System

Abstract

A system is provided.SOLUTION: This system includes a means for receiving address data of a user, a means for collecting price information on the Internet, a means for integrating the collected price data and calculating the cheapest menu, and a means for proposing and displaying the cheapest menu to the user.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] As prices continue to rise, many families are finding it difficult to afford food. This problem is particularly pronounced among low-income households, who are seeking concrete help to reduce their monthly food expenses, even if only slightly. Finding effective ways to save money is difficult, and gathering information takes time, so a means to automate this process and provide efficient support is needed. [Means for solving the problem]

[0005] The present invention relates to a system that receives a user's address data and collects price information from nearby stores and restaurants on the Internet based on that address. It includes a means for integrating the collected price data, calculating the cheapest menu, and presenting it to the user. It also includes a means for negotiating on behalf of the user according to their wishes, further reducing food costs. In this way, it is possible to provide users with an efficient and optimal way to reduce food costs.

[0006] "Address data" is information indicating the location of the user's home, and is used as a base point for the system to collect price information.

[0007] "Price information" is data that includes current sales prices and campaign information for products and services, and is collected from stores such as supermarkets and restaurants.

[0008] "Means of collection" refers to the methods and technologies used to obtain price information from each store or restaurant via the Internet, and are used by the system to provide users with the latest information.

[0009] "Integration" refers to the process of combining multiple collected price data into a single data set to derive the most appropriate option.

[0010] "Cheapest Menu" refers to the most cost-effective meal plan or dish suggestion calculated based on collected price information.

[0011] "Means for suggesting and displaying" refers to methods and techniques for conveying the cheapest menu and purchasing information to users, and is usually provided in the form of a display on the terminal screen.

[0012] "Proxy negotiation" refers to the function and process by which the system negotiates directly with stores and restaurants at the user's request to obtain even cheaper terms. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The system according to the present invention is designed to help users save money on food by suggesting the cheapest menu items based on their address data. This system is mainly composed of a server, a user terminal, and user operations.

[0035] Server-side processing

[0036] 1. Obtaining user address data

[0037] The server receives the home address data sent from the user terminal and analyzes it.

[0038] For example: "When a user enters an address into the app, the server receives and parses the information."

[0039] 2. Collecting information from the Internet

[0040] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address using web crawling and other techniques.

[0041] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[0042] 3. Price data integration and lowest price menu calculation

[0043] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[0044] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[0045] 4. Lowest price menu suggestions

[0046] Based on the calculation results, the server generates data suggesting the cheapest menu and specific purchasing information to the user, and transmits this to the user's terminal.

[0047] Example: "The server creates a list of the cheapest menu items and their purchases, and sends it to the user's terminal."

[0048] Terminal side processing

[0049] 1. Displaying the user interface

[0050] The terminal displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[0051] Example: "The device presents the user with an address entry form as the initial screen of the app."

[0052] 2. Send input data

[0053] When the user enters address data, the terminal transmits the data to the server.

[0054] Example: "The user enters an address and the device sends the data to the server."

[0055] 3. Receiving and displaying the proposal menu

[0056] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[0057] Example: "The device displays the curry recipe received from the server and lists the ingredients needed and where to purchase them."

[0058] User operation

[0059] 1. Enter your address

[0060] The user enters their home address into the app, and the information is sent by the device to the server.

[0061] Example: "The user opens the app and enters their home address into the address form."

[0062] 2. Check the cheapest menu

[0063] The user checks the cheapest menu and purchasing information proposed by the server and decides whether to purchase.

[0064] Example: "The user sees the ingredients list for the curry and the price at the nearest supermarket before deciding to buy it."

[0065] Specific examples

[0066] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at WinMart and carrots costing 50 yen at Supermarket A. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[0067] This system allows users to save money on food efficiently and hassle-free.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] Launching the application

[0071] User

[0072] The user launches the food cost saving tool app on their smartphone or PC.

[0073] Example: "A user launches a food cost savings app."

[0074] Step 2:

[0075] Enter your address

[0076] User

[0077] The user enters their home address into the app's address form.

[0078] Example: "A user enters their home address into an address form."

[0079] Terminal

[0080] Prepare to send the entered address data to the server.

[0081] Example: "The terminal prepares the address data entered by the user for transmission to the server."

[0082] Step 3:

[0083] Sending address data

[0084] Terminal

[0085] The address data is sent to the server.

[0086] Example: "The device sends the address data to the server."

[0087] Step 4:

[0088] Receiving and parsing address data

[0089] server

[0090] Receives address data sent from the terminal and analyzes it.

[0091] Example: "The server receives and analyzes the address data sent from the device."

[0092] Step 5:

[0093] Internet information gathering

[0094] server

[0095] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[0096] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[0097] Step 6:

[0098] Price data integration and lowest price menu calculation

[0099] server

[0100] Integrate collected pricing data to calculate the most cost-effective menu.

[0101] Example: "The server aggregates the price data and calculates the cheapest dinner menu for the day."

[0102] Step 7:

[0103] Generate proposal data for the cheapest menu

[0104] server

[0105] Based on the integration and calculation results, data suggesting the cheapest menu is generated.

[0106] Example: "The server creates a list of the cheapest menu items and their purchases."

[0107] Step 8:

[0108] Submitting proposal data

[0109] server

[0110] The proposal data is transmitted to the user terminal.

[0111] Example: "The server sends the proposal data to the user's device."

[0112] Step 9:

[0113] Receiving and displaying suggestion menus

[0114] Terminal

[0115] The proposed data transmitted from the server is received and displayed to the user.

[0116] Example: "The device displays the received lowest price menu and purchase information to the user."

[0117] Step 10:

[0118] Review and select the suggestions

[0119] User

[0120] Check the suggested lowest price menu and purchasing information to make the best choice.

[0121] For example: "The user reviews the presented materials list and prices and then decides to purchase."

[0122] Example 1

[0123] 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."

[0124] In the past, in order to save on food costs, users had to personally research multiple retail stores and online stores, compare prices, and identify the most cost-effective source of purchase. This required time and effort, and was particularly cumbersome when purchasing everyday ingredients. There was a need for a system that could improve this situation and enable users to efficiently save on food costs.

[0125] 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.

[0126] In this invention, the server includes means for receiving and analyzing the user's address data, means for collecting price information of nearby stores over the Internet based on the address data, and means for integrating the collected price data to calculate the most cost-effective menu. This allows the user to automatically collect price information of nearby stores and propose the cheapest menu by simply inputting their address, thereby enabling efficient savings on food costs.

[0127] "Address data" indicates the location information or address of the user's home as input by the user.

[0128] "Sales outlet" is a general term for places that provide price information, such as supermarkets, stores that sell food, or restaurants.

[0129] "Price information" is data relating to the prices of products sold at each store.

[0130] A "menu" is a list of ingredients needed for a particular meal and the dishes that use them.

[0131] "Suggestion" is the act of showing the user the best option based on collected information.

[0132] "Analysis" means converting received data into an understandable format and understanding its contents.

[0133] "Collection" means gathering the necessary information via the Internet.

[0134] "Integration" means combining multiple pieces of data into one and making it possible to analyze it as a whole.

[0135] "Cost-effectiveness" refers to the state in which maximum effect can be obtained with minimum cost.

[0136] "Proposal data" is data generated by the server that includes the cheapest menu and information on where to purchase it.

[0137] The present invention is a system that supports food cost savings by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[0138] First, the user enters their home address into the application. This application runs on the user's device and provides an address input form through a user interface. When the user enters the address and presses the submit button, the device sends the address data to the server.

[0139] The server receives and analyzes the address data sent from the user's device. The analyzed address data is used to collect price information from nearby stores via the Internet. Specifically, a web crawler is used to obtain the latest price information from each store's website. The web crawler used here can be a general web scraping tool.

[0140] The collected price information is integrated within the server, and the next step is to calculate the most cost-effective menu. The server analyzes the collected price data and integrates data from multiple stores. For example, price information from supermarkets and restaurants near the address specified by the user is integrated, and the cheapest menu is calculated taking into account special sales and inventory status.

[0141] The calculated cheapest menu item and its specific purchasing location information are generated as data on the server side and sent back to the user's device. The user device receives this data and displays it to the user in an intuitive and easy-to-understand format. For example, it may display something like "potatoes are 100 yen at supermarket A, and carrots are 50 yen at supermarket B."

[0142] Based on the information provided, users can decide which inventory to purchase and at which store. This system allows users to save on food costs efficiently and without hassle.

[0143] Specific examples

[0144] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at one supermarket and carrots costing 50 yen at another. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[0145] Using ChatGPT as a generative AI model, specific explanatory text can be generated using the following prompt text:

[0146] Example prompt sentence:

[0147] "This system suggests the cheapest menu items based on the user's address data, helping them save on food expenses. The server-side process first receives and analyzes the address data sent from the user's device. Next, it crawls the web to collect price information from supermarkets and restaurants around the specified address. It integrates the collected price data, calculates the most cost-effective menu items, and suggests them to the user. The device-side process displays a user interface, sends the address data to the server, and receives and displays the cheapest menu items. User operations include entering the address and confirming the cheapest menu items. For example, if the user lives in Shinjuku Ward, Tokyo, the server will collect price information from supermarkets and restaurants around Shinjuku Ward and provide a list of ingredients for the most cost-effective curry."

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1:

[0150] Enter and submit address data

[0151] Input: The user enters their home address into the device's address input form.

[0152] Specific operation: The terminal displays an address input form through the user interface, and the user inputs his / her address.

[0153] Data processing / calculation: The device converts the address data into JSON format and sends it to the server.

[0154] Output: Address data is sent to the server in JSON format.

[0155] For example, when a user inputs "Shinjuku-ku, Tokyo" and presses the send button, the terminal transmits the data to the server as a POST request.

[0156] Step 2:

[0157] Receiving and parsing address data

[0158] Input: Address data sent from the terminal.

[0159] Specific operation: The server receives data sent from the user terminal.

[0160] Data processing / calculation: The server parses the received address data in JSON format and stores it in an internal database.

[0161] Output: Parsed address data is saved in a database.

[0162] For example, address data such as "Shinjuku-ku, Tokyo" is parsed in JSON format and stored in a database.

[0163] Step 3:

[0164] Gathering price information from nearby stores

[0165] Input: Parsed address data.

[0166] Specific operation: The server launches a web crawler and collects price information for nearby stores based on the address data.

[0167] Data processing / calculation: The web crawler accesses the specified websites and extracts price information from HTML pages. The extracted information is converted into JSON format and sent to the server.

[0168] Output: Price information of nearby stores is collected in JSON format.

[0169] For example, sales information for nearby supermarkets and coupon information for restaurants is collected and sent to the server in JSON format.

[0170] Step 4:

[0171] Price data integration and lowest price menu calculation

[0172] Input: Collected pricing information.

[0173] Specific operation: The server retrieves the collected price data from the database and consolidates it.

[0174] Data processing / calculation: Based on the combined data, an algorithm is run to generate the lowest-priced ingredient list, taking into account special offers and availability.

[0175] Output: Cheapest menu and where to buy information.

[0176] For example, it can integrate price data for potatoes and carrots collected from multiple supermarkets to calculate the cheapest curry recipe.

[0177] Step 5:

[0178] Propose and send the cheapest menu

[0179] Input: Cheapest menu and where to buy information.

[0180] Specific operation: Based on the calculation results, the server generates data to suggest to the user.

[0181] Data processing / calculation: Generate the cheapest menu and its purchase list in HTML or JSON format.

[0182] Output: The proposed data is sent to the user device.

[0183] For example, proposal data including information that potatoes cost 100 yen at one supermarket and carrots cost 50 yen at another supermarket is generated and sent to the user terminal.

[0184] Step 6:

[0185] Receiving and displaying suggestion menus

[0186] Input: Proposal data sent by the server.

[0187] Specific operation: The terminal receives the cheapest menu suggestion data sent from the server.

[0188] Data processing / calculation: Analyzes the received data and displays it in a form that is easy for the user to understand.

[0189] Output: The cheapest menu and purchasing information will be displayed on the device.

[0190] For example, the user terminal displays a curry recipe received from the server and presents it to the user in the form of potatoes costing 100 yen and carrots costing 50 yen.

[0191] (Application example 1)

[0192] 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."

[0193] With conventional food delivery services, users had to go through the trouble of comparing multiple services and stores to find the cheapest menu, making it difficult to effectively reduce food costs.In addition, price information was not updated in real time, making it difficult to suggest optimal menu items based on the latest price information.

[0194] 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.

[0195] In this invention, the server includes means for receiving user address data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for proposing and displaying the cheapest menu to the user, means for collecting price information of delivery services based on the user's address, and means for providing options for placing a delivery order. This saves the user the trouble of comparing price information of multiple services and stores, and allows the user to receive suggestions for the cheapest menu in real time, enabling efficient savings on food costs.

[0196] The "means for receiving user address data" refers to a method by which a user inputs his or her address information and the system receives it.

[0197] "Methods for collecting price information on the Internet" refers to methods for obtaining price information for goods and services from websites and online databases.

[0198] The "means of integrating collected price data to calculate the cheapest menu" is a method of aggregating price information obtained from multiple data sources and calculating the lowest cost menu based on that information.

[0199] The "means for proposing and displaying the cheapest menu to the user" is a method for presenting the calculated cheapest menu and information on where to purchase it to the user.

[0200] "Means for collecting price information for delivery services based on the user's address" refers to a method for collecting price information for delivery services available in the vicinity from stores or services that provide such information based on the user's address information.

[0201] The "means for providing an option to place a delivery order" is a method for providing a function for a user to directly place a delivery order based on the suggested cheapest menu item.

[0202] The present invention is a system that aims to efficiently reduce food costs by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[0203] Server-side processing

[0204] 1. Obtaining user address data

[0205] The server receives address data entered by the user from the device. For example, when a user enters their home address into a smartphone app, the information is sent to the server and analyzed.

[0206] 2. Collecting information from the Internet

[0207] The server uses the received address data to collect price information for delivery services (restaurants and supermarkets) near the user's address. This information is collected using techniques such as web crawling.

[0208] 3. Price data integration and lowest price menu calculation

[0209] The server aggregates the collected price data and calculates the most cost-effective delivery options, taking into account product availability and special offers at each store.

[0210] 4. Lowest price menu suggestions

[0211] Based on the calculation results, the server proposes the cheapest menu and specific delivery purchasing information to the user, and sends this data to the user's terminal.

[0212] Terminal side processing

[0213] 1. Displaying the user interface

[0214] The device (such as a smartphone) displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[0215] 2. Send input data

[0216] When the user enters address data, the terminal transmits the data to the server.

[0217] 3. Receiving and displaying the proposal menu

[0218] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[0219] 4. Delivery ordering options

[0220] The device will offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to order directly from the app and save money on food.

[0221] User operation

[0222] 1. Enter your address

[0223] The user enters their home address into the app, and the information is sent by the device to the server.

[0224] 2. Check the cheapest menu and order

[0225] The user checks the cheapest menu and purchasing information suggested by the server, and places a delivery order based on the suggested menu.

[0226] Specific examples

[0227] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information for delivery restaurants in the Shinjuku area. The server will then calculate the most cost-effective delivery menu and generate a detailed ingredient list and pricing information for the nearest delivery service. Based on this information, users can place a delivery order directly, effectively saving money on food.

[0228] Hardware and software used

[0229] Hardware: Smartphone

[0230] Software: Python, Requests, BeautifulSoup

[0231] Prompt Sentence Examples

[0232] "Enter your address: Shinjuku-ku, Tokyo. I'd like to calculate the cheapest menu item and place a delivery order based on that."

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1:

[0235] A user starts a smartphone app and enters their home address. The entered address data is sent to the server by the device, allowing the server to obtain the user's address information.

[0236] Input: User address data

[0237] Output: Send address data to server

[0238] Step 2:

[0239] The server analyzes the received address data and collects price information for delivery services (restaurants and supermarkets) near the user's address on the Internet. It uses web crawling technology to obtain the latest price data.

[0240] Input: User address data

[0241] Output: Price information for nearby delivery services

[0242] Step 3:

[0243] The server aggregates the collected price data and calculates the most cost-effective delivery menu, taking into account the product availability and sales information at each store. The data is analyzed to calculate the cheapest menu.

[0244] Input: Collected price data

[0245] Output: Cheapest menu

[0246] Step 4:

[0247] The server generates the calculated cheapest menu and specific delivery vendor information and sends this data to the user's terminal, allowing the user to see the cheapest menu available at home.

[0248] Input: Cheapest menu

[0249] Output: Cheapest menu and purchasing information data

[0250] Step 5:

[0251] The terminal displays the cheapest menu suggestion data received from the server to the user. This display includes specific purchase locations and prices, and is designed to be intuitive and easy for the user to understand.

[0252] Input: Data for the suggested menu

[0253] Output: Menu displayed to the user

[0254] Step 6:

[0255] The device will then offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to select this option and place the order directly through the app, effectively saving money on food.

[0256] Input: Cheapest menu and purchase information

[0257] Output: Delivery order options displayed

[0258] Step 7:

[0259] The user checks the presented lowest price menu and purchasing information, and places an order based on the suggested delivery menu. The user's order information is sent from the device to the server and linked to the selected delivery service.

[0260] Input: User order data

[0261] Output: Send order information to delivery service

[0262] Through the above processing steps, the user is presented with the cheapest menu based on the latest price information, allowing them to efficiently place delivery orders and save on food costs.

[0263] 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.

[0264] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[0265] Server-side processing

[0266] 1. Obtaining user address data

[0267] The server receives the home address data sent from the user terminal and analyzes it.

[0268] For example: "When a user enters an address into the app, the server receives and parses the information."

[0269] 2. Collecting information from the Internet

[0270] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address from the Internet, using techniques such as web crawling.

[0271] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[0272] 3. Price data integration and lowest price menu calculation

[0273] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[0274] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[0275] 4. Acquisition and Analysis of Emotion Data

[0276] The server receives and analyzes the user's emotional data through the emotion engine, which is collected based on voice input and facial expression recognition.

[0277] Example: "The server receives the user's emotion data from the emotion engine and analyzes it."

[0278] 5. Emotion-based menu optimization

[0279] Based on the emotional data, the server adjusts the cheapest menu, taking into account specific ingredients and recipes to reduce the user's stress.

[0280] Example: "The server will adjust the menu to reduce user frustration."

[0281] 6. Generate data to suggest the cheapest menu

[0282] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[0283] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[0284] 7. Submitting Proposal Data

[0285] The proposal data is transmitted to the user terminal.

[0286] Example: "The server sends the proposal data to the user's device."

[0287] Terminal side processing

[0288] 1. Displaying the user interface

[0289] The terminal displays an address input screen to the user and then provides an interface for inputting emotion data.

[0290] Example: "The device presents the user with an address input form and an emotion input interface as the initial screen of the app."

[0291] 2. Send input data

[0292] When the user inputs the address and emotion data, the terminal transmits the data to the server.

[0293] Example: "The user enters address and emotion data, and the device sends the data to the server."

[0294] 3. Receiving and displaying the proposal menu

[0295] The device receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[0296] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[0297] User operation

[0298] 1. Enter address and emotion data

[0299] Users enter their home address and emotional data into the app, and the information is sent to the server by the device.

[0300] For example: "The user opens the app, enters their home address into the address form, and provides emotion data."

[0301] 2. Check the cheapest menu

[0302] The user checks the cheapest menu, purchasing information, and emotion adjustment menu proposed by the server, and decides whether to purchase.

[0303] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[0304] Specific examples

[0305] For example, suppose a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. Additionally, the server considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[0306] This system allows users to save money on food efficiently and effortlessly, and to obtain the optimal menu based on their emotional state at the time.

[0307] The processing flow will be explained below.

[0308] Step 1:

[0309] Launching the application

[0310] User

[0311] The user launches the food cost saving tool app on their smartphone or PC.

[0312] Example: "A user launches a food cost savings app."

[0313] Step 2:

[0314] Entering address and emotion data

[0315] User

[0316] The user enters their home address in the address input form of the app and enters their current emotional state in the emotion data input interface.

[0317] Example: "A user enters their home address into an address form and enters emotion data."

[0318] Terminal

[0319] Prepare to send the input address data and emotion data to the server.

[0320] Example: "The device prepares the address data and emotion data entered by the user to be sent to the server."

[0321] Step 3:

[0322] Sending address and emotion data

[0323] Terminal

[0324] Address data and emotion data are sent to the server.

[0325] Example: "The device sends address data and emotion data to the server."

[0326] Step 4:

[0327] Receiving and parsing address data

[0328] server

[0329] Receives address data sent from the terminal and analyzes it.

[0330] Example: "The server receives and analyzes the address data sent from the device."

[0331] Step 5:

[0332] Receiving and analyzing emotion data

[0333] server

[0334] Emotion data sent from the device is received and analyzed by the emotion engine.

[0335] Example: "The server receives and analyzes the emotion data sent through the emotion engine."

[0336] Step 6:

[0337] Internet information gathering

[0338] server

[0339] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[0340] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[0341] Step 7:

[0342] Price Data Integration

[0343] server

[0344] Integrate collected pricing data to calculate the most cost-effective menu.

[0345] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[0346] Step 8:

[0347] Emotion-based menu adjustment

[0348] server

[0349] Based on the analyzed emotional data, the menu is adjusted to reflect specific ingredients and recipes to reduce the user's stress.

[0350] Example: "The server will adjust the menu to reduce user frustration."

[0351] Step 9:

[0352] Generate proposal data for the cheapest menu

[0353] server

[0354] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[0355] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[0356] Step 10:

[0357] Submitting proposal data

[0358] server

[0359] The proposal data is transmitted to the user terminal.

[0360] Example: "The server sends the proposal data to the user's device."

[0361] Step 11:

[0362] Receiving and displaying suggestion menus

[0363] Terminal

[0364] It receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[0365] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[0366] Step 12:

[0367] Review and select the suggestions

[0368] User

[0369] Check the suggested lowest price menu, purchasing information, and emotion adjustment menu to make the best choice.

[0370] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[0371] Example 2

[0372] 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."

[0373] Conventional systems require users to calculate the cheapest menu themselves and do not consider emotional factors that contribute to saving on food costs. Therefore, there is a need for a method to efficiently save on food costs while taking into account users' stress and satisfaction. Furthermore, there are limited means to collect price information from nearby stores in real time and provide optimal menus. This has created an issue where it is difficult for many users to obtain the optimal menu without spending time and effort.

[0374] 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.

[0375] In this invention, the server includes means for receiving and analyzing user address data, means for collecting price information on the Internet and storing it in a database, means for integrating the collected price data and calculating the cheapest menu using an algorithm, means for acquiring and analyzing user emotion data, means for adjusting the cheapest menu with specific ingredients or recipes based on the acquired emotion data, and means for suggesting and displaying the cheapest menu and an adjusted menu based on the emotion to the user. This allows the user to save on food costs efficiently and without hassle, and to obtain the optimal menu according to their emotional state at the time.

[0376] "User Address Data" means location information about a home or other specific location that a User enters into an Application.

[0377] A "server" is a central computer system that receives data sent by users, analyzes it, performs calculations and adjustments, and sends the results to the user terminal.

[0378] "Means for receiving and analyzing address data" refers to the function by which the server receives address information entered by a user and analyzes that information in order to understand and use it.

[0379] "Means for collecting price information on the Internet" refers to technology that allows a server to automatically collect price information from nearby stores and restaurants via the Internet.

[0380] A "database" is an information system in which price information and other related data collected by a server is systematically stored for later retrieval and use.

[0381] An "algorithm" is a set of procedures and calculation methods for performing calculations based on collected data and deriving optimal results.

[0382] "Means for calculating the cheapest menu" refers to a function that uses collected price data to calculate the most cost-effective menu.

[0383] "User emotion data" is data that indicates the user's current emotional state, and is acquired by voice input, facial expression recognition, or other methods.

[0384] "Means for acquiring and analyzing emotional data" refers to the technology and functions for collecting the user's emotional state and analyzing that data.

[0385] "Means for adjusting with specific ingredients or recipes" refers to a function that allows you to add or adjust specific ingredients or recipes to the cheapest menu based on the user's emotional state.

[0386] "Means for proposing and displaying" refers to a function that transmits the cheapest menu calculated by the server and an adjusted menu based on emotion data to the user's terminal and visually presents it to the user.

[0387] "Menu" refers to a list of ingredients and dishes needed for a particular meal.

[0388] "Emotionally tailored menus" refer to menus that include specific ingredients and recipes chosen with the user's emotional state in mind.

[0389] Overall system configuration

[0390] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[0391] Server-side processing

[0392] The server first receives and analyzes the home address data sent from the user's device. The address data is received in the format {"address": "Shinjuku-ku, Tokyo"}, for example. To collect price information from the Internet, the server uses web crawling technology. This technology obtains price information from the Google Maps API and the official websites of each supermarket, and stores it in a database.

[0393] The server then integrates the collected price data and uses an algorithm to calculate the cheapest menu item. For example, an SQL query might be used to search for the lowest price: SELECT MIN(price) FROM prices WHERE item="potatoes". Once the aggregation process is complete, the server receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial recognition.

[0394] Based on the user's emotional data, the system adjusts the cheapest menu by adding specific ingredients or recipes. For example, if the user is feeling stressed, it adds foods with a calming effect (e.g., chamomile tea) to the menu. This recalculates the cheapest menu and generates the final menu in JSON format. The generated menu is in the format {"menu": [{"item": "Potato", "price": 100}, {"item": "Carrot", "price": 50}], "total_price": 150}, for example.

[0395] The generated menu proposal data is sent to the user terminal. At this time, the server sends the data using an HTTP POST request. The user terminal analyzes the received data and displays it on the user interface.

[0396] Terminal side processing

[0397] The user terminal displays an address input screen to the user, and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server. For example, it is transmitted in the format of {"address": "Shinjuku-ku, Tokyo", "emotion": "stress"}.

[0398] The device receives the suggestion data sent from the server and displays it to the user. Specifically, it displays the cheapest menu suggested, its purchasing information, and an adjusted menu based on emotions. This allows the user to efficiently save on food costs and receive emotional support.

[0399] User operation

[0400] The user enters their home address and emotional data through the application. After entering the address and emotional data into the input form and clicking the submit button, the data is sent. The server suggests the cheapest menu, specific product price information, and an adjusted menu based on emotions, and the user can then decide on a purchase. This allows the user to efficiently save on food costs while obtaining a menu that takes emotional factors into consideration.

[0401] Examples of concrete examples and prompts

[0402] For example, consider a situation where a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. In addition, it considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[0403] Example prompt sentence:

[0404] "My address is Shinjuku-ku, Tokyo, and I'm feeling stressed. Based on these conditions, please suggest the cheapest menu item."

[0405] "I live in Kita-ku, Osaka, and I'm feeling depressed. Please recommend the cheapest and most emotionally sensitive option for this."

[0406] In this way, the system of the present invention can efficiently save on food costs and suggest optimal menus according to the user's emotional state.

[0407] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0408] Step 1:

[0409] Enter and submit user address data

[0410] The user opens the application and enters their home address into the input form. The device then sends the entered address data to the server. Specifically, when the user enters the address as text and presses the "Send" button, the device issues an HTTP POST request and sends the data in JSON format to the server.

[0411] Input: User's address data (e.g., Shinjuku-ku, Tokyo)

[0412] Output: Send address data to server

[0413] Step 2:

[0414] Server receives and analyzes address data

[0415] The server receives and analyzes the address data sent from the device. It parses the received JSON format address data and converts it into an internal data format. As a specific example, it analyzes the data {"address": "Shinjuku-ku, Tokyo"} and stores it in a variable for internal use.

[0416] Input: Address data received from the terminal

[0417] Output: Parsed address data

[0418] Step 3:

[0419] Collecting price information from the internet

[0420] Based on the address data, the server collects price information for supermarkets and restaurants in the specified area from the Internet. Using web crawling technology, it obtains price information from Google Maps API and each store's official website. This process requires setting an API key and specifying an endpoint.

[0421] Input: Parsed address data

[0422] Output: Collected price information data (e.g., the price of potatoes is 100 yen)

[0423] Step 4:

[0424] Price data stored in a database

[0425] The server stores the collected price information in a database. The database table contains information such as item name, price, store name, acquisition date and time, etc. In this step, an insert operation is performed using an SQL query.

[0426] Input: Collected pricing information data

[0427] Output: Price information stored in a database

[0428] Step 5:

[0429] Calculating the cheapest menu

[0430] The server uses algorithms to calculate the most cost-effective menu based on pricing data stored in a database, for example by using SQL queries to find the cheapest price for each item and combining them to build the cheapest menu.

[0431] Input: Price information stored in a database

[0432] Output: Data of the cheapest menu item (e.g., potatoes 100 yen, carrots 50 yen)

[0433] Step 6:

[0434] Entering and sending emotional data

[0435] The user inputs their current emotional state through the application. The input emotional data is sent to the server by the device. Specifically, the user selects an emotion from a drop-down menu and presses the "Send" button, which causes the device to send the emotional data as an HTTP POST request.

[0436] Input: User's emotional data (e.g., stress)

[0437] Output: Sending emotion data to the server

[0438] Step 7:

[0439] Acquiring and analyzing emotion data

[0440] The server receives and analyzes the user's emotional data through the emotion engine. This analysis may involve using voice input or facial expression recognition technology. The analyzed emotional data is stored in specific variables.

[0441] Input: Emotion data sent by the user

[0442] Output: Parsed emotion data

[0443] Step 8:

[0444] Emotionally driven adjustment of the cheapest menu

[0445] The server then adjusts the cheapest menu based on the analyzed emotion data, taking into account specific ingredients and recipes. For example, if the user is feeling stressed, it will add foods with a calming effect to the menu. In this step, the price is calculated again.

[0446] Input: Analyzed emotion data, cheapest menu data

[0447] Output: Adjusted lowest price menu

[0448] Step 9:

[0449] Generate proposal data for the cheapest menu

[0450] The server generates the final lowest price menu and an adjusted menu based on the sentiment data in JSON format, which is then ready to be sent to the user's device.

[0451] Input: Adjusted lowest price menu

[0452] Output: Generated proposal data

[0453] Step 10:

[0454] Submitting proposal data

[0455] The server sends the generated proposal data to the user device as an HTTP POST request, for example, in the format {"menu": [{"item": "potato", "price": 100}, {"item": "carrot", "price": 50}], "total_price": 150}.

[0456] Input: Generated proposal data

[0457] Output: Proposal data sent to the user device

[0458] Step 11:

[0459] Receiving and displaying suggestion menus

[0460] The device receives the proposal data sent from the server and visually displays it to the user. Specifically, it parses the received JSON data and displays the material list and price information on the user interface.

[0461] Input: Proposal data sent from the server

[0462] Output: The lowest price menu and the adjusted menu displayed to the user

[0463] (Application example 2)

[0464] 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."

[0465] Conventional food delivery services do not suggest optimal meals based on a user's emotional state, making it difficult for users to easily select meals that will reduce stress and discomfort. Even if systems exist that suggest the cheapest menu plans, they cannot provide optimized menus that take emotional data into account, preventing users from receiving truly satisfying suggestions. Therefore, there is a need for a system that offers the best menu at the lowest price based on a user's emotional state.

[0466] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user address data, means for receiving and analyzing user emotion data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for adjusting the cheapest menu based on the user emotion data, and means for proposing and displaying the cheapest menu to the user. This makes it possible to provide the optimal menu plan at the cheapest price based on the user's address data and emotion data, thereby reducing the user's stress and discomfort.

[0467] Definitions of important words

[0468] "Address data" is data that indicates information about the place where the user resides.

[0469] "Emotion data" is data that represents the user's current emotional state, and is obtained from voice input, facial expression recognition, or the like.

[0470] "Price information on the Internet" is information about product prices that can be collected from the Internet.

[0471] The "cheapest menu" is the most cost-effective menu plan calculated based on price information collected from multiple stores and restaurants.

[0472] The "means for adjusting the cheapest menu" is a means for changing the content of the cheapest menu based on the user's emotional data and making suggestions that match the user's emotional state.

[0473] The "means for displaying proposed data to the user" refers to a means for visually or audibly presenting the cheapest menu calculated by the server and its adjustment details to the user.

[0474] MODE FOR CARRYING OUT THE INVENTION

[0475] To implement this invention, a system is required that links and operates a server, user terminal, and emotion engine. This system provides the most appropriate, lowest-priced menu based on the user's address data and emotion data. Below, we will explain in detail each component of this system and its processing.

[0476] Server-side processing

[0477] The server performs several functions. First, it receives and analyzes the user's address data from the user's device. Second, it collects price information from stores and restaurants near the user's address via the Internet. This information is collected using web crawling.

[0478] The server integrates the collected price data and calculates the cheapest menu, taking into account each store's inventory status and special sales information. It also receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial expression recognition.

[0479] Finally, the server adjusts the cheapest menu based on the emotion data, taking into account specific ingredients and recipes to reduce the user's stress. Based on the results, it generates the cheapest menu suggestion data and sends it to the user's device.

[0480] Terminal side processing

[0481] The user terminal displays an address input screen to the user and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server.

[0482] The recommendation data sent from the server is received by the user's device and displayed to the user. This display includes not only specific purchase locations and prices, but also emotion-based adjustment menus.

[0483] User operation

[0484] The user enters their home address and emotional data into the app. They then check the cheapest menu items, purchasing locations, and emotion-adjusting menu items suggested by the server and decide whether to purchase them. By purchasing ingredients based on the cheapest menu items suggested by the server, the user can efficiently save on food costs while also receiving emotional support.

[0485] Hardware and software used

[0486] The hardware required is a smartphone and a server, while the software required is a program implemented using Python, web crawling technology, and a sentiment analysis engine.

[0487] Specific examples

[0488] For example, suppose a user lives in Shibuya Ward, Tokyo, and is currently feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shibuya Ward and consolidates the most cost-effective curry ingredient list. Additionally, the server considers specific foods (e.g., chamomile tea) that can help reduce the user's stress, and generates a tailored menu, where, for example, potatoes are 100 yen at one supermarket and carrots are 50 yen at another. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[0489] Example prompts to input to the generative AI model

[0490] The user is stressed and lives in Shibuya, Tokyo. Design a food delivery app that suggests the cheapest stress-reducing menu. The menu should include ingredients with calming effects. Also, provide information on where to purchase each ingredient and their price.

[0491] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0492] Processing Steps

[0493] Step 1:

[0494] Enter and submit user address and emotion data

[0495] Operation:

[0496] The user inputs address data and emotion data using a smartphone terminal.

[0497] Emotional data is collected through voice input or facial expression recognition.

[0498] input:

[0499] Address data and emotion data entered by the user.

[0500] Data processing / calculation:

[0501] Formats the input data and prepares it for sending to the server.

[0502] output:

[0503] The formatted address data and emotion data are sent to a server.

[0504] Step 2:

[0505] Receiving and parsing address data

[0506] Operation:

[0507] The server receives the address data sent from the user terminal.

[0508] The received address data is analyzed to extract specific geographic information.

[0509] input:

[0510] Address data sent from the device.

[0511] Data processing / calculation:

[0512] Format analysis of address data and extraction of geographic information.

[0513] output:

[0514] The extracted geographic information.

[0515] Step 3:

[0516] Collecting price information from the internet

[0517] Operation:

[0518] Based on the extracted geographical information, the server collects price information from nearby stores and restaurants from the Internet.

[0519] The latest price information is obtained using web crawling technology.

[0520] input:

[0521] Geographic information.

[0522] Data processing / calculation:

[0523] Price information gathering using web crawling.

[0524] output:

[0525] Price information for nearby stores and restaurants.

[0526] Step 4:

[0527] Price data integration and lowest price menu calculation

[0528] Operation:

[0529] The server consolidates the collected pricing data and generates the most cost-effective menu plan.

[0530] It also takes into account inventory information and special sales information from each store.

[0531] input:

[0532] Price information for nearby stores and restaurants.

[0533] Data processing / calculation:

[0534] Integrates price data and calculates the cheapest menu.

[0535] output:

[0536] Data on the cheapest menu.

[0537] Step 5:

[0538] Emotional data analysis and menu adjustment

[0539] Operation:

[0540] The server analyzes the received emotion data through an emotion engine.

[0541] The cheapest menu is adjusted according to the user's emotional state.

[0542] For example, for a user who is feeling stressed, foods with a calming effect can be added to the menu.

[0543] input:

[0544] User sentiment data and cheapest menu data.

[0545] Data processing / calculation:

[0546] Analyzing sentiment data and adjusting the cheapest menu.

[0547] output:

[0548] Adjusted data for cheapest menu.

[0549] Step 6:

[0550] Generate and send proposal data for the cheapest menu

[0551] Operation:

[0552] The server generates adjusted lowest price menu suggestion data.

[0553] The optimized menu plan is transmitted to the user terminal.

[0554] input:

[0555] Adjusted data for cheapest menu.

[0556] Data processing / calculation:

[0557] Proposal data generation.

[0558] output:

[0559] The cheapest menu suggestion data is sent to the user's device.

[0560] Step 7:

[0561] Receiving and displaying suggestion menus

[0562] Operation:

[0563] The user terminal receives the proposal data sent from the server and displays it to the user.

[0564] It also displays specific purchase locations, prices, and emotional adjustment menus.

[0565] input:

[0566] The cheapest menu suggestion data sent from the server.

[0567] Data processing / calculation:

[0568] Prepare to display proposed data.

[0569] output:

[0570] The suggestion menu that is displayed to the user.

[0571] Step 8:

[0572] The user checks the suggested menu and makes a purchase

[0573] Operation:

[0574] The user checks the suggested lowest price menu, purchasing information, and emotion adjustment menu.

[0575] Purchase your materials in-store or online based on the suggested information.

[0576] input:

[0577] Suggestion menu data.

[0578] Data processing / calculation:

[0579] User verification and decision-making process.

[0580] output:

[0581] Purchase of materials.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] [Second embodiment]

[0586] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0587] 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.

[0588] 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).

[0589] 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.

[0590] 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.

[0591] 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).

[0592] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0593] 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.

[0594] 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.

[0595] 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.

[0596] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0597] 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."

[0598] The system according to the present invention is designed to help users save money on food by suggesting the cheapest menu items based on their address data. This system is mainly composed of a server, a user terminal, and user operations.

[0599] Server-side processing

[0600] 1. Obtaining user address data

[0601] The server receives the home address data sent from the user terminal and analyzes it.

[0602] For example: "When a user enters an address into the app, the server receives and parses the information."

[0603] 2. Collecting information from the Internet

[0604] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address using web crawling and other techniques.

[0605] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[0606] 3. Price data integration and lowest price menu calculation

[0607] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[0608] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[0609] 4. Lowest price menu suggestions

[0610] Based on the calculation results, the server generates data suggesting the cheapest menu and specific purchasing information to the user, and transmits this to the user's terminal.

[0611] Example: "The server creates a list of the cheapest menu items and their purchases, and sends it to the user's terminal."

[0612] Terminal side processing

[0613] 1. Displaying the user interface

[0614] The terminal displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[0615] Example: "The device presents the user with an address entry form as the initial screen of the app."

[0616] 2. Send input data

[0617] When the user enters address data, the terminal transmits the data to the server.

[0618] Example: "The user enters an address and the device sends the data to the server."

[0619] 3. Receiving and displaying the proposal menu

[0620] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[0621] Example: "The device displays the curry recipe received from the server and lists the ingredients needed and where to purchase them."

[0622] User operation

[0623] 1. Enter your address

[0624] The user enters their home address into the app, and the information is sent by the device to the server.

[0625] Example: "The user opens the app and enters their home address into the address form."

[0626] 2. Check the cheapest menu

[0627] The user checks the cheapest menu and purchasing information proposed by the server and decides whether to purchase.

[0628] Example: "The user sees the ingredients list for the curry and the price at the nearest supermarket before deciding to buy it."

[0629] Specific examples

[0630] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at WinMart and carrots costing 50 yen at Supermarket A. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[0631] This system allows users to save money on food efficiently and hassle-free.

[0632] The processing flow will be explained below.

[0633] Step 1:

[0634] Launching the application

[0635] User

[0636] The user launches the food cost saving tool app on their smartphone or PC.

[0637] Example: "A user launches a food cost savings app."

[0638] Step 2:

[0639] Enter your address

[0640] User

[0641] The user enters their home address into the app's address form.

[0642] Example: "A user enters their home address into an address form."

[0643] Terminal

[0644] Prepare to send the entered address data to the server.

[0645] Example: "The terminal prepares the address data entered by the user for transmission to the server."

[0646] Step 3:

[0647] Sending address data

[0648] Terminal

[0649] The address data is sent to the server.

[0650] Example: "The device sends the address data to the server."

[0651] Step 4:

[0652] Receiving and parsing address data

[0653] server

[0654] Receives address data sent from the terminal and analyzes it.

[0655] Example: "The server receives and analyzes the address data sent from the device."

[0656] Step 5:

[0657] Internet information gathering

[0658] server

[0659] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[0660] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[0661] Step 6:

[0662] Price data integration and lowest price menu calculation

[0663] server

[0664] Integrate collected pricing data to calculate the most cost-effective menu.

[0665] Example: "The server aggregates the price data and calculates the cheapest dinner menu for the day."

[0666] Step 7:

[0667] Generate proposal data for the cheapest menu

[0668] server

[0669] Based on the integration and calculation results, data suggesting the cheapest menu is generated.

[0670] Example: "The server creates a list of the cheapest menu items and their purchases."

[0671] Step 8:

[0672] Submitting proposal data

[0673] server

[0674] The proposal data is transmitted to the user terminal.

[0675] Example: "The server sends the proposal data to the user's device."

[0676] Step 9:

[0677] Receiving and displaying suggestion menus

[0678] Terminal

[0679] The proposed data transmitted from the server is received and displayed to the user.

[0680] Example: "The device displays the received lowest price menu and purchase information to the user."

[0681] Step 10:

[0682] Review and select the suggestions

[0683] User

[0684] Check the suggested lowest price menu and purchasing information to make the best choice.

[0685] For example: "The user reviews the presented materials list and prices and then decides to purchase."

[0686] Example 1

[0687] 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."

[0688] In the past, in order to save on food costs, users had to personally research multiple retail stores and online stores, compare prices, and identify the most cost-effective source of purchase. This required time and effort, and was particularly cumbersome when purchasing everyday ingredients. There was a need for a system that could improve this situation and enable users to efficiently save on food costs.

[0689] 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.

[0690] In this invention, the server includes means for receiving and analyzing the user's address data, means for collecting price information of nearby stores over the Internet based on the address data, and means for integrating the collected price data to calculate the most cost-effective menu. This allows the user to automatically collect price information of nearby stores and propose the cheapest menu by simply inputting their address, thereby enabling efficient savings on food costs.

[0691] "Address data" indicates the location information or address of the user's home as input by the user.

[0692] "Sales outlet" is a general term for places that provide price information, such as supermarkets, stores that sell food, or restaurants.

[0693] "Price information" is data relating to the prices of products sold at each store.

[0694] A "menu" is a list of ingredients needed for a particular meal and the dishes that use them.

[0695] "Suggestion" is the act of showing the user the best option based on collected information.

[0696] "Analysis" means converting received data into an understandable format and understanding its contents.

[0697] "Collection" means gathering the necessary information via the Internet.

[0698] "Integration" means combining multiple pieces of data into one and making it possible to analyze it as a whole.

[0699] "Cost-effectiveness" refers to the state in which maximum effect can be obtained with minimum cost.

[0700] "Proposal data" is data generated by the server that includes the cheapest menu and information on where to purchase it.

[0701] The present invention is a system that supports food cost savings by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[0702] First, the user enters their home address into the application. This application runs on the user's device and provides an address input form through a user interface. When the user enters the address and presses the submit button, the device sends the address data to the server.

[0703] The server receives and analyzes the address data sent from the user's device. The analyzed address data is used to collect price information from nearby stores via the Internet. Specifically, a web crawler is used to obtain the latest price information from each store's website. The web crawler used here can be a general web scraping tool.

[0704] The collected price information is integrated within the server, and the next step is to calculate the most cost-effective menu. The server analyzes the collected price data and integrates data from multiple stores. For example, price information from supermarkets and restaurants near the address specified by the user is integrated, and the cheapest menu is calculated taking into account special sales and inventory status.

[0705] The calculated cheapest menu item and its specific purchasing location information are generated as data on the server side and sent back to the user's device. The user device receives this data and displays it to the user in an intuitive and easy-to-understand format. For example, it may display something like "potatoes are 100 yen at supermarket A, and carrots are 50 yen at supermarket B."

[0706] Based on the information provided, users can decide which inventory to purchase and at which store. This system allows users to save on food costs efficiently and without hassle.

[0707] Specific examples

[0708] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at one supermarket and carrots costing 50 yen at another. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[0709] Using ChatGPT as a generative AI model, specific explanatory text can be generated using the following prompt text:

[0710] Example prompt sentence:

[0711] "This system suggests the cheapest menu items based on the user's address data, helping them save on food expenses. The server-side process first receives and analyzes the address data sent from the user's device. Next, it crawls the web to collect price information from supermarkets and restaurants around the specified address. It integrates the collected price data, calculates the most cost-effective menu items, and suggests them to the user. The device-side process displays a user interface, sends the address data to the server, and receives and displays the cheapest menu items. User operations include entering the address and confirming the cheapest menu items. For example, if the user lives in Shinjuku Ward, Tokyo, the server will collect price information from supermarkets and restaurants around Shinjuku Ward and provide a list of ingredients for the most cost-effective curry."

[0712] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0713] Step 1:

[0714] Enter and submit address data

[0715] Input: The user enters their home address into the device's address input form.

[0716] Specific operation: The terminal displays an address input form through the user interface, and the user inputs his / her address.

[0717] Data processing / calculation: The device converts the address data into JSON format and sends it to the server.

[0718] Output: Address data is sent to the server in JSON format.

[0719] For example, when a user inputs "Shinjuku-ku, Tokyo" and presses the send button, the terminal transmits the data to the server as a POST request.

[0720] Step 2:

[0721] Receiving and parsing address data

[0722] Input: Address data sent from the terminal.

[0723] Specific operation: The server receives data sent from the user terminal.

[0724] Data processing / calculation: The server parses the received address data in JSON format and stores it in an internal database.

[0725] Output: Parsed address data is saved in a database.

[0726] For example, address data such as "Shinjuku-ku, Tokyo" is parsed in JSON format and stored in a database.

[0727] Step 3:

[0728] Gathering price information from nearby stores

[0729] Input: Parsed address data.

[0730] Specific operation: The server launches a web crawler and collects price information for nearby stores based on the address data.

[0731] Data processing / calculation: The web crawler accesses the specified websites and extracts price information from HTML pages. The extracted information is converted into JSON format and sent to the server.

[0732] Output: Price information of nearby stores is collected in JSON format.

[0733] For example, sales information for nearby supermarkets and coupon information for restaurants is collected and sent to the server in JSON format.

[0734] Step 4:

[0735] Price data integration and lowest price menu calculation

[0736] Input: Collected pricing information.

[0737] Specific operation: The server retrieves the collected price data from the database and consolidates it.

[0738] Data processing / calculation: Based on the combined data, an algorithm is run to generate the lowest-priced ingredient list, taking into account special offers and availability.

[0739] Output: Cheapest menu and where to buy information.

[0740] For example, it can integrate price data for potatoes and carrots collected from multiple supermarkets to calculate the cheapest curry recipe.

[0741] Step 5:

[0742] Propose and send the cheapest menu

[0743] Input: Cheapest menu and where to buy information.

[0744] Specific operation: Based on the calculation results, the server generates data to suggest to the user.

[0745] Data processing / calculation: Generate the cheapest menu and its purchase list in HTML or JSON format.

[0746] Output: The proposed data is sent to the user device.

[0747] For example, proposal data including information that potatoes cost 100 yen at one supermarket and carrots cost 50 yen at another supermarket is generated and sent to the user terminal.

[0748] Step 6:

[0749] Receiving and displaying suggestion menus

[0750] Input: Proposal data sent by the server.

[0751] Specific operation: The terminal receives the cheapest menu suggestion data sent from the server.

[0752] Data processing / calculation: Analyzes the received data and displays it in a form that is easy for the user to understand.

[0753] Output: The cheapest menu and purchasing information will be displayed on the device.

[0754] For example, the user terminal displays a curry recipe received from the server and presents it to the user in the form of potatoes costing 100 yen and carrots costing 50 yen.

[0755] (Application example 1)

[0756] 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."

[0757] With conventional food delivery services, users had to go through the trouble of comparing multiple services and stores to find the cheapest menu, making it difficult to effectively reduce food costs.In addition, price information was not updated in real time, making it difficult to suggest optimal menu items based on the latest price information.

[0758] 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.

[0759] In this invention, the server includes means for receiving user address data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for proposing and displaying the cheapest menu to the user, means for collecting price information of delivery services based on the user's address, and means for providing options for placing a delivery order. This saves the user the trouble of comparing price information of multiple services and stores, and allows the user to receive suggestions for the cheapest menu in real time, enabling efficient savings on food costs.

[0760] The "means for receiving user address data" refers to a method by which a user inputs his or her address information and the system receives it.

[0761] "Methods for collecting price information on the Internet" refers to methods for obtaining price information for goods and services from websites and online databases.

[0762] The "means of integrating collected price data to calculate the cheapest menu" is a method of aggregating price information obtained from multiple data sources and calculating the lowest cost menu based on that information.

[0763] The "means for proposing and displaying the cheapest menu to the user" is a method for presenting the calculated cheapest menu and information on where to purchase it to the user.

[0764] "Means for collecting price information for delivery services based on the user's address" refers to a method for collecting price information for delivery services available in the vicinity from stores or services that provide such information based on the user's address information.

[0765] The "means for providing an option to place a delivery order" is a method for providing a function for a user to directly place a delivery order based on the suggested cheapest menu item.

[0766] The present invention is a system that aims to efficiently reduce food costs by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[0767] Server-side processing

[0768] 1. Obtaining user address data

[0769] The server receives address data entered by the user from the device. For example, when a user enters their home address into a smartphone app, the information is sent to the server and analyzed.

[0770] 2. Collecting information from the Internet

[0771] The server uses the received address data to collect price information for delivery services (restaurants and supermarkets) near the user's address. This information is collected using techniques such as web crawling.

[0772] 3. Price data integration and lowest price menu calculation

[0773] The server aggregates the collected price data and calculates the most cost-effective delivery options, taking into account product availability and special offers at each store.

[0774] 4. Lowest price menu suggestions

[0775] Based on the calculation results, the server proposes the cheapest menu and specific delivery purchasing information to the user, and sends this data to the user's terminal.

[0776] Terminal side processing

[0777] 1. Displaying the user interface

[0778] The device (such as a smartphone) displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[0779] 2. Send input data

[0780] When the user enters address data, the terminal transmits the data to the server.

[0781] 3. Receiving and displaying the proposal menu

[0782] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[0783] 4. Delivery ordering options

[0784] The device will offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to order directly from the app and save money on food.

[0785] User operation

[0786] 1. Enter your address

[0787] The user enters their home address into the app, and the information is sent by the device to the server.

[0788] 2. Check the cheapest menu and order

[0789] The user checks the cheapest menu and purchasing information suggested by the server, and places a delivery order based on the suggested menu.

[0790] Specific examples

[0791] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information for delivery restaurants in the Shinjuku area. The server will then calculate the most cost-effective delivery menu and generate a detailed ingredient list and pricing information for the nearest delivery service. Based on this information, users can place a delivery order directly, effectively saving money on food.

[0792] Hardware and software used

[0793] Hardware: Smartphone

[0794] Software: Python, Requests, BeautifulSoup

[0795] Prompt Sentence Examples

[0796] "Enter your address: Shinjuku-ku, Tokyo. I'd like to calculate the cheapest menu item and place a delivery order based on that."

[0797] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0798] Step 1:

[0799] A user starts a smartphone app and enters their home address. The entered address data is sent to the server by the device, allowing the server to obtain the user's address information.

[0800] Input: User address data

[0801] Output: Send address data to server

[0802] Step 2:

[0803] The server analyzes the received address data and collects price information for delivery services (restaurants and supermarkets) near the user's address on the Internet. It uses web crawling technology to obtain the latest price data.

[0804] Input: User address data

[0805] Output: Price information for nearby delivery services

[0806] Step 3:

[0807] The server aggregates the collected price data and calculates the most cost-effective delivery menu, taking into account the product availability and sales information at each store. The data is analyzed to calculate the cheapest menu.

[0808] Input: Collected price data

[0809] Output: Cheapest menu

[0810] Step 4:

[0811] The server generates the calculated cheapest menu and specific delivery vendor information and sends this data to the user's terminal, allowing the user to see the cheapest menu available at home.

[0812] Input: Cheapest menu

[0813] Output: Cheapest menu and purchasing information data

[0814] Step 5:

[0815] The terminal displays the cheapest menu suggestion data received from the server to the user. This display includes specific purchase locations and prices, and is designed to be intuitive and easy for the user to understand.

[0816] Input: Data for the suggested menu

[0817] Output: Menu displayed to the user

[0818] Step 6:

[0819] The device will then offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to select this option and place the order directly through the app, effectively saving money on food.

[0820] Input: Cheapest menu and purchase information

[0821] Output: Delivery order options displayed

[0822] Step 7:

[0823] The user checks the presented lowest price menu and purchasing information, and places an order based on the suggested delivery menu. The user's order information is sent from the device to the server and linked to the selected delivery service.

[0824] Input: User order data

[0825] Output: Send order information to delivery service

[0826] Through the above processing steps, the user is presented with the cheapest menu based on the latest price information, allowing them to efficiently place delivery orders and save on food costs.

[0827] 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.

[0828] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[0829] Server-side processing

[0830] 1. Obtaining user address data

[0831] The server receives the home address data sent from the user terminal and analyzes it.

[0832] For example: "When a user enters an address into the app, the server receives and parses the information."

[0833] 2. Collecting information from the Internet

[0834] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address from the Internet, using techniques such as web crawling.

[0835] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[0836] 3. Price data integration and lowest price menu calculation

[0837] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[0838] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[0839] 4. Acquisition and Analysis of Emotion Data

[0840] The server receives and analyzes the user's emotional data through the emotion engine, which is collected based on voice input and facial expression recognition.

[0841] Example: "The server receives the user's emotion data from the emotion engine and analyzes it."

[0842] 5. Emotion-based menu optimization

[0843] Based on the emotional data, the server adjusts the cheapest menu, taking into account specific ingredients and recipes to reduce the user's stress.

[0844] Example: "The server will adjust the menu to reduce user frustration."

[0845] 6. Generate data to suggest the cheapest menu

[0846] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[0847] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[0848] 7. Submitting Proposal Data

[0849] The proposal data is transmitted to the user terminal.

[0850] Example: "The server sends the proposal data to the user's device."

[0851] Terminal side processing

[0852] 1. Displaying the user interface

[0853] The terminal displays an address input screen to the user and then provides an interface for inputting emotion data.

[0854] Example: "The device presents the user with an address input form and an emotion input interface as the initial screen of the app."

[0855] 2. Send input data

[0856] When the user inputs the address and emotion data, the terminal transmits the data to the server.

[0857] Example: "The user enters address and emotion data, and the device sends the data to the server."

[0858] 3. Receiving and displaying the proposal menu

[0859] The device receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[0860] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[0861] User operation

[0862] 1. Enter address and emotion data

[0863] Users enter their home address and emotional data into the app, and the information is sent to the server by the device.

[0864] For example: "The user opens the app, enters their home address into the address form, and provides emotion data."

[0865] 2. Check the cheapest menu

[0866] The user checks the cheapest menu, purchasing information, and emotion adjustment menu proposed by the server, and decides whether to purchase.

[0867] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[0868] Specific examples

[0869] For example, suppose a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. Additionally, the server considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[0870] This system allows users to save money on food efficiently and effortlessly, and to obtain the optimal menu based on their emotional state at the time.

[0871] The processing flow will be explained below.

[0872] Step 1:

[0873] Launching the application

[0874] User

[0875] The user launches the food cost saving tool app on their smartphone or PC.

[0876] Example: "A user launches a food cost savings app."

[0877] Step 2:

[0878] Entering address and emotion data

[0879] User

[0880] The user enters their home address in the address input form of the app and enters their current emotional state in the emotion data input interface.

[0881] Example: "A user enters their home address into an address form and enters emotion data."

[0882] Terminal

[0883] Prepare to send the input address data and emotion data to the server.

[0884] Example: "The device prepares the address data and emotion data entered by the user to be sent to the server."

[0885] Step 3:

[0886] Sending address and emotion data

[0887] Terminal

[0888] Address data and emotion data are sent to the server.

[0889] Example: "The device sends address data and emotion data to the server."

[0890] Step 4:

[0891] Receiving and parsing address data

[0892] server

[0893] Receives address data sent from the terminal and analyzes it.

[0894] Example: "The server receives and analyzes the address data sent from the device."

[0895] Step 5:

[0896] Receiving and analyzing emotion data

[0897] server

[0898] Emotion data sent from the device is received and analyzed by the emotion engine.

[0899] Example: "The server receives and analyzes the emotion data sent through the emotion engine."

[0900] Step 6:

[0901] Internet information gathering

[0902] server

[0903] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[0904] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[0905] Step 7:

[0906] Price Data Integration

[0907] server

[0908] Integrate collected pricing data to calculate the most cost-effective menu.

[0909] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[0910] Step 8:

[0911] Emotion-based menu adjustment

[0912] server

[0913] Based on the analyzed emotional data, the menu is adjusted to reflect specific ingredients and recipes to reduce the user's stress.

[0914] Example: "The server will adjust the menu to reduce user frustration."

[0915] Step 9:

[0916] Generate proposal data for the cheapest menu

[0917] server

[0918] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[0919] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[0920] Step 10:

[0921] Submitting proposal data

[0922] server

[0923] The proposal data is transmitted to the user terminal.

[0924] Example: "The server sends the proposal data to the user's device."

[0925] Step 11:

[0926] Receiving and displaying suggestion menus

[0927] Terminal

[0928] It receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[0929] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[0930] Step 12:

[0931] Review and select the suggestions

[0932] User

[0933] Check the suggested lowest price menu, purchasing information, and emotion adjustment menu to make the best choice.

[0934] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[0935] Example 2

[0936] 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."

[0937] Conventional systems require users to calculate the cheapest menu themselves and do not consider emotional factors that contribute to saving on food costs. Therefore, there is a need for a method to efficiently save on food costs while taking into account users' stress and satisfaction. Furthermore, there are limited means to collect price information from nearby stores in real time and provide optimal menus. This has created an issue where it is difficult for many users to obtain the optimal menu without spending time and effort.

[0938] 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.

[0939] In this invention, the server includes means for receiving and analyzing user address data, means for collecting price information on the Internet and storing it in a database, means for integrating the collected price data and calculating the cheapest menu using an algorithm, means for acquiring and analyzing user emotion data, means for adjusting the cheapest menu with specific ingredients or recipes based on the acquired emotion data, and means for suggesting and displaying the cheapest menu and an adjusted menu based on the emotion to the user. This allows the user to save on food costs efficiently and without hassle, and to obtain the optimal menu according to their emotional state at the time.

[0940] "User Address Data" means location information about a home or other specific location that a User enters into an Application.

[0941] A "server" is a central computer system that receives data sent by users, analyzes it, performs calculations and adjustments, and sends the results to the user terminal.

[0942] "Means for receiving and analyzing address data" refers to the function by which the server receives address information entered by a user and analyzes that information in order to understand and use it.

[0943] "Means for collecting price information on the Internet" refers to technology that allows a server to automatically collect price information from nearby stores and restaurants via the Internet.

[0944] A "database" is an information system in which price information and other related data collected by a server is systematically stored for later retrieval and use.

[0945] An "algorithm" is a set of procedures and calculation methods for performing calculations based on collected data and deriving optimal results.

[0946] "Means for calculating the cheapest menu" refers to a function that uses collected price data to calculate the most cost-effective menu.

[0947] "User emotion data" is data that indicates the user's current emotional state, and is acquired by voice input, facial expression recognition, or other methods.

[0948] "Means for acquiring and analyzing emotional data" refers to the technology and functions for collecting the user's emotional state and analyzing that data.

[0949] "Means for adjusting with specific ingredients or recipes" refers to a function that allows you to add or adjust specific ingredients or recipes to the cheapest menu based on the user's emotional state.

[0950] "Means for proposing and displaying" refers to a function that transmits the cheapest menu calculated by the server and an adjusted menu based on emotion data to the user's terminal and visually presents it to the user.

[0951] "Menu" refers to a list of ingredients and dishes needed for a particular meal.

[0952] "Emotionally tailored menus" refer to menus that include specific ingredients and recipes chosen with the user's emotional state in mind.

[0953] Overall system configuration

[0954] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[0955] Server-side processing

[0956] The server first receives and analyzes the home address data sent from the user's device. The address data is received in the format {"address": "Shinjuku-ku, Tokyo"}, for example. To collect price information from the Internet, the server uses web crawling technology. This technology obtains price information from the Google Maps API and the official websites of each supermarket, and stores it in a database.

[0957] The server then integrates the collected price data and uses an algorithm to calculate the cheapest menu item. For example, an SQL query might be used to search for the lowest price: SELECT MIN(price) FROM prices WHERE item="potatoes". Once the aggregation process is complete, the server receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial recognition.

[0958] Based on the user's emotional data, the system adjusts the cheapest menu by adding specific ingredients or recipes. For example, if the user is feeling stressed, it adds foods with a calming effect (e.g., chamomile tea) to the menu. This recalculates the cheapest menu and generates the final menu in JSON format. The generated menu is in the format {"menu": [{"item": "Potato", "price": 100}, {"item": "Carrot", "price": 50}], "total_price": 150}, for example.

[0959] The generated menu proposal data is sent to the user terminal. At this time, the server sends the data using an HTTP POST request. The user terminal analyzes the received data and displays it on the user interface.

[0960] Terminal side processing

[0961] The user terminal displays an address input screen to the user, and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server. For example, it is transmitted in the format of {"address": "Shinjuku-ku, Tokyo", "emotion": "stress"}.

[0962] The device receives the suggestion data sent from the server and displays it to the user. Specifically, it displays the cheapest menu suggested, its purchasing information, and an adjusted menu based on emotions. This allows the user to efficiently save on food costs and receive emotional support.

[0963] User operation

[0964] The user enters their home address and emotional data through the application. After entering the address and emotional data into the input form and clicking the submit button, the data is sent. The server suggests the cheapest menu, specific product price information, and an adjusted menu based on emotions, and the user can then decide on a purchase. This allows the user to efficiently save on food costs while obtaining a menu that takes emotional factors into consideration.

[0965] Examples of concrete examples and prompts

[0966] For example, consider a situation where a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. In addition, it considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[0967] Example prompt sentence:

[0968] "My address is Shinjuku-ku, Tokyo, and I'm feeling stressed. Based on these conditions, please suggest the cheapest menu item."

[0969] "I live in Kita-ku, Osaka, and I'm feeling depressed. Please recommend the cheapest and most emotionally sensitive option for this."

[0970] In this way, the system of the present invention can efficiently save on food costs and suggest optimal menus according to the user's emotional state.

[0971] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0972] Step 1:

[0973] Enter and submit user address data

[0974] The user opens the application and enters their home address into the input form. The device then sends the entered address data to the server. Specifically, when the user enters the address as text and presses the "Send" button, the device issues an HTTP POST request and sends the data in JSON format to the server.

[0975] Input: User's address data (e.g., Shinjuku-ku, Tokyo)

[0976] Output: Send address data to server

[0977] Step 2:

[0978] Server receives and analyzes address data

[0979] The server receives and analyzes the address data sent from the device. It parses the received JSON format address data and converts it into an internal data format. As a specific example, it analyzes the data {"address": "Shinjuku-ku, Tokyo"} and stores it in a variable for internal use.

[0980] Input: Address data received from the terminal

[0981] Output: Parsed address data

[0982] Step 3:

[0983] Collecting price information from the internet

[0984] Based on the address data, the server collects price information for supermarkets and restaurants in the specified area from the Internet. Using web crawling technology, it obtains price information from Google Maps API and each store's official website. This process requires setting an API key and specifying an endpoint.

[0985] Input: Parsed address data

[0986] Output: Collected price information data (e.g., the price of potatoes is 100 yen)

[0987] Step 4:

[0988] Price data stored in a database

[0989] The server stores the collected price information in a database. The database table contains information such as item name, price, store name, acquisition date and time, etc. In this step, an insert operation is performed using an SQL query.

[0990] Input: Collected pricing information data

[0991] Output: Price information stored in a database

[0992] Step 5:

[0993] Calculating the cheapest menu

[0994] The server uses algorithms to calculate the most cost-effective menu based on pricing data stored in a database, for example by using SQL queries to find the cheapest price for each item and combining them to build the cheapest menu.

[0995] Input: Price information stored in a database

[0996] Output: Data of the cheapest menu item (e.g., potatoes 100 yen, carrots 50 yen)

[0997] Step 6:

[0998] Entering and sending emotional data

[0999] The user inputs their current emotional state through the application. The input emotional data is sent to the server by the device. Specifically, the user selects an emotion from a drop-down menu and presses the "Send" button, which causes the device to send the emotional data as an HTTP POST request.

[1000] Input: User's emotional data (e.g., stress)

[1001] Output: Sending emotion data to the server

[1002] Step 7:

[1003] Acquiring and analyzing emotion data

[1004] The server receives and analyzes the user's emotional data through the emotion engine. This analysis may involve using voice input or facial expression recognition technology. The analyzed emotional data is stored in specific variables.

[1005] Input: Emotion data sent by the user

[1006] Output: Parsed emotion data

[1007] Step 8:

[1008] Emotionally driven adjustment of the cheapest menu

[1009] The server then adjusts the cheapest menu based on the analyzed emotion data, taking into account specific ingredients and recipes. For example, if the user is feeling stressed, it will add foods with a calming effect to the menu. In this step, the price is calculated again.

[1010] Input: Analyzed emotion data, cheapest menu data

[1011] Output: Adjusted lowest price menu

[1012] Step 9:

[1013] Generate proposal data for the cheapest menu

[1014] The server generates the final lowest price menu and an adjusted menu based on the sentiment data in JSON format, which is then ready to be sent to the user's device.

[1015] Input: Adjusted lowest price menu

[1016] Output: Generated proposal data

[1017] Step 10:

[1018] Submitting proposal data

[1019] The server sends the generated proposal data to the user device as an HTTP POST request, for example, in the format {"menu": [{"item": "potato", "price": 100}, {"item": "carrot", "price": 50}], "total_price": 150}.

[1020] Input: Generated proposal data

[1021] Output: Proposal data sent to the user device

[1022] Step 11:

[1023] Receiving and displaying suggestion menus

[1024] The device receives the proposal data sent from the server and visually displays it to the user. Specifically, it parses the received JSON data and displays the material list and price information on the user interface.

[1025] Input: Proposal data sent from the server

[1026] Output: The lowest price menu and the adjusted menu displayed to the user

[1027] (Application example 2)

[1028] 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."

[1029] Conventional food delivery services do not suggest optimal meals based on a user's emotional state, making it difficult for users to easily select meals that will reduce stress and discomfort. Even if systems exist that suggest the cheapest menu plans, they cannot provide optimized menus that take emotional data into account, preventing users from receiving truly satisfying suggestions. Therefore, there is a need for a system that offers the best menu at the lowest price based on a user's emotional state.

[1030] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user address data, means for receiving and analyzing user emotion data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for adjusting the cheapest menu based on the user emotion data, and means for proposing and displaying the cheapest menu to the user. This makes it possible to provide the optimal menu plan at the cheapest price based on the user's address data and emotion data, thereby reducing the user's stress and discomfort.

[1031] Definitions of important words

[1032] "Address data" is data that indicates information about the place where the user resides.

[1033] "Emotion data" is data that represents the user's current emotional state, and is obtained from voice input, facial expression recognition, or the like.

[1034] "Price information on the Internet" is information about product prices that can be collected from the Internet.

[1035] The "cheapest menu" is the most cost-effective menu plan calculated based on price information collected from multiple stores and restaurants.

[1036] The "means for adjusting the cheapest menu" is a means for changing the content of the cheapest menu based on the user's emotional data and making suggestions that match the user's emotional state.

[1037] The "means for displaying proposed data to the user" refers to a means for visually or audibly presenting the cheapest menu calculated by the server and its adjustment details to the user.

[1038] MODE FOR CARRYING OUT THE INVENTION

[1039] To implement this invention, a system is required that links and operates a server, user terminal, and emotion engine. This system provides the most appropriate, lowest-priced menu based on the user's address data and emotion data. Below, we will explain in detail each component of this system and its processing.

[1040] Server-side processing

[1041] The server performs several functions. First, it receives and analyzes the user's address data from the user's device. Second, it collects price information from stores and restaurants near the user's address via the Internet. This information is collected using web crawling.

[1042] The server integrates the collected price data and calculates the cheapest menu, taking into account each store's inventory status and special sales information. It also receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial expression recognition.

[1043] Finally, the server adjusts the cheapest menu based on the emotion data, taking into account specific ingredients and recipes to reduce the user's stress. Based on the results, it generates the cheapest menu suggestion data and sends it to the user's device.

[1044] Terminal side processing

[1045] The user terminal displays an address input screen to the user and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server.

[1046] The recommendation data sent from the server is received by the user's device and displayed to the user. This display includes not only specific purchase locations and prices, but also emotion-based adjustment menus.

[1047] User operation

[1048] The user enters their home address and emotional data into the app. They then check the cheapest menu items, purchasing locations, and emotion-adjusting menu items suggested by the server and decide whether to purchase them. By purchasing ingredients based on the cheapest menu items suggested by the server, the user can efficiently save on food costs while also receiving emotional support.

[1049] Hardware and software used

[1050] The hardware required is a smartphone and a server, while the software required is a program implemented using Python, web crawling technology, and a sentiment analysis engine.

[1051] Specific examples

[1052] For example, suppose a user lives in Shibuya Ward, Tokyo, and is currently feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shibuya Ward and consolidates the most cost-effective curry ingredient list. Additionally, the server considers specific foods (e.g., chamomile tea) that can help reduce the user's stress, and generates a tailored menu, where, for example, potatoes are 100 yen at one supermarket and carrots are 50 yen at another. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[1053] Example prompts to input to the generative AI model

[1054] The user is stressed and lives in Shibuya, Tokyo. Design a food delivery app that suggests the cheapest stress-reducing menu. The menu should include ingredients with calming effects. Also, provide information on where to purchase each ingredient and their price.

[1055] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1056] Processing Steps

[1057] Step 1:

[1058] Enter and submit user address and emotion data

[1059] Operation:

[1060] The user inputs address data and emotion data using a smartphone terminal.

[1061] Emotional data is collected through voice input or facial expression recognition.

[1062] input:

[1063] Address data and emotion data entered by the user.

[1064] Data processing / calculation:

[1065] Formats the input data and prepares it for sending to the server.

[1066] output:

[1067] The formatted address data and emotion data are sent to a server.

[1068] Step 2:

[1069] Receiving and parsing address data

[1070] Operation:

[1071] The server receives the address data sent from the user terminal.

[1072] The received address data is analyzed to extract specific geographic information.

[1073] input:

[1074] Address data sent from the device.

[1075] Data processing / calculation:

[1076] Format analysis of address data and extraction of geographic information.

[1077] output:

[1078] The extracted geographic information.

[1079] Step 3:

[1080] Collecting price information from the internet

[1081] Operation:

[1082] Based on the extracted geographical information, the server collects price information from nearby stores and restaurants from the Internet.

[1083] The latest price information is obtained using web crawling technology.

[1084] input:

[1085] Geographic information.

[1086] Data processing / calculation:

[1087] Price information gathering using web crawling.

[1088] output:

[1089] Price information for nearby stores and restaurants.

[1090] Step 4:

[1091] Price data integration and lowest price menu calculation

[1092] Operation:

[1093] The server consolidates the collected pricing data and generates the most cost-effective menu plan.

[1094] It also takes into account inventory information and special sales information from each store.

[1095] input:

[1096] Price information for nearby stores and restaurants.

[1097] Data processing / calculation:

[1098] Integrates price data and calculates the cheapest menu.

[1099] output:

[1100] Data on the cheapest menu.

[1101] Step 5:

[1102] Emotional data analysis and menu adjustment

[1103] Operation:

[1104] The server analyzes the received emotion data through an emotion engine.

[1105] The cheapest menu is adjusted according to the user's emotional state.

[1106] For example, for a user who is feeling stressed, foods with a calming effect can be added to the menu.

[1107] input:

[1108] User sentiment data and cheapest menu data.

[1109] Data processing / calculation:

[1110] Analyzing sentiment data and adjusting the cheapest menu.

[1111] output:

[1112] Adjusted data for cheapest menu.

[1113] Step 6:

[1114] Generate and send proposal data for the cheapest menu

[1115] Operation:

[1116] The server generates adjusted lowest price menu suggestion data.

[1117] The optimized menu plan is transmitted to the user terminal.

[1118] input:

[1119] Adjusted data for cheapest menu.

[1120] Data processing / calculation:

[1121] Proposal data generation.

[1122] output:

[1123] The cheapest menu suggestion data is sent to the user's device.

[1124] Step 7:

[1125] Receiving and displaying suggestion menus

[1126] Operation:

[1127] The user terminal receives the proposal data sent from the server and displays it to the user.

[1128] It also displays specific purchase locations, prices, and emotional adjustment menus.

[1129] input:

[1130] The cheapest menu suggestion data sent from the server.

[1131] Data processing / calculation:

[1132] Prepare to display proposed data.

[1133] output:

[1134] The suggestion menu that is displayed to the user.

[1135] Step 8:

[1136] The user checks the suggested menu and makes a purchase

[1137] Operation:

[1138] The user checks the suggested lowest price menu, purchasing information, and emotion adjustment menu.

[1139] Purchase your materials in-store or online based on the suggested information.

[1140] input:

[1141] Suggestion menu data.

[1142] Data processing / calculation:

[1143] User verification and decision-making process.

[1144] output:

[1145] Purchase of materials.

[1146] 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.

[1147] 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.

[1148] 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.

[1149] [Third embodiment]

[1150] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1151] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1152] 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).

[1153] 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.

[1154] 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.

[1155] 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).

[1156] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1157] 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.

[1158] 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.

[1159] 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.

[1160] 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.

[1161] 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."

[1162] The system according to the present invention is designed to help users save money on food by suggesting the cheapest menu items based on their address data. This system is mainly composed of a server, a user terminal, and user operations.

[1163] Server-side processing

[1164] 1. Obtaining user address data

[1165] The server receives the home address data sent from the user terminal and analyzes it.

[1166] For example: "When a user enters an address into the app, the server receives and parses the information."

[1167] 2. Collecting information from the Internet

[1168] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address using web crawling and other techniques.

[1169] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[1170] 3. Price data integration and lowest price menu calculation

[1171] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[1172] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[1173] 4. Lowest price menu suggestions

[1174] Based on the calculation results, the server generates data suggesting the cheapest menu and specific purchasing information to the user, and transmits this to the user's terminal.

[1175] Example: "The server creates a list of the cheapest menu items and their purchases, and sends it to the user's terminal."

[1176] Terminal side processing

[1177] 1. Displaying the user interface

[1178] The terminal displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[1179] Example: "The device presents the user with an address entry form as the initial screen of the app."

[1180] 2. Send input data

[1181] When the user enters address data, the terminal transmits the data to the server.

[1182] Example: "The user enters an address and the device sends the data to the server."

[1183] 3. Receiving and displaying the proposal menu

[1184] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[1185] Example: "The device displays the curry recipe received from the server and lists the ingredients needed and where to purchase them."

[1186] User operation

[1187] 1. Enter your address

[1188] The user enters their home address into the app, and the information is sent by the device to the server.

[1189] Example: "The user opens the app and enters their home address into the address form."

[1190] 2. Check the cheapest menu

[1191] The user checks the cheapest menu and purchasing information proposed by the server and decides whether to purchase.

[1192] Example: "The user sees the ingredients list for the curry and the price at the nearest supermarket before deciding to buy it."

[1193] Specific examples

[1194] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at WinMart and carrots costing 50 yen at Supermarket A. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[1195] This system allows users to save money on food efficiently and hassle-free.

[1196] The processing flow will be explained below.

[1197] Step 1:

[1198] Launching the application

[1199] User

[1200] The user launches the food cost saving tool app on their smartphone or PC.

[1201] Example: "A user launches a food cost savings app."

[1202] Step 2:

[1203] Enter your address

[1204] User

[1205] The user enters their home address into the app's address form.

[1206] Example: "A user enters their home address into an address form."

[1207] Terminal

[1208] Prepare to send the entered address data to the server.

[1209] Example: "The terminal prepares the address data entered by the user for transmission to the server."

[1210] Step 3:

[1211] Sending address data

[1212] Terminal

[1213] The address data is sent to the server.

[1214] Example: "The device sends the address data to the server."

[1215] Step 4:

[1216] Receiving and parsing address data

[1217] server

[1218] Receives address data sent from the terminal and analyzes it.

[1219] Example: "The server receives and analyzes the address data sent from the device."

[1220] Step 5:

[1221] Internet information gathering

[1222] server

[1223] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[1224] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[1225] Step 6:

[1226] Price data integration and lowest price menu calculation

[1227] server

[1228] Integrate collected pricing data to calculate the most cost-effective menu.

[1229] Example: "The server aggregates the price data and calculates the cheapest dinner menu for the day."

[1230] Step 7:

[1231] Generate proposal data for the cheapest menu

[1232] server

[1233] Based on the integration and calculation results, data suggesting the cheapest menu is generated.

[1234] Example: "The server creates a list of the cheapest menu items and their purchases."

[1235] Step 8:

[1236] Submitting proposal data

[1237] server

[1238] The proposal data is transmitted to the user terminal.

[1239] Example: "The server sends the proposal data to the user's device."

[1240] Step 9:

[1241] Receiving and displaying suggestion menus

[1242] Terminal

[1243] The proposed data transmitted from the server is received and displayed to the user.

[1244] Example: "The device displays the received lowest price menu and purchase information to the user."

[1245] Step 10:

[1246] Review and select the suggestions

[1247] User

[1248] Check the suggested lowest price menu and purchasing information to make the best choice.

[1249] For example: "The user reviews the presented materials list and prices and then decides to purchase."

[1250] Example 1

[1251] 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."

[1252] In the past, in order to save on food costs, users had to personally research multiple retail stores and online stores, compare prices, and identify the most cost-effective source of purchase. This required time and effort, and was particularly cumbersome when purchasing everyday ingredients. There was a need for a system that could improve this situation and enable users to efficiently save on food costs.

[1253] 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.

[1254] In this invention, the server includes means for receiving and analyzing the user's address data, means for collecting price information of nearby stores over the Internet based on the address data, and means for integrating the collected price data to calculate the most cost-effective menu. This allows the user to automatically collect price information of nearby stores and propose the cheapest menu by simply inputting their address, thereby enabling efficient savings on food costs.

[1255] "Address data" indicates the location information or address of the user's home as input by the user.

[1256] "Sales outlet" is a general term for places that provide price information, such as supermarkets, stores that sell food, or restaurants.

[1257] "Price information" is data relating to the prices of products sold at each store.

[1258] A "menu" is a list of ingredients needed for a particular meal and the dishes that use them.

[1259] "Suggestion" is the act of showing the user the best option based on collected information.

[1260] "Analysis" means converting received data into an understandable format and understanding its contents.

[1261] "Collection" means gathering the necessary information via the Internet.

[1262] "Integration" means combining multiple pieces of data into one and making it possible to analyze it as a whole.

[1263] "Cost-effectiveness" refers to the state in which maximum effect can be obtained with minimum cost.

[1264] "Proposal data" is data generated by the server that includes the cheapest menu and information on where to purchase it.

[1265] The present invention is a system that supports food cost savings by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[1266] First, the user enters their home address into the application. This application runs on the user's device and provides an address input form through a user interface. When the user enters the address and presses the submit button, the device sends the address data to the server.

[1267] The server receives and analyzes the address data sent from the user's device. The analyzed address data is used to collect price information from nearby stores via the Internet. Specifically, a web crawler is used to obtain the latest price information from each store's website. The web crawler used here can be a general web scraping tool.

[1268] The collected price information is integrated within the server, and the next step is to calculate the most cost-effective menu. The server analyzes the collected price data and integrates data from multiple stores. For example, price information from supermarkets and restaurants near the address specified by the user is integrated, and the cheapest menu is calculated taking into account special sales and inventory status.

[1269] The calculated cheapest menu item and its specific purchasing location information are generated as data on the server side and sent back to the user's device. The user device receives this data and displays it to the user in an intuitive and easy-to-understand format. For example, it may display something like "potatoes are 100 yen at supermarket A, and carrots are 50 yen at supermarket B."

[1270] Based on the information provided, users can decide which inventory to purchase and at which store. This system allows users to save on food costs efficiently and without hassle.

[1271] Specific examples

[1272] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at one supermarket and carrots costing 50 yen at another. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[1273] Using ChatGPT as a generative AI model, specific explanatory text can be generated using the following prompt text:

[1274] Example prompt sentence:

[1275] "This system suggests the cheapest menu items based on the user's address data, helping them save on food expenses. The server-side process first receives and analyzes the address data sent from the user's device. Next, it crawls the web to collect price information from supermarkets and restaurants around the specified address. It integrates the collected price data, calculates the most cost-effective menu items, and suggests them to the user. The device-side process displays a user interface, sends the address data to the server, and receives and displays the cheapest menu items. User operations include entering the address and confirming the cheapest menu items. For example, if the user lives in Shinjuku Ward, Tokyo, the server will collect price information from supermarkets and restaurants around Shinjuku Ward and provide a list of ingredients for the most cost-effective curry."

[1276] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1277] Step 1:

[1278] Enter and submit address data

[1279] Input: The user enters their home address into the device's address input form.

[1280] Specific operation: The terminal displays an address input form through the user interface, and the user inputs his / her address.

[1281] Data processing / calculation: The device converts the address data into JSON format and sends it to the server.

[1282] Output: Address data is sent to the server in JSON format.

[1283] For example, when a user inputs "Shinjuku-ku, Tokyo" and presses the send button, the terminal transmits the data to the server as a POST request.

[1284] Step 2:

[1285] Receiving and parsing address data

[1286] Input: Address data sent from the terminal.

[1287] Specific operation: The server receives data sent from the user terminal.

[1288] Data processing / calculation: The server parses the received address data in JSON format and stores it in an internal database.

[1289] Output: Parsed address data is saved in a database.

[1290] For example, address data such as "Shinjuku-ku, Tokyo" is parsed in JSON format and stored in a database.

[1291] Step 3:

[1292] Gathering price information from nearby stores

[1293] Input: Parsed address data.

[1294] Specific operation: The server launches a web crawler and collects price information for nearby stores based on the address data.

[1295] Data processing / calculation: The web crawler accesses the specified websites and extracts price information from HTML pages. The extracted information is converted into JSON format and sent to the server.

[1296] Output: Price information of nearby stores is collected in JSON format.

[1297] For example, sales information for nearby supermarkets and coupon information for restaurants is collected and sent to the server in JSON format.

[1298] Step 4:

[1299] Price data integration and lowest price menu calculation

[1300] Input: Collected pricing information.

[1301] Specific operation: The server retrieves the collected price data from the database and consolidates it.

[1302] Data processing / calculation: Based on the combined data, an algorithm is run to generate the lowest-priced ingredient list, taking into account special offers and availability.

[1303] Output: Cheapest menu and where to buy information.

[1304] For example, it can integrate price data for potatoes and carrots collected from multiple supermarkets to calculate the cheapest curry recipe.

[1305] Step 5:

[1306] Propose and send the cheapest menu

[1307] Input: Cheapest menu and where to buy information.

[1308] Specific operation: Based on the calculation results, the server generates data to suggest to the user.

[1309] Data processing / calculation: Generate the cheapest menu and its purchase list in HTML or JSON format.

[1310] Output: The proposed data is sent to the user device.

[1311] For example, proposal data including information that potatoes cost 100 yen at one supermarket and carrots cost 50 yen at another supermarket is generated and sent to the user terminal.

[1312] Step 6:

[1313] Receiving and displaying suggestion menus

[1314] Input: Proposal data sent by the server.

[1315] Specific operation: The terminal receives the cheapest menu suggestion data sent from the server.

[1316] Data processing / calculation: Analyzes the received data and displays it in a form that is easy for the user to understand.

[1317] Output: The cheapest menu and purchasing information will be displayed on the device.

[1318] For example, the user terminal displays a curry recipe received from the server and presents it to the user in the form of potatoes costing 100 yen and carrots costing 50 yen.

[1319] (Application example 1)

[1320] 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."

[1321] With conventional food delivery services, users had to go through the trouble of comparing multiple services and stores to find the cheapest menu, making it difficult to effectively reduce food costs.In addition, price information was not updated in real time, making it difficult to suggest optimal menu items based on the latest price information.

[1322] 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.

[1323] In this invention, the server includes means for receiving user address data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for proposing and displaying the cheapest menu to the user, means for collecting price information of delivery services based on the user's address, and means for providing options for placing a delivery order. This saves the user the trouble of comparing price information of multiple services and stores, and allows the user to receive suggestions for the cheapest menu in real time, enabling efficient savings on food costs.

[1324] The "means for receiving user address data" refers to a method by which a user inputs his or her address information and the system receives it.

[1325] "Methods for collecting price information on the Internet" refers to methods for obtaining price information for goods and services from websites and online databases.

[1326] The "means of integrating collected price data to calculate the cheapest menu" is a method of aggregating price information obtained from multiple data sources and calculating the lowest cost menu based on that information.

[1327] The "means for proposing and displaying the cheapest menu to the user" is a method for presenting the calculated cheapest menu and information on where to purchase it to the user.

[1328] "Means for collecting price information for delivery services based on the user's address" refers to a method for collecting price information for delivery services available in the vicinity from stores or services that provide such information based on the user's address information.

[1329] The "means for providing an option to place a delivery order" is a method for providing a function for a user to directly place a delivery order based on the suggested cheapest menu item.

[1330] The present invention is a system that aims to efficiently reduce food costs by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[1331] Server-side processing

[1332] 1. Obtaining user address data

[1333] The server receives address data entered by the user from the device. For example, when a user enters their home address into a smartphone app, the information is sent to the server and analyzed.

[1334] 2. Collecting information from the Internet

[1335] The server uses the received address data to collect price information for delivery services (restaurants and supermarkets) near the user's address. This information is collected using techniques such as web crawling.

[1336] 3. Price data integration and lowest price menu calculation

[1337] The server aggregates the collected price data and calculates the most cost-effective delivery options, taking into account product availability and special offers at each store.

[1338] 4. Lowest price menu suggestions

[1339] Based on the calculation results, the server proposes the cheapest menu and specific delivery purchasing information to the user, and sends this data to the user's terminal.

[1340] Terminal side processing

[1341] 1. Displaying the user interface

[1342] The device (such as a smartphone) displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[1343] 2. Send input data

[1344] When the user enters address data, the terminal transmits the data to the server.

[1345] 3. Receiving and displaying the proposal menu

[1346] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[1347] 4. Delivery ordering options

[1348] The device will offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to order directly from the app and save money on food.

[1349] User operation

[1350] 1. Enter your address

[1351] The user enters their home address into the app, and the information is sent by the device to the server.

[1352] 2. Check the cheapest menu and order

[1353] The user checks the cheapest menu and purchasing information suggested by the server, and places a delivery order based on the suggested menu.

[1354] Specific examples

[1355] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information for delivery restaurants in the Shinjuku area. The server will then calculate the most cost-effective delivery menu and generate a detailed ingredient list and pricing information for the nearest delivery service. Based on this information, users can place a delivery order directly, effectively saving money on food.

[1356] Hardware and software used

[1357] Hardware: Smartphone

[1358] Software: Python, Requests, BeautifulSoup

[1359] Prompt Sentence Examples

[1360] "Enter your address: Shinjuku-ku, Tokyo. I'd like to calculate the cheapest menu item and place a delivery order based on that."

[1361] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1362] Step 1:

[1363] A user starts a smartphone app and enters their home address. The entered address data is sent to the server by the device, allowing the server to obtain the user's address information.

[1364] Input: User address data

[1365] Output: Send address data to server

[1366] Step 2:

[1367] The server analyzes the received address data and collects price information for delivery services (restaurants and supermarkets) near the user's address on the Internet. It uses web crawling technology to obtain the latest price data.

[1368] Input: User address data

[1369] Output: Price information for nearby delivery services

[1370] Step 3:

[1371] The server aggregates the collected price data and calculates the most cost-effective delivery menu, taking into account the product availability and sales information at each store. The data is analyzed to calculate the cheapest menu.

[1372] Input: Collected price data

[1373] Output: Cheapest menu

[1374] Step 4:

[1375] The server generates the calculated cheapest menu and specific delivery vendor information and sends this data to the user's terminal, allowing the user to see the cheapest menu available at home.

[1376] Input: Cheapest menu

[1377] Output: Cheapest menu and purchasing information data

[1378] Step 5:

[1379] The terminal displays the cheapest menu suggestion data received from the server to the user. This display includes specific purchase locations and prices, and is designed to be intuitive and easy for the user to understand.

[1380] Input: Data for the suggested menu

[1381] Output: Menu displayed to the user

[1382] Step 6:

[1383] The device will then offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to select this option and place the order directly through the app, effectively saving money on food.

[1384] Input: Cheapest menu and purchase information

[1385] Output: Delivery order options displayed

[1386] Step 7:

[1387] The user checks the presented lowest price menu and purchasing information, and places an order based on the suggested delivery menu. The user's order information is sent from the device to the server and linked to the selected delivery service.

[1388] Input: User order data

[1389] Output: Send order information to delivery service

[1390] Through the above processing steps, the user is presented with the cheapest menu based on the latest price information, allowing them to efficiently place delivery orders and save on food costs.

[1391] 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.

[1392] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[1393] Server-side processing

[1394] 1. Obtaining user address data

[1395] The server receives the home address data sent from the user terminal and analyzes it.

[1396] For example: "When a user enters an address into the app, the server receives and parses the information."

[1397] 2. Collecting information from the Internet

[1398] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address from the Internet, using techniques such as web crawling.

[1399] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[1400] 3. Price data integration and lowest price menu calculation

[1401] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[1402] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[1403] 4. Acquisition and Analysis of Emotion Data

[1404] The server receives and analyzes the user's emotional data through the emotion engine, which is collected based on voice input and facial expression recognition.

[1405] Example: "The server receives the user's emotion data from the emotion engine and analyzes it."

[1406] 5. Emotion-based menu optimization

[1407] Based on the emotional data, the server adjusts the cheapest menu, taking into account specific ingredients and recipes to reduce the user's stress.

[1408] Example: "The server will adjust the menu to reduce user frustration."

[1409] 6. Generate data to suggest the cheapest menu

[1410] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[1411] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[1412] 7. Submitting Proposal Data

[1413] The proposal data is transmitted to the user terminal.

[1414] Example: "The server sends the proposal data to the user's device."

[1415] Terminal side processing

[1416] 1. Displaying the user interface

[1417] The terminal displays an address input screen to the user and then provides an interface for inputting emotion data.

[1418] Example: "The device presents the user with an address input form and an emotion input interface as the initial screen of the app."

[1419] 2. Send input data

[1420] When the user inputs the address and emotion data, the terminal transmits the data to the server.

[1421] Example: "The user enters address and emotion data, and the device sends the data to the server."

[1422] 3. Receiving and displaying the proposal menu

[1423] The device receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[1424] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[1425] User operation

[1426] 1. Enter address and emotion data

[1427] Users enter their home address and emotional data into the app, and the information is sent to the server by the device.

[1428] For example: "The user opens the app, enters their home address into the address form, and provides emotion data."

[1429] 2. Check the cheapest menu

[1430] The user checks the cheapest menu, purchasing information, and emotion adjustment menu proposed by the server, and decides whether to purchase.

[1431] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[1432] Specific examples

[1433] For example, suppose a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. Additionally, the server considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[1434] This system allows users to save money on food efficiently and effortlessly, and to obtain the optimal menu based on their emotional state at the time.

[1435] The processing flow will be explained below.

[1436] Step 1:

[1437] Launching the application

[1438] User

[1439] The user launches the food cost saving tool app on their smartphone or PC.

[1440] Example: "A user launches a food cost savings app."

[1441] Step 2:

[1442] Entering address and emotion data

[1443] User

[1444] The user enters their home address in the address input form of the app and enters their current emotional state in the emotion data input interface.

[1445] Example: "A user enters their home address into an address form and enters emotion data."

[1446] Terminal

[1447] Prepare to send the input address data and emotion data to the server.

[1448] Example: "The device prepares the address data and emotion data entered by the user to be sent to the server."

[1449] Step 3:

[1450] Sending address and emotion data

[1451] Terminal

[1452] Address data and emotion data are sent to the server.

[1453] Example: "The device sends address data and emotion data to the server."

[1454] Step 4:

[1455] Receiving and parsing address data

[1456] server

[1457] Receives address data sent from the terminal and analyzes it.

[1458] Example: "The server receives and analyzes the address data sent from the device."

[1459] Step 5:

[1460] Receiving and analyzing emotion data

[1461] server

[1462] Emotion data sent from the device is received and analyzed by the emotion engine.

[1463] Example: "The server receives and analyzes the emotion data sent through the emotion engine."

[1464] Step 6:

[1465] Internet information gathering

[1466] server

[1467] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[1468] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[1469] Step 7:

[1470] Price Data Integration

[1471] server

[1472] Integrate collected pricing data to calculate the most cost-effective menu.

[1473] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[1474] Step 8:

[1475] Emotion-based menu adjustment

[1476] server

[1477] Based on the analyzed emotional data, the menu is adjusted to reflect specific ingredients and recipes to reduce the user's stress.

[1478] Example: "The server will adjust the menu to reduce user frustration."

[1479] Step 9:

[1480] Generate proposal data for the cheapest menu

[1481] server

[1482] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[1483] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[1484] Step 10:

[1485] Submitting proposal data

[1486] server

[1487] The proposal data is transmitted to the user terminal.

[1488] Example: "The server sends the proposal data to the user's device."

[1489] Step 11:

[1490] Receiving and displaying suggestion menus

[1491] Terminal

[1492] It receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[1493] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[1494] Step 12:

[1495] Review and select the suggestions

[1496] User

[1497] Check the suggested lowest price menu, purchasing information, and emotion adjustment menu to make the best choice.

[1498] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[1499] Example 2

[1500] 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."

[1501] Conventional systems require users to calculate the cheapest menu themselves and do not consider emotional factors that contribute to saving on food costs. Therefore, there is a need for a method to efficiently save on food costs while taking into account users' stress and satisfaction. Furthermore, there are limited means to collect price information from nearby stores in real time and provide optimal menus. This has created an issue where it is difficult for many users to obtain the optimal menu without spending time and effort.

[1502] 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.

[1503] In this invention, the server includes means for receiving and analyzing user address data, means for collecting price information on the Internet and storing it in a database, means for integrating the collected price data and calculating the cheapest menu using an algorithm, means for acquiring and analyzing user emotion data, means for adjusting the cheapest menu with specific ingredients or recipes based on the acquired emotion data, and means for suggesting and displaying the cheapest menu and an adjusted menu based on the emotion to the user. This allows the user to save on food costs efficiently and without hassle, and to obtain the optimal menu according to their emotional state at the time.

[1504] "User Address Data" means location information about a home or other specific location that a User enters into an Application.

[1505] A "server" is a central computer system that receives data sent by users, analyzes it, performs calculations and adjustments, and sends the results to the user terminal.

[1506] "Means for receiving and analyzing address data" refers to the function by which the server receives address information entered by a user and analyzes that information in order to understand and use it.

[1507] "Means for collecting price information on the Internet" refers to technology that allows a server to automatically collect price information from nearby stores and restaurants via the Internet.

[1508] A "database" is an information system in which price information and other related data collected by a server is systematically stored for later retrieval and use.

[1509] An "algorithm" is a set of procedures and calculation methods for performing calculations based on collected data and deriving optimal results.

[1510] "Means for calculating the cheapest menu" refers to a function that uses collected price data to calculate the most cost-effective menu.

[1511] "User emotion data" is data that indicates the user's current emotional state, and is acquired by voice input, facial expression recognition, or other methods.

[1512] "Means for acquiring and analyzing emotional data" refers to the technology and functions for collecting the user's emotional state and analyzing that data.

[1513] "Means for adjusting with specific ingredients or recipes" refers to a function that allows you to add or adjust specific ingredients or recipes to the cheapest menu based on the user's emotional state.

[1514] "Means for proposing and displaying" refers to a function that transmits the cheapest menu calculated by the server and an adjusted menu based on emotion data to the user's terminal and visually presents it to the user.

[1515] "Menu" refers to a list of ingredients and dishes needed for a particular meal.

[1516] "Emotionally tailored menus" refer to menus that include specific ingredients and recipes chosen with the user's emotional state in mind.

[1517] Overall system configuration

[1518] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[1519] Server-side processing

[1520] The server first receives and analyzes the home address data sent from the user's device. The address data is received in the format {"address": "Shinjuku-ku, Tokyo"}, for example. To collect price information from the Internet, the server uses web crawling technology. This technology obtains price information from the Google Maps API and the official websites of each supermarket, and stores it in a database.

[1521] The server then integrates the collected price data and uses an algorithm to calculate the cheapest menu item. For example, an SQL query might be used to search for the lowest price: SELECT MIN(price) FROM prices WHERE item="potatoes". Once the aggregation process is complete, the server receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial recognition.

[1522] Based on the user's emotional data, the system adjusts the cheapest menu by adding specific ingredients or recipes. For example, if the user is feeling stressed, it adds foods with a calming effect (e.g., chamomile tea) to the menu. This recalculates the cheapest menu and generates the final menu in JSON format. The generated menu is in the format {"menu": [{"item": "Potato", "price": 100}, {"item": "Carrot", "price": 50}], "total_price": 150}, for example.

[1523] The generated menu proposal data is sent to the user terminal. At this time, the server sends the data using an HTTP POST request. The user terminal analyzes the received data and displays it on the user interface.

[1524] Terminal side processing

[1525] The user terminal displays an address input screen to the user, and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server. For example, it is transmitted in the format of {"address": "Shinjuku-ku, Tokyo", "emotion": "stress"}.

[1526] The device receives the suggestion data sent from the server and displays it to the user. Specifically, it displays the cheapest menu suggested, its purchasing information, and an adjusted menu based on emotions. This allows the user to efficiently save on food costs and receive emotional support.

[1527] User operation

[1528] The user enters their home address and emotional data through the application. After entering the address and emotional data into the input form and clicking the submit button, the data is sent. The server suggests the cheapest menu, specific product price information, and an adjusted menu based on emotions, and the user can then decide on a purchase. This allows the user to efficiently save on food costs while obtaining a menu that takes emotional factors into consideration.

[1529] Examples of concrete examples and prompts

[1530] For example, consider a situation where a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. In addition, it considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[1531] Example prompt sentence:

[1532] "My address is Shinjuku-ku, Tokyo, and I'm feeling stressed. Based on these conditions, please suggest the cheapest menu item."

[1533] "I live in Kita-ku, Osaka, and I'm feeling depressed. Please recommend the cheapest and most emotionally sensitive option for this."

[1534] In this way, the system of the present invention can efficiently save on food costs and suggest optimal menus according to the user's emotional state.

[1535] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1536] Step 1:

[1537] Enter and submit user address data

[1538] The user opens the application and enters their home address into the input form. The device then sends the entered address data to the server. Specifically, when the user enters the address as text and presses the "Send" button, the device issues an HTTP POST request and sends the data in JSON format to the server.

[1539] Input: User's address data (e.g., Shinjuku-ku, Tokyo)

[1540] Output: Send address data to server

[1541] Step 2:

[1542] Server receives and analyzes address data

[1543] The server receives and analyzes the address data sent from the device. It parses the received JSON format address data and converts it into an internal data format. As a specific example, it analyzes the data {"address": "Shinjuku-ku, Tokyo"} and stores it in a variable for internal use.

[1544] Input: Address data received from the terminal

[1545] Output: Parsed address data

[1546] Step 3:

[1547] Collecting price information from the internet

[1548] Based on the address data, the server collects price information for supermarkets and restaurants in the specified area from the Internet. Using web crawling technology, it obtains price information from Google Maps API and each store's official website. This process requires setting an API key and specifying an endpoint.

[1549] Input: Parsed address data

[1550] Output: Collected price information data (e.g., the price of potatoes is 100 yen)

[1551] Step 4:

[1552] Price data stored in a database

[1553] The server stores the collected price information in a database. The database table contains information such as item name, price, store name, acquisition date and time, etc. In this step, an insert operation is performed using an SQL query.

[1554] Input: Collected pricing information data

[1555] Output: Price information stored in a database

[1556] Step 5:

[1557] Calculating the cheapest menu

[1558] The server uses algorithms to calculate the most cost-effective menu based on pricing data stored in a database, for example by using SQL queries to find the cheapest price for each item and combining them to build the cheapest menu.

[1559] Input: Price information stored in a database

[1560] Output: Data of the cheapest menu item (e.g., potatoes 100 yen, carrots 50 yen)

[1561] Step 6:

[1562] Entering and sending emotional data

[1563] The user inputs their current emotional state through the application. The input emotional data is sent to the server by the device. Specifically, the user selects an emotion from a drop-down menu and presses the "Send" button, which causes the device to send the emotional data as an HTTP POST request.

[1564] Input: User's emotional data (e.g., stress)

[1565] Output: Sending emotion data to the server

[1566] Step 7:

[1567] Acquiring and analyzing emotion data

[1568] The server receives and analyzes the user's emotional data through the emotion engine. This analysis may involve using voice input or facial expression recognition technology. The analyzed emotional data is stored in specific variables.

[1569] Input: Emotion data sent by the user

[1570] Output: Parsed emotion data

[1571] Step 8:

[1572] Emotionally driven adjustment of the cheapest menu

[1573] The server then adjusts the cheapest menu based on the analyzed emotion data, taking into account specific ingredients and recipes. For example, if the user is feeling stressed, it will add foods with a calming effect to the menu. In this step, the price is calculated again.

[1574] Input: Analyzed emotion data, cheapest menu data

[1575] Output: Adjusted lowest price menu

[1576] Step 9:

[1577] Generate proposal data for the cheapest menu

[1578] The server generates the final lowest price menu and an adjusted menu based on the sentiment data in JSON format, which is then ready to be sent to the user's device.

[1579] Input: Adjusted lowest price menu

[1580] Output: Generated proposal data

[1581] Step 10:

[1582] Submitting proposal data

[1583] The server sends the generated proposal data to the user device as an HTTP POST request, for example, in the format {"menu": [{"item": "potato", "price": 100}, {"item": "carrot", "price": 50}], "total_price": 150}.

[1584] Input: Generated proposal data

[1585] Output: Proposal data sent to the user device

[1586] Step 11:

[1587] Receiving and displaying suggestion menus

[1588] The device receives the proposal data sent from the server and visually displays it to the user. Specifically, it parses the received JSON data and displays the material list and price information on the user interface.

[1589] Input: Proposal data sent from the server

[1590] Output: The lowest price menu and the adjusted menu displayed to the user

[1591] (Application example 2)

[1592] 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."

[1593] Conventional food delivery services do not suggest optimal meals based on a user's emotional state, making it difficult for users to easily select meals that will reduce stress and discomfort. Even if systems exist that suggest the cheapest menu plans, they cannot provide optimized menus that take emotional data into account, preventing users from receiving truly satisfying suggestions. Therefore, there is a need for a system that offers the best menu at the lowest price based on a user's emotional state.

[1594] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user address data, means for receiving and analyzing user emotion data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for adjusting the cheapest menu based on the user emotion data, and means for proposing and displaying the cheapest menu to the user. This makes it possible to provide the optimal menu plan at the cheapest price based on the user's address data and emotion data, thereby reducing the user's stress and discomfort.

[1595] Definitions of important words

[1596] "Address data" is data that indicates information about the place where the user resides.

[1597] "Emotion data" is data that represents the user's current emotional state, and is obtained from voice input, facial expression recognition, or the like.

[1598] "Price information on the Internet" is information about product prices that can be collected from the Internet.

[1599] The "cheapest menu" is the most cost-effective menu plan calculated based on price information collected from multiple stores and restaurants.

[1600] The "means for adjusting the cheapest menu" is a means for changing the content of the cheapest menu based on the user's emotional data and making suggestions that match the user's emotional state.

[1601] The "means for displaying proposed data to the user" refers to a means for visually or audibly presenting the cheapest menu calculated by the server and its adjustment details to the user.

[1602] MODE FOR CARRYING OUT THE INVENTION

[1603] To implement this invention, a system is required that links and operates a server, user terminal, and emotion engine. This system provides the most appropriate, lowest-priced menu based on the user's address data and emotion data. Below, we will explain in detail each component of this system and its processing.

[1604] Server-side processing

[1605] The server performs several functions. First, it receives and analyzes the user's address data from the user's device. Second, it collects price information from stores and restaurants near the user's address via the Internet. This information is collected using web crawling.

[1606] The server integrates the collected price data and calculates the cheapest menu, taking into account each store's inventory status and special sales information. It also receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial expression recognition.

[1607] Finally, the server adjusts the cheapest menu based on the emotion data, taking into account specific ingredients and recipes to reduce the user's stress. Based on the results, it generates the cheapest menu suggestion data and sends it to the user's device.

[1608] Terminal side processing

[1609] The user terminal displays an address input screen to the user and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server.

[1610] The recommendation data sent from the server is received by the user's device and displayed to the user. This display includes not only specific purchase locations and prices, but also emotion-based adjustment menus.

[1611] User operation

[1612] The user enters their home address and emotional data into the app. They then check the cheapest menu items, purchasing locations, and emotion-adjusting menu items suggested by the server and decide whether to purchase them. By purchasing ingredients based on the cheapest menu items suggested by the server, the user can efficiently save on food costs while also receiving emotional support.

[1613] Hardware and software used

[1614] The hardware required is a smartphone and a server, while the software required is a program implemented using Python, web crawling technology, and a sentiment analysis engine.

[1615] Specific examples

[1616] For example, suppose a user lives in Shibuya Ward, Tokyo, and is currently feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shibuya Ward and consolidates the most cost-effective curry ingredient list. Additionally, the server considers specific foods (e.g., chamomile tea) that can help reduce the user's stress, and generates a tailored menu, where, for example, potatoes are 100 yen at one supermarket and carrots are 50 yen at another. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[1617] Example prompts to input to the generative AI model

[1618] The user is stressed and lives in Shibuya, Tokyo. Design a food delivery app that suggests the cheapest stress-reducing menu. The menu should include ingredients with calming effects. Also, provide information on where to purchase each ingredient and their price.

[1619] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1620] Processing Steps

[1621] Step 1:

[1622] Enter and submit user address and emotion data

[1623] Operation:

[1624] The user inputs address data and emotion data using a smartphone terminal.

[1625] Emotional data is collected through voice input or facial expression recognition.

[1626] input:

[1627] Address data and emotion data entered by the user.

[1628] Data processing / calculation:

[1629] Formats the input data and prepares it for sending to the server.

[1630] output:

[1631] The formatted address data and emotion data are sent to a server.

[1632] Step 2:

[1633] Receiving and parsing address data

[1634] Operation:

[1635] The server receives the address data sent from the user terminal.

[1636] The received address data is analyzed to extract specific geographic information.

[1637] input:

[1638] Address data sent from the device.

[1639] Data processing / calculation:

[1640] Format analysis of address data and extraction of geographic information.

[1641] output:

[1642] The extracted geographic information.

[1643] Step 3:

[1644] Collecting price information from the internet

[1645] Operation:

[1646] Based on the extracted geographical information, the server collects price information from nearby stores and restaurants from the Internet.

[1647] The latest price information is obtained using web crawling technology.

[1648] input:

[1649] Geographic information.

[1650] Data processing / calculation:

[1651] Price information gathering using web crawling.

[1652] output:

[1653] Price information for nearby stores and restaurants.

[1654] Step 4:

[1655] Price data integration and lowest price menu calculation

[1656] Operation:

[1657] The server consolidates the collected pricing data and generates the most cost-effective menu plan.

[1658] It also takes into account inventory information and special sales information from each store.

[1659] input:

[1660] Price information for nearby stores and restaurants.

[1661] Data processing / calculation:

[1662] Integrates price data and calculates the cheapest menu.

[1663] output:

[1664] Data on the cheapest menu.

[1665] Step 5:

[1666] Emotional data analysis and menu adjustment

[1667] Operation:

[1668] The server analyzes the received emotion data through an emotion engine.

[1669] The cheapest menu is adjusted according to the user's emotional state.

[1670] For example, for a user who is feeling stressed, foods with a calming effect can be added to the menu.

[1671] input:

[1672] User sentiment data and cheapest menu data.

[1673] Data processing / calculation:

[1674] Analyzing sentiment data and adjusting the cheapest menu.

[1675] output:

[1676] Adjusted data for cheapest menu.

[1677] Step 6:

[1678] Generate and send proposal data for the cheapest menu

[1679] Operation:

[1680] The server generates adjusted lowest price menu suggestion data.

[1681] The optimized menu plan is transmitted to the user terminal.

[1682] input:

[1683] Adjusted data for cheapest menu.

[1684] Data processing / calculation:

[1685] Proposal data generation.

[1686] output:

[1687] The cheapest menu suggestion data is sent to the user's device.

[1688] Step 7:

[1689] Receiving and displaying suggestion menus

[1690] Operation:

[1691] The user terminal receives the proposal data sent from the server and displays it to the user.

[1692] It also displays specific purchase locations, prices, and emotional adjustment menus.

[1693] input:

[1694] The cheapest menu suggestion data sent from the server.

[1695] Data processing / calculation:

[1696] Prepare to display proposed data.

[1697] output:

[1698] The suggestion menu that is displayed to the user.

[1699] Step 8:

[1700] The user checks the suggested menu and makes a purchase

[1701] Operation:

[1702] The user checks the suggested lowest price menu, purchasing information, and emotion adjustment menu.

[1703] Purchase your materials in-store or online based on the suggested information.

[1704] input:

[1705] Suggestion menu data.

[1706] Data processing / calculation:

[1707] User verification and decision-making process.

[1708] output:

[1709] Purchase of materials.

[1710] 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.

[1711] 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.

[1712] 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.

[1713] [Fourth embodiment]

[1714] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1715] 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.

[1716] 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).

[1717] 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.

[1718] 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.

[1719] 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).

[1720] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1721] 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.

[1722] 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.

[1723] 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.

[1724] 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.

[1725] 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.

[1726] 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."

[1727] The system according to the present invention is designed to help users save money on food by suggesting the cheapest menu items based on their address data. This system is mainly composed of a server, a user terminal, and user operations.

[1728] Server-side processing

[1729] 1. Obtaining user address data

[1730] The server receives the home address data sent from the user terminal and analyzes it.

[1731] For example: "When a user enters an address into the app, the server receives and parses the information."

[1732] 2. Collecting information from the Internet

[1733] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address using web crawling and other techniques.

[1734] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[1735] 3. Price data integration and lowest price menu calculation

[1736] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[1737] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[1738] 4. Lowest price menu suggestions

[1739] Based on the calculation results, the server generates data suggesting the cheapest menu and specific purchasing information to the user, and transmits this to the user's terminal.

[1740] Example: "The server creates a list of the cheapest menu items and their purchases, and sends it to the user's terminal."

[1741] Terminal side processing

[1742] 1. Displaying the user interface

[1743] The terminal displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[1744] Example: "The device presents the user with an address entry form as the initial screen of the app."

[1745] 2. Send input data

[1746] When the user enters address data, the terminal transmits the data to the server.

[1747] Example: "The user enters an address and the device sends the data to the server."

[1748] 3. Receiving and displaying the proposal menu

[1749] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[1750] Example: "The device displays the curry recipe received from the server and lists the ingredients needed and where to purchase them."

[1751] User operation

[1752] 1. Enter your address

[1753] The user enters their home address into the app, and the information is sent by the device to the server.

[1754] Example: "The user opens the app and enters their home address into the address form."

[1755] 2. Check the cheapest menu

[1756] The user checks the cheapest menu and purchasing information proposed by the server and decides whether to purchase.

[1757] Example: "The user sees the ingredients list for the curry and the price at the nearest supermarket before deciding to buy it."

[1758] Specific examples

[1759] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at WinMart and carrots costing 50 yen at Supermarket A. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[1760] This system allows users to save money on food efficiently and hassle-free.

[1761] The processing flow will be explained below.

[1762] Step 1:

[1763] Launching the application

[1764] User

[1765] The user launches the food cost saving tool app on their smartphone or PC.

[1766] Example: "A user launches a food cost savings app."

[1767] Step 2:

[1768] Enter your address

[1769] User

[1770] The user enters their home address into the app's address form.

[1771] Example: "A user enters their home address into an address form."

[1772] Terminal

[1773] Prepare to send the entered address data to the server.

[1774] Example: "The terminal prepares the address data entered by the user for transmission to the server."

[1775] Step 3:

[1776] Sending address data

[1777] Terminal

[1778] The address data is sent to the server.

[1779] Example: "The device sends the address data to the server."

[1780] Step 4:

[1781] Receiving and parsing address data

[1782] server

[1783] Receives address data sent from the terminal and analyzes it.

[1784] Example: "The server receives and analyzes the address data sent from the device."

[1785] Step 5:

[1786] Internet information gathering

[1787] server

[1788] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[1789] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[1790] Step 6:

[1791] Price data integration and lowest price menu calculation

[1792] server

[1793] Integrate collected pricing data to calculate the most cost-effective menu.

[1794] Example: "The server aggregates the price data and calculates the cheapest dinner menu for the day."

[1795] Step 7:

[1796] Generate proposal data for the cheapest menu

[1797] server

[1798] Based on the integration and calculation results, data suggesting the cheapest menu is generated.

[1799] Example: "The server creates a list of the cheapest menu items and their purchases."

[1800] Step 8:

[1801] Submitting proposal data

[1802] server

[1803] The proposal data is transmitted to the user terminal.

[1804] Example: "The server sends the proposal data to the user's device."

[1805] Step 9:

[1806] Receiving and displaying suggestion menus

[1807] Terminal

[1808] The proposed data transmitted from the server is received and displayed to the user.

[1809] Example: "The device displays the received lowest price menu and purchase information to the user."

[1810] Step 10:

[1811] Review and select the suggestions

[1812] User

[1813] Check the suggested lowest price menu and purchasing information to make the best choice.

[1814] For example: "The user reviews the presented materials list and prices and then decides to purchase."

[1815] Example 1

[1816] 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."

[1817] In the past, in order to save on food costs, users had to personally research multiple retail stores and online stores, compare prices, and identify the most cost-effective source of purchase. This required time and effort, and was particularly cumbersome when purchasing everyday ingredients. There was a need for a system that could improve this situation and enable users to efficiently save on food costs.

[1818] 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.

[1819] In this invention, the server includes means for receiving and analyzing the user's address data, means for collecting price information of nearby stores over the Internet based on the address data, and means for integrating the collected price data to calculate the most cost-effective menu. This allows the user to automatically collect price information of nearby stores and propose the cheapest menu by simply inputting their address, thereby enabling efficient savings on food costs.

[1820] "Address data" indicates the location information or address of the user's home as input by the user.

[1821] "Sales outlet" is a general term for places that provide price information, such as supermarkets, stores that sell food, or restaurants.

[1822] "Price information" is data relating to the prices of products sold at each store.

[1823] A "menu" is a list of ingredients needed for a particular meal and the dishes that use them.

[1824] "Suggestion" is the act of showing the user the best option based on collected information.

[1825] "Analysis" means converting received data into an understandable format and understanding its contents.

[1826] "Collection" means gathering the necessary information via the Internet.

[1827] "Integration" means combining multiple pieces of data into one and making it possible to analyze it as a whole.

[1828] "Cost-effectiveness" refers to the state in which maximum effect can be obtained with minimum cost.

[1829] "Proposal data" is data generated by the server that includes the cheapest menu and information on where to purchase it.

[1830] The present invention is a system that supports food cost savings by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[1831] First, the user enters their home address into the application. This application runs on the user's device and provides an address input form through a user interface. When the user enters the address and presses the submit button, the device sends the address data to the server.

[1832] The server receives and analyzes the address data sent from the user's device. The analyzed address data is used to collect price information from nearby stores via the Internet. Specifically, a web crawler is used to obtain the latest price information from each store's website. The web crawler used here can be a general web scraping tool.

[1833] The collected price information is integrated within the server, and the next step is to calculate the most cost-effective menu. The server analyzes the collected price data and integrates data from multiple stores. For example, price information from supermarkets and restaurants near the address specified by the user is integrated, and the cheapest menu is calculated taking into account special sales and inventory status.

[1834] The calculated cheapest menu item and its specific purchasing location information are generated as data on the server side and sent back to the user's device. The user device receives this data and displays it to the user in an intuitive and easy-to-understand format. For example, it may display something like "potatoes are 100 yen at supermarket A, and carrots are 50 yen at supermarket B."

[1835] Based on the information provided, users can decide which inventory to purchase and at which store. This system allows users to save on food costs efficiently and without hassle.

[1836] Specific examples

[1837] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information from supermarkets and restaurants in the Shinjuku area. The server will then compile a list of ingredients for the most cost-effective curry, generating information such as potatoes costing 100 yen at one supermarket and carrots costing 50 yen at another. This information is then sent to the user's device, and the user can purchase ingredients based on this information, effectively saving on food costs.

[1838] Using ChatGPT as a generative AI model, specific explanatory text can be generated using the following prompt text:

[1839] Example prompt sentence:

[1840] "This system suggests the cheapest menu items based on the user's address data, helping them save on food expenses. The server-side process first receives and analyzes the address data sent from the user's device. Next, it crawls the web to collect price information from supermarkets and restaurants around the specified address. It integrates the collected price data, calculates the most cost-effective menu items, and suggests them to the user. The device-side process displays a user interface, sends the address data to the server, and receives and displays the cheapest menu items. User operations include entering the address and confirming the cheapest menu items. For example, if the user lives in Shinjuku Ward, Tokyo, the server will collect price information from supermarkets and restaurants around Shinjuku Ward and provide a list of ingredients for the most cost-effective curry."

[1841] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1842] Step 1:

[1843] Enter and submit address data

[1844] Input: The user enters their home address into the device's address input form.

[1845] Specific operation: The terminal displays an address input form through the user interface, and the user inputs his / her address.

[1846] Data processing / calculation: The device converts the address data into JSON format and sends it to the server.

[1847] Output: Address data is sent to the server in JSON format.

[1848] For example, when a user inputs "Shinjuku-ku, Tokyo" and presses the send button, the terminal transmits the data to the server as a POST request.

[1849] Step 2:

[1850] Receiving and parsing address data

[1851] Input: Address data sent from the terminal.

[1852] Specific operation: The server receives data sent from the user terminal.

[1853] Data processing / calculation: The server parses the received address data in JSON format and stores it in an internal database.

[1854] Output: Parsed address data is saved in a database.

[1855] For example, address data such as "Shinjuku-ku, Tokyo" is parsed in JSON format and stored in a database.

[1856] Step 3:

[1857] Gathering price information from nearby stores

[1858] Input: Parsed address data.

[1859] Specific operation: The server launches a web crawler and collects price information for nearby stores based on the address data.

[1860] Data processing / calculation: The web crawler accesses the specified websites and extracts price information from HTML pages. The extracted information is converted into JSON format and sent to the server.

[1861] Output: Price information of nearby stores is collected in JSON format.

[1862] For example, sales information for nearby supermarkets and coupon information for restaurants is collected and sent to the server in JSON format.

[1863] Step 4:

[1864] Price data integration and lowest price menu calculation

[1865] Input: Collected pricing information.

[1866] Specific operation: The server retrieves the collected price data from the database and consolidates it.

[1867] Data processing / calculation: Based on the combined data, an algorithm is run to generate the lowest-priced ingredient list, taking into account special offers and availability.

[1868] Output: Cheapest menu and where to buy information.

[1869] For example, it can integrate price data for potatoes and carrots collected from multiple supermarkets to calculate the cheapest curry recipe.

[1870] Step 5:

[1871] Propose and send the cheapest menu

[1872] Input: Cheapest menu and where to buy information.

[1873] Specific operation: Based on the calculation results, the server generates data to suggest to the user.

[1874] Data processing / calculation: Generate the cheapest menu and its purchase list in HTML or JSON format.

[1875] Output: The proposed data is sent to the user device.

[1876] For example, proposal data including information that potatoes cost 100 yen at one supermarket and carrots cost 50 yen at another supermarket is generated and sent to the user terminal.

[1877] Step 6:

[1878] Receiving and displaying suggestion menus

[1879] Input: Proposal data sent by the server.

[1880] Specific operation: The terminal receives the cheapest menu suggestion data sent from the server.

[1881] Data processing / calculation: Analyzes the received data and displays it in a form that is easy for the user to understand.

[1882] Output: The cheapest menu and purchasing information will be displayed on the device.

[1883] For example, the user terminal displays a curry recipe received from the server and presents it to the user in the form of potatoes costing 100 yen and carrots costing 50 yen.

[1884] (Application example 1)

[1885] 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."

[1886] With conventional food delivery services, users had to go through the trouble of comparing multiple services and stores to find the cheapest menu, making it difficult to effectively reduce food costs.In addition, price information was not updated in real time, making it difficult to suggest optimal menu items based on the latest price information.

[1887] 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.

[1888] In this invention, the server includes means for receiving user address data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for proposing and displaying the cheapest menu to the user, means for collecting price information of delivery services based on the user's address, and means for providing options for placing a delivery order. This saves the user the trouble of comparing price information of multiple services and stores, and allows the user to receive suggestions for the cheapest menu in real time, enabling efficient savings on food costs.

[1889] The "means for receiving user address data" refers to a method by which a user inputs his or her address information and the system receives it.

[1890] "Methods for collecting price information on the Internet" refers to methods for obtaining price information for goods and services from websites and online databases.

[1891] The "means of integrating collected price data to calculate the cheapest menu" is a method of aggregating price information obtained from multiple data sources and calculating the lowest cost menu based on that information.

[1892] The "means for proposing and displaying the cheapest menu to the user" is a method for presenting the calculated cheapest menu and information on where to purchase it to the user.

[1893] "Means for collecting price information for delivery services based on the user's address" refers to a method for collecting price information for delivery services available in the vicinity from stores or services that provide such information based on the user's address information.

[1894] The "means for providing an option to place a delivery order" is a method for providing a function for a user to directly place a delivery order based on the suggested cheapest menu item.

[1895] The present invention is a system that aims to efficiently reduce food costs by suggesting the cheapest menu items based on the user's address data. This system is mainly composed of a server, a user terminal, and user operations.

[1896] Server-side processing

[1897] 1. Obtaining user address data

[1898] The server receives address data entered by the user from the device. For example, when a user enters their home address into a smartphone app, the information is sent to the server and analyzed.

[1899] 2. Collecting information from the Internet

[1900] The server uses the received address data to collect price information for delivery services (restaurants and supermarkets) near the user's address. This information is collected using techniques such as web crawling.

[1901] 3. Price data integration and lowest price menu calculation

[1902] The server aggregates the collected price data and calculates the most cost-effective delivery options, taking into account product availability and special offers at each store.

[1903] 4. Lowest price menu suggestions

[1904] Based on the calculation results, the server proposes the cheapest menu and specific delivery purchasing information to the user, and sends this data to the user's terminal.

[1905] Terminal side processing

[1906] 1. Displaying the user interface

[1907] The device (such as a smartphone) displays an address entry screen to the user, which is designed to be intuitive and easy to use.

[1908] 2. Send input data

[1909] When the user enters address data, the terminal transmits the data to the server.

[1910] 3. Receiving and displaying the proposal menu

[1911] The terminal receives the cheapest menu suggestion data sent from the server and displays it to the user, including specific purchase locations and prices.

[1912] 4. Delivery ordering options

[1913] The device will offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to order directly from the app and save money on food.

[1914] User operation

[1915] 1. Enter your address

[1916] The user enters their home address into the app, and the information is sent by the device to the server.

[1917] 2. Check the cheapest menu and order

[1918] The user checks the cheapest menu and purchasing information suggested by the server, and places a delivery order based on the suggested menu.

[1919] Specific examples

[1920] For example, if a user lives in Shinjuku Ward, Tokyo, they can open the app and enter their address. The server will then collect price information for delivery restaurants in the Shinjuku area. The server will then calculate the most cost-effective delivery menu and generate a detailed ingredient list and pricing information for the nearest delivery service. Based on this information, users can place a delivery order directly, effectively saving money on food.

[1921] Hardware and software used

[1922] Hardware: Smartphone

[1923] Software: Python, Requests, BeautifulSoup

[1924] Prompt Sentence Examples

[1925] "Enter your address: Shinjuku-ku, Tokyo. I'd like to calculate the cheapest menu item and place a delivery order based on that."

[1926] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1927] Step 1:

[1928] A user starts a smartphone app and enters their home address. The entered address data is sent to the server by the device, allowing the server to obtain the user's address information.

[1929] Input: User address data

[1930] Output: Send address data to server

[1931] Step 2:

[1932] The server analyzes the received address data and collects price information for delivery services (restaurants and supermarkets) near the user's address on the Internet. It uses web crawling technology to obtain the latest price data.

[1933] Input: User address data

[1934] Output: Price information for nearby delivery services

[1935] Step 3:

[1936] The server aggregates the collected price data and calculates the most cost-effective delivery menu, taking into account the product availability and sales information at each store. The data is analyzed to calculate the cheapest menu.

[1937] Input: Collected price data

[1938] Output: Cheapest menu

[1939] Step 4:

[1940] The server generates the calculated cheapest menu and specific delivery vendor information and sends this data to the user's terminal, allowing the user to see the cheapest menu available at home.

[1941] Input: Cheapest menu

[1942] Output: Cheapest menu and purchasing information data

[1943] Step 5:

[1944] The terminal displays the cheapest menu suggestion data received from the server to the user. This display includes specific purchase locations and prices, and is designed to be intuitive and easy for the user to understand.

[1945] Input: Data for the suggested menu

[1946] Output: Menu displayed to the user

[1947] Step 6:

[1948] The device will then offer users the option to place a delivery order based on the suggested cheapest menu item, allowing them to select this option and place the order directly through the app, effectively saving money on food.

[1949] Input: Cheapest menu and purchase information

[1950] Output: Delivery order options displayed

[1951] Step 7:

[1952] The user checks the presented lowest price menu and purchasing information, and places an order based on the suggested delivery menu. The user's order information is sent from the device to the server and linked to the selected delivery service.

[1953] Input: User order data

[1954] Output: Send order information to delivery service

[1955] Through the above processing steps, the user is presented with the cheapest menu based on the latest price information, allowing them to efficiently place delivery orders and save on food costs.

[1956] 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.

[1957] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[1958] Server-side processing

[1959] 1. Obtaining user address data

[1960] The server receives the home address data sent from the user terminal and analyzes it.

[1961] For example: "When a user enters an address into the app, the server receives and parses the information."

[1962] 2. Collecting information from the Internet

[1963] The server uses the received address data to collect price information for supermarkets and restaurants near the user's address from the Internet, using techniques such as web crawling.

[1964] Example: "The server collects sales information for nearby supermarkets and coupon information for restaurants in real time."

[1965] 3. Price data integration and lowest price menu calculation

[1966] The server aggregates the collected pricing data and calculates the most cost-effective menu, taking into account product availability and special offers at each store.

[1967] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[1968] 4. Acquisition and Analysis of Emotion Data

[1969] The server receives and analyzes the user's emotional data through the emotion engine, which is collected based on voice input and facial expression recognition.

[1970] Example: "The server receives the user's emotion data from the emotion engine and analyzes it."

[1971] 5. Emotion-based menu optimization

[1972] Based on the emotional data, the server adjusts the cheapest menu, taking into account specific ingredients and recipes to reduce the user's stress.

[1973] Example: "The server will adjust the menu to reduce user frustration."

[1974] 6. Generate data to suggest the cheapest menu

[1975] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[1976] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[1977] 7. Submitting Proposal Data

[1978] The proposal data is transmitted to the user terminal.

[1979] Example: "The server sends the proposal data to the user's device."

[1980] Terminal side processing

[1981] 1. Displaying the user interface

[1982] The terminal displays an address input screen to the user and then provides an interface for inputting emotion data.

[1983] Example: "The device presents the user with an address input form and an emotion input interface as the initial screen of the app."

[1984] 2. Send input data

[1985] When the user inputs the address and emotion data, the terminal transmits the data to the server.

[1986] Example: "The user enters address and emotion data, and the device sends the data to the server."

[1987] 3. Receiving and displaying the proposal menu

[1988] The device receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[1989] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[1990] User operation

[1991] 1. Enter address and emotion data

[1992] Users enter their home address and emotional data into the app, and the information is sent to the server by the device.

[1993] For example: "The user opens the app, enters their home address into the address form, and provides emotion data."

[1994] 2. Check the cheapest menu

[1995] The user checks the cheapest menu, purchasing information, and emotion adjustment menu proposed by the server, and decides whether to purchase.

[1996] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[1997] Specific examples

[1998] For example, suppose a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. Additionally, the server considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[1999] This system allows users to save money on food efficiently and effortlessly, and to obtain the optimal menu based on their emotional state at the time.

[2000] The processing flow will be explained below.

[2001] Step 1:

[2002] Launching the application

[2003] User

[2004] The user launches the food cost saving tool app on their smartphone or PC.

[2005] Example: "A user launches a food cost savings app."

[2006] Step 2:

[2007] Entering address and emotion data

[2008] User

[2009] The user enters their home address in the address input form of the app and enters their current emotional state in the emotion data input interface.

[2010] Example: "A user enters their home address into an address form and enters emotion data."

[2011] Terminal

[2012] Prepare to send the input address data and emotion data to the server.

[2013] Example: "The device prepares the address data and emotion data entered by the user to be sent to the server."

[2014] Step 3:

[2015] Sending address and emotion data

[2016] Terminal

[2017] Address data and emotion data are sent to the server.

[2018] Example: "The device sends address data and emotion data to the server."

[2019] Step 4:

[2020] Receiving and parsing address data

[2021] server

[2022] Receives address data sent from the terminal and analyzes it.

[2023] Example: "The server receives and analyzes the address data sent from the device."

[2024] Step 5:

[2025] Receiving and analyzing emotion data

[2026] server

[2027] Emotion data sent from the device is received and analyzed by the emotion engine.

[2028] Example: "The server receives and analyzes the emotion data sent through the emotion engine."

[2029] Step 6:

[2030] Internet information gathering

[2031] server

[2032] Based on address data, price information for nearby supermarkets and restaurants is collected from the Internet.

[2033] Example: "The server collects price information for supermarkets and restaurants near the user's address."

[2034] Step 7:

[2035] Price Data Integration

[2036] server

[2037] Integrate collected pricing data to calculate the most cost-effective menu.

[2038] Example: "The server aggregates price data from multiple supermarkets and calculates the cheapest dinner menu for the day."

[2039] Step 8:

[2040] Emotion-based menu adjustment

[2041] server

[2042] Based on the analyzed emotional data, the menu is adjusted to reflect specific ingredients and recipes to reduce the user's stress.

[2043] Example: "The server will adjust the menu to reduce user frustration."

[2044] Step 9:

[2045] Generate proposal data for the cheapest menu

[2046] server

[2047] Based on the integration and calculation results and adjustment results based on emotional data, the system generates proposal data for the cheapest menu.

[2048] For example: "The server will create a list of the cheapest items and their purchases, and include items adjusted based on emotion."

[2049] Step 10:

[2050] Submitting proposal data

[2051] server

[2052] The proposal data is transmitted to the user terminal.

[2053] Example: "The server sends the proposal data to the user's device."

[2054] Step 11:

[2055] Receiving and displaying suggestion menus

[2056] Terminal

[2057] It receives the recommendation data sent from the server and displays it to the user, including not only specific purchase locations and prices, but also emotion-based adjustment menus.

[2058] Example: "The device displays the received lowest price menu and menu adjustment information based on emotions to the user."

[2059] Step 12:

[2060] Review and select the suggestions

[2061] User

[2062] Check the suggested lowest price menu, purchasing information, and emotion adjustment menu to make the best choice.

[2063] For example: "The user reviews the ingredients list, prices, and emotional adjustments provided, then makes a purchase decision."

[2064] Example 2

[2065] 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."

[2066] Conventional systems require users to calculate the cheapest menu themselves and do not consider emotional factors that contribute to saving on food costs. Therefore, there is a need for a method to efficiently save on food costs while taking into account users' stress and satisfaction. Furthermore, there are limited means to collect price information from nearby stores in real time and provide optimal menus. This has created an issue where it is difficult for many users to obtain the optimal menu without spending time and effort.

[2067] 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.

[2068] In this invention, the server includes means for receiving and analyzing user address data, means for collecting price information on the Internet and storing it in a database, means for integrating the collected price data and calculating the cheapest menu using an algorithm, means for acquiring and analyzing user emotion data, means for adjusting the cheapest menu with specific ingredients or recipes based on the acquired emotion data, and means for suggesting and displaying the cheapest menu and an adjusted menu based on the emotion to the user. This allows the user to save on food costs efficiently and without hassle, and to obtain the optimal menu according to their emotional state at the time.

[2069] "User Address Data" means location information about a home or other specific location that a User enters into an Application.

[2070] A "server" is a central computer system that receives data sent by users, analyzes it, performs calculations and adjustments, and sends the results to the user terminal.

[2071] "Means for receiving and analyzing address data" refers to the function by which the server receives address information entered by a user and analyzes that information in order to understand and use it.

[2072] "Means for collecting price information on the Internet" refers to technology that allows a server to automatically collect price information from nearby stores and restaurants via the Internet.

[2073] A "database" is an information system in which price information and other related data collected by a server is systematically stored for later retrieval and use.

[2074] An "algorithm" is a set of procedures and calculation methods for performing calculations based on collected data and deriving optimal results.

[2075] "Means for calculating the cheapest menu" refers to a function that uses collected price data to calculate the most cost-effective menu.

[2076] "User emotion data" is data that indicates the user's current emotional state, and is acquired by voice input, facial expression recognition, or other methods.

[2077] "Means for acquiring and analyzing emotional data" refers to the technology and functions for collecting the user's emotional state and analyzing that data.

[2078] "Means for adjusting with specific ingredients or recipes" refers to a function that allows you to add or adjust specific ingredients or recipes to the cheapest menu based on the user's emotional state.

[2079] "Means for proposing and displaying" refers to a function that transmits the cheapest menu calculated by the server and an adjusted menu based on emotion data to the user's terminal and visually presents it to the user.

[2080] "Menu" refers to a list of ingredients and dishes needed for a particular meal.

[2081] "Emotionally tailored menus" refer to menus that include specific ingredients and recipes chosen with the user's emotional state in mind.

[2082] Overall system configuration

[2083] The system of the present invention proposes the cheapest menu based on the user's address data and emotion data, helping to save on food costs and providing a menu that corresponds to the user's emotion. This system is mainly composed of a server, a user terminal, user operation, and an emotion engine.

[2084] Server-side processing

[2085] The server first receives and analyzes the home address data sent from the user's device. The address data is received in the format {"address": "Shinjuku-ku, Tokyo"}, for example. To collect price information from the Internet, the server uses web crawling technology. This technology obtains price information from the Google Maps API and the official websites of each supermarket, and stores it in a database.

[2086] The server then integrates the collected price data and uses an algorithm to calculate the cheapest menu item. For example, an SQL query might be used to search for the lowest price: SELECT MIN(price) FROM prices WHERE item="potatoes". Once the aggregation process is complete, the server receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial recognition.

[2087] Based on the user's emotional data, the system adjusts the cheapest menu by adding specific ingredients or recipes. For example, if the user is feeling stressed, it adds foods with a calming effect (e.g., chamomile tea) to the menu. This recalculates the cheapest menu and generates the final menu in JSON format. The generated menu is in the format {"menu": [{"item": "Potato", "price": 100}, {"item": "Carrot", "price": 50}], "total_price": 150}, for example.

[2088] The generated menu proposal data is sent to the user terminal. At this time, the server sends the data using an HTTP POST request. The user terminal analyzes the received data and displays it on the user interface.

[2089] Terminal side processing

[2090] The user terminal displays an address input screen to the user, and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server. For example, it is transmitted in the format of {"address": "Shinjuku-ku, Tokyo", "emotion": "stress"}.

[2091] The device receives the suggestion data sent from the server and displays it to the user. Specifically, it displays the cheapest menu suggested, its purchasing information, and an adjusted menu based on emotions. This allows the user to efficiently save on food costs and receive emotional support.

[2092] User operation

[2093] The user enters their home address and emotional data through the application. After entering the address and emotional data into the input form and clicking the submit button, the data is sent. The server suggests the cheapest menu, specific product price information, and an adjusted menu based on emotions, and the user can then decide on a purchase. This allows the user to efficiently save on food costs while obtaining a menu that takes emotional factors into consideration.

[2094] Examples of concrete examples and prompts

[2095] For example, consider a situation where a user lives in Shinjuku Ward, Tokyo, and is feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shinjuku Ward and synthesizes the most cost-effective curry ingredient list. In addition, it considers specific foods that can reduce the user's stress (e.g., foods with a calming effect) and generates a tailored menu, such as potatoes for 100 yen at WinMart and carrots for 50 yen at Supermarket A. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[2096] Example prompt sentence:

[2097] "My address is Shinjuku-ku, Tokyo, and I'm feeling stressed. Based on these conditions, please suggest the cheapest menu item."

[2098] "I live in Kita-ku, Osaka, and I'm feeling depressed. Please recommend the cheapest and most emotionally sensitive option for this."

[2099] In this way, the system of the present invention can efficiently save on food costs and suggest optimal menus according to the user's emotional state.

[2100] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2101] Step 1:

[2102] Enter and submit user address data

[2103] The user opens the application and enters their home address into the input form. The device then sends the entered address data to the server. Specifically, when the user enters the address as text and presses the "Send" button, the device issues an HTTP POST request and sends the data in JSON format to the server.

[2104] Input: User's address data (e.g., Shinjuku-ku, Tokyo)

[2105] Output: Send address data to server

[2106] Step 2:

[2107] Server receives and analyzes address data

[2108] The server receives and analyzes the address data sent from the device. It parses the received JSON format address data and converts it into an internal data format. As a specific example, it analyzes the data {"address": "Shinjuku-ku, Tokyo"} and stores it in a variable for internal use.

[2109] Input: Address data received from the terminal

[2110] Output: Parsed address data

[2111] Step 3:

[2112] Collecting price information from the internet

[2113] Based on the address data, the server collects price information for supermarkets and restaurants in the specified area from the Internet. Using web crawling technology, it obtains price information from Google Maps API and each store's official website. This process requires setting an API key and specifying an endpoint.

[2114] Input: Parsed address data

[2115] Output: Collected price information data (e.g., the price of potatoes is 100 yen)

[2116] Step 4:

[2117] Price data stored in a database

[2118] The server stores the collected price information in a database. The database table contains information such as item name, price, store name, acquisition date and time, etc. In this step, an insert operation is performed using an SQL query.

[2119] Input: Collected pricing information data

[2120] Output: Price information stored in a database

[2121] Step 5:

[2122] Calculating the cheapest menu

[2123] The server uses algorithms to calculate the most cost-effective menu based on pricing data stored in a database, for example by using SQL queries to find the cheapest price for each item and combining them to build the cheapest menu.

[2124] Input: Price information stored in a database

[2125] Output: Data of the cheapest menu item (e.g., potatoes 100 yen, carrots 50 yen)

[2126] Step 6:

[2127] Entering and sending emotional data

[2128] The user inputs their current emotional state through the application. The input emotional data is sent to the server by the device. Specifically, the user selects an emotion from a drop-down menu and presses the "Send" button, which causes the device to send the emotional data as an HTTP POST request.

[2129] Input: User's emotional data (e.g., stress)

[2130] Output: Sending emotion data to the server

[2131] Step 7:

[2132] Acquiring and analyzing emotion data

[2133] The server receives and analyzes the user's emotional data through the emotion engine. This analysis may involve using voice input or facial expression recognition technology. The analyzed emotional data is stored in specific variables.

[2134] Input: Emotion data sent by the user

[2135] Output: Parsed emotion data

[2136] Step 8:

[2137] Emotionally driven adjustment of the cheapest menu

[2138] The server then adjusts the cheapest menu based on the analyzed emotion data, taking into account specific ingredients and recipes. For example, if the user is feeling stressed, it will add foods with a calming effect to the menu. In this step, the price is calculated again.

[2139] Input: Analyzed emotion data, cheapest menu data

[2140] Output: Adjusted lowest price menu

[2141] Step 9:

[2142] Generate proposal data for the cheapest menu

[2143] The server generates the final lowest price menu and an adjusted menu based on the sentiment data in JSON format, which is then ready to be sent to the user's device.

[2144] Input: Adjusted lowest price menu

[2145] Output: Generated proposal data

[2146] Step 10:

[2147] Submitting proposal data

[2148] The server sends the generated proposal data to the user device as an HTTP POST request, for example, in the format {"menu": [{"item": "potato", "price": 100}, {"item": "carrot", "price": 50}], "total_price": 150}.

[2149] Input: Generated proposal data

[2150] Output: Proposal data sent to the user device

[2151] Step 11:

[2152] Receiving and displaying suggestion menus

[2153] The device receives the proposal data sent from the server and visually displays it to the user. Specifically, it parses the received JSON data and displays the material list and price information on the user interface.

[2154] Input: Proposal data sent from the server

[2155] Output: The lowest price menu and the adjusted menu displayed to the user

[2156] (Application example 2)

[2157] 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."

[2158] Conventional food delivery services do not suggest optimal meals based on a user's emotional state, making it difficult for users to easily select meals that will reduce stress and discomfort. Even if systems exist that suggest the cheapest menu plans, they cannot provide optimized menus that take emotional data into account, preventing users from receiving truly satisfying suggestions. Therefore, there is a need for a system that offers the best menu at the lowest price based on a user's emotional state.

[2159] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user address data, means for receiving and analyzing user emotion data, means for collecting price information on the Internet, means for integrating the collected price data to calculate the cheapest menu, means for adjusting the cheapest menu based on the user emotion data, and means for proposing and displaying the cheapest menu to the user. This makes it possible to provide the optimal menu plan at the cheapest price based on the user's address data and emotion data, thereby reducing the user's stress and discomfort.

[2160] Definitions of important words

[2161] "Address data" is data that indicates information about the place where the user resides.

[2162] "Emotion data" is data that represents the user's current emotional state, and is obtained from voice input, facial expression recognition, or the like.

[2163] "Price information on the Internet" is information about product prices that can be collected from the Internet.

[2164] The "cheapest menu" is the most cost-effective menu plan calculated based on price information collected from multiple stores and restaurants.

[2165] The "means for adjusting the cheapest menu" is a means for changing the content of the cheapest menu based on the user's emotional data and making suggestions that match the user's emotional state.

[2166] The "means for displaying proposed data to the user" refers to a means for visually or audibly presenting the cheapest menu calculated by the server and its adjustment details to the user.

[2167] MODE FOR CARRYING OUT THE INVENTION

[2168] To implement this invention, a system is required that links and operates a server, user terminal, and emotion engine. This system provides the most appropriate, lowest-priced menu based on the user's address data and emotion data. Below, we will explain in detail each component of this system and its processing.

[2169] Server-side processing

[2170] The server performs several functions. First, it receives and analyzes the user's address data from the user's device. Second, it collects price information from stores and restaurants near the user's address via the Internet. This information is collected using web crawling.

[2171] The server integrates the collected price data and calculates the cheapest menu, taking into account each store's inventory status and special sales information. It also receives and analyzes the user's emotional data through an emotion engine. Emotional data is collected based on voice input and facial expression recognition.

[2172] Finally, the server adjusts the cheapest menu based on the emotion data, taking into account specific ingredients and recipes to reduce the user's stress. Based on the results, it generates the cheapest menu suggestion data and sends it to the user's device.

[2173] Terminal side processing

[2174] The user terminal displays an address input screen to the user and then provides an interface for inputting emotion data. After the user inputs the address and emotion data, the terminal transmits the data to the server.

[2175] The recommendation data sent from the server is received by the user's device and displayed to the user. This display includes not only specific purchase locations and prices, but also emotion-based adjustment menus.

[2176] User operation

[2177] The user enters their home address and emotional data into the app. They then check the cheapest menu items, purchasing locations, and emotion-adjusting menu items suggested by the server and decide whether to purchase them. By purchasing ingredients based on the cheapest menu items suggested by the server, the user can efficiently save on food costs while also receiving emotional support.

[2178] Hardware and software used

[2179] The hardware required is a smartphone and a server, while the software required is a program implemented using Python, web crawling technology, and a sentiment analysis engine.

[2180] Specific examples

[2181] For example, suppose a user lives in Shibuya Ward, Tokyo, and is currently feeling stressed. The user opens the app and enters their address and current emotional state. The server collects price information from supermarkets and restaurants around Shibuya Ward and consolidates the most cost-effective curry ingredient list. Additionally, the server considers specific foods (e.g., chamomile tea) that can help reduce the user's stress, and generates a tailored menu, where, for example, potatoes are 100 yen at one supermarket and carrots are 50 yen at another. This menu is then sent to the user's device, and the user can purchase ingredients based on this information, efficiently saving on food costs while also receiving emotional support.

[2182] Example prompts to input to the generative AI model

[2183] The user is stressed and lives in Shibuya, Tokyo. Design a food delivery app that suggests the cheapest stress-reducing menu. The menu should include ingredients with calming effects. Also, provide information on where to purchase each ingredient and their price.

[2184] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2185] Processing Steps

[2186] Step 1:

[2187] Enter and submit user address and emotion data

[2188] Operation:

[2189] The user inputs address data and emotion data using a smartphone terminal.

[2190] Emotional data is collected through voice input or facial expression recognition.

[2191] input:

[2192] Address data and emotion data entered by the user.

[2193] Data processing / calculation:

[2194] Formats the input data and prepares it for sending to the server.

[2195] output:

[2196] The formatted address data and emotion data are sent to a server.

[2197] Step 2:

[2198] Receiving and parsing address data

[2199] Operation:

[2200] The server receives the address data sent from the user terminal.

[2201] The received address data is analyzed to extract specific geographic information.

[2202] input:

[2203] Address data sent from the device.

[2204] Data processing / calculation:

[2205] Format analysis of address data and extraction of geographic information.

[2206] output:

[2207] The extracted geographic information.

[2208] Step 3:

[2209] Collecting price information from the internet

[2210] Operation:

[2211] Based on the extracted geographical information, the server collects price information from nearby stores and restaurants from the Internet.

[2212] The latest price information is obtained using web crawling technology.

[2213] input:

[2214] Geographic information.

[2215] Data processing / calculation:

[2216] Price information gathering using web crawling.

[2217] output:

[2218] Price information for nearby stores and restaurants.

[2219] Step 4:

[2220] Price data integration and lowest price menu calculation

[2221] Operation:

[2222] The server consolidates the collected pricing data and generates the most cost-effective menu plan.

[2223] It also takes into account inventory information and special sales information from each store.

[2224] input:

[2225] Price information for nearby stores and restaurants.

[2226] Data processing / calculation:

[2227] Integrates price data and calculates the cheapest menu.

[2228] output:

[2229] Data on the cheapest menu.

[2230] Step 5:

[2231] Emotional data analysis and menu adjustment

[2232] Operation:

[2233] The server analyzes the received emotion data through an emotion engine.

[2234] The cheapest menu is adjusted according to the user's emotional state.

[2235] For example, for a user who is feeling stressed, foods with a calming effect can be added to the menu.

[2236] input:

[2237] User sentiment data and cheapest menu data.

[2238] Data processing / calculation:

[2239] Analyzing sentiment data and adjusting the cheapest menu.

[2240] output:

[2241] Adjusted data for cheapest menu.

[2242] Step 6:

[2243] Generate and send proposal data for the cheapest menu

[2244] Operation:

[2245] The server generates adjusted lowest price menu suggestion data.

[2246] The optimized menu plan is transmitted to the user terminal.

[2247] input:

[2248] Adjusted data for cheapest menu.

[2249] Data processing / calculation:

[2250] Proposal data generation.

[2251] output:

[2252] The cheapest menu suggestion data is sent to the user's device.

[2253] Step 7:

[2254] Receiving and displaying suggestion menus

[2255] Operation:

[2256] The user terminal receives the proposal data sent from the server and displays it to the user.

[2257] It also displays specific purchase locations, prices, and emotional adjustment menus.

[2258] input:

[2259] The cheapest menu suggestion data sent from the server.

[2260] Data processing / calculation:

[2261] Prepare to display proposed data.

[2262] output:

[2263] The suggestion menu that is displayed to the user.

[2264] Step 8:

[2265] The user checks the suggested menu and makes a purchase

[2266] Operation:

[2267] The user checks the suggested lowest price menu, purchasing information, and emotion adjustment menu.

[2268] Purchase your materials in-store or online based on the suggested information.

[2269] input:

[2270] Suggestion menu data.

[2271] Data processing / calculation:

[2272] User verification and decision-making process.

[2273] output:

[2274] Purchase of materials.

[2275] 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.

[2276] 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.

[2277] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2278] 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.

[2279] 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.

[2280] 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.

[2281] 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).

[2282] 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.

[2283] 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."

[2284] 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.

[2285] 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).

[2286] 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.

[2287] 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.

[2288] 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.

[2289] 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.

[2290] 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.

[2291] 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.

[2292] 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.

[2293] 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.

[2294] 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.

[2295] 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.

[2296] The following is further disclosed regarding the above embodiment.

[2297] (Claim 1)

[2298] means for receiving user address data;

[2299] a means for collecting price information on the Internet;

[2300] A means of integrating the collected price data to calculate the cheapest menu,

[2301] A means for suggesting and displaying the cheapest menu to the user;

[2302] A system including:

[2303] (Claim 2)

[2304] The system of claim 1, wherein price information is collected from surrounding stores and restaurants based on the address data.

[2305] (Claim 3)

[2306] 10. The system of claim 1, further comprising means for negotiating on behalf of the user at their request to further reduce food costs.

[2307] "Example 1"

[2308] (Claim 1)

[2309] means for receiving and analyzing user address data;

[2310] A means for collecting price information of nearby stores on the Internet based on the address data;

[2311] A means to integrate collected price data and calculate the most cost-effective menu;

[2312] a means for suggesting and displaying the calculated cheapest menu and purchasing information to the user;

[2313] A system including:

[2314] (Claim 2)

[2315] The system of claim 1, further comprising: collecting price information from nearby retail stores based on the address data.

[2316] (Claim 3)

[2317] 10. The system of claim 1, further comprising means for negotiating on behalf of the user at their request to further reduce food costs.

[2318] "Application Example 1"

[2319] (Claim 1)

[2320] means for receiving user address data;

[2321] a means for collecting price information on the Internet;

[2322] A means of integrating the collected price data to calculate the cheapest menu,

[2323] A means for suggesting and displaying the cheapest menu to the user;

[2324] means for collecting price information for delivery services based on the user's address;

[2325] A means to provide the option to place a delivery order;

[2326] A system including:

[2327] (Claim 2)

[2328] The system of claim 1, wherein price information is collected from surrounding stores and restaurants based on the address data.

[2329] (Claim 3)

[2330] 10. The system of claim 1, further comprising means for negotiating on behalf of the user at their request to further reduce food costs.

[2331] "Example 2: Combining Emotion Engines"

[2332] (Claim 1)

[2333] means for receiving and analyzing user address data;

[2334] a means for collecting price information on the Internet and storing it in a database;

[2335] A means of integrating the collected price data and using an algorithm to calculate the cheapest menu;

[2336] A means for acquiring and analyzing user emotion data;

[2337] A method to adjust the cheapest menu with specific ingredients and recipes based on the acquired emotional data,

[2338] A means for suggesting and displaying a cheapest menu and an adjustment menu based on emotions to a user;

[2339] A system including:

[2340] (Claim 2)

[2341] The system of claim 1, wherein price information is collected from surrounding stores and restaurants based on the address data.

[2342] (Claim 3)

[2343] 10. The system of claim 1, further comprising means for negotiating on behalf of the user at their request to further reduce food costs.

[2344] "Application example 2 when combining emotion engines"

[2345] (Claim 1)

[2346] means for receiving user address data;

[2347] means for receiving and analyzing user emotion data;

[2348] a means for collecting price information on the Internet;

[2349] A means of integrating the collected price data to calculate the cheapest menu,

[2350] A means for adjusting the cheapest menu based on the user's emotional data;

[2351] A means for suggesting and displaying the cheapest menu to the user;

[2352] A system including:

[2353] (Claim 2)

[2354] The system of claim 1 collects price information from surrounding stores and restaurants based on address data and makes adjustments based on emotion data.

[2355] (Claim 3)

[2356] 2. The system according to claim 1, further comprising means for negotiating on behalf of a user in accordance with the user's wishes and for saving on food expenses adjusted based on emotion data. [Explanation of symbols]

[2357] 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. means for receiving user address data; a means for collecting price information on the Internet; A means of integrating the collected price data to calculate the cheapest menu, A means for suggesting and displaying the cheapest menu to the user; A system including:

2. The system according to claim 1, wherein price information is collected from surrounding stores and restaurants based on the address data.

3. 2. The system of claim 1, further comprising means for negotiating on behalf of the user at the user's request to further reduce food costs.

Images