sensor API to retrieve the data sent by the Toilet Sensor. The characteristics of the excrement analyzed by the Toilet Sensor are provided in JSON format, indicating the user's current health status, including, for example, bowel movement frequency and water content.

[0041] Dinner menu generation

[0042] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine, which analyzes this data and generates an optimal dinner menu. The generated menu takes the user's physical condition into consideration, providing a healthy and balanced meal.

[0043] Calculate and automatically purchase ingredients needed

[0044] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[0045] Specific examples

[0046] scenario

[0047] User A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0048] tomato

[0049] chicken meat

[0050] lettuce

[0051] According to the user's toilet sensor, User A is suffering from constipation.

[0052] process

[0053] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[0054] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[0055] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[0056] {"Bow frequency": "Low", "Moisture": "Low"}

[0057] 3. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[0058] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[0059] 4. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[0060] In this way, User A can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator.

[0064] Step 2:

[0065] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content.

[0066] Step 3:

[0067] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The transmitted data includes inventory information and health data. The AI ​​engine uses this information to generate the optimal dinner menu.

[0068] Step 4:

[0069] The server receives the menu data returned by the AI ​​engine, which includes specific menu suggestions, such as "tomato and lettuce salad" or "grilled chicken."

[0070] Step 5:

[0071] The server calculates the ingredients needed to prepare the generated menu based on the received menu data, and checks the refrigerator's inventory to see which ingredients are in short supply.

[0072] Step 6:

[0073] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the ingredients needed. The server receives a response from the online store confirming that the order is complete.

[0074] Step 7:

[0075] The server sends the final menu and purchase results to the user's device, where the user can check today's dinner menu and whether the necessary ingredients are available. As a result, the user can prepare a healthy dinner without any hassle.

[0076] Example 1

[0077] 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."

[0078] Conventional refrigerator and health management systems often manage inventory and collect health data separately, which is insufficient for comprehensive health management. Furthermore, there were no systems that automatically generated dinner menus and automatically purchased the necessary ingredients, so users had to take the time and effort to plan their meals. Furthermore, there were no systems that properly notified users of this information and provided accurate menus, so users had to spend time and effort checking and preparing meals.

[0079] 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.

[0080] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for creating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the created menu, means for automatically purchasing the necessary ingredients, means for notifying the user's terminal of the acquired inventory information and physical condition data, and means for displaying the menu created based on the acquired inventory information and physical condition data. This allows the user to effortlessly plan a dinner menu and automatically purchase the necessary ingredients. Furthermore, the user can check the information in real time and receive support for living a healthy lifestyle.

[0081] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the types and quantities of food and ingredients in the refrigerator using sensors and cameras installed in the refrigerator.

[0082] The "means for acquiring health data based on analysis of excrement" is a means for collecting data on excrement from sensors installed in the toilet and acquiring health data on the user based on that data.

[0083] The "means for generating dinner menus" refers to a means for using an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information and health data.

[0084] The "means for calculating the necessary ingredients" is a means for identifying the necessary ingredients based on the generated dinner menu and calculating the ingredients that are lacking by checking against the inventory information.

[0085] "Means for automatically purchasing necessary ingredients" refers to a means for automatically purchasing ingredients that are in short supply using an online store's API.

[0086] The "means for notifying the user's terminal of the acquired inventory information and health data" refers to a means for notifying the user's terminal, such as a smartphone or tablet, of the inventory information and health data acquired by the server in real time.

[0087] The "means for displaying a menu created based on the acquired inventory information and physical condition data" is a means for displaying the dinner menu created by the server on the user's terminal.

[0088] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, generates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu generation means, an ingredient calculation means, an automatic purchasing means, a means for notifying the user of this information, and a means for displaying the generated menu. Specific operations will now be described.

[0089] The server sends a request to the refrigerator's inventory API to obtain data from sensors and cameras connected to the refrigerator. The sensors and cameras detect the type and quantity of food and ingredients in the refrigerator, structure that information in JSON format, and send it to the server. For example, if the sensor detects three tomatoes, one pack of chicken, and one lettuce, the following data is obtained:

[0090] json

[0091] {

[0092] "Tomato": 3,

[0093] "chicken": 1,

[0094] "Lettuce": 1

[0095] }

[0096] The server sends a request to the Toilet Sensor API to retrieve data sent from the Toilet Sensor. The Toilet Sensor analyzes the user's waste and provides the data in JSON format, including data such as bowel movement frequency and water content.

[0097] json

[0098] {

[0099] "Bowel frequency": "low",

[0100] "Moisture": "Low"

[0101] }

[0102] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. This menu takes the user's physical condition into consideration and provides healthy, balanced meals. For example, a menu rich in dietary fiber is generated for a user who tends to be constipated.

[0103] json

[0104] {

[0105] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[0106] }

[0107] Based on the generated menu, the server checks whether the necessary ingredients are available in the refrigerator. If any of the necessary ingredients are in short supply, the server automatically purchases them using the online store's API. The server sends the information about the necessary ingredients to the online store's API and executes the purchasing process. For example, if there is a shortage of chicken, the server orders the required amount of chicken from the online store.

[0108] The server then sends the acquired inventory information, health data, and the generated menu to the user's device, allowing the user to check the dinner menu on their smartphone or tablet and ensure that all the necessary ingredients have been prepared.

[0109] For example, user A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0110] tomato

[0111] chicken meat

[0112] lettuce

[0113] According to the user's toilet sensor, User A is slightly constipated. The server obtains this information and analyzes it with an AI engine, generating the optimal dinner menu of "tomato and lettuce salad" and "grilled chicken." Based on this, it is determined that the necessary ingredients are already present and no additional purchases are necessary.

[0114] As an example of input to the generative AI model, we will use the following prompt:

[0115] I'd like some suggestions for dinner using winter vegetables.

[0116] Generate healthy dinner menus based on your waste data.

[0117] Suggest a dish using the tomatoes, chicken, and lettuce in your fridge.

[0118] By using this prompt, users can get specific meal suggestions from the AI ​​model. This system is very useful for many users who lead busy daily lives.

[0119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0120] Step 1:

[0121] The server obtains data from sensors and cameras connected to the refrigerator. Specifically, the server sends a request to the refrigerator's inventory API to obtain information about the types and quantities of food and ingredients in the refrigerator. The input is the types and quantities of food and ingredients in the refrigerator, and the output is inventory information in JSON format. For example, the sensor detects three tomatoes, one pack of chicken, and one head of lettuce, and returns that information in JSON format.

[0122] json

[0123] {

[0124] "Tomato": 3,

[0125] "chicken": 1,

[0126] "Lettuce": 1

[0127] }

[0128] Step 2:

[0129] The server sends a request to the toilet sensor's API to obtain data sent from the toilet sensor. The toilet sensor analyzes the user's excrement and provides the data in JSON format. The input is excrement data, and the output is user health data. Specifically, this data includes bowel movement frequency and water content.

[0130] json

[0131] {

[0132] "Bowel frequency": "low",

[0133] "Moisture": "Low"

[0134] }

[0135] Step 3:

[0136] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The input is refrigerator inventory information and health data, and the output is the generated menu information. For example, a menu rich in dietary fiber can be generated for a user who is prone to constipation.

[0137] json

[0138] {

[0139] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[0140] }

[0141] Step 4:

[0142] The server checks whether the necessary ingredients are available in the refrigerator based on the generated menu. The input is the generated menu information and inventory information, and the output is a list of the necessary ingredients and their stock status. If a necessary ingredient is in short supply, the server automatically purchases it using the online store's API. For example, if chicken is in short supply, the server will order the required amount of chicken from the online store.

[0143] json

[0144] {

[0145] "order": "chicken"

[0146] }

[0147] Step 5:

[0148] The server notifies the terminal of the created menu and the information on ingredients that have been purchased. The input is the created menu information and the information on the completed purchase, and the output is a notification message sent to the user's terminal. This allows the user to confirm that the menu and the ingredients for it are available.

[0149] json

[0150] {

[0151] "notification": "Today's menu is 'Tomato and Lettuce Salad' and 'Grilled Chicken'. All the ingredients you need are here."

[0152] }

[0153] Through this process, users can effortlessly plan their dinner menu, automatically purchase the necessary ingredients, and prepare healthy meals. This system will significantly support users' daily lives.

[0154] (Application example 1)

[0155] 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."

[0156] In modern society, people are busy with work and daily life, making it difficult to easily prepare a healthy dinner. Managing refrigerator inventory and planning a meal plan that is appropriate for their physical condition can also take a lot of time and effort. Furthermore, the hassle of visiting a store to purchase the necessary ingredients can be a problem. There is a need for a system that can solve these issues and allow users to easily prepare a healthy, balanced dinner.

[0157] 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.

[0158] In this invention, the server includes means for acquiring inventory information from the refrigerator, means for acquiring physical condition data based on an analysis of excrement, means for generating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the generated menu, means for automatically purchasing the necessary ingredients, and means for integrating and managing meal suggestions and ingredient delivery services based on the generated menu and purchased ingredients. This allows users to easily obtain an optimal dinner menu based on the inventory information from the refrigerator and their physical condition, and any missing ingredients are automatically purchased and delivered, allowing them to enjoy healthy meals without any effort.

[0159] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the type and quantity of food in the refrigerator using sensors and cameras installed in the refrigerator.

[0160] "Means for obtaining health data based on analysis of excrement" refers to a means for analyzing the user's excrement using a sensor installed in the toilet and obtaining health data such as bowel movement frequency and water content.

[0161] The "means for generating dinner menus" refers to a means for using an AI engine to create optimal dinner menus based on the acquired refrigerator inventory information and health data.

[0162] The "means for calculating the necessary ingredients" is a means for calculating the shortage of ingredients in the refrigerator based on the generated menu, and determining the necessary ingredients.

[0163] "Means for automatically purchasing necessary ingredients" refers to a means for automatically ordering and purchasing necessary ingredients using the API of an online store or food delivery service.

[0164] The "means for integrated management of meal suggestions and ingredient delivery services" is a means for making meal suggestions to users based on the generated menu and purchased ingredients, and for centrally managing ingredient delivery.

[0165] MODE FOR CARRYING OUT THE INVENTION

[0166] The system of the present invention uses a smartphone application at its core to create an optimal dinner menu based on refrigerator inventory information and the user's physical condition data. It then automatically purchases the necessary ingredients and provides an integrated process of delivering them to the user via a food delivery service. The main processes involved in this system are described below.

[0167] Hardware and software used

[0168] Hardware:

[0169] Smartphone: Used as a user interface.

[0170] Refrigerator sensors and cameras: Used to obtain inventory information inside the refrigerator.

[0171] Toilet sensor: Used to analyze the user's waste and obtain health data.

[0172] software:

[0173] Server: The core of the application, acquiring, processing, and transmitting various data.

[0174] AI engine: Generates optimal dinner menus based on refrigerator inventory data and health data.

[0175] API: Handles data communication between the refrigerator sensor, toilet sensor, food delivery service and server.

[0176] Data processing and calculation

[0177] Get refrigerator inventory:

[0178] Data acquired from sensors and cameras installed in the refrigerator is sent to the server and interpreted in JSON format, including the type and quantity of food in the refrigerator.

[0179] Obtaining health data based on excrement analysis:

[0180] A sensor installed in the toilet analyzes the user's waste and sends the results, including bowel movement frequency and water content, to a server.

[0181] Dinner menu generation:

[0182] The server sends the acquired inventory information and health data to the AI ​​engine, which then analyzes this data and generates an optimal menu based on the user's health condition.

[0183] Calculate and auto-purchase ingredients needed:

[0184] The server calculates the ingredients needed based on the generated menu, and if any ingredients are not in the refrigerator, it automatically purchases them through the API of the food delivery service.

[0185] Meal suggestions and delivery management:

[0186] The server makes meal suggestions to the user based on the generated menu and purchased ingredient information, and also manages the ingredient delivery service in an integrated manner.

[0187] Specific examples

[0188] scenario

[0189] User A has a very busy job and does not want to spend too much time preparing dinner. User A has the following foods in his refrigerator:

[0190] tomato

[0191] chicken meat

[0192] lettuce

[0193] Additionally, data from the toilet sensor indicates that User A is constipated. Based on this information, the following prompt is generated:

[0194] "Here's what's in your refrigerator:

[0195] Tomato: 3, Chicken: 1, Lettuce: 1

[0196] Here is the user's health data:

[0197] Bowel frequency: "Low", moisture: "Low"

[0198] Based on this information, please suggest the perfect dinner menu for you.

[0199] Based on the acquired data, the AI ​​engine generates a menu including "tomato and lettuce salad" and "grilled chicken" and confirms the necessary ingredients. This system not only provides User A with the optimal dinner recommendation, but also automatically purchases and delivers the necessary ingredients, saving him a lot of time and effort.

[0200] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0201] Step 1:

[0202] Process to obtain refrigerator inventory information

[0203] The server obtains inventory information through sensors and cameras installed in the refrigerator. Specifically, it sends a request to the refrigerator's inventory API and receives JSON-formatted data including the type and quantity of food in the refrigerator. For example, this data includes "Tomatoes: 3, Chicken: 1, Lettuce: 1."

[0204] Input: Food information in the refrigerator

[0205] Output: Inventory information data in JSON format

[0206] Specific operation: The server sends a request to the refrigerator inventory API and structures the data obtained from the sensors and camera in JSON format.

[0207] Step 2:

[0208] Processing to obtain health data based on excrement analysis

[0209] The server obtains analysis data of excrement from sensors installed in the toilet. It sends a request to the toilet sensor's API and receives JSON-formatted data containing excrement characteristics. This data includes bowel movement frequency and water content, e.g., "Bow movement frequency: 'low', Water content: 'low'."

[0210] Input: fecal analysis data

[0211] Output: Physical condition data in JSON format

[0212] Specific operation: The server sends a request to the toilet sensor's API and structures the excrement analysis results obtained from the sensor in JSON format.

[0213] Step 3:

[0214] Process for generating dinner menus

[0215] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine and generates the optimal dinner menu. The prompt used is, "The user's refrigerator inventory information is as follows: Tomatoes: 3, Chicken: 1, Lettuce: 1. The user's health data is as follows: Bowel frequency: 'Low', Water content: 'Low'. Please suggest the optimal dinner menu based on this information."

[0216] Input: JSON format inventory information data and health data

[0217] Output: JSON format data containing menu items

[0218] Specific operation: The server sends data to the AI ​​engine and receives the API response generated as the analysis result.

[0219] Step 4:

[0220] Process to calculate the necessary ingredients

[0221] The server calculates the ingredients needed based on the generated menu, compares it with the inventory information in the refrigerator, and identifies any ingredients that are lacking. This process generates an automatic purchasing list of ingredients.

[0222] Input: Generated menu and inventory information

[0223] Output: List of ingredients needed

[0224] Specific operation: The server compares the menu with inventory information and creates a list of ingredients that are in short supply.

[0225] Step 5:

[0226] Automatically purchase the ingredients you need

[0227] The server automatically purchases ingredients using the API of the food delivery service based on the list of ingredients that are in short supply. It sends a request to the API of the food delivery service to order the necessary ingredients and process the delivery.

[0228] Input: Missing ingredients list

[0229] Output: Ingredient purchase completion data

[0230] Specific operation: The server sends a request to the food delivery service's API, processes the purchase, and completes the delivery procedure.

[0231] Step 6:

[0232] Process to suggest meals and manage delivery

[0233] The server makes meal suggestions to users based on the generated menu and purchased ingredient information, and manages the food delivery service in an integrated manner. It notifies users of the expected arrival date of ingredients and menu details.

[0234] Input: Generated menu and purchased ingredients information

[0235] Output: User notifications and administrative information

[0236] Specific operation: The server sends notifications to the user's smartphone and manages the status of the food delivery service.

[0237] 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.

[0238] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[0239] Get refrigerator inventory information

[0240] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[0241] Obtaining health data based on excrement analysis

[0242] The server sends a request to the toilet sensor's API to retrieve the data sent by the toilet sensor. The server receives the characteristics of the excrement analyzed by the toilet sensor in JSON format, which indicates the user's current health status, such as bowel movement frequency and water content.

[0243] User Emotion Recognition

[0244] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This emotion data indicates the user's emotional state (e.g., stress, joy, fatigue, etc.) and is reflected in the generation of dinner menus.

[0245] Dinner menu generation

[0246] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. The generated menu takes into account the user's physical condition and emotions, providing a healthy and balanced meal.

[0247] Calculate and automatically purchase ingredients needed

[0248] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[0249] Specific examples

[0250] scenario

[0251] User B is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0252] tomato

[0253] chicken meat

[0254] lettuce

[0255] According to the user's toilet sensor, User B is suffering from constipation. Furthermore, according to the emotion engine, User B is feeling stressed.

[0256] process

[0257] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[0258] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[0259] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[0260] {"Bow frequency": "Low", "Moisture": "Low"}

[0261] 3. The server obtains the user's emotional data using the emotion engine. As a result of the analysis, it finds out that User B is feeling stressed:

[0262] {"emotion": "stress"}

[0263] 4. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[0264] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[0265] 5. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[0266] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[0267] The processing flow will be explained below.

[0268] Step 1:

[0269] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator. For example, the server receives the following inventory information:

[0270] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[0271] Step 2:

[0272] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content. For example, the server receives the following health data:

[0273] {"Bow frequency": "Low", "Moisture": "Low"}

[0274] Step 3:

[0275] The server uses the emotion engine to analyze the user's facial expressions and voice to recognize the user's emotions. The server obtains the emotion data from the emotion engine and checks the user's emotional state. For example, the emotion engine returns the following data:

[0276] {"emotion": "stress"}

[0277] Step 4:

[0278] The server sends the acquired refrigerator inventory information, health data, and emotion data to the AI ​​engine. The transmitted data includes inventory information, health data, and emotion data. For example, the following data is transmitted:

[0279] {

[0280] "fridge_data": {"tomato": 3, "chicken": 1, "lettuce": 1},

[0281] "toilet_data": {"Defecation frequency": "Low", "Water": "Low"},

[0282] "emotion_data": {"emotion": "stress"}

[0283] }

[0284] Step 5:

[0285] The server receives the dinner menu data returned by the AI ​​engine. The AI ​​engine analyzes the data and generates the optimal dinner menu. For example, the server receives the following menu data:

[0286] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[0287] Step 6:

[0288] The server calculates the ingredients needed to make the generated menu based on the received menu data. The server checks the refrigerator's inventory information. For example, if all the necessary ingredients are in the refrigerator, the server will get the following result:

[0289] {"required_ingredients": [], "status": "all ingredients available"}

[0290] Step 7:

[0291] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the missing ingredients. If all ingredients are available, the server receives a result indicating that no additional purchases are necessary. For example, the server might receive a response like this:

[0292] {"purchase_status": "no purchase needed"}

[0293] Step 8:

[0294] The server sends the final menu and purchase results to the user's device. The user can then check today's dinner menu and whether the necessary ingredients are available. For example, the server provides the user with the following information:

[0295] {"Today's Dinner Menu": ["Tomato and Lettuce Salad", "Grilled Chicken"], "Purchase Result": "I have all the ingredients I need."}

[0296] In this way, users can prepare a healthy dinner without much effort.In addition, the introduction of an emotion engine will suggest optimal menus based on the user's emotional state, which will also help with maintaining physical and mental health.

[0297] Example 2

[0298] 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."

[0299] Conventional dinner menu suggestion systems often generate menus without considering the user's health or emotional state, making it difficult to suggest a menu that is optimal for each user's physical condition and psychological state. Furthermore, because ingredients are purchased based solely on refrigerator inventory, unnecessary ingredients may be purchased or an appropriate nutritional balance may not be ensured. Therefore, there is a need for a system that can improve users' health management and psychological satisfaction.

[0300] 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.

[0301] In this invention, the server includes a means for acquiring refrigerator inventory information, a means for acquiring physical condition data based on an analysis of excrement, and a means for acquiring emotional data. This makes it possible to generate a dinner menu based on the acquired inventory information, physical condition data, and emotional data. Specifically, an AI engine is used to analyze various data, suggest an optimal menu for the user, and automatically purchase any missing ingredients using an online store's API, thereby achieving personalized support based on the user's health and emotional state.

[0302] A "means for acquiring inventory information in a refrigerator" is a device or system that uses sensors or cameras installed in the refrigerator to detect the type and quantity of food or ingredients in the refrigerator and acquires that data.

[0303] A "means for acquiring health data based on analysis of excrement" is a device or system that uses sensors or analytical devices connected to the toilet to analyze the characteristics of excrement and acquire data on the user's health condition.

[0304] The "means for acquiring emotional data" is a device or system that acquires data relating to the emotional state of a user using an emotion recognition engine that analyzes the user's facial expressions and voice.

[0305] The "means for generating dinner menus" refers to a device or system that uses an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information, physical condition data, and emotional data.

[0306] The "means for calculating the necessary ingredients" is a device or system that calculates the number of necessary ingredients based on the generated menu and in conjunction with the inventory information in the refrigerator.

[0307] A "means for automatically purchasing the necessary ingredients" is a device or system that uses the online store's API to automatically order the necessary ingredients and complete the purchase process.

[0308] The phrase "the means for generating a dinner menu transmits the acquired inventory information, physical condition data, and emotional data to the AI ​​engine" means that information about ingredients in the user's refrigerator, the user's health condition, and emotional state are provided to the AI ​​engine.

[0309] The phrase "purchase the necessary ingredients using the online store's API" means automatically ordering the missing ingredients using the online store's application program interface and completing the delivery procedure.

[0310] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means.

[0311] Get refrigerator inventory information

[0312] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator. The retrieved inventory data is structured in JSON format and indicates the types and quantities of food and ingredients present in the refrigerator. For example, the server sends an HTTP request to the refrigerator API, and the refrigerator API returns inventory data to the server. This data is stored on the server and used in the processes described below.

[0313] Obtaining health data based on excrement analysis

[0314] The server sends a request to the toilet sensor's API to retrieve data sent from the toilet sensor. Health data based on the characteristics of excrement provided by the toilet sensor is also provided to the server in JSON format. The server retrieves this data and stores the analysis results on the server.

[0315] User Emotion Recognition

[0316] The server recognizes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice via a webcam or microphone to generate emotion data. The emotion engine generates data indicating the user's emotional state (e.g., stress, joy, fatigue, etc.) and provides it to the server. The server stores this data.

[0317] Dinner menu generation

[0318] The server sends this acquired information (refrigerator inventory information, physical condition data, and emotional data) to the AI ​​engine, which then generates an optimal dinner menu. The AI ​​engine analyzes this data and proposes a balanced and healthy dinner menu. The generated menu takes into account the user's physical condition and emotions, and is presented to the user by the server.

[0319] Calculate and automatically purchase ingredients needed

[0320] The server checks whether the necessary ingredients based on the generated menu are available in the refrigerator. If necessary ingredients are not available, the server automatically purchases them using the online store's API. The online store API orders the necessary ingredients and executes the purchase process.

[0321] Specific examples

[0322] scenario

[0323] User B is busy at work and doesn't have time to prepare dinner tonight. There are tomatoes, chicken, and lettuce in the refrigerator. According to the toilet sensor, User B is constipated. Furthermore, according to the emotion engine, User B is feeling stressed.

[0324] process

[0325] The server retrieves inventory information via the refrigerator API, resulting in the following data:

[0326] Tomato: 3

[0327] Chicken: 1

[0328] Lettuce: 1

[0329] The server receives data from the toilet sensor and analyzes it to find out that the user is constipated:

[0330] Bowel movement frequency: Low

[0331] Moisture: low

[0332] The server obtains the user's emotional data using the emotion engine, and as a result of the analysis, it obtains information that User B is feeling stressed:

[0333] Emotion: Stress

[0334] The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken":

[0335] menu: [ "Tomato and lettuce salad", "Grilled chicken" ]

[0336] The server will check the ingredients needed based on the menu, and since all ingredients are already in the refrigerator, no additional purchases are necessary.

[0337] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[0338] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0339] Step 1:

[0340] Get refrigerator inventory information

[0341] The server sends a request to the refrigerator's inventory API to retrieve inventory data from sensors and cameras connected to the refrigerator. This request uses the HTTP GET method, and the refrigerator API returns data in JSON format. The input includes the current status of food and ingredients in the refrigerator, and the output is inventory data in JSON format. This data is stored in a database on the server and used for subsequent processing.

[0342] Specific behavior:

[0343] 1. The server generates an HTTP request and sends it to the refrigerator inventory API.

[0344] 2. The refrigerator API receives the request and sends the inventory data back to the server in JSON format.

[0345] 3. The server stores the received JSON data in the database.

[0346] Step 2:

[0347] Obtaining health data based on excrement analysis

[0348] The server sends a request to the Toilet Sensor API to retrieve the excrement data sent from the Toilet Sensor. This request also uses the HTTP GET method. The Toilet Sensor API returns excrement characteristic data in JSON format. The input contains the user's excrement data, and the output is analyzed health data. This data is also stored in the server's database.

[0349] Specific behavior:

[0350] 1. The server generates an HTTP request and sends it to the Toilet Sensor API.

[0351] 2. The Toilet Sensor API receives the request and returns the excrement data in JSON format to the server.

[0352] 3. The server analyzes the received data and stores it in a database.

[0353] Step 3:

[0354] Obtaining user emotion data

[0355] The server uses an emotion engine to obtain emotion data from the user's facial expressions and voice. To do this, the server sends data obtained from a webcam or microphone to the emotion engine and receives the analysis results. The input includes images of the user's facial expressions and voice data, and the output is data indicating the user's emotional state. This data is also stored in a database.

[0356] Specific behavior:

[0357] 1. The server acquires the user's facial expression images and voice data.

[0358] 2. The server sends these data to the emotion engine.

[0359] 3. The emotion engine analyzes the data and sends data indicating the emotional state back to the server.

[0360] 4. The server stores the received data in a database.

[0361] Step 4:

[0362] Generate a dinner menu

[0363] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The inputs include inventory information, physical condition data, and emotional data, and the output is menu data. The generated menu is notified to the user by the server.

[0364] Specific behavior:

[0365] 1. The server sends refrigerator inventory information, health data, and emotional data to the AI ​​engine.

[0366] 2. The AI ​​engine analyzes this data and generates the optimal dinner menu.

[0367] 3. The server receives the generated menu data and notifies the user.

[0368] Step 5:

[0369] Calculate and automatically purchase ingredients needed

[0370] The server checks whether the refrigerator has all the necessary ingredients based on the generated menu. If any ingredients are missing, the server automatically purchases them using the online store's API. The inputs include menu data and inventory data, and the output is a list of missing ingredients and a purchase procedure.

[0371] Specific behavior:

[0372] 1. The server compares the generated menu with the inventory information in the refrigerator and lists the necessary ingredients.

[0373] 2. If any ingredients are missing, the server sends a request to the online store API to purchase the ingredients.

[0374] 3. The server receives the results of the purchase and stores them in a database.

[0375] (Application example 2)

[0376] 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."

[0377] In today's busy lifestyles, it is difficult for users to easily prepare healthy, balanced meals. Furthermore, it takes time and effort to check and purchase each ingredient needed for meal preparation, and it is even more difficult to consider the user's physical condition and emotions. This often leads to inadequate nutrition and makes it difficult to maintain health. Even when users shop in physical stores, efficiently gathering the necessary ingredients is extremely time-consuming. To solve these problems, there is a need for an automatic menu generation and ingredient purchasing support system that takes into account the user's health and emotions.

[0378] 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.

[0379] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for recognizing the user's facial expression and acquiring emotional data, means for generating a dinner menu based on the acquired inventory information, physical condition data, and emotional data, means for calculating the necessary ingredients based on the generated menu, and means for automatically purchasing the necessary ingredients. This enables the preparation of healthy and balanced meals that take the user's physical condition and emotions into consideration. Furthermore, automating the purchase of necessary ingredients significantly reduces the effort and time required for shopping. Furthermore, when a user is shopping in a physical store, the in-store map API can be used to efficiently guide the user to the necessary ingredients.

[0380] "Refrigerator inventory information" refers to information about the types and quantities of food and ingredients stored in the refrigerator.

[0381] "Physical condition data" is data relating to the health condition of the user obtained based on an analysis of the user's excrement.

[0382] "Emotion data" is data that indicates the emotional state of the user recognized by analyzing the user's facial expressions and voice.

[0383] The "means for generating a menu" is a means for calculating an optimal dinner menu based on the acquired inventory information, physical condition data, and emotion data.

[0384] The "means for calculating the necessary ingredients" refers to a means for identifying the necessary ingredients based on the generated menu by checking against the inventory information in the refrigerator and calculating the shortage.

[0385] "Means for automatic purchasing" refers to means for automatically purchasing or providing guidance on the necessary ingredients using the online store's API or in-store map API.

[0386] The "Store Map API" is an API that provides a guide for users to efficiently find the ingredients they need in physical stores.

[0387] The system for implementing this invention acquires refrigerator inventory information, analyzes the user's waste to acquire health data, and recognizes the user's facial expressions to acquire emotional data, then creates an optimal dinner menu based on this information, calculates the necessary ingredients, and automatically purchases the necessary ingredients.

[0388] This system consists of a means for acquiring data from sensors and cameras placed in the refrigerator, a means for acquiring data from sensors installed in the toilet, a means for recognizing the user's facial expressions using a camera on a smartphone or smart glasses, a means for generating menus using an AI engine based on this data, a means for calculating the necessary ingredients based on the generated menu, and a means for automatically purchasing or providing guidance on the necessary ingredients using an online store API or an in-store map API.

[0389] For example, when a user goes shopping at a physical store, the system first obtains inventory information from a sensor connected to the refrigerator. This data is sent to the server in JSON format, and the types and quantities of food and ingredients in the refrigerator are identified. Next, data is obtained from the toilet sensor and the user's physical condition data is analyzed. This provides the user's health status, such as bowel movement frequency and water content. Furthermore, the system captures the user's facial expressions using a camera on a smartphone or smart glasses, and obtains the user's emotional data through an emotion engine. Emotional data includes information such as the stress, joy, and fatigue the user is feeling.

[0390] This data is sent to an AI engine to generate an optimal dinner menu. The generated menu is healthy and balanced, taking into account the user's physical condition and emotions. The system then calculates the ingredients needed based on the generated menu and checks it against the inventory information in the refrigerator to identify any shortages. The system uses the online store's API to automatically purchase the necessary ingredients. When the user makes a purchase in a physical store, the system also uses the in-store map API to guide them to the location of product shelves.

[0391] As a concrete example, consider the case where User A is shopping at a supermarket. There are tomatoes, chicken, and lettuce in the refrigerator, but User A is feeling constipated and a little stressed. The system sends this information to the AI ​​engine, which suggests "tomato and lettuce salad" and "grilled chicken" as the optimal menu. It then uses the in-store map API to guide User A to the specific shelf locations where he should purchase the salad and chicken.

[0392] Examples of prompts include:

[0393] 1. Get the latest inventory data from the refrigerator API.

[0394] 2. Get the user's latest health data from the health management app API.

[0395] 3. Capture the user's facial expressions with the camera and use the emotion engine to obtain emotion data.

[0396] 4. Use the AI ​​engine to suggest the best products based on the inventory, health, and emotion data you have acquired.

[0397] 5. Use Maps API to show the location of the suggested products in the store.

[0398] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0399] Step 1:

[0400] The server obtains inventory information from sensors and cameras connected to the refrigerator.

[0401] Input: Data from refrigerator inventory sensors and cameras

[0402] Data processing: Convert to JSON format

[0403] Output: Data on the type and quantity of food and ingredients in the refrigerator

[0404] Specific operation: The server sends a request to the refrigerator inventory API and parses the retrieved data in JSON format.

[0405] Step 2:

[0406] The server acquires the data sent from the toilet sensor and analyzes the user's physical condition data.

[0407] Input: Excrement data from toilet sensor

[0408] Data processing: Convert to JSON format

[0409] Output: User's health data such as bowel movement frequency and water content

[0410] Specific operation: The server sends a request to the toilet sensor's API and parses the acquired data in JSON format.

[0411] Step 3:

[0412] The device captures the user's facial expressions using a camera on a smartphone or smart glasses and obtains emotional data through an emotion engine.

[0413] Input: Image data from a smartphone or smart glasses camera

[0414] Data processing: Generating emotion data through facial expression analysis

[0415] Output: Emotional data such as stress, joy, fatigue, etc.

[0416] Specific operation: The device captures the user's facial expressions with a camera and sends the data to the emotion engine to obtain analysis results.

[0417] Step 4:

[0418] The server sends the acquired inventory information, health data, and emotional data to the AI ​​engine to generate a dinner menu.

[0419] Input: inventory data, physical condition data, emotional data

[0420] Data processing: Menu generation using AI models

[0421] Output: Optimal dinner menu

[0422] Specific operation: The server sends this data to the AI ​​engine as a single request and receives menu suggestions.

[0423] Step 5:

[0424] The server calculates the ingredients needed based on the generated menu and identifies any ingredients that are lacking.

[0425] Input: Menu data, inventory data

[0426] Data processing: Checking against inventory data and identifying shortages

[0427] Output: List of ingredients needed

[0428] Specific operation: The server compares the ingredients required for the generated menu with the inventory in the refrigerator and lists the necessary ingredients.

[0429] Step 6:

[0430] The server automatically purchases the necessary ingredients through an online store API, or when the user purchases at a physical store, it uses an in-store map API to guide the user to the location within the store.

[0431] Input: List of ingredients needed

[0432] Data processing: Data generation for purchase requests or location guidance

[0433] Output: Purchase instructions for online stores or in-store location guidance

[0434] Specific operation: The server sends the necessary ingredient information to the online store API and automatically purchases it. If the user purchases at a physical store, the server uses the store's map API to guide the user to the location of the necessary ingredients.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] [Second embodiment]

[0439] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0440] 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.

[0441] 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).

[0442] 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.

[0443] 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.

[0444] 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).

[0445] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] In the smart glasses 214, 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.

[0450] 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."

[0451] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, creates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[0452] Get refrigerator inventory information

[0453] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[0454] Obtaining health data based on excrement analysis

[0455] The server sends a request to the Toilet Sensor API to retrieve the data sent by the Toilet Sensor. The characteristics of the excrement analyzed by the Toilet Sensor are provided in JSON format, indicating the user's current health status, including, for example, bowel movement frequency and water content.

[0456] Dinner menu generation

[0457] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine, which analyzes this data and generates an optimal dinner menu. The generated menu takes the user's physical condition into consideration, providing a healthy and balanced meal.

[0458] Calculate and automatically purchase ingredients needed

[0459] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[0460] Specific examples

[0461] scenario

[0462] User A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0463] tomato

[0464] chicken meat

[0465] lettuce

[0466] According to the user's toilet sensor, User A is suffering from constipation.

[0467] process

[0468] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[0469] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[0470] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[0471] {"Bow frequency": "Low", "Moisture": "Low"}

[0472] 3. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[0473] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[0474] 4. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[0475] In this way, User A can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives.

[0476] The processing flow will be explained below.

[0477] Step 1:

[0478] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator.

[0479] Step 2:

[0480] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content.

[0481] Step 3:

[0482] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The transmitted data includes inventory information and health data. The AI ​​engine uses this information to generate the optimal dinner menu.

[0483] Step 4:

[0484] The server receives the menu data returned by the AI ​​engine, which includes specific menu suggestions, such as "tomato and lettuce salad" or "grilled chicken."

[0485] Step 5:

[0486] The server calculates the ingredients needed to prepare the generated menu based on the received menu data, and checks the refrigerator's inventory to see which ingredients are in short supply.

[0487] Step 6:

[0488] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the ingredients needed. The server receives a response from the online store confirming that the order is complete.

[0489] Step 7:

[0490] The server sends the final menu and purchase results to the user's device, where the user can check today's dinner menu and whether the necessary ingredients are available. As a result, the user can prepare a healthy dinner without any hassle.

[0491] Example 1

[0492] 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."

[0493] Conventional refrigerator and health management systems often manage inventory and collect health data separately, which is insufficient for comprehensive health management. Furthermore, there were no systems that automatically generated dinner menus and automatically purchased the necessary ingredients, so users had to take the time and effort to plan their meals. Furthermore, there were no systems that properly notified users of this information and provided accurate menus, so users had to spend time and effort checking and preparing meals.

[0494] 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.

[0495] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for creating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the created menu, means for automatically purchasing the necessary ingredients, means for notifying the user's terminal of the acquired inventory information and physical condition data, and means for displaying the menu created based on the acquired inventory information and physical condition data. This allows the user to effortlessly plan a dinner menu and automatically purchase the necessary ingredients. Furthermore, the user can check the information in real time and receive support for living a healthy lifestyle.

[0496] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the types and quantities of food and ingredients in the refrigerator using sensors and cameras installed in the refrigerator.

[0497] The "means for acquiring health data based on analysis of excrement" is a means for collecting data on excrement from sensors installed in the toilet and acquiring health data on the user based on that data.

[0498] The "means for generating dinner menus" refers to a means for using an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information and health data.

[0499] The "means for calculating the necessary ingredients" is a means for identifying the necessary ingredients based on the generated dinner menu and calculating the ingredients that are lacking by checking against the inventory information.

[0500] "Means for automatically purchasing necessary ingredients" refers to a means for automatically purchasing ingredients that are in short supply using an online store's API.

[0501] The "means for notifying the user's terminal of the acquired inventory information and health data" refers to a means for notifying the user's terminal, such as a smartphone or tablet, of the inventory information and health data acquired by the server in real time.

[0502] The "means for displaying a menu created based on the acquired inventory information and physical condition data" is a means for displaying the dinner menu created by the server on the user's terminal.

[0503] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, generates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu generation means, an ingredient calculation means, an automatic purchasing means, a means for notifying the user of this information, and a means for displaying the generated menu. Specific operations will now be described.

[0504] The server sends a request to the refrigerator's inventory API to obtain data from sensors and cameras connected to the refrigerator. The sensors and cameras detect the type and quantity of food and ingredients in the refrigerator, structure that information in JSON format, and send it to the server. For example, if the sensor detects three tomatoes, one pack of chicken, and one lettuce, the following data is obtained:

[0505] json

[0506] {

[0507] "Tomato": 3,

[0508] "chicken": 1,

[0509] "Lettuce": 1

[0510] }

[0511] The server sends a request to the Toilet Sensor API to retrieve data sent from the Toilet Sensor. The Toilet Sensor analyzes the user's waste and provides the data in JSON format, including data such as bowel movement frequency and water content.

[0512] json

[0513] {

[0514] "Bowel frequency": "low",

[0515] "Moisture": "Low"

[0516] }

[0517] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. This menu takes the user's physical condition into consideration and provides healthy, balanced meals. For example, a menu rich in dietary fiber is generated for a user who tends to be constipated.

[0518] json

[0519] {

[0520] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[0521] }

[0522] Based on the generated menu, the server checks whether the necessary ingredients are available in the refrigerator. If any of the necessary ingredients are in short supply, the server automatically purchases them using the online store's API. The server sends the information about the necessary ingredients to the online store's API and executes the purchasing process. For example, if there is a shortage of chicken, the server orders the required amount of chicken from the online store.

[0523] The server then sends the acquired inventory information, health data, and the generated menu to the user's device, allowing the user to check the dinner menu on their smartphone or tablet and ensure that all the necessary ingredients have been prepared.

[0524] For example, user A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0525] tomato

[0526] chicken meat

[0527] lettuce

[0528] According to the user's toilet sensor, User A is slightly constipated. The server obtains this information and analyzes it with an AI engine, generating the optimal dinner menu of "tomato and lettuce salad" and "grilled chicken." Based on this, it is determined that the necessary ingredients are already present and no additional purchases are necessary.

[0529] As an example of input to the generative AI model, we will use the following prompt:

[0530] I'd like some suggestions for dinner using winter vegetables.

[0531] Generate healthy dinner menus based on your waste data.

[0532] Suggest a dish using the tomatoes, chicken, and lettuce in your fridge.

[0533] By using this prompt, users can get specific meal suggestions from the AI ​​model. This system is very useful for many users who lead busy daily lives.

[0534] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0535] Step 1:

[0536] The server obtains data from sensors and cameras connected to the refrigerator. Specifically, the server sends a request to the refrigerator's inventory API to obtain information about the types and quantities of food and ingredients in the refrigerator. The input is the types and quantities of food and ingredients in the refrigerator, and the output is inventory information in JSON format. For example, the sensor detects three tomatoes, one pack of chicken, and one head of lettuce, and returns that information in JSON format.

[0537] json

[0538] {

[0539] "Tomato": 3,

[0540] "chicken": 1,

[0541] "Lettuce": 1

[0542] }

[0543] Step 2:

[0544] The server sends a request to the toilet sensor's API to obtain data sent from the toilet sensor. The toilet sensor analyzes the user's excrement and provides the data in JSON format. The input is excrement data, and the output is user health data. Specifically, this data includes bowel movement frequency and water content.

[0545] json

[0546] {

[0547] "Bowel frequency": "low",

[0548] "Moisture": "Low"

[0549] }

[0550] Step 3:

[0551] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The input is refrigerator inventory information and health data, and the output is the generated menu information. For example, a menu rich in dietary fiber can be generated for a user who is prone to constipation.

[0552] json

[0553] {

[0554] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[0555] }

[0556] Step 4:

[0557] The server checks whether the necessary ingredients are available in the refrigerator based on the generated menu. The input is the generated menu information and inventory information, and the output is a list of the necessary ingredients and their stock status. If a necessary ingredient is in short supply, the server automatically purchases it using the online store's API. For example, if chicken is in short supply, the server will order the required amount of chicken from the online store.

[0558] json

[0559] {

[0560] "order": "chicken"

[0561] }

[0562] Step 5:

[0563] The server notifies the terminal of the created menu and the information on ingredients that have been purchased. The input is the created menu information and the information on the completed purchase, and the output is a notification message sent to the user's terminal. This allows the user to confirm that the menu and the ingredients for it are available.

[0564] json

[0565] {

[0566] "notification": "Today's menu is 'Tomato and Lettuce Salad' and 'Grilled Chicken'. All the ingredients you need are here."

[0567] }

[0568] Through this process, users can effortlessly plan their dinner menu, automatically purchase the necessary ingredients, and prepare healthy meals. This system will significantly support users' daily lives.

[0569] (Application example 1)

[0570] 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."

[0571] In modern society, people are busy with work and daily life, making it difficult to easily prepare a healthy dinner. Managing refrigerator inventory and planning a meal plan that is appropriate for their physical condition can also take a lot of time and effort. Furthermore, the hassle of visiting a store to purchase the necessary ingredients can be a problem. There is a need for a system that can solve these issues and allow users to easily prepare a healthy, balanced dinner.

[0572] 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.

[0573] In this invention, the server includes means for acquiring inventory information from the refrigerator, means for acquiring physical condition data based on an analysis of excrement, means for generating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the generated menu, means for automatically purchasing the necessary ingredients, and means for integrating and managing meal suggestions and ingredient delivery services based on the generated menu and purchased ingredients. This allows users to easily obtain an optimal dinner menu based on the inventory information from the refrigerator and their physical condition, and any missing ingredients are automatically purchased and delivered, allowing them to enjoy healthy meals without any effort.

[0574] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the type and quantity of food in the refrigerator using sensors and cameras installed in the refrigerator.

[0575] "Means for obtaining health data based on analysis of excrement" refers to a means for analyzing the user's excrement using a sensor installed in the toilet and obtaining health data such as bowel movement frequency and water content.

[0576] The "means for generating dinner menus" refers to a means for using an AI engine to create optimal dinner menus based on the acquired refrigerator inventory information and health data.

[0577] The "means for calculating the necessary ingredients" is a means for calculating the shortage of ingredients in the refrigerator based on the generated menu, and determining the necessary ingredients.

[0578] "Means for automatically purchasing necessary ingredients" refers to a means for automatically ordering and purchasing necessary ingredients using the API of an online store or food delivery service.

[0579] The "means for integrated management of meal suggestions and ingredient delivery services" is a means for making meal suggestions to users based on the generated menu and purchased ingredients, and for centrally managing ingredient delivery.

[0580] MODE FOR CARRYING OUT THE INVENTION

[0581] The system of the present invention uses a smartphone application at its core to create an optimal dinner menu based on refrigerator inventory information and the user's physical condition data. It then automatically purchases the necessary ingredients and provides an integrated process of delivering them to the user via a food delivery service. The main processes involved in this system are described below.

[0582] Hardware and software used

[0583] Hardware:

[0584] Smartphone: Used as a user interface.

[0585] Refrigerator sensors and cameras: Used to obtain inventory information inside the refrigerator.

[0586] Toilet sensor: Used to analyze the user's waste and obtain health data.

[0587] software:

[0588] Server: The core of the application, acquiring, processing, and transmitting various data.

[0589] AI engine: Generates optimal dinner menus based on refrigerator inventory data and health data.

[0590] API: Handles data communication between the refrigerator sensor, toilet sensor, food delivery service and server.

[0591] Data processing and calculation

[0592] Get refrigerator inventory:

[0593] Data acquired from sensors and cameras installed in the refrigerator is sent to the server and interpreted in JSON format, including the type and quantity of food in the refrigerator.

[0594] Obtaining health data based on excrement analysis:

[0595] A sensor installed in the toilet analyzes the user's waste and sends the results, including bowel movement frequency and water content, to a server.

[0596] Dinner menu generation:

[0597] The server sends the acquired inventory information and health data to the AI ​​engine, which then analyzes this data and generates an optimal menu based on the user's health condition.

[0598] Calculate and auto-purchase ingredients needed:

[0599] The server calculates the ingredients needed based on the generated menu, and if any ingredients are not in the refrigerator, it automatically purchases them through the API of the food delivery service.

[0600] Meal suggestions and delivery management:

[0601] The server makes meal suggestions to the user based on the generated menu and purchased ingredient information, and also manages the ingredient delivery service in an integrated manner.

[0602] Specific examples

[0603] scenario

[0604] User A has a very busy job and does not want to spend too much time preparing dinner. User A has the following foods in his refrigerator:

[0605] tomato

[0606] chicken meat

[0607] lettuce

[0608] Additionally, data from the toilet sensor indicates that User A is constipated. Based on this information, the following prompt is generated:

[0609] "Here's what's in your refrigerator:

[0610] Tomato: 3, Chicken: 1, Lettuce: 1

[0611] Here is the user's health data:

[0612] Bowel frequency: "Low", moisture: "Low"

[0613] Based on this information, please suggest the perfect dinner menu for you.

[0614] Based on the acquired data, the AI ​​engine generates a menu including "tomato and lettuce salad" and "grilled chicken" and confirms the necessary ingredients. This system not only provides User A with the optimal dinner recommendation, but also automatically purchases and delivers the necessary ingredients, saving him a lot of time and effort.

[0615] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0616] Step 1:

[0617] Process to obtain refrigerator inventory information

[0618] The server obtains inventory information through sensors and cameras installed in the refrigerator. Specifically, it sends a request to the refrigerator's inventory API and receives JSON-formatted data including the type and quantity of food in the refrigerator. For example, this data includes "Tomatoes: 3, Chicken: 1, Lettuce: 1."

[0619] Input: Food information in the refrigerator

[0620] Output: Inventory information data in JSON format

[0621] Specific operation: The server sends a request to the refrigerator inventory API and structures the data obtained from the sensors and camera in JSON format.

[0622] Step 2:

[0623] Processing to obtain health data based on excrement analysis

[0624] The server obtains analysis data of excrement from sensors installed in the toilet. It sends a request to the toilet sensor's API and receives JSON-formatted data containing excrement characteristics. This data includes bowel movement frequency and water content, e.g., "Bow movement frequency: 'low', Water content: 'low'."

[0625] Input: fecal analysis data

[0626] Output: Physical condition data in JSON format

[0627] Specific operation: The server sends a request to the toilet sensor's API and structures the excrement analysis results obtained from the sensor in JSON format.

[0628] Step 3:

[0629] Process for generating dinner menus

[0630] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine and generates the optimal dinner menu. The prompt used is, "The user's refrigerator inventory information is as follows: Tomatoes: 3, Chicken: 1, Lettuce: 1. The user's health data is as follows: Bowel frequency: 'Low', Water content: 'Low'. Please suggest the optimal dinner menu based on this information."

[0631] Input: JSON format inventory information data and health data

[0632] Output: JSON format data containing menu items

[0633] Specific operation: The server sends data to the AI ​​engine and receives the API response generated as the analysis result.

[0634] Step 4:

[0635] Process to calculate the necessary ingredients

[0636] The server calculates the ingredients needed based on the generated menu, compares it with the inventory information in the refrigerator, and identifies any ingredients that are lacking. This process generates an automatic purchasing list of ingredients.

[0637] Input: Generated menu and inventory information

[0638] Output: List of ingredients needed

[0639] Specific operation: The server compares the menu with inventory information and creates a list of ingredients that are in short supply.

[0640] Step 5:

[0641] Automatically purchase the ingredients you need

[0642] The server automatically purchases ingredients using the API of the food delivery service based on the list of ingredients that are in short supply. It sends a request to the API of the food delivery service to order the necessary ingredients and process the delivery.

[0643] Input: Missing ingredients list

[0644] Output: Ingredient purchase completion data

[0645] Specific operation: The server sends a request to the food delivery service's API, processes the purchase, and completes the delivery procedure.

[0646] Step 6:

[0647] Process to suggest meals and manage delivery

[0648] The server makes meal suggestions to users based on the generated menu and purchased ingredient information, and manages the food delivery service in an integrated manner. It notifies users of the expected arrival date of ingredients and menu details.

[0649] Input: Generated menu and purchased ingredients information

[0650] Output: User notifications and administrative information

[0651] Specific operation: The server sends notifications to the user's smartphone and manages the status of the food delivery service.

[0652] 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.

[0653] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[0654] Get refrigerator inventory information

[0655] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[0656] Obtaining health data based on excrement analysis

[0657] The server sends a request to the toilet sensor's API to retrieve the data sent by the toilet sensor. The server receives the characteristics of the excrement analyzed by the toilet sensor in JSON format, which indicates the user's current health status, such as bowel movement frequency and water content.

[0658] User Emotion Recognition

[0659] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This emotion data indicates the user's emotional state (e.g., stress, joy, fatigue, etc.) and is reflected in the generation of dinner menus.

[0660] Dinner menu generation

[0661] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. The generated menu takes into account the user's physical condition and emotions, providing a healthy and balanced meal.

[0662] Calculate and automatically purchase ingredients needed

[0663] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[0664] Specific examples

[0665] scenario

[0666] User B is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0667] tomato

[0668] chicken meat

[0669] lettuce

[0670] According to the user's toilet sensor, User B is suffering from constipation. Furthermore, according to the emotion engine, User B is feeling stressed.

[0671] process

[0672] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[0673] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[0674] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[0675] {"Bow frequency": "Low", "Moisture": "Low"}

[0676] 3. The server obtains the user's emotional data using the emotion engine. As a result of the analysis, it finds out that User B is feeling stressed:

[0677] {"emotion": "stress"}

[0678] 4. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[0679] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[0680] 5. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[0681] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[0682] The processing flow will be explained below.

[0683] Step 1:

[0684] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator. For example, the server receives the following inventory information:

[0685] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[0686] Step 2:

[0687] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content. For example, the server receives the following health data:

[0688] {"Bow frequency": "Low", "Moisture": "Low"}

[0689] Step 3:

[0690] The server uses the emotion engine to analyze the user's facial expressions and voice to recognize the user's emotions. The server obtains the emotion data from the emotion engine and checks the user's emotional state. For example, the emotion engine returns the following data:

[0691] {"emotion": "stress"}

[0692] Step 4:

[0693] The server sends the acquired refrigerator inventory information, health data, and emotion data to the AI ​​engine. The transmitted data includes inventory information, health data, and emotion data. For example, the following data is transmitted:

[0694] {

[0695] "fridge_data": {"tomato": 3, "chicken": 1, "lettuce": 1},

[0696] "toilet_data": {"Defecation frequency": "Low", "Water": "Low"},

[0697] "emotion_data": {"emotion": "stress"}

[0698] }

[0699] Step 5:

[0700] The server receives the dinner menu data returned by the AI ​​engine. The AI ​​engine analyzes the data and generates the optimal dinner menu. For example, the server receives the following menu data:

[0701] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[0702] Step 6:

[0703] The server calculates the ingredients needed to make the generated menu based on the received menu data. The server checks the refrigerator's inventory information. For example, if all the necessary ingredients are in the refrigerator, the server will get the following result:

[0704] {"required_ingredients": [], "status": "all ingredients available"}

[0705] Step 7:

[0706] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the missing ingredients. If all ingredients are available, the server receives a result indicating that no additional purchases are necessary. For example, the server might receive a response like this:

[0707] {"purchase_status": "no purchase needed"}

[0708] Step 8:

[0709] The server sends the final menu and purchase results to the user's device. The user can then check today's dinner menu and whether the necessary ingredients are available. For example, the server provides the user with the following information:

[0710] {"Today's Dinner Menu": ["Tomato and Lettuce Salad", "Grilled Chicken"], "Purchase Result": "I have all the ingredients I need."}

[0711] In this way, users can prepare a healthy dinner without much effort.In addition, the introduction of an emotion engine will suggest optimal menus based on the user's emotional state, which will also help with maintaining physical and mental health.

[0712] Example 2

[0713] 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."

[0714] Conventional dinner menu suggestion systems often generate menus without considering the user's health or emotional state, making it difficult to suggest a menu that is optimal for each user's physical condition and psychological state. Furthermore, because ingredients are purchased based solely on refrigerator inventory, unnecessary ingredients may be purchased or an appropriate nutritional balance may not be ensured. Therefore, there is a need for a system that can improve users' health management and psychological satisfaction.

[0715] 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.

[0716] In this invention, the server includes a means for acquiring refrigerator inventory information, a means for acquiring physical condition data based on an analysis of excrement, and a means for acquiring emotional data. This makes it possible to generate a dinner menu based on the acquired inventory information, physical condition data, and emotional data. Specifically, an AI engine is used to analyze various data, suggest an optimal menu for the user, and automatically purchase any missing ingredients using an online store's API, thereby achieving personalized support based on the user's health and emotional state.

[0717] A "means for acquiring inventory information in a refrigerator" is a device or system that uses sensors or cameras installed in the refrigerator to detect the type and quantity of food or ingredients in the refrigerator and acquires that data.

[0718] A "means for acquiring health data based on analysis of excrement" is a device or system that uses sensors or analytical devices connected to the toilet to analyze the characteristics of excrement and acquire data on the user's health condition.

[0719] The "means for acquiring emotional data" is a device or system that acquires data relating to the emotional state of a user using an emotion recognition engine that analyzes the user's facial expressions and voice.

[0720] The "means for generating dinner menus" refers to a device or system that uses an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information, physical condition data, and emotional data.

[0721] The "means for calculating the necessary ingredients" is a device or system that calculates the number of necessary ingredients based on the generated menu and in conjunction with the inventory information in the refrigerator.

[0722] A "means for automatically purchasing the necessary ingredients" is a device or system that uses the online store's API to automatically order the necessary ingredients and complete the purchase process.

[0723] The phrase "the means for generating a dinner menu transmits the acquired inventory information, physical condition data, and emotional data to the AI ​​engine" means that information about ingredients in the user's refrigerator, the user's health condition, and emotional state are provided to the AI ​​engine.

[0724] The phrase "purchase the necessary ingredients using the online store's API" means automatically ordering the missing ingredients using the online store's application program interface and completing the delivery procedure.

[0725] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means.

[0726] Get refrigerator inventory information

[0727] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator. The retrieved inventory data is structured in JSON format and indicates the types and quantities of food and ingredients present in the refrigerator. For example, the server sends an HTTP request to the refrigerator API, and the refrigerator API returns inventory data to the server. This data is stored on the server and used in the processes described below.

[0728] Obtaining health data based on excrement analysis

[0729] The server sends a request to the toilet sensor's API to retrieve data sent from the toilet sensor. Health data based on the characteristics of excrement provided by the toilet sensor is also provided to the server in JSON format. The server retrieves this data and stores the analysis results on the server.

[0730] User Emotion Recognition

[0731] The server recognizes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice via a webcam or microphone to generate emotion data. The emotion engine generates data indicating the user's emotional state (e.g., stress, joy, fatigue, etc.) and provides it to the server. The server stores this data.

[0732] Dinner menu generation

[0733] The server sends this acquired information (refrigerator inventory information, physical condition data, and emotional data) to the AI ​​engine, which then generates an optimal dinner menu. The AI ​​engine analyzes this data and proposes a balanced and healthy dinner menu. The generated menu takes into account the user's physical condition and emotions, and is presented to the user by the server.

[0734] Calculate and automatically purchase ingredients needed

[0735] The server checks whether the necessary ingredients based on the generated menu are available in the refrigerator. If necessary ingredients are not available, the server automatically purchases them using the online store's API. The online store API orders the necessary ingredients and executes the purchase process.

[0736] Specific examples

[0737] scenario

[0738] User B is busy at work and doesn't have time to prepare dinner tonight. There are tomatoes, chicken, and lettuce in the refrigerator. According to the toilet sensor, User B is constipated. Furthermore, according to the emotion engine, User B is feeling stressed.

[0739] process

[0740] The server retrieves inventory information via the refrigerator API, resulting in the following data:

[0741] Tomato: 3

[0742] Chicken: 1

[0743] Lettuce: 1

[0744] The server receives data from the toilet sensor and analyzes it to find out that the user is constipated:

[0745] Bowel movement frequency: Low

[0746] Moisture: low

[0747] The server obtains the user's emotional data using the emotion engine, and as a result of the analysis, it obtains information that User B is feeling stressed:

[0748] Emotion: Stress

[0749] The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken":

[0750] menu: [ "Tomato and lettuce salad", "Grilled chicken" ]

[0751] The server will check the ingredients needed based on the menu, and since all ingredients are already in the refrigerator, no additional purchases are necessary.

[0752] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[0753] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0754] Step 1:

[0755] Get refrigerator inventory information

[0756] The server sends a request to the refrigerator's inventory API to retrieve inventory data from sensors and cameras connected to the refrigerator. This request uses the HTTP GET method, and the refrigerator API returns data in JSON format. The input includes the current status of food and ingredients in the refrigerator, and the output is inventory data in JSON format. This data is stored in a database on the server and used for subsequent processing.

[0757] Specific behavior:

[0758] 1. The server generates an HTTP request and sends it to the refrigerator inventory API.

[0759] 2. The refrigerator API receives the request and sends the inventory data back to the server in JSON format.

[0760] 3. The server stores the received JSON data in the database.

[0761] Step 2:

[0762] Obtaining health data based on excrement analysis

[0763] The server sends a request to the Toilet Sensor API to retrieve the excrement data sent from the Toilet Sensor. This request also uses the HTTP GET method. The Toilet Sensor API returns excrement characteristic data in JSON format. The input contains the user's excrement data, and the output is analyzed health data. This data is also stored in the server's database.

[0764] Specific behavior:

[0765] 1. The server generates an HTTP request and sends it to the Toilet Sensor API.

[0766] 2. The Toilet Sensor API receives the request and returns the excrement data in JSON format to the server.

[0767] 3. The server analyzes the received data and stores it in a database.

[0768] Step 3:

[0769] Obtaining user emotion data

[0770] The server uses an emotion engine to obtain emotion data from the user's facial expressions and voice. To do this, the server sends data obtained from a webcam or microphone to the emotion engine and receives the analysis results. The input includes images of the user's facial expressions and voice data, and the output is data indicating the user's emotional state. This data is also stored in a database.

[0771] Specific behavior:

[0772] 1. The server acquires the user's facial expression images and voice data.

[0773] 2. The server sends these data to the emotion engine.

[0774] 3. The emotion engine analyzes the data and sends data indicating the emotional state back to the server.

[0775] 4. The server stores the received data in a database.

[0776] Step 4:

[0777] Generate a dinner menu

[0778] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The inputs include inventory information, physical condition data, and emotional data, and the output is menu data. The generated menu is notified to the user by the server.

[0779] Specific behavior:

[0780] 1. The server sends refrigerator inventory information, health data, and emotional data to the AI ​​engine.

[0781] 2. The AI ​​engine analyzes this data and generates the optimal dinner menu.

[0782] 3. The server receives the generated menu data and notifies the user.

[0783] Step 5:

[0784] Calculate and automatically purchase ingredients needed

[0785] The server checks whether the refrigerator has all the necessary ingredients based on the generated menu. If any ingredients are missing, the server automatically purchases them using the online store's API. The inputs include menu data and inventory data, and the output is a list of missing ingredients and a purchase procedure.

[0786] Specific behavior:

[0787] 1. The server compares the generated menu with the inventory information in the refrigerator and lists the necessary ingredients.

[0788] 2. If any ingredients are missing, the server sends a request to the online store API to purchase the ingredients.

[0789] 3. The server receives the results of the purchase and stores them in a database.

[0790] (Application example 2)

[0791] 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."

[0792] In today's busy lifestyles, it is difficult for users to easily prepare healthy, balanced meals. Furthermore, it takes time and effort to check and purchase each ingredient needed for meal preparation, and it is even more difficult to consider the user's physical condition and emotions. This often leads to inadequate nutrition and makes it difficult to maintain health. Even when users shop in physical stores, efficiently gathering the necessary ingredients is extremely time-consuming. To solve these problems, there is a need for an automatic menu generation and ingredient purchasing support system that takes into account the user's health and emotions.

[0793] 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.

[0794] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for recognizing the user's facial expression and acquiring emotional data, means for generating a dinner menu based on the acquired inventory information, physical condition data, and emotional data, means for calculating the necessary ingredients based on the generated menu, and means for automatically purchasing the necessary ingredients. This enables the preparation of healthy and balanced meals that take the user's physical condition and emotions into consideration. Furthermore, automating the purchase of necessary ingredients significantly reduces the effort and time required for shopping. Furthermore, when a user is shopping in a physical store, the in-store map API can be used to efficiently guide the user to the necessary ingredients.

[0795] "Refrigerator inventory information" refers to information about the types and quantities of food and ingredients stored in the refrigerator.

[0796] "Physical condition data" is data relating to the health condition of the user obtained based on an analysis of the user's excrement.

[0797] "Emotion data" is data that indicates the emotional state of the user recognized by analyzing the user's facial expressions and voice.

[0798] The "means for generating a menu" is a means for calculating an optimal dinner menu based on the acquired inventory information, physical condition data, and emotion data.

[0799] The "means for calculating the necessary ingredients" refers to a means for identifying the necessary ingredients based on the generated menu by checking against the inventory information in the refrigerator and calculating the shortage.

[0800] "Means for automatic purchasing" refers to means for automatically purchasing or providing guidance on the necessary ingredients using the online store's API or in-store map API.

[0801] The "Store Map API" is an API that provides a guide for users to efficiently find the ingredients they need in physical stores.

[0802] The system for implementing this invention acquires refrigerator inventory information, analyzes the user's waste to acquire health data, and recognizes the user's facial expressions to acquire emotional data, then creates an optimal dinner menu based on this information, calculates the necessary ingredients, and automatically purchases the necessary ingredients.

[0803] This system consists of a means for acquiring data from sensors and cameras placed in the refrigerator, a means for acquiring data from sensors installed in the toilet, a means for recognizing the user's facial expressions using a camera on a smartphone or smart glasses, a means for generating menus using an AI engine based on this data, a means for calculating the necessary ingredients based on the generated menu, and a means for automatically purchasing or providing guidance on the necessary ingredients using an online store API or an in-store map API.

[0804] For example, when a user goes shopping at a physical store, the system first obtains inventory information from a sensor connected to the refrigerator. This data is sent to the server in JSON format, and the types and quantities of food and ingredients in the refrigerator are identified. Next, data is obtained from the toilet sensor and the user's physical condition data is analyzed. This provides the user's health status, such as bowel movement frequency and water content. Furthermore, the system captures the user's facial expressions using a camera on a smartphone or smart glasses, and obtains the user's emotional data through an emotion engine. Emotional data includes information such as the stress, joy, and fatigue the user is feeling.

[0805] This data is sent to an AI engine to generate an optimal dinner menu. The generated menu is healthy and balanced, taking into account the user's physical condition and emotions. The system then calculates the ingredients needed based on the generated menu and checks it against the inventory information in the refrigerator to identify any shortages. The system uses the online store's API to automatically purchase the necessary ingredients. When the user makes a purchase in a physical store, the system also uses the in-store map API to guide them to the location of product shelves.

[0806] As a concrete example, consider the case where User A is shopping at a supermarket. There are tomatoes, chicken, and lettuce in the refrigerator, but User A is feeling constipated and a little stressed. The system sends this information to the AI ​​engine, which suggests "tomato and lettuce salad" and "grilled chicken" as the optimal menu. It then uses the in-store map API to guide User A to the specific shelf locations where he should purchase the salad and chicken.

[0807] Examples of prompts include:

[0808] 1. Get the latest inventory data from the refrigerator API.

[0809] 2. Get the user's latest health data from the health management app API.

[0810] 3. Capture the user's facial expressions with the camera and use the emotion engine to obtain emotion data.

[0811] 4. Use the AI ​​engine to suggest the best products based on the inventory, health, and emotion data you have acquired.

[0812] 5. Use Maps API to show the location of the suggested products in the store.

[0813] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0814] Step 1:

[0815] The server obtains inventory information from sensors and cameras connected to the refrigerator.

[0816] Input: Data from refrigerator inventory sensors and cameras

[0817] Data processing: Convert to JSON format

[0818] Output: Data on the type and quantity of food and ingredients in the refrigerator

[0819] Specific operation: The server sends a request to the refrigerator inventory API and parses the retrieved data in JSON format.

[0820] Step 2:

[0821] The server acquires the data sent from the toilet sensor and analyzes the user's physical condition data.

[0822] Input: Excrement data from toilet sensor

[0823] Data processing: Convert to JSON format

[0824] Output: User's health data such as bowel movement frequency and water content

[0825] Specific operation: The server sends a request to the toilet sensor's API and parses the acquired data in JSON format.

[0826] Step 3:

[0827] The device captures the user's facial expressions using a camera on a smartphone or smart glasses and obtains emotional data through an emotion engine.

[0828] Input: Image data from a smartphone or smart glasses camera

[0829] Data processing: Generating emotion data through facial expression analysis

[0830] Output: Emotional data such as stress, joy, fatigue, etc.

[0831] Specific operation: The device captures the user's facial expressions with a camera and sends the data to the emotion engine to obtain analysis results.

[0832] Step 4:

[0833] The server sends the acquired inventory information, health data, and emotional data to the AI ​​engine to generate a dinner menu.

[0834] Input: inventory data, physical condition data, emotional data

[0835] Data processing: Menu generation using AI models

[0836] Output: Optimal dinner menu

[0837] Specific operation: The server sends this data to the AI ​​engine as a single request and receives menu suggestions.

[0838] Step 5:

[0839] The server calculates the ingredients needed based on the generated menu and identifies any ingredients that are lacking.

[0840] Input: Menu data, inventory data

[0841] Data processing: Checking against inventory data and identifying shortages

[0842] Output: List of ingredients needed

[0843] Specific operation: The server compares the ingredients required for the generated menu with the inventory in the refrigerator and lists the necessary ingredients.

[0844] Step 6:

[0845] The server automatically purchases the necessary ingredients through an online store API, or when the user purchases at a physical store, it uses an in-store map API to guide the user to the location within the store.

[0846] Input: List of ingredients needed

[0847] Data processing: Data generation for purchase requests or location guidance

[0848] Output: Purchase instructions for online stores or in-store location guidance

[0849] Specific operation: The server sends the necessary ingredient information to the online store API and automatically purchases it. If the user purchases at a physical store, the server uses the store's map API to guide the user to the location of the necessary ingredients.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] [Third embodiment]

[0854] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0855] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0856] 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).

[0857] 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.

[0858] 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.

[0859] 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).

[0860] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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."

[0866] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, creates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[0867] Get refrigerator inventory information

[0868] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[0869] Obtaining health data based on excrement analysis

[0870] The server sends a request to the Toilet Sensor API to retrieve the data sent by the Toilet Sensor. The characteristics of the excrement analyzed by the Toilet Sensor are provided in JSON format, indicating the user's current health status, including, for example, bowel movement frequency and water content.

[0871] Dinner menu generation

[0872] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine, which analyzes this data and generates an optimal dinner menu. The generated menu takes the user's physical condition into consideration, providing a healthy and balanced meal.

[0873] Calculate and automatically purchase ingredients needed

[0874] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[0875] Specific examples

[0876] scenario

[0877] User A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0878] tomato

[0879] chicken meat

[0880] lettuce

[0881] According to the user's toilet sensor, User A is suffering from constipation.

[0882] process

[0883] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[0884] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[0885] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[0886] {"Bow frequency": "Low", "Moisture": "Low"}

[0887] 3. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[0888] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[0889] 4. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[0890] In this way, User A can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives.

[0891] The processing flow will be explained below.

[0892] Step 1:

[0893] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator.

[0894] Step 2:

[0895] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content.

[0896] Step 3:

[0897] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The transmitted data includes inventory information and health data. The AI ​​engine uses this information to generate the optimal dinner menu.

[0898] Step 4:

[0899] The server receives the menu data returned by the AI ​​engine, which includes specific menu suggestions, such as "tomato and lettuce salad" or "grilled chicken."

[0900] Step 5:

[0901] The server calculates the ingredients needed to prepare the generated menu based on the received menu data, and checks the refrigerator's inventory to see which ingredients are in short supply.

[0902] Step 6:

[0903] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the ingredients needed. The server receives a response from the online store confirming that the order is complete.

[0904] Step 7:

[0905] The server sends the final menu and purchase results to the user's device, where the user can check today's dinner menu and whether the necessary ingredients are available. As a result, the user can prepare a healthy dinner without any hassle.

[0906] Example 1

[0907] 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."

[0908] Conventional refrigerator and health management systems often manage inventory and collect health data separately, which is insufficient for comprehensive health management. Furthermore, there were no systems that automatically generated dinner menus and automatically purchased the necessary ingredients, so users had to take the time and effort to plan their meals. Furthermore, there were no systems that properly notified users of this information and provided accurate menus, so users had to spend time and effort checking and preparing meals.

[0909] 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.

[0910] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for creating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the created menu, means for automatically purchasing the necessary ingredients, means for notifying the user's terminal of the acquired inventory information and physical condition data, and means for displaying the menu created based on the acquired inventory information and physical condition data. This allows the user to effortlessly plan a dinner menu and automatically purchase the necessary ingredients. Furthermore, the user can check the information in real time and receive support for living a healthy lifestyle.

[0911] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the types and quantities of food and ingredients in the refrigerator using sensors and cameras installed in the refrigerator.

[0912] The "means for acquiring health data based on analysis of excrement" is a means for collecting data on excrement from sensors installed in the toilet and acquiring health data on the user based on that data.

[0913] The "means for generating dinner menus" refers to a means for using an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information and health data.

[0914] The "means for calculating the necessary ingredients" is a means for identifying the necessary ingredients based on the generated dinner menu and calculating the ingredients that are lacking by checking against the inventory information.

[0915] "Means for automatically purchasing necessary ingredients" refers to a means for automatically purchasing ingredients that are in short supply using an online store's API.

[0916] The "means for notifying the user's terminal of the acquired inventory information and health data" refers to a means for notifying the user's terminal, such as a smartphone or tablet, of the inventory information and health data acquired by the server in real time.

[0917] The "means for displaying a menu created based on the acquired inventory information and physical condition data" is a means for displaying the dinner menu created by the server on the user's terminal.

[0918] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, generates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu generation means, an ingredient calculation means, an automatic purchasing means, a means for notifying the user of this information, and a means for displaying the generated menu. Specific operations will now be described.

[0919] The server sends a request to the refrigerator's inventory API to obtain data from sensors and cameras connected to the refrigerator. The sensors and cameras detect the type and quantity of food and ingredients in the refrigerator, structure that information in JSON format, and send it to the server. For example, if the sensor detects three tomatoes, one pack of chicken, and one lettuce, the following data is obtained:

[0920] json

[0921] {

[0922] "Tomato": 3,

[0923] "chicken": 1,

[0924] "Lettuce": 1

[0925] }

[0926] The server sends a request to the Toilet Sensor API to retrieve data sent from the Toilet Sensor. The Toilet Sensor analyzes the user's waste and provides the data in JSON format, including data such as bowel movement frequency and water content.

[0927] json

[0928] {

[0929] "Bowel frequency": "low",

[0930] "Moisture": "Low"

[0931] }

[0932] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. This menu takes the user's physical condition into consideration and provides healthy, balanced meals. For example, a menu rich in dietary fiber is generated for a user who tends to be constipated.

[0933] json

[0934] {

[0935] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[0936] }

[0937] Based on the generated menu, the server checks whether the necessary ingredients are available in the refrigerator. If any of the necessary ingredients are in short supply, the server automatically purchases them using the online store's API. The server sends the information about the necessary ingredients to the online store's API and executes the purchasing process. For example, if there is a shortage of chicken, the server orders the required amount of chicken from the online store.

[0938] The server then sends the acquired inventory information, health data, and the generated menu to the user's device, allowing the user to check the dinner menu on their smartphone or tablet and ensure that all the necessary ingredients have been prepared.

[0939] For example, user A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[0940] tomato

[0941] chicken meat

[0942] lettuce

[0943] According to the user's toilet sensor, User A is slightly constipated. The server obtains this information and analyzes it with an AI engine, generating the optimal dinner menu of "tomato and lettuce salad" and "grilled chicken." Based on this, it is determined that the necessary ingredients are already present and no additional purchases are necessary.

[0944] As an example of input to the generative AI model, we will use the following prompt:

[0945] I'd like some suggestions for dinner using winter vegetables.

[0946] Generate healthy dinner menus based on your waste data.

[0947] Suggest a dish using the tomatoes, chicken, and lettuce in your fridge.

[0948] By using this prompt, users can get specific meal suggestions from the AI ​​model. This system is very useful for many users who lead busy daily lives.

[0949] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0950] Step 1:

[0951] The server obtains data from sensors and cameras connected to the refrigerator. Specifically, the server sends a request to the refrigerator's inventory API to obtain information about the types and quantities of food and ingredients in the refrigerator. The input is the types and quantities of food and ingredients in the refrigerator, and the output is inventory information in JSON format. For example, the sensor detects three tomatoes, one pack of chicken, and one head of lettuce, and returns that information in JSON format.

[0952] json

[0953] {

[0954] "Tomato": 3,

[0955] "chicken": 1,

[0956] "Lettuce": 1

[0957] }

[0958] Step 2:

[0959] The server sends a request to the toilet sensor's API to obtain data sent from the toilet sensor. The toilet sensor analyzes the user's excrement and provides the data in JSON format. The input is excrement data, and the output is user health data. Specifically, this data includes bowel movement frequency and water content.

[0960] json

[0961] {

[0962] "Bowel frequency": "low",

[0963] "Moisture": "Low"

[0964] }

[0965] Step 3:

[0966] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The input is refrigerator inventory information and health data, and the output is the generated menu information. For example, a menu rich in dietary fiber can be generated for a user who is prone to constipation.

[0967] json

[0968] {

[0969] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[0970] }

[0971] Step 4:

[0972] The server checks whether the necessary ingredients are available in the refrigerator based on the generated menu. The input is the generated menu information and inventory information, and the output is a list of the necessary ingredients and their stock status. If a necessary ingredient is in short supply, the server automatically purchases it using the online store's API. For example, if chicken is in short supply, the server will order the required amount of chicken from the online store.

[0973] json

[0974] {

[0975] "order": "chicken"

[0976] }

[0977] Step 5:

[0978] The server notifies the terminal of the created menu and the information on ingredients that have been purchased. The input is the created menu information and the information on the completed purchase, and the output is a notification message sent to the user's terminal. This allows the user to confirm that the menu and the ingredients for it are available.

[0979] json

[0980] {

[0981] "notification": "Today's menu is 'Tomato and Lettuce Salad' and 'Grilled Chicken'. All the ingredients you need are here."

[0982] }

[0983] Through this process, users can effortlessly plan their dinner menu, automatically purchase the necessary ingredients, and prepare healthy meals. This system will significantly support users' daily lives.

[0984] (Application example 1)

[0985] 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."

[0986] In modern society, people are busy with work and daily life, making it difficult to easily prepare a healthy dinner. Managing refrigerator inventory and planning a meal plan that is appropriate for their physical condition can also take a lot of time and effort. Furthermore, the hassle of visiting a store to purchase the necessary ingredients can be a problem. There is a need for a system that can solve these issues and allow users to easily prepare a healthy, balanced dinner.

[0987] 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.

[0988] In this invention, the server includes means for acquiring inventory information from the refrigerator, means for acquiring physical condition data based on an analysis of excrement, means for generating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the generated menu, means for automatically purchasing the necessary ingredients, and means for integrating and managing meal suggestions and ingredient delivery services based on the generated menu and purchased ingredients. This allows users to easily obtain an optimal dinner menu based on the inventory information from the refrigerator and their physical condition, and any missing ingredients are automatically purchased and delivered, allowing them to enjoy healthy meals without any effort.

[0989] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the type and quantity of food in the refrigerator using sensors and cameras installed in the refrigerator.

[0990] "Means for obtaining health data based on analysis of excrement" refers to a means for analyzing the user's excrement using a sensor installed in the toilet and obtaining health data such as bowel movement frequency and water content.

[0991] The "means for generating dinner menus" refers to a means for using an AI engine to create optimal dinner menus based on the acquired refrigerator inventory information and health data.

[0992] The "means for calculating the necessary ingredients" is a means for calculating the shortage of ingredients in the refrigerator based on the generated menu, and determining the necessary ingredients.

[0993] "Means for automatically purchasing necessary ingredients" refers to a means for automatically ordering and purchasing necessary ingredients using the API of an online store or food delivery service.

[0994] The "means for integrated management of meal suggestions and ingredient delivery services" is a means for making meal suggestions to users based on the generated menu and purchased ingredients, and for centrally managing ingredient delivery.

[0995] MODE FOR CARRYING OUT THE INVENTION

[0996] The system of the present invention uses a smartphone application at its core to create an optimal dinner menu based on refrigerator inventory information and the user's physical condition data. It then automatically purchases the necessary ingredients and provides an integrated process of delivering them to the user via a food delivery service. The main processes involved in this system are described below.

[0997] Hardware and software used

[0998] Hardware:

[0999] Smartphone: Used as a user interface.

[1000] Refrigerator sensors and cameras: Used to obtain inventory information inside the refrigerator.

[1001] Toilet sensor: Used to analyze the user's waste and obtain health data.

[1002] software:

[1003] Server: The core of the application, acquiring, processing, and transmitting various data.

[1004] AI engine: Generates optimal dinner menus based on refrigerator inventory data and health data.

[1005] API: Handles data communication between the refrigerator sensor, toilet sensor, food delivery service and server.

[1006] Data processing and calculation

[1007] Get refrigerator inventory:

[1008] Data acquired from sensors and cameras installed in the refrigerator is sent to the server and interpreted in JSON format, including the type and quantity of food in the refrigerator.

[1009] Obtaining health data based on excrement analysis:

[1010] A sensor installed in the toilet analyzes the user's waste and sends the results, including bowel movement frequency and water content, to a server.

[1011] Dinner menu generation:

[1012] The server sends the acquired inventory information and health data to the AI ​​engine, which then analyzes this data and generates an optimal menu based on the user's health condition.

[1013] Calculate and auto-purchase ingredients needed:

[1014] The server calculates the ingredients needed based on the generated menu, and if any ingredients are not in the refrigerator, it automatically purchases them through the API of the food delivery service.

[1015] Meal suggestions and delivery management:

[1016] The server makes meal suggestions to the user based on the generated menu and purchased ingredient information, and also manages the ingredient delivery service in an integrated manner.

[1017] Specific examples

[1018] scenario

[1019] User A has a very busy job and does not want to spend too much time preparing dinner. User A has the following foods in his refrigerator:

[1020] tomato

[1021] chicken meat

[1022] lettuce

[1023] Additionally, data from the toilet sensor indicates that User A is constipated. Based on this information, the following prompt is generated:

[1024] "Here's what's in your refrigerator:

[1025] Tomato: 3, Chicken: 1, Lettuce: 1

[1026] Here is the user's health data:

[1027] Bowel frequency: "Low", moisture: "Low"

[1028] Based on this information, please suggest the perfect dinner menu for you.

[1029] Based on the acquired data, the AI ​​engine generates a menu including "tomato and lettuce salad" and "grilled chicken" and confirms the necessary ingredients. This system not only provides User A with the optimal dinner recommendation, but also automatically purchases and delivers the necessary ingredients, saving him a lot of time and effort.

[1030] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1031] Step 1:

[1032] Process to obtain refrigerator inventory information

[1033] The server obtains inventory information through sensors and cameras installed in the refrigerator. Specifically, it sends a request to the refrigerator's inventory API and receives JSON-formatted data including the type and quantity of food in the refrigerator. For example, this data includes "Tomatoes: 3, Chicken: 1, Lettuce: 1."

[1034] Input: Food information in the refrigerator

[1035] Output: Inventory information data in JSON format

[1036] Specific operation: The server sends a request to the refrigerator inventory API and structures the data obtained from the sensors and camera in JSON format.

[1037] Step 2:

[1038] Processing to obtain health data based on excrement analysis

[1039] The server obtains analysis data of excrement from sensors installed in the toilet. It sends a request to the toilet sensor's API and receives JSON-formatted data containing excrement characteristics. This data includes bowel movement frequency and water content, e.g., "Bow movement frequency: 'low', Water content: 'low'."

[1040] Input: fecal analysis data

[1041] Output: Physical condition data in JSON format

[1042] Specific operation: The server sends a request to the toilet sensor's API and structures the excrement analysis results obtained from the sensor in JSON format.

[1043] Step 3:

[1044] Process for generating dinner menus

[1045] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine and generates the optimal dinner menu. The prompt used is, "The user's refrigerator inventory information is as follows: Tomatoes: 3, Chicken: 1, Lettuce: 1. The user's health data is as follows: Bowel frequency: 'Low', Water content: 'Low'. Please suggest the optimal dinner menu based on this information."

[1046] Input: JSON format inventory information data and health data

[1047] Output: JSON format data containing menu items

[1048] Specific operation: The server sends data to the AI ​​engine and receives the API response generated as the analysis result.

[1049] Step 4:

[1050] Process to calculate the necessary ingredients

[1051] The server calculates the ingredients needed based on the generated menu, compares it with the inventory information in the refrigerator, and identifies any ingredients that are lacking. This process generates an automatic purchasing list of ingredients.

[1052] Input: Generated menu and inventory information

[1053] Output: List of ingredients needed

[1054] Specific operation: The server compares the menu with inventory information and creates a list of ingredients that are in short supply.

[1055] Step 5:

[1056] Automatically purchase the ingredients you need

[1057] The server automatically purchases ingredients using the API of the food delivery service based on the list of ingredients that are in short supply. It sends a request to the API of the food delivery service to order the necessary ingredients and process the delivery.

[1058] Input: Missing ingredients list

[1059] Output: Ingredient purchase completion data

[1060] Specific operation: The server sends a request to the food delivery service's API, processes the purchase, and completes the delivery procedure.

[1061] Step 6:

[1062] Process to suggest meals and manage delivery

[1063] The server makes meal suggestions to users based on the generated menu and purchased ingredient information, and manages the food delivery service in an integrated manner. It notifies users of the expected arrival date of ingredients and menu details.

[1064] Input: Generated menu and purchased ingredients information

[1065] Output: User notifications and administrative information

[1066] Specific operation: The server sends notifications to the user's smartphone and manages the status of the food delivery service.

[1067] 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.

[1068] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[1069] Get refrigerator inventory information

[1070] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[1071] Obtaining health data based on excrement analysis

[1072] The server sends a request to the toilet sensor's API to retrieve the data sent by the toilet sensor. The server receives the characteristics of the excrement analyzed by the toilet sensor in JSON format, which indicates the user's current health status, such as bowel movement frequency and water content.

[1073] User Emotion Recognition

[1074] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This emotion data indicates the user's emotional state (e.g., stress, joy, fatigue, etc.) and is reflected in the generation of dinner menus.

[1075] Dinner menu generation

[1076] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. The generated menu takes into account the user's physical condition and emotions, providing a healthy and balanced meal.

[1077] Calculate and automatically purchase ingredients needed

[1078] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[1079] Specific examples

[1080] scenario

[1081] User B is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[1082] tomato

[1083] chicken meat

[1084] lettuce

[1085] According to the user's toilet sensor, User B is suffering from constipation. Furthermore, according to the emotion engine, User B is feeling stressed.

[1086] process

[1087] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[1088] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[1089] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[1090] {"Bow frequency": "Low", "Moisture": "Low"}

[1091] 3. The server obtains the user's emotional data using the emotion engine. As a result of the analysis, it finds out that User B is feeling stressed:

[1092] {"emotion": "stress"}

[1093] 4. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[1094] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[1095] 5. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[1096] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[1097] The processing flow will be explained below.

[1098] Step 1:

[1099] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator. For example, the server receives the following inventory information:

[1100] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[1101] Step 2:

[1102] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content. For example, the server receives the following health data:

[1103] {"Bow frequency": "Low", "Moisture": "Low"}

[1104] Step 3:

[1105] The server uses the emotion engine to analyze the user's facial expressions and voice to recognize the user's emotions. The server obtains the emotion data from the emotion engine and checks the user's emotional state. For example, the emotion engine returns the following data:

[1106] {"emotion": "stress"}

[1107] Step 4:

[1108] The server sends the acquired refrigerator inventory information, health data, and emotion data to the AI ​​engine. The transmitted data includes inventory information, health data, and emotion data. For example, the following data is transmitted:

[1109] {

[1110] "fridge_data": {"tomato": 3, "chicken": 1, "lettuce": 1},

[1111] "toilet_data": {"Defecation frequency": "Low", "Water": "Low"},

[1112] "emotion_data": {"emotion": "stress"}

[1113] }

[1114] Step 5:

[1115] The server receives the dinner menu data returned by the AI ​​engine. The AI ​​engine analyzes the data and generates the optimal dinner menu. For example, the server receives the following menu data:

[1116] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[1117] Step 6:

[1118] The server calculates the ingredients needed to make the generated menu based on the received menu data. The server checks the refrigerator's inventory information. For example, if all the necessary ingredients are in the refrigerator, the server will get the following result:

[1119] {"required_ingredients": [], "status": "all ingredients available"}

[1120] Step 7:

[1121] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the missing ingredients. If all ingredients are available, the server receives a result indicating that no additional purchases are necessary. For example, the server might receive a response like this:

[1122] {"purchase_status": "no purchase needed"}

[1123] Step 8:

[1124] The server sends the final menu and purchase results to the user's device. The user can then check today's dinner menu and whether the necessary ingredients are available. For example, the server provides the user with the following information:

[1125] {"Today's Dinner Menu": ["Tomato and Lettuce Salad", "Grilled Chicken"], "Purchase Result": "I have all the ingredients I need."}

[1126] In this way, users can prepare a healthy dinner without much effort.In addition, the introduction of an emotion engine will suggest optimal menus based on the user's emotional state, which will also help with maintaining physical and mental health.

[1127] Example 2

[1128] 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."

[1129] Conventional dinner menu suggestion systems often generate menus without considering the user's health or emotional state, making it difficult to suggest a menu that is optimal for each user's physical condition and psychological state. Furthermore, because ingredients are purchased based solely on refrigerator inventory, unnecessary ingredients may be purchased or an appropriate nutritional balance may not be ensured. Therefore, there is a need for a system that can improve users' health management and psychological satisfaction.

[1130] 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.

[1131] In this invention, the server includes a means for acquiring refrigerator inventory information, a means for acquiring physical condition data based on an analysis of excrement, and a means for acquiring emotional data. This makes it possible to generate a dinner menu based on the acquired inventory information, physical condition data, and emotional data. Specifically, an AI engine is used to analyze various data, suggest an optimal menu for the user, and automatically purchase any missing ingredients using an online store's API, thereby achieving personalized support based on the user's health and emotional state.

[1132] A "means for acquiring inventory information in a refrigerator" is a device or system that uses sensors or cameras installed in the refrigerator to detect the type and quantity of food or ingredients in the refrigerator and acquires that data.

[1133] A "means for acquiring health data based on analysis of excrement" is a device or system that uses sensors or analytical devices connected to the toilet to analyze the characteristics of excrement and acquire data on the user's health condition.

[1134] The "means for acquiring emotional data" is a device or system that acquires data relating to the emotional state of a user using an emotion recognition engine that analyzes the user's facial expressions and voice.

[1135] The "means for generating dinner menus" refers to a device or system that uses an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information, physical condition data, and emotional data.

[1136] The "means for calculating the necessary ingredients" is a device or system that calculates the number of necessary ingredients based on the generated menu and in conjunction with the inventory information in the refrigerator.

[1137] A "means for automatically purchasing the necessary ingredients" is a device or system that uses the online store's API to automatically order the necessary ingredients and complete the purchase process.

[1138] The phrase "the means for generating a dinner menu transmits the acquired inventory information, physical condition data, and emotional data to the AI ​​engine" means that information about ingredients in the user's refrigerator, the user's health condition, and emotional state are provided to the AI ​​engine.

[1139] The phrase "purchase the necessary ingredients using the online store's API" means automatically ordering the missing ingredients using the online store's application program interface and completing the delivery procedure.

[1140] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means.

[1141] Get refrigerator inventory information

[1142] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator. The retrieved inventory data is structured in JSON format and indicates the types and quantities of food and ingredients present in the refrigerator. For example, the server sends an HTTP request to the refrigerator API, and the refrigerator API returns inventory data to the server. This data is stored on the server and used in the processes described below.

[1143] Obtaining health data based on excrement analysis

[1144] The server sends a request to the toilet sensor's API to retrieve data sent from the toilet sensor. Health data based on the characteristics of excrement provided by the toilet sensor is also provided to the server in JSON format. The server retrieves this data and stores the analysis results on the server.

[1145] User Emotion Recognition

[1146] The server recognizes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice via a webcam or microphone to generate emotion data. The emotion engine generates data indicating the user's emotional state (e.g., stress, joy, fatigue, etc.) and provides it to the server. The server stores this data.

[1147] Dinner menu generation

[1148] The server sends this acquired information (refrigerator inventory information, physical condition data, and emotional data) to the AI ​​engine, which then generates an optimal dinner menu. The AI ​​engine analyzes this data and proposes a balanced and healthy dinner menu. The generated menu takes into account the user's physical condition and emotions, and is presented to the user by the server.

[1149] Calculate and automatically purchase ingredients needed

[1150] The server checks whether the necessary ingredients based on the generated menu are available in the refrigerator. If necessary ingredients are not available, the server automatically purchases them using the online store's API. The online store API orders the necessary ingredients and executes the purchase process.

[1151] Specific examples

[1152] scenario

[1153] User B is busy at work and doesn't have time to prepare dinner tonight. There are tomatoes, chicken, and lettuce in the refrigerator. According to the toilet sensor, User B is constipated. Furthermore, according to the emotion engine, User B is feeling stressed.

[1154] process

[1155] The server retrieves inventory information via the refrigerator API, resulting in the following data:

[1156] Tomato: 3

[1157] Chicken: 1

[1158] Lettuce: 1

[1159] The server receives data from the toilet sensor and analyzes it to find out that the user is constipated:

[1160] Bowel movement frequency: Low

[1161] Moisture: low

[1162] The server obtains the user's emotional data using the emotion engine, and as a result of the analysis, it obtains information that User B is feeling stressed:

[1163] Emotion: Stress

[1164] The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken":

[1165] menu: [ "Tomato and lettuce salad", "Grilled chicken" ]

[1166] The server will check the ingredients needed based on the menu, and since all ingredients are already in the refrigerator, no additional purchases are necessary.

[1167] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[1168] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1169] Step 1:

[1170] Get refrigerator inventory information

[1171] The server sends a request to the refrigerator's inventory API to retrieve inventory data from sensors and cameras connected to the refrigerator. This request uses the HTTP GET method, and the refrigerator API returns data in JSON format. The input includes the current status of food and ingredients in the refrigerator, and the output is inventory data in JSON format. This data is stored in a database on the server and used for subsequent processing.

[1172] Specific behavior:

[1173] 1. The server generates an HTTP request and sends it to the refrigerator inventory API.

[1174] 2. The refrigerator API receives the request and sends the inventory data back to the server in JSON format.

[1175] 3. The server stores the received JSON data in the database.

[1176] Step 2:

[1177] Obtaining health data based on excrement analysis

[1178] The server sends a request to the Toilet Sensor API to retrieve the excrement data sent from the Toilet Sensor. This request also uses the HTTP GET method. The Toilet Sensor API returns excrement characteristic data in JSON format. The input contains the user's excrement data, and the output is analyzed health data. This data is also stored in the server's database.

[1179] Specific behavior:

[1180] 1. The server generates an HTTP request and sends it to the Toilet Sensor API.

[1181] 2. The Toilet Sensor API receives the request and returns the excrement data in JSON format to the server.

[1182] 3. The server analyzes the received data and stores it in a database.

[1183] Step 3:

[1184] Obtaining user emotion data

[1185] The server uses an emotion engine to obtain emotion data from the user's facial expressions and voice. To do this, the server sends data obtained from a webcam or microphone to the emotion engine and receives the analysis results. The input includes images of the user's facial expressions and voice data, and the output is data indicating the user's emotional state. This data is also stored in a database.

[1186] Specific behavior:

[1187] 1. The server acquires the user's facial expression images and voice data.

[1188] 2. The server sends these data to the emotion engine.

[1189] 3. The emotion engine analyzes the data and sends data indicating the emotional state back to the server.

[1190] 4. The server stores the received data in a database.

[1191] Step 4:

[1192] Generate a dinner menu

[1193] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The inputs include inventory information, physical condition data, and emotional data, and the output is menu data. The generated menu is notified to the user by the server.

[1194] Specific behavior:

[1195] 1. The server sends refrigerator inventory information, health data, and emotional data to the AI ​​engine.

[1196] 2. The AI ​​engine analyzes this data and generates the optimal dinner menu.

[1197] 3. The server receives the generated menu data and notifies the user.

[1198] Step 5:

[1199] Calculate and automatically purchase ingredients needed

[1200] The server checks whether the refrigerator has all the necessary ingredients based on the generated menu. If any ingredients are missing, the server automatically purchases them using the online store's API. The inputs include menu data and inventory data, and the output is a list of missing ingredients and a purchase procedure.

[1201] Specific behavior:

[1202] 1. The server compares the generated menu with the inventory information in the refrigerator and lists the necessary ingredients.

[1203] 2. If any ingredients are missing, the server sends a request to the online store API to purchase the ingredients.

[1204] 3. The server receives the results of the purchase and stores them in a database.

[1205] (Application example 2)

[1206] 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."

[1207] In today's busy lifestyles, it is difficult for users to easily prepare healthy, balanced meals. Furthermore, it takes time and effort to check and purchase each ingredient needed for meal preparation, and it is even more difficult to consider the user's physical condition and emotions. This often leads to inadequate nutrition and makes it difficult to maintain health. Even when users shop in physical stores, efficiently gathering the necessary ingredients is extremely time-consuming. To solve these problems, there is a need for an automatic menu generation and ingredient purchasing support system that takes into account the user's health and emotions.

[1208] 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.

[1209] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for recognizing the user's facial expression and acquiring emotional data, means for generating a dinner menu based on the acquired inventory information, physical condition data, and emotional data, means for calculating the necessary ingredients based on the generated menu, and means for automatically purchasing the necessary ingredients. This enables the preparation of healthy and balanced meals that take the user's physical condition and emotions into consideration. Furthermore, automating the purchase of necessary ingredients significantly reduces the effort and time required for shopping. Furthermore, when a user is shopping in a physical store, the in-store map API can be used to efficiently guide the user to the necessary ingredients.

[1210] "Refrigerator inventory information" refers to information about the types and quantities of food and ingredients stored in the refrigerator.

[1211] "Physical condition data" is data relating to the health condition of the user obtained based on an analysis of the user's excrement.

[1212] "Emotion data" is data that indicates the emotional state of the user recognized by analyzing the user's facial expressions and voice.

[1213] The "means for generating a menu" is a means for calculating an optimal dinner menu based on the acquired inventory information, physical condition data, and emotion data.

[1214] The "means for calculating the necessary ingredients" refers to a means for identifying the necessary ingredients based on the generated menu by checking against the inventory information in the refrigerator and calculating the shortage.

[1215] "Means for automatic purchasing" refers to means for automatically purchasing or providing guidance on the necessary ingredients using the online store's API or in-store map API.

[1216] The "Store Map API" is an API that provides a guide for users to efficiently find the ingredients they need in physical stores.

[1217] The system for implementing this invention acquires refrigerator inventory information, analyzes the user's waste to acquire health data, and recognizes the user's facial expressions to acquire emotional data, then creates an optimal dinner menu based on this information, calculates the necessary ingredients, and automatically purchases the necessary ingredients.

[1218] This system consists of a means for acquiring data from sensors and cameras placed in the refrigerator, a means for acquiring data from sensors installed in the toilet, a means for recognizing the user's facial expressions using a camera on a smartphone or smart glasses, a means for generating menus using an AI engine based on this data, a means for calculating the necessary ingredients based on the generated menu, and a means for automatically purchasing or providing guidance on the necessary ingredients using an online store API or an in-store map API.

[1219] For example, when a user goes shopping at a physical store, the system first obtains inventory information from a sensor connected to the refrigerator. This data is sent to the server in JSON format, and the types and quantities of food and ingredients in the refrigerator are identified. Next, data is obtained from the toilet sensor and the user's physical condition data is analyzed. This provides the user's health status, such as bowel movement frequency and water content. Furthermore, the system captures the user's facial expressions using a camera on a smartphone or smart glasses, and obtains the user's emotional data through an emotion engine. Emotional data includes information such as the stress, joy, and fatigue the user is feeling.

[1220] This data is sent to an AI engine to generate an optimal dinner menu. The generated menu is healthy and balanced, taking into account the user's physical condition and emotions. The system then calculates the ingredients needed based on the generated menu and checks it against the inventory information in the refrigerator to identify any shortages. The system uses the online store's API to automatically purchase the necessary ingredients. When the user makes a purchase in a physical store, the system also uses the in-store map API to guide them to the location of product shelves.

[1221] As a concrete example, consider the case where User A is shopping at a supermarket. There are tomatoes, chicken, and lettuce in the refrigerator, but User A is feeling constipated and a little stressed. The system sends this information to the AI ​​engine, which suggests "tomato and lettuce salad" and "grilled chicken" as the optimal menu. It then uses the in-store map API to guide User A to the specific shelf locations where he should purchase the salad and chicken.

[1222] Examples of prompts include:

[1223] 1. Get the latest inventory data from the refrigerator API.

[1224] 2. Get the user's latest health data from the health management app API.

[1225] 3. Capture the user's facial expressions with the camera and use the emotion engine to obtain emotion data.

[1226] 4. Use the AI ​​engine to suggest the best products based on the inventory, health, and emotion data you have acquired.

[1227] 5. Use Maps API to show the location of the suggested products in the store.

[1228] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1229] Step 1:

[1230] The server obtains inventory information from sensors and cameras connected to the refrigerator.

[1231] Input: Data from refrigerator inventory sensors and cameras

[1232] Data processing: Convert to JSON format

[1233] Output: Data on the type and quantity of food and ingredients in the refrigerator

[1234] Specific operation: The server sends a request to the refrigerator inventory API and parses the retrieved data in JSON format.

[1235] Step 2:

[1236] The server acquires the data sent from the toilet sensor and analyzes the user's physical condition data.

[1237] Input: Excrement data from toilet sensor

[1238] Data processing: Convert to JSON format

[1239] Output: User's health data such as bowel movement frequency and water content

[1240] Specific operation: The server sends a request to the toilet sensor's API and parses the acquired data in JSON format.

[1241] Step 3:

[1242] The device captures the user's facial expressions using a camera on a smartphone or smart glasses and obtains emotional data through an emotion engine.

[1243] Input: Image data from a smartphone or smart glasses camera

[1244] Data processing: Generating emotion data through facial expression analysis

[1245] Output: Emotional data such as stress, joy, fatigue, etc.

[1246] Specific operation: The device captures the user's facial expressions with a camera and sends the data to the emotion engine to obtain analysis results.

[1247] Step 4:

[1248] The server sends the acquired inventory information, health data, and emotional data to the AI ​​engine to generate a dinner menu.

[1249] Input: inventory data, physical condition data, emotional data

[1250] Data processing: Menu generation using AI models

[1251] Output: Optimal dinner menu

[1252] Specific operation: The server sends this data to the AI ​​engine as a single request and receives menu suggestions.

[1253] Step 5:

[1254] The server calculates the ingredients needed based on the generated menu and identifies any ingredients that are lacking.

[1255] Input: Menu data, inventory data

[1256] Data processing: Checking against inventory data and identifying shortages

[1257] Output: List of ingredients needed

[1258] Specific operation: The server compares the ingredients required for the generated menu with the inventory in the refrigerator and lists the necessary ingredients.

[1259] Step 6:

[1260] The server automatically purchases the necessary ingredients through an online store API, or when the user purchases at a physical store, it uses an in-store map API to guide the user to the location within the store.

[1261] Input: List of ingredients needed

[1262] Data processing: Data generation for purchase requests or location guidance

[1263] Output: Purchase instructions for online stores or in-store location guidance

[1264] Specific operation: The server sends the necessary ingredient information to the online store API and automatically purchases it. If the user purchases at a physical store, the server uses the store's map API to guide the user to the location of the necessary ingredients.

[1265] 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.

[1266] 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.

[1267] 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.

[1268] [Fourth embodiment]

[1269] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1270] 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.

[1271] 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).

[1272] 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.

[1273] 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.

[1274] 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).

[1275] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1276] 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.

[1277] 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.

[1278] 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.

[1279] 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.

[1280] 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.

[1281] 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."

[1282] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, creates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[1283] Get refrigerator inventory information

[1284] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[1285] Obtaining health data based on excrement analysis

[1286] The server sends a request to the Toilet Sensor API to retrieve the data sent by the Toilet Sensor. The characteristics of the excrement analyzed by the Toilet Sensor are provided in JSON format, indicating the user's current health status, including, for example, bowel movement frequency and water content.

[1287] Dinner menu generation

[1288] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine, which analyzes this data and generates an optimal dinner menu. The generated menu takes the user's physical condition into consideration, providing a healthy and balanced meal.

[1289] Calculate and automatically purchase ingredients needed

[1290] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[1291] Specific examples

[1292] scenario

[1293] User A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[1294] tomato

[1295] chicken meat

[1296] lettuce

[1297] According to the user's toilet sensor, User A is suffering from constipation.

[1298] process

[1299] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[1300] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[1301] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[1302] {"Bow frequency": "Low", "Moisture": "Low"}

[1303] 3. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[1304] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[1305] 4. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[1306] In this way, User A can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives.

[1307] The processing flow will be explained below.

[1308] Step 1:

[1309] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator.

[1310] Step 2:

[1311] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content.

[1312] Step 3:

[1313] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The transmitted data includes inventory information and health data. The AI ​​engine uses this information to generate the optimal dinner menu.

[1314] Step 4:

[1315] The server receives the menu data returned by the AI ​​engine, which includes specific menu suggestions, such as "tomato and lettuce salad" or "grilled chicken."

[1316] Step 5:

[1317] The server calculates the ingredients needed to prepare the generated menu based on the received menu data, and checks the refrigerator's inventory to see which ingredients are in short supply.

[1318] Step 6:

[1319] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the ingredients needed. The server receives a response from the online store confirming that the order is complete.

[1320] Step 7:

[1321] The server sends the final menu and purchase results to the user's device, where the user can check today's dinner menu and whether the necessary ingredients are available. As a result, the user can prepare a healthy dinner without any hassle.

[1322] Example 1

[1323] 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."

[1324] Conventional refrigerator and health management systems often manage inventory and collect health data separately, which is insufficient for comprehensive health management. Furthermore, there were no systems that automatically generated dinner menus and automatically purchased the necessary ingredients, so users had to take the time and effort to plan their meals. Furthermore, there were no systems that properly notified users of this information and provided accurate menus, so users had to spend time and effort checking and preparing meals.

[1325] 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.

[1326] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for creating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the created menu, means for automatically purchasing the necessary ingredients, means for notifying the user's terminal of the acquired inventory information and physical condition data, and means for displaying the menu created based on the acquired inventory information and physical condition data. This allows the user to effortlessly plan a dinner menu and automatically purchase the necessary ingredients. Furthermore, the user can check the information in real time and receive support for living a healthy lifestyle.

[1327] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the types and quantities of food and ingredients in the refrigerator using sensors and cameras installed in the refrigerator.

[1328] The "means for acquiring health data based on analysis of excrement" is a means for collecting data on excrement from sensors installed in the toilet and acquiring health data on the user based on that data.

[1329] The "means for generating dinner menus" refers to a means for using an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information and health data.

[1330] The "means for calculating the necessary ingredients" is a means for identifying the necessary ingredients based on the generated dinner menu and calculating the ingredients that are lacking by checking against the inventory information.

[1331] "Means for automatically purchasing necessary ingredients" refers to a means for automatically purchasing ingredients that are in short supply using an online store's API.

[1332] The "means for notifying the user's terminal of the acquired inventory information and health data" refers to a means for notifying the user's terminal, such as a smartphone or tablet, of the inventory information and health data acquired by the server in real time.

[1333] The "means for displaying a menu created based on the acquired inventory information and physical condition data" is a means for displaying the dinner menu created by the server on the user's terminal.

[1334] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire health data, generates an appropriate dinner menu based on this information, and automatically purchases the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, a menu generation means, an ingredient calculation means, an automatic purchasing means, a means for notifying the user of this information, and a means for displaying the generated menu. Specific operations will now be described.

[1335] The server sends a request to the refrigerator's inventory API to obtain data from sensors and cameras connected to the refrigerator. The sensors and cameras detect the type and quantity of food and ingredients in the refrigerator, structure that information in JSON format, and send it to the server. For example, if the sensor detects three tomatoes, one pack of chicken, and one lettuce, the following data is obtained:

[1336] json

[1337] {

[1338] "Tomato": 3,

[1339] "chicken": 1,

[1340] "Lettuce": 1

[1341] }

[1342] The server sends a request to the Toilet Sensor API to retrieve data sent from the Toilet Sensor. The Toilet Sensor analyzes the user's waste and provides the data in JSON format, including data such as bowel movement frequency and water content.

[1343] json

[1344] {

[1345] "Bowel frequency": "low",

[1346] "Moisture": "Low"

[1347] }

[1348] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. This menu takes the user's physical condition into consideration and provides healthy, balanced meals. For example, a menu rich in dietary fiber is generated for a user who tends to be constipated.

[1349] json

[1350] {

[1351] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[1352] }

[1353] Based on the generated menu, the server checks whether the necessary ingredients are available in the refrigerator. If any of the necessary ingredients are in short supply, the server automatically purchases them using the online store's API. The server sends the information about the necessary ingredients to the online store's API and executes the purchasing process. For example, if there is a shortage of chicken, the server orders the required amount of chicken from the online store.

[1354] The server then sends the acquired inventory information, health data, and the generated menu to the user's device, allowing the user to check the dinner menu on their smartphone or tablet and ensure that all the necessary ingredients have been prepared.

[1355] For example, user A is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[1356] tomato

[1357] chicken meat

[1358] lettuce

[1359] According to the user's toilet sensor, User A is slightly constipated. The server obtains this information and analyzes it with an AI engine, generating the optimal dinner menu of "tomato and lettuce salad" and "grilled chicken." Based on this, it is determined that the necessary ingredients are already present and no additional purchases are necessary.

[1360] As an example of input to the generative AI model, we will use the following prompt:

[1361] I'd like some suggestions for dinner using winter vegetables.

[1362] Generate healthy dinner menus based on your waste data.

[1363] Suggest a dish using the tomatoes, chicken, and lettuce in your fridge.

[1364] By using this prompt, users can get specific meal suggestions from the AI ​​model. This system is very useful for many users who lead busy daily lives.

[1365] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1366] Step 1:

[1367] The server obtains data from sensors and cameras connected to the refrigerator. Specifically, the server sends a request to the refrigerator's inventory API to obtain information about the types and quantities of food and ingredients in the refrigerator. The input is the types and quantities of food and ingredients in the refrigerator, and the output is inventory information in JSON format. For example, the sensor detects three tomatoes, one pack of chicken, and one head of lettuce, and returns that information in JSON format.

[1368] json

[1369] {

[1370] "Tomato": 3,

[1371] "chicken": 1,

[1372] "Lettuce": 1

[1373] }

[1374] Step 2:

[1375] The server sends a request to the toilet sensor's API to obtain data sent from the toilet sensor. The toilet sensor analyzes the user's excrement and provides the data in JSON format. The input is excrement data, and the output is user health data. Specifically, this data includes bowel movement frequency and water content.

[1376] json

[1377] {

[1378] "Bowel frequency": "low",

[1379] "Moisture": "Low"

[1380] }

[1381] Step 3:

[1382] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The input is refrigerator inventory information and health data, and the output is the generated menu information. For example, a menu rich in dietary fiber can be generated for a user who is prone to constipation.

[1383] json

[1384] {

[1385] "menu": ["Tomato and lettuce salad", "Grilled chicken"]

[1386] }

[1387] Step 4:

[1388] The server checks whether the necessary ingredients are available in the refrigerator based on the generated menu. The input is the generated menu information and inventory information, and the output is a list of the necessary ingredients and their stock status. If a necessary ingredient is in short supply, the server automatically purchases it using the online store's API. For example, if chicken is in short supply, the server will order the required amount of chicken from the online store.

[1389] json

[1390] {

[1391] "order": "chicken"

[1392] }

[1393] Step 5:

[1394] The server notifies the terminal of the created menu and the information on ingredients that have been purchased. The input is the created menu information and the information on the completed purchase, and the output is a notification message sent to the user's terminal. This allows the user to confirm that the menu and the ingredients for it are available.

[1395] json

[1396] {

[1397] "notification": "Today's menu is 'Tomato and Lettuce Salad' and 'Grilled Chicken'. All the ingredients you need are here."

[1398] }

[1399] Through this process, users can effortlessly plan their dinner menu, automatically purchase the necessary ingredients, and prepare healthy meals. This system will significantly support users' daily lives.

[1400] (Application example 1)

[1401] 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."

[1402] In modern society, people are busy with work and daily life, making it difficult to easily prepare a healthy dinner. Managing refrigerator inventory and planning a meal plan that is appropriate for their physical condition can also take a lot of time and effort. Furthermore, the hassle of visiting a store to purchase the necessary ingredients can be a problem. There is a need for a system that can solve these issues and allow users to easily prepare a healthy, balanced dinner.

[1403] 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.

[1404] In this invention, the server includes means for acquiring inventory information from the refrigerator, means for acquiring physical condition data based on an analysis of excrement, means for generating a dinner menu based on the acquired inventory information and physical condition data, means for calculating the necessary ingredients based on the generated menu, means for automatically purchasing the necessary ingredients, and means for integrating and managing meal suggestions and ingredient delivery services based on the generated menu and purchased ingredients. This allows users to easily obtain an optimal dinner menu based on the inventory information from the refrigerator and their physical condition, and any missing ingredients are automatically purchased and delivered, allowing them to enjoy healthy meals without any effort.

[1405] The "means for obtaining inventory information in the refrigerator" refers to a means for obtaining data on the type and quantity of food in the refrigerator using sensors and cameras installed in the refrigerator.

[1406] "Means for obtaining health data based on analysis of excrement" refers to a means for analyzing the user's excrement using a sensor installed in the toilet and obtaining health data such as bowel movement frequency and water content.

[1407] The "means for generating dinner menus" refers to a means for using an AI engine to create optimal dinner menus based on the acquired refrigerator inventory information and health data.

[1408] The "means for calculating the necessary ingredients" is a means for calculating the shortage of ingredients in the refrigerator based on the generated menu, and determining the necessary ingredients.

[1409] "Means for automatically purchasing necessary ingredients" refers to a means for automatically ordering and purchasing necessary ingredients using the API of an online store or food delivery service.

[1410] The "means for integrated management of meal suggestions and ingredient delivery services" is a means for making meal suggestions to users based on the generated menu and purchased ingredients, and for centrally managing ingredient delivery.

[1411] MODE FOR CARRYING OUT THE INVENTION

[1412] The system of the present invention uses a smartphone application at its core to create an optimal dinner menu based on refrigerator inventory information and the user's physical condition data. It then automatically purchases the necessary ingredients and provides an integrated process of delivering them to the user via a food delivery service. The main processes involved in this system are described below.

[1413] Hardware and software used

[1414] Hardware:

[1415] Smartphone: Used as a user interface.

[1416] Refrigerator sensors and cameras: Used to obtain inventory information inside the refrigerator.

[1417] Toilet sensor: Used to analyze the user's waste and obtain health data.

[1418] software:

[1419] Server: The core of the application, acquiring, processing, and transmitting various data.

[1420] AI engine: Generates optimal dinner menus based on refrigerator inventory data and health data.

[1421] API: Handles data communication between the refrigerator sensor, toilet sensor, food delivery service and server.

[1422] Data processing and calculation

[1423] Get refrigerator inventory:

[1424] Data acquired from sensors and cameras installed in the refrigerator is sent to the server and interpreted in JSON format, including the type and quantity of food in the refrigerator.

[1425] Obtaining health data based on excrement analysis:

[1426] A sensor installed in the toilet analyzes the user's waste and sends the results, including bowel movement frequency and water content, to a server.

[1427] Dinner menu generation:

[1428] The server sends the acquired inventory information and health data to the AI ​​engine, which then analyzes this data and generates an optimal menu based on the user's health condition.

[1429] Calculate and auto-purchase ingredients needed:

[1430] The server calculates the ingredients needed based on the generated menu, and if any ingredients are not in the refrigerator, it automatically purchases them through the API of the food delivery service.

[1431] Meal suggestions and delivery management:

[1432] The server makes meal suggestions to the user based on the generated menu and purchased ingredient information, and also manages the ingredient delivery service in an integrated manner.

[1433] Specific examples

[1434] scenario

[1435] User A has a very busy job and does not want to spend too much time preparing dinner. User A has the following foods in his refrigerator:

[1436] tomato

[1437] chicken meat

[1438] lettuce

[1439] Additionally, data from the toilet sensor indicates that User A is constipated. Based on this information, the following prompt is generated:

[1440] "Here's what's in your refrigerator:

[1441] Tomato: 3, Chicken: 1, Lettuce: 1

[1442] Here is the user's health data:

[1443] Bowel frequency: "Low", moisture: "Low"

[1444] Based on this information, please suggest the perfect dinner menu for you.

[1445] Based on the acquired data, the AI ​​engine generates a menu including "tomato and lettuce salad" and "grilled chicken" and confirms the necessary ingredients. This system not only provides User A with the optimal dinner recommendation, but also automatically purchases and delivers the necessary ingredients, saving him a lot of time and effort.

[1446] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1447] Step 1:

[1448] Process to obtain refrigerator inventory information

[1449] The server obtains inventory information through sensors and cameras installed in the refrigerator. Specifically, it sends a request to the refrigerator's inventory API and receives JSON-formatted data including the type and quantity of food in the refrigerator. For example, this data includes "Tomatoes: 3, Chicken: 1, Lettuce: 1."

[1450] Input: Food information in the refrigerator

[1451] Output: Inventory information data in JSON format

[1452] Specific operation: The server sends a request to the refrigerator inventory API and structures the data obtained from the sensors and camera in JSON format.

[1453] Step 2:

[1454] Processing to obtain health data based on excrement analysis

[1455] The server obtains analysis data of excrement from sensors installed in the toilet. It sends a request to the toilet sensor's API and receives JSON-formatted data containing excrement characteristics. This data includes bowel movement frequency and water content, e.g., "Bow movement frequency: 'low', Water content: 'low'."

[1456] Input: fecal analysis data

[1457] Output: Physical condition data in JSON format

[1458] Specific operation: The server sends a request to the toilet sensor's API and structures the excrement analysis results obtained from the sensor in JSON format.

[1459] Step 3:

[1460] Process for generating dinner menus

[1461] The server sends the acquired refrigerator inventory information and health data to the AI ​​engine and generates the optimal dinner menu. The prompt used is, "The user's refrigerator inventory information is as follows: Tomatoes: 3, Chicken: 1, Lettuce: 1. The user's health data is as follows: Bowel frequency: 'Low', Water content: 'Low'. Please suggest the optimal dinner menu based on this information."

[1462] Input: JSON format inventory information data and health data

[1463] Output: JSON format data containing menu items

[1464] Specific operation: The server sends data to the AI ​​engine and receives the API response generated as the analysis result.

[1465] Step 4:

[1466] Process to calculate the necessary ingredients

[1467] The server calculates the ingredients needed based on the generated menu, compares it with the inventory information in the refrigerator, and identifies any ingredients that are lacking. This process generates an automatic purchasing list of ingredients.

[1468] Input: Generated menu and inventory information

[1469] Output: List of ingredients needed

[1470] Specific operation: The server compares the menu with inventory information and creates a list of ingredients that are in short supply.

[1471] Step 5:

[1472] Automatically purchase the ingredients you need

[1473] The server automatically purchases ingredients using the API of the food delivery service based on the list of ingredients that are in short supply. It sends a request to the API of the food delivery service to order the necessary ingredients and process the delivery.

[1474] Input: Missing ingredients list

[1475] Output: Ingredient purchase completion data

[1476] Specific operation: The server sends a request to the food delivery service's API, processes the purchase, and completes the delivery procedure.

[1477] Step 6:

[1478] Process to suggest meals and manage delivery

[1479] The server makes meal suggestions to users based on the generated menu and purchased ingredient information, and manages the food delivery service in an integrated manner. It notifies users of the expected arrival date of ingredients and menu details.

[1480] Input: Generated menu and purchased ingredients information

[1481] Output: User notifications and administrative information

[1482] Specific operation: The server sends notifications to the user's smartphone and manages the status of the food delivery service.

[1483] 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.

[1484] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means. Specific operations are described below.

[1485] Get refrigerator inventory information

[1486] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator, which is then structured in JSON format to indicate the type and quantity of food and ingredients present in the refrigerator.

[1487] Obtaining health data based on excrement analysis

[1488] The server sends a request to the toilet sensor's API to retrieve the data sent by the toilet sensor. The server receives the characteristics of the excrement analyzed by the toilet sensor in JSON format, which indicates the user's current health status, such as bowel movement frequency and water content.

[1489] User Emotion Recognition

[1490] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This emotion data indicates the user's emotional state (e.g., stress, joy, fatigue, etc.) and is reflected in the generation of dinner menus.

[1491] Dinner menu generation

[1492] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates an optimal dinner menu. The generated menu takes into account the user's physical condition and emotions, providing a healthy and balanced meal.

[1493] Calculate and automatically purchase ingredients needed

[1494] The server checks whether the refrigerator contains all the necessary ingredients based on the generated menu. If any ingredients are missing, it automatically purchases them using the online store's API. It sends the necessary ingredient information to the online store's API and executes the purchase process.

[1495] Specific examples

[1496] scenario

[1497] User B is busy at work and doesn't have time to prepare dinner tonight. He has the following foods in his refrigerator:

[1498] tomato

[1499] chicken meat

[1500] lettuce

[1501] According to the user's toilet sensor, User B is suffering from constipation. Furthermore, according to the emotion engine, User B is feeling stressed.

[1502] process

[1503] 1. The server retrieves inventory information via the refrigerator inventory API, resulting in the following data:

[1504] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[1505] 2. The server receives data from the toilet sensor. Analysis reveals that the user is slightly constipated:

[1506] {"Bow frequency": "Low", "Moisture": "Low"}

[1507] 3. The server obtains the user's emotional data using the emotion engine. As a result of the analysis, it finds out that User B is feeling stressed:

[1508] {"emotion": "stress"}

[1509] 4. The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken."

[1510] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[1511] 5. The server checks the ingredients needed based on the menu and finds that all ingredients are already in the refrigerator, so no additional purchases are necessary.

[1512] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[1513] The processing flow will be explained below.

[1514] Step 1:

[1515] The server sends a GET request to the refrigerator's inventory API to get the refrigerator's inventory information. The server receives the JSON data in response and analyzes the types and quantities of food and ingredients in the refrigerator. For example, the server receives the following inventory information:

[1516] {"Tomato": 3, "Chicken": 1, "Lettuce": 1}

[1517] Step 2:

[1518] The server sends a GET request to the toilet sensor's API to obtain the user's health data. The server receives the JSON data sent from the toilet sensor and checks the user's health status, such as bowel movement frequency and water content. For example, the server receives the following health data:

[1519] {"Bow frequency": "Low", "Moisture": "Low"}

[1520] Step 3:

[1521] The server uses the emotion engine to analyze the user's facial expressions and voice to recognize the user's emotions. The server obtains the emotion data from the emotion engine and checks the user's emotional state. For example, the emotion engine returns the following data:

[1522] {"emotion": "stress"}

[1523] Step 4:

[1524] The server sends the acquired refrigerator inventory information, health data, and emotion data to the AI ​​engine. The transmitted data includes inventory information, health data, and emotion data. For example, the following data is transmitted:

[1525] {

[1526] "fridge_data": {"tomato": 3, "chicken": 1, "lettuce": 1},

[1527] "toilet_data": {"Defecation frequency": "Low", "Water": "Low"},

[1528] "emotion_data": {"emotion": "stress"}

[1529] }

[1530] Step 5:

[1531] The server receives the dinner menu data returned by the AI ​​engine. The AI ​​engine analyzes the data and generates the optimal dinner menu. For example, the server receives the following menu data:

[1532] {"menu": ["Tomato and lettuce salad", "Grilled chicken"]}

[1533] Step 6:

[1534] The server calculates the ingredients needed to make the generated menu based on the received menu data. The server checks the refrigerator's inventory information. For example, if all the necessary ingredients are in the refrigerator, the server will get the following result:

[1535] {"required_ingredients": [], "status": "all ingredients available"}

[1536] Step 7:

[1537] The server sends a POST request to the online store's API to automatically purchase any missing ingredients. The request data includes a list of the missing ingredients. If all ingredients are available, the server receives a result indicating that no additional purchases are necessary. For example, the server might receive a response like this:

[1538] {"purchase_status": "no purchase needed"}

[1539] Step 8:

[1540] The server sends the final menu and purchase results to the user's device. The user can then check today's dinner menu and whether the necessary ingredients are available. For example, the server provides the user with the following information:

[1541] {"Today's Dinner Menu": ["Tomato and Lettuce Salad", "Grilled Chicken"], "Purchase Result": "I have all the ingredients I need."}

[1542] In this way, users can prepare a healthy dinner without much effort.In addition, the introduction of an emotion engine will suggest optimal menus based on the user's emotional state, which will also help with maintaining physical and mental health.

[1543] Example 2

[1544] 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."

[1545] Conventional dinner menu suggestion systems often generate menus without considering the user's health or emotional state, making it difficult to suggest a menu that is optimal for each user's physical condition and psychological state. Furthermore, because ingredients are purchased based solely on refrigerator inventory, unnecessary ingredients may be purchased or an appropriate nutritional balance may not be ensured. Therefore, there is a need for a system that can improve users' health management and psychological satisfaction.

[1546] 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.

[1547] In this invention, the server includes a means for acquiring refrigerator inventory information, a means for acquiring physical condition data based on an analysis of excrement, and a means for acquiring emotional data. This makes it possible to generate a dinner menu based on the acquired inventory information, physical condition data, and emotional data. Specifically, an AI engine is used to analyze various data, suggest an optimal menu for the user, and automatically purchase any missing ingredients using an online store's API, thereby achieving personalized support based on the user's health and emotional state.

[1548] A "means for acquiring inventory information in a refrigerator" is a device or system that uses sensors or cameras installed in the refrigerator to detect the type and quantity of food or ingredients in the refrigerator and acquires that data.

[1549] A "means for acquiring health data based on analysis of excrement" is a device or system that uses sensors or analytical devices connected to the toilet to analyze the characteristics of excrement and acquire data on the user's health condition.

[1550] The "means for acquiring emotional data" is a device or system that acquires data relating to the emotional state of a user using an emotion recognition engine that analyzes the user's facial expressions and voice.

[1551] The "means for generating dinner menus" refers to a device or system that uses an AI engine to generate optimal dinner menus based on the acquired refrigerator inventory information, physical condition data, and emotional data.

[1552] The "means for calculating the necessary ingredients" is a device or system that calculates the number of necessary ingredients based on the generated menu and in conjunction with the inventory information in the refrigerator.

[1553] A "means for automatically purchasing the necessary ingredients" is a device or system that uses the online store's API to automatically order the necessary ingredients and complete the purchase process.

[1554] The phrase "the means for generating a dinner menu transmits the acquired inventory information, physical condition data, and emotional data to the AI ​​engine" means that information about ingredients in the user's refrigerator, the user's health condition, and emotional state are provided to the AI ​​engine.

[1555] The phrase "purchase the necessary ingredients using the online store's API" means automatically ordering the missing ingredients using the online store's application program interface and completing the delivery procedure.

[1556] The system of the present invention acquires refrigerator inventory information, analyzes the user's excrement to acquire physical condition data, and combines this information with an emotion engine that recognizes the user's emotions to create an appropriate dinner menu and automatically purchase the necessary ingredients. This system includes a refrigerator inventory information acquisition means, an excrement analysis means, an emotion recognition means, a menu creation means, an ingredient calculation means, and an automatic purchasing means.

[1557] Get refrigerator inventory information

[1558] The server sends a request to the refrigerator's inventory API to retrieve data from sensors and cameras connected to the refrigerator. The retrieved inventory data is structured in JSON format and indicates the types and quantities of food and ingredients present in the refrigerator. For example, the server sends an HTTP request to the refrigerator API, and the refrigerator API returns inventory data to the server. This data is stored on the server and used in the processes described below.

[1559] Obtaining health data based on excrement analysis

[1560] The server sends a request to the toilet sensor's API to retrieve data sent from the toilet sensor. Health data based on the characteristics of excrement provided by the toilet sensor is also provided to the server in JSON format. The server retrieves this data and stores the analysis results on the server.

[1561] User Emotion Recognition

[1562] The server recognizes the user's emotions using an emotion engine. The emotion engine analyzes the user's facial expressions and voice via a webcam or microphone to generate emotion data. The emotion engine generates data indicating the user's emotional state (e.g., stress, joy, fatigue, etc.) and provides it to the server. The server stores this data.

[1563] Dinner menu generation

[1564] The server sends this acquired information (refrigerator inventory information, physical condition data, and emotional data) to the AI ​​engine, which then generates an optimal dinner menu. The AI ​​engine analyzes this data and proposes a balanced and healthy dinner menu. The generated menu takes into account the user's physical condition and emotions, and is presented to the user by the server.

[1565] Calculate and automatically purchase ingredients needed

[1566] The server checks whether the necessary ingredients based on the generated menu are available in the refrigerator. If necessary ingredients are not available, the server automatically purchases them using the online store's API. The online store API orders the necessary ingredients and executes the purchase process.

[1567] Specific examples

[1568] scenario

[1569] User B is busy at work and doesn't have time to prepare dinner tonight. There are tomatoes, chicken, and lettuce in the refrigerator. According to the toilet sensor, User B is constipated. Furthermore, according to the emotion engine, User B is feeling stressed.

[1570] process

[1571] The server retrieves inventory information via the refrigerator API, resulting in the following data:

[1572] Tomato: 3

[1573] Chicken: 1

[1574] Lettuce: 1

[1575] The server receives data from the toilet sensor and analyzes it to find out that the user is constipated:

[1576] Bowel movement frequency: Low

[1577] Moisture: low

[1578] The server obtains the user's emotional data using the emotion engine, and as a result of the analysis, it obtains information that User B is feeling stressed:

[1579] Emotion: Stress

[1580] The server sends this data to the AI ​​engine, and the resulting menu is "Tomato and lettuce salad" and "Grilled chicken":

[1581] menu: [ "Tomato and lettuce salad", "Grilled chicken" ]

[1582] The server will check the ingredients needed based on the menu, and since all ingredients are already in the refrigerator, no additional purchases are necessary.

[1583] In this way, User B can prepare a healthy dinner without much effort. This system is very useful for many users who lead busy daily lives. Furthermore, by suggesting menus based on the user's emotional state, it can support their physical and mental health.

[1584] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1585] Step 1:

[1586] Get refrigerator inventory information

[1587] The server sends a request to the refrigerator's inventory API to retrieve inventory data from sensors and cameras connected to the refrigerator. This request uses the HTTP GET method, and the refrigerator API returns data in JSON format. The input includes the current status of food and ingredients in the refrigerator, and the output is inventory data in JSON format. This data is stored in a database on the server and used for subsequent processing.

[1588] Specific behavior:

[1589] 1. The server generates an HTTP request and sends it to the refrigerator inventory API.

[1590] 2. The refrigerator API receives the request and sends the inventory data back to the server in JSON format.

[1591] 3. The server stores the received JSON data in the database.

[1592] Step 2:

[1593] Obtaining health data based on excrement analysis

[1594] The server sends a request to the Toilet Sensor API to retrieve the excrement data sent from the Toilet Sensor. This request also uses the HTTP GET method. The Toilet Sensor API returns excrement characteristic data in JSON format. The input contains the user's excrement data, and the output is analyzed health data. This data is also stored in the server's database.

[1595] Specific behavior:

[1596] 1. The server generates an HTTP request and sends it to the Toilet Sensor API.

[1597] 2. The Toilet Sensor API receives the request and returns the excrement data in JSON format to the server.

[1598] 3. The server analyzes the received data and stores it in a database.

[1599] Step 3:

[1600] Obtaining user emotion data

[1601] The server uses an emotion engine to obtain emotion data from the user's facial expressions and voice. To do this, the server sends data obtained from a webcam or microphone to the emotion engine and receives the analysis results. The input includes images of the user's facial expressions and voice data, and the output is data indicating the user's emotional state. This data is also stored in a database.

[1602] Specific behavior:

[1603] 1. The server acquires the user's facial expression images and voice data.

[1604] 2. The server sends these data to the emotion engine.

[1605] 3. The emotion engine analyzes the data and sends data indicating the emotional state back to the server.

[1606] 4. The server stores the received data in a database.

[1607] Step 4:

[1608] Generate a dinner menu

[1609] The server sends the acquired refrigerator inventory information, physical condition data, and emotional data to the AI ​​engine. The AI ​​engine analyzes this data and generates the optimal dinner menu. The inputs include inventory information, physical condition data, and emotional data, and the output is menu data. The generated menu is notified to the user by the server.

[1610] Specific behavior:

[1611] 1. The server sends refrigerator inventory information, health data, and emotional data to the AI ​​engine.

[1612] 2. The AI ​​engine analyzes this data and generates the optimal dinner menu.

[1613] 3. The server receives the generated menu data and notifies the user.

[1614] Step 5:

[1615] Calculate and automatically purchase ingredients needed

[1616] The server checks whether the refrigerator has all the necessary ingredients based on the generated menu. If any ingredients are missing, the server automatically purchases them using the online store's API. The inputs include menu data and inventory data, and the output is a list of missing ingredients and a purchase procedure.

[1617] Specific behavior:

[1618] 1. The server compares the generated menu with the inventory information in the refrigerator and lists the necessary ingredients.

[1619] 2. If any ingredients are missing, the server sends a request to the online store API to purchase the ingredients.

[1620] 3. The server receives the results of the purchase and stores them in a database.

[1621] (Application example 2)

[1622] 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."

[1623] In today's busy lifestyles, it is difficult for users to easily prepare healthy, balanced meals. Furthermore, it takes time and effort to check and purchase each ingredient needed for meal preparation, and it is even more difficult to consider the user's physical condition and emotions. This often leads to inadequate nutrition and makes it difficult to maintain health. Even when users shop in physical stores, efficiently gathering the necessary ingredients is extremely time-consuming. To solve these problems, there is a need for an automatic menu generation and ingredient purchasing support system that takes into account the user's health and emotions.

[1624] 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.

[1625] In this invention, the server includes means for acquiring refrigerator inventory information, means for acquiring physical condition data based on an analysis of excrement, means for recognizing the user's facial expression and acquiring emotional data, means for generating a dinner menu based on the acquired inventory information, physical condition data, and emotional data, means for calculating the necessary ingredients based on the generated menu, and means for automatically purchasing the necessary ingredients. This enables the preparation of healthy and balanced meals that take the user's physical condition and emotions into consideration. Furthermore, automating the purchase of necessary ingredients significantly reduces the effort and time required for shopping. Furthermore, when a user is shopping in a physical store, the in-store map API can be used to efficiently guide the user to the necessary ingredients.

[1626] "Refrigerator inventory information" refers to information about the types and quantities of food and ingredients stored in the refrigerator.

[1627] "Physical condition data" is data relating to the health condition of the user obtained based on an analysis of the user's excrement.

[1628] "Emotion data" is data that indicates the emotional state of the user recognized by analyzing the user's facial expressions and voice.

[1629] The "means for generating a menu" is a means for calculating an optimal dinner menu based on the acquired inventory information, physical condition data, and emotion data.

[1630] The "means for calculating the necessary ingredients" refers to a means for identifying the necessary ingredients based on the generated menu by checking against the inventory information in the refrigerator and calculating the shortage.

[1631] "Means for automatic purchasing" refers to means for automatically purchasing or providing guidance on the necessary ingredients using the online store's API or in-store map API.

[1632] The "Store Map API" is an API that provides a guide for users to efficiently find the ingredients they need in physical stores.

[1633] The system for implementing this invention acquires refrigerator inventory information, analyzes the user's waste to acquire health data, and recognizes the user's facial expressions to acquire emotional data, then creates an optimal dinner menu based on this information, calculates the necessary ingredients, and automatically purchases the necessary ingredients.

[1634] This system consists of a means for acquiring data from sensors and cameras placed in the refrigerator, a means for acquiring data from sensors installed in the toilet, a means for recognizing the user's facial expressions using a camera on a smartphone or smart glasses, a means for generating menus using an AI engine based on this data, a means for calculating the necessary ingredients based on the generated menu, and a means for automatically purchasing or providing guidance on the necessary ingredients using an online store API or an in-store map API.

[1635] For example, when a user goes shopping at a physical store, the system first obtains inventory information from a sensor connected to the refrigerator. This data is sent to the server in JSON format, and the types and quantities of food and ingredients in the refrigerator are identified. Next, data is obtained from the toilet sensor and the user's physical condition data is analyzed. This provides the user's health status, such as bowel movement frequency and water content. Furthermore, the system captures the user's facial expressions using a camera on a smartphone or smart glasses, and obtains the user's emotional data through an emotion engine. Emotional data includes information such as the stress, joy, and fatigue the user is feeling.

[1636] This data is sent to an AI engine to generate an optimal dinner menu. The generated menu is healthy and balanced, taking into account the user's physical condition and emotions. The system then calculates the ingredients needed based on the generated menu and checks it against the inventory information in the refrigerator to identify any shortages. The system uses the online store's API to automatically purchase the necessary ingredients. When the user makes a purchase in a physical store, the system also uses the in-store map API to guide them to the location of product shelves.

[1637] As a concrete example, consider the case where User A is shopping at a supermarket. There are tomatoes, chicken, and lettuce in the refrigerator, but User A is feeling constipated and a little stressed. The system sends this information to the AI ​​engine, which suggests "tomato and lettuce salad" and "grilled chicken" as the optimal menu. It then uses the in-store map API to guide User A to the specific shelf locations where he should purchase the salad and chicken.

[1638] Examples of prompts include:

[1639] 1. Get the latest inventory data from the refrigerator API.

[1640] 2. Get the user's latest health data from the health management app API.

[1641] 3. Capture the user's facial expressions with the camera and use the emotion engine to obtain emotion data.

[1642] 4. Use the AI ​​engine to suggest the best products based on the inventory, health, and emotion data you have acquired.

[1643] 5. Use Maps API to show the location of the suggested products in the store.

[1644] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1645] Step 1:

[1646] The server obtains inventory information from sensors and cameras connected to the refrigerator.

[1647] Input: Data from refrigerator inventory sensors and cameras

[1648] Data processing: Convert to JSON format

[1649] Output: Data on the type and quantity of food and ingredients in the refrigerator

[1650] Specific operation: The server sends a request to the refrigerator inventory API and parses the retrieved data in JSON format.

[1651] Step 2:

[1652] The server acquires the data sent from the toilet sensor and analyzes the user's physical condition data.

[1653] Input: Excrement data from toilet sensor

[1654] Data processing: Convert to JSON format

[1655] Output: User's health data such as bowel movement frequency and water content

[1656] Specific operation: The server sends a request to the toilet sensor's API and parses the acquired data in JSON format.

[1657] Step 3:

[1658] The device captures the user's facial expressions using a camera on a smartphone or smart glasses and obtains emotional data through an emotion engine.

[1659] Input: Image data from a smartphone or smart glasses camera

[1660] Data processing: Generating emotion data through facial expression analysis

[1661] Output: Emotional data such as stress, joy, fatigue, etc.

[1662] Specific operation: The device captures the user's facial expressions with a camera and sends the data to the emotion engine to obtain analysis results.

[1663] Step 4:

[1664] The server sends the acquired inventory information, health data, and emotional data to the AI ​​engine to generate a dinner menu.

[1665] Input: inventory data, physical condition data, emotional data

[1666] Data processing: Menu generation using AI models

[1667] Output: Optimal dinner menu

[1668] Specific operation: The server sends this data to the AI ​​engine as a single request and receives menu suggestions.

[1669] Step 5:

[1670] The server calculates the ingredients needed based on the generated menu and identifies any ingredients that are lacking.

[1671] Input: Menu data, inventory data

[1672] Data processing: Checking against inventory data and identifying shortages

[1673] Output: List of ingredients needed

[1674] Specific operation: The server compares the ingredients required for the generated menu with the inventory in the refrigerator and lists the necessary ingredients.

[1675] Step 6:

[1676] The server automatically purchases the necessary ingredients through an online store API, or when the user purchases at a physical store, it uses an in-store map API to guide the user to the location within the store.

[1677] Input: List of ingredients needed

[1678] Data processing: Data generation for purchase requests or location guidance

[1679] Output: Purchase instructions for online stores or in-store location guidance

[1680] Specific operation: The server sends the necessary ingredient information to the online store API and automatically purchases it. If the user purchases at a physical store, the server uses the store's map API to guide the user to the location of the necessary ingredients.

[1681] 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.

[1682] 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.

[1683] 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 robot 414.

[1684] 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.

[1685] 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.

[1686] 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.

[1687] 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).

[1688] 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.

[1689] 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."

[1690] 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.

[1691] 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).

[1692] 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.

[1693] 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.

[1694] 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.

[1695] 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.

[1696] 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.

[1697] 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.

[1698] 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.

[1699] 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.

[1700] 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.

[1701] 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.

[1702] The following is further disclosed regarding the above embodiment.

[1703] (Claim 1)

[1704] A means for acquiring inventory information in a refrigerator;

[1705] A means for acquiring physical condition data based on an analysis of excrement;

[1706] A means for generating a dinner menu based on the acquired inventory information and physical condition data;

[1707] A means for calculating necessary ingredients based on the generated menu;

[1708] A means to automatically purchase the ingredients you need,

[1709] A system including:

[1710] (Claim 2)

[1711] The system according to claim 1, characterized in that the means for generating the dinner menu transmits the acquired inventory information and physical condition data to an AI engine and determines the menu based on a response from the AI ​​engine.

[1712] (Claim 3)

[1713] 2. The system according to claim 1, wherein the means for automatically purchasing ingredients uses an API of an online store to purchase the necessary ingredients.

[1714] "Example 1"

[1715] (Claim 1)

[1716] A means for acquiring inventory information in a refrigerator;

[1717] A means for acquiring physical condition data based on an analysis of excrement;

[1718] A means for generating a dinner menu based on the acquired inventory information and physical condition data;

[1719] A means for calculating necessary ingredients based on the generated menu;

[1720] A means to automatically purchase the ingredients you need,

[1721] means for notifying the acquired inventory information and physical condition data to a user's terminal;

[1722] A means for displaying a menu created based on the acquired inventory information and physical condition data;

[1723] A system including:

[1724] (Claim 2)

[1725] The system according to claim 1, characterized in that the means for generating the dinner menu transmits the acquired inventory information and physical condition data to an AI engine and determines the menu based on a response from the AI ​​engine.

[1726] (Claim 3)

[1727] 2. The system according to claim 1, wherein the means for automatically purchasing ingredients uses an API of an online store to purchase the necessary ingredients.

[1728] "Application Example 1"

[1729] (Claim 1)

[1730] A means for acquiring inventory information in a refrigerator;

[1731] A means for acquiring physical condition data based on an analysis of excrement;

[1732] A means for generating a dinner menu based on the acquired inventory information and physical condition data;

[1733] A means for calculating necessary ingredients based on the generated menu;

[1734] A means to automatically purchase the ingredients you need,

[1735] A means for integrating and managing meal suggestions and food delivery services based on the generated menu and purchased ingredients;

[1736] A system including:

[1737] (Claim 2)

[1738] The system according to claim 1, characterized in that the means for generating the dinner menu transmits the acquired inventory information and physical condition data to an AI engine and determines the menu based on a response from the AI ​​engine.

[1739] (Claim 3)

[1740] 2. The system according to claim 1, wherein the means for automatically purchasing ingredients purchases the necessary ingredients using an API of an ingredient delivery service.

[1741] "Example 2: Combining Emotion Engines"

[1742] (Claim 1)

[1743] A means for acquiring inventory information in a refrigerator;

[1744] A means for acquiring physical condition data based on an analysis of excrement;

[1745] A means for acquiring emotion data;

[1746] A means for generating a dinner menu based on the acquired inventory information, physical condition data, and emotional data;

[1747] A means for calculating necessary ingredients based on the generated menu;

[1748] A means to automatically purchase the ingredients you need,

[1749] A system including:

[1750] (Claim 2)

[1751] The system according to claim 1, characterized in that the means for generating the dinner menu transmits the acquired inventory information, physical condition data and emotional data to an AI engine, and determines the menu based on the response from the AI ​​engine.

[1752] (Claim 3)

[1753] 2. The system according to claim 1, wherein the means for automatically purchasing ingredients uses an API of an online store to purchase the necessary ingredients.

[1754] "Application example 2 when combining emotion engines"

[1755] (Claim 1)

[1756] A means for acquiring inventory information in a refrigerator;

[1757] A means for acquiring physical condition data based on an analysis of excrement;

[1758] means for recognizing a user's facial expression and acquiring emotion data;

[1759] A means for generating a dinner menu based on the acquired inventory information, physical condition data, and emotion data;

[1760] A means for calculating necessary ingredients based on the generated menu;

[1761] A means to automatically purchase the ingredients you need,

[1762] A system including:

[1763] (Claim 2)

[1764] The system of claim 1, characterized in that the means for generating the dinner menu transmits the acquired inventory information, physical condition data, and emotional data to an AI engine and determines the menu based on the response from the AI ​​engine.

[1765] (Claim 3)

[1766] The system described in claim 1, characterized in that when a user makes a purchase at a physical store, the means for automatically purchasing the ingredients uses an in-store map API to guide the user to the necessary ingredients. [Explanation of symbols]

[1767] 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 acquiring inventory information in a refrigerator; A means for acquiring physical condition data based on an analysis of excrement; A means for generating a dinner menu based on the acquired inventory information and physical condition data; A means for calculating necessary ingredients based on the generated menu; A means to automatically purchase the ingredients you need, A system including:

2. The system according to claim 1, characterized in that the means for generating the dinner menu transmits the acquired inventory information and physical condition data to an AI engine and determines the menu based on a response from the AI ​​engine.

3. 2. The system according to claim 1, wherein the means for automatically purchasing ingredients purchases the necessary ingredients using an API of an online store.

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