system

Abstract

Provide a system. [Solution] A means for collecting payment information in conjunction with the payment method; A means for automatically registering collected payment information in a household account book; an artificial intelligence means for analyzing the registered household accounting data and learning the user's hobbies and preferences; means for generating saving advice based on the analysis results; A means for acquiring user location information; A means of providing special offers from nearby stores and facilities based on acquired location information A system including:

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] Traditional household management methods require users to manually enter spending data, which takes time and effort and makes accurate data management difficult. There is also a lack of systems that automatically analyze users' spending patterns and provide effective savings advice. Furthermore, there is no established method for collecting real-time information on deals at nearby stores and facilities and notifying users. This makes it difficult for users to optimize their spending and save money. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for collecting payment information in conjunction with a payment method and a means for automatically registering the collected payment information in a household account book. It also includes an artificial intelligence means for analyzing the registered household account book data to learn the user's hobbies and preferences, and a means for generating money-saving advice based on the analysis results. Furthermore, the system includes a means for acquiring the user's location information and a means for providing information on special offers at nearby stores and facilities based on the acquired location information, thereby streamlining the user's spending management and enabling effective savings.

[0006] "Payment Instrument" means a system or device for electronically processing payments for goods and services.

[0007] "Payment information" refers to information related to a transaction, including the purchase details, amount, date and time, store name, etc.

[0008] A "household account book" is a ledger or electronic recording system used to record and manage the income and expenses of an individual or household.

[0009] "Artificial intelligence tools" are algorithms or systems that analyze and learn from data, and are used to recognize specific patterns and user behavior and generate recommendations.

[0010] "Location information" is geographical information that indicates the user's current location and movement history.

[0011] "Nearby stores and facilities" refers to commercial facilities and service providers located around the user's current location.

[0012] "Special Offers" are limited-time offers on specific products or services at lower prices than usual.

[0013] "Savings advice" refers to specific suggestions or guidelines for reducing a user's spending. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] As an embodiment of the present invention, a system configured as follows is provided.

[0036] System Configuration

[0037] The system includes functions for collecting payment information linked to payment methods, registering household accounts, analyzing data using artificial intelligence, generating money-saving advice, acquiring location information, and providing information on special offers at nearby stores and facilities.

[0038] 1. Collection of payment information

[0039] Terminal

[0040] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[0041] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[0042] The acquired payment information is temporarily stored in a database within the terminal.

[0043] 2. Data household ledger registration

[0044] Terminal

[0045] The payment information stored in the terminal is sent to the server.

[0046] server

[0047] The server analyzes the received payment information and converts it into household accounting data format.

[0048] The analyzed information is registered in the household accounting app's database.

[0049] 3. AI-based analysis

[0050] server

[0051] The server inputs the household accounting data into an artificial intelligence (AI) engine.

[0052] The AI ​​engine analyzes patterns such as a user's purchase history, spending frequency, and time of day, and learns about the user's hobbies and preferences.

[0053] 4. Generating Savings Advice

[0054] server

[0055] The server further analyzes the user's spending patterns based on the analysis results of the AI ​​engine.

[0056] The AI ​​generates specific advice for reducing expenses, such as "Since your monthly convenience store spending is high, we suggest you buy in bulk."

[0057] The generated advice is sent to the user's terminal.

[0058] 5. Utilizing location information

[0059] Terminal

[0060] The terminal periodically acquires the user's location information.

[0061] Send location information to the server.

[0062] server

[0063] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[0064] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[0065] The filtered special offers are sent to the user's device via push notification.

[0066] Specific examples

[0067] Execution scenario

[0068] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[0069] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[0070] 3. The terminal sends this payment information to the server.

[0071] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[0072] 5. The server registers the analyzed household accounting data in the household accounting app database.

[0073] 6. The server's AI engine processes the new household accounting data and updates the user's spending patterns. For example, data such as "visiting convenience stores 15 times a month" is obtained.

[0074] 7. Based on this spending pattern, the server generates money-saving advice such as, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk."

[0075] 8. The server sends this advice to the user's device.

[0076] 9. The device periodically obtains the user's location information and sends it to the server.

[0077] 10. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[0078] This system allows users to efficiently manage their spending and receive specific advice on how to save money. Furthermore, location information is used to provide information on special offers at nearby stores, allowing for even more effective savings.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[0082] Step 2:

[0083] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[0084] Step 3:

[0085] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[0086] Step 4:

[0087] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[0088] Step 5:

[0089] The server inputs household accounting data into an AI engine, which processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[0090] Step 6:

[0091] The server retrieves the AI ​​engine's learning results and further analyzes the user's spending patterns. Based on the analysis results, it generates specific advice for saving money. For example, it might suggest "Since your monthly convenience store spending is high, we suggest buying in bulk."

[0092] Step 7:

[0093] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[0094] Step 8:

[0095] The device periodically acquires the user's location information and sends it to the server.

[0096] Step 9:

[0097] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[0098] Step 10:

[0099] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[0100] In this way, the entire system works together to provide users with efficient household management and savings support.

[0101] Example 1

[0102] 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."

[0103] In modern society, users are seeking ways to efficiently manage their spending and receive specific advice on how to save money. However, existing household accounting apps and expense management systems lack the functionality to accurately analyze users' hobbies, preferences, and spending patterns and provide appropriate saving advice. Furthermore, there are also limited systems that utilize location information to provide information on special offers at nearby stores. This makes spending management cumbersome for users, making it difficult to save effectively.

[0104] 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.

[0105] In this invention, the server includes a means for converting the transmitted payment information into a household accounting data format and registering it in a household accounting database, a means for inputting the registered household accounting data into an AI engine and analyzing the user's hobbies, preferences, and spending patterns, and a means for generating and transmitting saving advice based on the analysis results to the user's terminal. This allows the user to efficiently manage their own spending and receive specific saving advice based on the AI ​​analysis results. Furthermore, by notifying the user of special offers based on location information, even more effective savings can be achieved.

[0106] "Payment Instrument" means an electronic or physical means used by a User to pay for goods or services.

[0107] "Payment information" is detailed information about the user's payment, such as the purchase details, amount, date and time, and store name.

[0108] "Server" is a central system for storing, analyzing, and processing collected data and coordinating with other components.

[0109] A "terminal" is a device that is directly operated by a user and that receives, transmits, saves, and notifies payment information.

[0110] The "household account book data format" is a data format converted into a specific format in order to centrally manage the user's income and expenditure information.

[0111] A "household account book database" is a database for storing data converted into a household account book data format.

[0112] The "AI engine" is an artificial intelligence system that analyzes users' hobbies, preferences, and spending patterns to generate specific advice.

[0113] "Savings advice" is a suggestion generated based on the analysis results, aimed at reducing the user's expenses.

[0114] "Location information" is data indicating the user's current location and movement history.

[0115] "Special offer information" is information about discounts and campaigns offered at nearby stores and facilities.

[0116] "Notification means" refers to a communication and display mechanism for providing information to the user.

[0117] The present invention provides a system that allows users to efficiently manage their spending and provides specific advice for saving money. The system has the following main functions:

[0118] 1. Collection of payment information

[0119] When a user purchases an item at a convenience store or other location, they pay using an electronic payment app on their smartphone. For example, when a user purchases a 500 yen item, they use a common electronic payment method. Once the payment is complete, the payment information (purchase details, amount, date and time, store name, etc.) is notified to the terminal.

[0120] 2. Data household ledger registration

[0121] The device temporarily stores this payment information in a database (e.g., SQLite) within the device. The device then sends the payment information to the server using an HTTPS request. The server receives the sent information, analyzes it, and converts it into a household accounting data format. The server then registers this information in the household accounting app's database (e.g., MySQL (registered trademark) or PostgreSQL).

[0122] 3. AI-based analysis

[0123] The server inputs the household accounting data into an artificial intelligence (AI) engine. This AI engine analyzes patterns such as the user's purchase history, spending frequency, and time of day based on the household accounting data, and learns the user's hobbies and preferences. The AI ​​algorithms used include random forest and K-means clustering.

[0124] 4. Generating Savings Advice

[0125] The server further analyzes the user's spending patterns based on the AI ​​engine's analysis results. For example, for a user who frequently visits convenience stores, it generates money-saving advice such as "Since monthly convenience store spending is high, we suggest bulk purchases." This advice is then sent to the device again via an HTTPS request.

[0126] 5. Utilizing location information

[0127] The device periodically obtains the user's location information and sends it to the server using an HTTPS request. The server uses the received location information to check against a geographic database and search for special offers at nearby stores and facilities. It then filters this information and pushes special offers based on the user's purchasing habits to the device. Push notifications are sent using services such as Firebase Cloud Messaging.

[0128] Specific examples

[0129] 1. Payment Scenario

[0130] When a user purchases a 500 yen item at a convenience store, the terminal receives the payment information and stores it in an internal database. This information is then sent to the server, which converts it into household accounting data format and registers it in the database.

[0131] 2. AI analysis and advice generation

[0132] The server's AI engine uses this new data to update the user's spending patterns and detects a pattern of "visiting convenience stores 15 times a month." The server then generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest bulk purchases," and sends it to the user's device.

[0133] 3. Use of location information

[0134] The device periodically acquires the user's location information and sends it to the server. The server receives this location information, searches for special offers at nearby stores, and sends push notifications to the user's device, such as "Rice is on sale today."

[0135] Examples of prompt statements

[0136] An example of a prompt for this system is shown below:

[0137] "After purchasing a 500 yen item using a common electronic payment method, please explain the entire process that takes place using a smartphone app, from collecting payment information, registering it in a household account book, analyzing spending patterns using AI, generating money-saving advice, and providing special offers based on location information."

[0138] This allows users to efficiently manage their spending and receive specific money-saving advice based on AI analysis results. Furthermore, by utilizing location information, users can easily obtain information on special offers at nearby stores, enabling further savings.

[0139] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0140] Step 1:

[0141] A user purchases a 500 yen item at a convenience store using a common electronic payment method (such as PayPay or LINE Pay). When the user presses the payment button, the payment app processes the payment and generates a payment completion notification, which is sent to the user's device. (Input: User payment operation, Output: Payment completion notification)

[0142] Step 2:

[0143] The device receives a payment completion notification. Specifically, the device's notification system receives the notification from the payment app, extracts data including payment information (purchase details, amount, date and time, store name), and temporarily stores it in internal storage. (Input: payment completion notification, Output: temporarily stored payment information)

[0144] Step 3:

[0145] The terminal sends the temporarily saved payment information to the server using a secure communication method (HTTPS). When sending, the payment information is serialized in JSON format and sent to the server as a POST request. (Input: temporarily saved payment information, Output: sent to server)

[0146] Step 4:

[0147] The server deserializes and interprets the received payment information and converts it into a household accounting data format. This process involves data mapping and cleansing. Specifically, the received JSON data is parsed, mapped to the appropriate fields, and converted into SQL format. (Input: Submitted payment information, Output: Household accounting data format)

[0148] Step 5:

[0149] The server registers the converted household accounting data in the household accounting app's database. This is where database operations (e.g., executing an INSERT SQL statement) are performed. (Input: household accounting data format, Output: database registration completed)

[0150] Step 6:

[0151] The server inputs the registered household accounting data into an AI engine for analysis. The AI ​​engine analyzes the user's purchase history, spending frequency, time period, etc. During this process, it uses machine learning algorithms (e.g., random forest and K-means clustering) to perform pattern recognition and data clustering. (Input: household accounting data, output: analysis results)

[0152] Step 7:

[0153] Based on the AI ​​engine's analysis results, the server further analyzes the user's spending patterns and performs specific operations to generate money-saving advice. For example, if the analysis results show that the user "visits convenience stores 15 times a month," the server generates advice such as "since monthly convenience store spending is high, we suggest bulk purchases." (Input: AI engine analysis results, output: money-saving advice)

[0154] Step 8:

[0155] The server sends the generated money saving advice to the user's device. This also uses HTTPS, a secure communication method, and the advice content is serialized in JSON format and sent. (Input: Money saving advice, Output: Transmission to user device completed)

[0156] Step 9:

[0157] The device periodically obtains the user's location information. It uses a location service (e.g., Google (registered trademark) Location Services) to collect GPS data and stores it in internal storage. (Input: Use of location service, Output: Obtained location information)

[0158] Step 10:

[0159] The location information acquired by the device is sent to the server. HTTPS is used for transmission, and the location information is serialized in JSON format and sent to the server as a POST request. (Input: acquired location information, Output: sent to server)

[0160] Step 11:

[0161] The server searches a database of nearby stores and facilities based on the location information received. It uses a geographic information system (GIS) to extract special offers around the user's current location and uses a personalized filtering algorithm to select the information that is most useful to the user. (Input: location information, output: filtered special offers)

[0162] Step 12:

[0163] The server sends the filtered special offer information to the user's device as a push notification. A service such as Firebase Cloud Messaging (FCM) is used for the push notification. (Input: filtered special offer information, Output: push notification to the user's device)

[0164] This allows users to efficiently manage their spending and receive specific advice on how to save money, as well as use their location to find out about special offers at nearby stores.

[0165] (Application example 1)

[0166] 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."

[0167] The purpose of this invention is to provide a system that, when a user uses an electronic payment method, collects expenditure information, automatically registers it in a household account book, analyzes expenditure patterns using AI and generates savings advice, and provides and notifies special offer information based on location information.Current systems have issues such as the time and effort required to manually input expenditure information, inappropriate savings advice, and missed special offer information, so these need to be resolved.

[0168] 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.

[0169] In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and learning the user's preferences, means for generating money-saving advice based on the analysis results, means for acquiring the user's location information, means for providing special offer information for nearby stores and facilities based on the acquired location information, and means for sending push notifications of the special offer information to the user, thereby enabling management of the user's spending, provision of money-saving advice, and notification of special offer information in real time.

[0170] A "payment instrument" is a method or device for making payments electronically for goods or services.

[0171] "Payment information" refers to transaction data such as the payment amount, store name, date and time when a user purchases a product or service.

[0172] A "household account book" is a record book for recording a user's daily income and expenditures and managing the financial situation of a household.

[0173] "Artificial intelligence" is a technology that allows computer systems to analyze user data and learn their needs and patterns.

[0174] "Savings advice" is advice that provides specific suggestions for cost reduction based on the user's spending patterns.

[0175] "Hobbies and preferences" refers to the types of products and services that a user is interested in and their tendencies.

[0176] "Location information" is geographical data that indicates the user's current location.

[0177] "Nearby stores and facilities" refer to stores and service providing facilities located near the user's current location.

[0178] "Special Offer Information" is information about special prices and discounts offered at nearby stores and facilities.

[0179] "Push notification" is a mechanism by which the system sends information to the user's device in real time.

[0180] This system works in conjunction with payment methods to collect payment information, automatically registers the collected information in a household account book, and analyzes the data using artificial intelligence (AI). Furthermore, it generates money-saving advice for users based on the analysis results, acquires the user's location information, and provides special offers at nearby stores and facilities. This system also includes a function to send push notifications of special offers to users.

[0181] System Configuration

[0182] 1. How payment information is collected

[0183] When a user pays for a product using an electronic payment method, a payment completion notice is sent to the smartphone terminal. This notice contains payment information such as the payment amount, store name, date and time, and this information is temporarily stored in the terminal's internal database.

[0184] 2. How to register household accounts

[0185] The payment information stored in the device is sent to a server via the Internet. The server analyzes the received information, converts it into a household accounting format, and registers it in a household accounting database.

[0186] 3. Artificial Intelligence Analysis Methods

[0187] The household accounting data registered on the server is input into an AI engine, an artificial intelligence (AI) engine. The AI ​​engine analyzes the user's purchase history and spending frequency, and learns the user's preferences. This makes it possible to generate money-saving advice based on the user's spending patterns.

[0188] 4. Means of generating saving advice

[0189] Based on the results of the analysis, the AI ​​engine generates specific money-saving advice. For example, if monthly convenience store spending is high, advice suggesting bulk purchases will be generated. This advice is sent from the server to the user's device and displayed.

[0190] 5. Location information acquisition means

[0191] The device periodically obtains the user's current location using location information services and sends this information to the server, which then uses the location information to search for special offers at nearby stores and facilities.

[0192] 6. Special Offer Information and Push Notification Methods

[0193] The server filters the special offer information based on the acquired location information and purchasing trends and sends it to the user's device via push notification, allowing the user to receive real-time information on special offers from nearby stores and facilities.

[0194] Specific examples

[0195] 1. When a user makes a 500 yen payment at a convenience store, the payment information is sent to the smartphone.

[0196] 2. The smartphone sends the payment information to the server.

[0197] 3. The server analyzes the payment information and records it in the household account book.

[0198] 4. The AI ​​engine analyzes the user's spending patterns based on the new household accounting data.

[0199] 5. The system generates a saving advice such as "Since your monthly convenience store spending is high, we suggest you buy in bulk" and notifies the user.

[0200] 6. The smartphone periodically obtains location information and sends it to the server.

[0201] 7. The server filters special offers from nearby stores and sends push notifications to the user, such as "Rice is on sale today."

[0202] Prompt Sentence Examples

[0203] Parse the following payment information and generate savings advice:

[0204] Store name: Convenience store

[0205] Price: 500 yen

[0206] Date and Time: 2023-10-03T12:00:00

[0207] Analyze your spending patterns and get advice on how to save money.

[0208] Hardware and software used

[0209] Smartphone: Receiving payment information and acquiring location information

[0210] Server: Receives and analyzes data

[0211] Database: Payment information, household accounting data storage

[0212] AI engine: Data analysis, generating savings advice

[0213] Push notification system: Providing information to users

[0214] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0215] Step 1:

[0216] Collection of payment information

[0217] When a user makes a payment using an electronic payment method at a store such as a convenience store, a payment completion notification is sent to the terminal (smartphone).

[0218] Input: Payment completion notice (payment amount, store name, date and time, etc.)

[0219] Processing: The terminal receives this notification information.

[0220] Output: Payment information temporarily stored in the device's internal database

[0221] Step 2:

[0222] Household accounting registration method

[0223] The payment information stored in the terminal is transmitted to a server via the Internet.

[0224] Input: Payment information from the device's internal database

[0225] Process: Send payment information to the server as an HTTP request

[0226] Output: Payment information received by the server

[0227] Step 3:

[0228] Conversion to household accounting data

[0229] The server analyzes the received payment information, converts it into a household accounting format, and registers it in a household accounting database.

[0230] Input: Received payment information

[0231] Processing: Analyze the data and convert it into a household accounting format

[0232] Output: Household accounting data stored in the household accounting database

[0233] Step 4:

[0234] Artificial Intelligence Analysis Methods

[0235] Household accounting data is input into an artificial intelligence (AI) engine to analyze users' spending patterns and preferences.

[0236] Input: Data from the household accounting database

[0237] Processing: AI engine analyzes data and learns spending patterns and preferences

[0238] Output: Analysis results (user spending patterns, preferences, etc.)

[0239] Step 5:

[0240] Savings advice generation method

[0241] Based on the analysis results of the AI ​​engine, saving advice is generated and sent from the server to the user's device.

[0242] Input: AI analysis results

[0243] Processing: Generate specific savings advice based on the analysis results

[0244] Output: Saving advice sent to the user's device

[0245] Step 6:

[0246] Location information acquisition means

[0247] The device periodically acquires the user's location information and sends it to the server.

[0248] Input: Device location data

[0249] Processing: The device obtains the current location using location services.

[0250] Output: Location information sent to the server

[0251] Step 7:

[0252] Special offer information and push notification methods

[0253] The server searches for nearby special offers based on the acquired location information and purchasing trends and sends a push notification to the user's device.

[0254] Input: Location information, purchasing trend data

[0255] Process: Search the database and filter the deals

[0256] Output: A push notification of the special offer sent to the user's device

[0257] 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.

[0258] As an embodiment of the present invention, a system configured as follows is provided.

[0259] System Configuration

[0260] The system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function to provide information on special offers at nearby stores and facilities.

[0261] 1. Collection of payment information

[0262] Terminal

[0263] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[0264] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[0265] The acquired payment information is temporarily stored in a database within the terminal.

[0266] 2. Data household ledger registration

[0267] Terminal

[0268] The payment information stored in the terminal is sent to the server.

[0269] server

[0270] The server analyzes the received payment information and converts it into household accounting data format.

[0271] The analyzed information is registered in the household accounting app's database.

[0272] 3. Acquiring Emotion Data

[0273] Terminal

[0274] Activate the emotion engine to recognize the user's emotions.

[0275] The emotion engine uses sensors such as a camera and microphone to obtain emotional data from the user's facial expressions, tone of voice, gestures, etc.

[0276] The acquired emotion data is stored in a database within the device and sent to a server.

[0277] 4. Analysis by AI and emotion engine

[0278] server

[0279] The server inputs the received household accounting data and emotion data into the AI ​​engine.

[0280] The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[0281] The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[0282] 5. Generating Savings Advice

[0283] server

[0284] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine.

[0285] Based on the analysis results, the system generates specific advice for saving energy depending on the user's emotional state, such as suggestions to reduce stress when stress levels are high and strong suggestions when users are relaxed.

[0286] The generated advice is sent to the user's terminal.

[0287] 6. Utilizing location information

[0288] Terminal

[0289] The terminal periodically acquires the user's location information.

[0290] Send location information to the server.

[0291] 7. Offering special offers

[0292] server

[0293] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[0294] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[0295] The filtered special offers are sent to the user's device via push notification.

[0296] Specific examples

[0297] Execution scenario

[0298] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[0299] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[0300] 3. The terminal sends this payment information to the server.

[0301] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[0302] 5. The server registers the analyzed household accounting data in the household accounting app database.

[0303] 6. The device activates an emotion engine to recognize the user's emotions.

[0304] 7. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to obtain emotion data, such as "satisfied."

[0305] 8. The device sends the acquired emotion data to the server.

[0306] 9. The server's AI engine processes the household accounting data and emotional data to learn the user's spending patterns (e.g., "visiting convenience stores 15 times a month") and emotional tendencies.

[0307] 10. Based on this spending pattern, the server generates money-saving advice such as, "Since your monthly convenience store spending is high, we suggest bulk purchases." If the user is feeling stressed, the server adds relaxation suggestions such as, "Enjoy shopping within your budget."

[0308] 11. The server sends this advice to the user's device.

[0309] 12. The device periodically obtains the user's location information and sends it to the server.

[0310] 13. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[0311] The system allows users to efficiently manage their spending, receive emotionally-driven savings advice, and utilizes location and emotional data to make purchasing more comfortable and effective.

[0312] The processing flow will be explained below.

[0313] Step 1:

[0314] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[0315] Step 2:

[0316] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[0317] Step 3:

[0318] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[0319] Step 4:

[0320] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[0321] Step 5:

[0322] The device activates an emotion engine to recognize the user's emotions. The emotion engine uses sensors such as a camera and microphone to acquire emotion data from the user's facial expressions, tone of voice, gestures, etc.

[0323] Step 6:

[0324] The device temporarily stores the acquired emotional data and transmits it to the server. The emotional data includes emotional states such as "satisfaction" and "stress."

[0325] Step 7:

[0326] The server inputs household accounting data and emotional data into the AI ​​engine, which analyzes the user's purchase history, spending frequency, time of day, etc. to learn about the user's hobbies and preferences.

[0327] Step 8:

[0328] The server combines the data analysis results of the emotion engine with the learning results of the AI ​​engine to further analyze the user's spending patterns. For example, if the user is feeling stressed, it will emphasize relaxation suggestions.

[0329] Step 9:

[0330] The server generates specific advice for saving money based on the user's emotions and spending patterns. For example, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk," and the advice is adjusted according to the user's emotional state.

[0331] Step 10:

[0332] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[0333] Step 11:

[0334] The device periodically acquires the user's location information and sends it to the server.

[0335] Step 12:

[0336] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[0337] Step 13:

[0338] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[0339] Example 2

[0340] 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."

[0341] Conventional household management systems simply record spending, but lack the ability to consider users' emotional state and provide specific savings advice. This makes it difficult for users to understand their spending patterns and find rational ways to save money. Furthermore, systems that utilize users' location information to provide relevant special offers are also lacking.

[0342] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, means for recognizing a user's emotions, means for analyzing the recognized emotional data to evaluate the user's psychological state, artificial intelligence means for analyzing the household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and psychological evaluation, means for acquiring the user's location information, and means for providing special offer information for nearby stores and facilities based on the acquired location information. This enables the user to efficiently manage their spending and receive appropriate saving advice based on their emotional state. Furthermore, providing special offer information using location information can make the user's purchasing activities more comfortable and effective.

[0343] "Payment Instrument" means an electronic instrument used by a User to pay for goods and services.

[0344] "Payment information" is data related to payments made by users, and includes information such as the purchase details, amount, date and time, and store name.

[0345] A "household account book" refers to a system or application for recording and managing a user's income and expenses.

[0346] "Artificial intelligence means" refers to machine learning algorithms and models used to analyze data and learn user preferences.

[0347] An "emotion engine" refers to a program or system that uses sensors such as cameras and microphones to acquire and analyze a user's emotional data.

[0348] "Location information" is data indicating the user's current location, and is obtained using technology such as GPS.

[0349] "Special Offer Information" refers to information about discounts and special offers offered by stores and facilities.

[0350] "Savings Advice" refers to specific suggestions or advice for reducing a user's spending.

[0351] "Database" refers to a system for systematically storing information and making it quickly searchable and accessible.

[0352] "Notification" refers to messages or alerts that inform users of important information.

[0353] "Analysis" refers to the process of examining data in detail to find useful information and patterns in it.

[0354] "Purchasing trends" refers to a user's behavioral patterns and preferences when purchasing products or services.

[0355] "Push notification" refers to a means for sending information to users in real time.

[0356] As an embodiment of the present invention, we provide a system configured as follows: This system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[0357] Collection of payment information

[0358] Terminal

[0359] When a user pays for a product or service using a smartphone payment app, a payment completion notification is sent to the terminal. The terminal receives this notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the terminal's internal database. For example, if a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed," and this information is stored in the database.

[0360] Data household ledger registration

[0361] Terminal

[0362] The terminal transmits the payment information stored in the internal database to the server.

[0363] server

[0364] The server analyzes the received payment information and converts it into household accounting data format. The analysis results are then registered in the household accounting app's database. For example, data such as "500 yen spent at a convenience store" can be converted into a format such as "Expense: convenience store, Amount: 500 yen, Date / Time: today" and saved in the household accounting database.

[0365] Acquiring emotion data

[0366] Terminal

[0367] The device activates the emotion engine and uses sensors such as a camera and microphone to acquire the user's emotional data. The acquired emotional data is stored in an internal database and sent to a server. For example, the device's camera and microphone may analyze the user's facial expressions and tone of voice, acquiring data indicating that the user is satisfied and sending it to the server.

[0368] AI and emotion engine analysis

[0369] server

[0370] The server inputs the received household accounting data and emotional data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotional engine also analyzes the emotional data to evaluate the user's psychological state. For example, based on data such as "spent 500 yen at a convenience store" and "user is satisfied," the server learns the tendency that "users visit convenience stores 15 times a month and are satisfied after each visit."

[0371] Generating Savings Advice

[0372] server

[0373] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific saving advice according to the user's emotional state. It also sends this advice to the user's device. For example, advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" is generated and sent from the server to the device.

[0374] Utilizing location information

[0375] Terminal

[0376] The device periodically acquires the user's location information and sends it to the server. When the user goes out, the device's GPS function acquires the location information and periodically sends it to the server.

[0377] Providing special offers

[0378] server

[0379] The server processes the location information received from the user and searches a database of nearby stores and facilities. Special offer information is extracted from the search results and filtered based on the user's current location and purchasing habits. The filtered special offer information is sent to the user's device via push notification. For example, information such as "Rice is on sale today" is extracted, filtered based on the user's purchasing habits, and a push notification is sent to the device.

[0380] Examples of prompt statements

[0381] Here are some example prompts to input to a generative AI model:

[0382] "I completed a 500 yen payment using an electronic payment method. Create household accounting data based on this payment, obtain emotional data, and generate savings advice."

[0383] By inputting this prompt, the AI ​​model is expected to perform actions according to the above processing steps.

[0384] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0385] Step 1:

[0386] Input: The user makes a payment using an electronic payment method.

[0387] Processing: The terminal receives a payment completion notification from the payment app and extracts payment information (purchase details, amount, date and time, store name, etc.) from the notification.

[0388] Output: Payment information is temporarily saved in the terminal's internal database.

[0389] Specific operation: When a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed." The terminal receives this notification and saves the payment information ("500 yen spent at convenience store") in the database.

[0390] Step 2:

[0391] Input: Payment information stored in the device's internal database.

[0392] Processing: The terminal sends the saved payment information to the server.

[0393] Output: Payment information is sent to the server.

[0394] Specific operation: The device sends data such as "500 yen spent at a convenience store" to the server.

[0395] Step 3:

[0396] Input: Payment information received by the server.

[0397] Processing: The server analyzes the payment information and converts it into household accounting data format.

[0398] Output: The analyzed household accounting data is registered in the household accounting app database.

[0399] Specific operation: The server receives data such as "500 yen spent at a convenience store," converts it into a format such as "Expense: convenience store, amount: 500 yen, date and time: today," and saves it in the household accounting database.

[0400] Step 4:

[0401] Input: The user picks up the device.

[0402] Processing: The device launches the emotion engine and acquires the user's emotion data using sensors such as the camera and microphone.

[0403] Output: The acquired emotion data is stored in a database within the device and sent to the server.

[0404] Specific operation: The device's camera and microphone analyze the user's facial expressions and tone of voice, obtain data indicating that the user is satisfied, and send this data to the server.

[0405] Step 5:

[0406] Input: Household accounting data and emotion data received by the server.

[0407] Processing: The server inputs household accounting data and emotional data into the AI ​​engine, processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[0408] Output: The AI ​​engine generates the learning results.

[0409] Specific operation: Based on the data "500 yen spent at a convenience store" and "user satisfaction," the server learns the tendency that "users use convenience stores 15 times a month and are satisfied after using them."

[0410] Step 6:

[0411] Input: AI engine learning results and emotion engine evaluation results.

[0412] Processing: Based on the analysis results, the server generates specific saving advice according to the user's emotional state and sends it to the user's device.

[0413] Output: The generated advice is sent to the user's terminal.

[0414] Specific operation: The server generates advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" and sends it to the device.

[0415] Step 7:

[0416] Input: User goes out.

[0417] Processing: The device periodically acquires the user's location information and sends it to the server.

[0418] Output: The obtained location information is sent to the server.

[0419] Specific operation: The device's GPS function acquires location information and periodically sends it to the server.

[0420] Step 8:

[0421] Input: The location information received by the server.

[0422] Processing: Based on the location information, the server searches a database of nearby stores and facilities, extracting and filtering special offers.

[0423] Output: The filtered special offers are pushed to the user's device.

[0424] Specific operation: The server extracts information such as "Rice is on sale today," filters it according to the user's purchasing habits, and sends a push notification to the device.

[0425] (Application example 2)

[0426] 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."

[0427] The present invention aims to provide a system that allows users to effectively reduce their spending by linking their payment information and emotional data to manage spending and providing appropriate money-saving advice and information on special offers at nearby stores based on the user's purchasing behavior and emotional state. However, while current systems collect payment information, they are limited in providing advice that takes the user's emotional state into account and information on special offers that utilize location information. Therefore, a system is needed that takes the user's emotional state and location information into account and provides personalized advice on reducing spending and information on special offers based on purchasing behavior.

[0428] 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 collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and the user's emotional state, means for acquiring the user's location information, and means for providing information on special offers at nearby stores and facilities based on the acquired location information and purchasing habits. This allows the user to receive optimal saving advice tailored to their emotional state and current location, and information on special offers at nearby stores is also provided in real time, allowing them to effectively reduce their spending.

[0429] A "Payment Instrument" is an electronic payment method used by a User to purchase goods or services.

[0430] "Payment information" refers to information related to a user's purchasing activity, such as the purchased item, amount, store name, date and time, etc.

[0431] "Household account book data" is a collection of data that records a user's income and expenses.

[0432] "Artificial intelligence means" refers to a system that has the ability to analyze large amounts of data and learn about the user's hobbies and preferences.

[0433] "Emotion data" is information about the user's emotional state obtained from facial expressions, tone of voice, gestures, and the like.

[0434] "Savings advice" refers to specific proposals and suggestions for reducing a user's spending.

[0435] "Location information" is information indicating the user's current location, and is obtained using technology such as GPS.

[0436] "Special Offer Information" refers to information about discounts and sales offered at nearby stores and facilities.

[0437] "Push notification" refers to a technology that sends information from an application to a user's device in real time.

[0438] "Purchase trends" refers to trends derived based on a user's past purchase history and spending patterns.

[0439] System Configuration

[0440] A system for implementing this invention is configured as follows: The system includes a payment information collection function linked to a payment method, a household account book registration function, an artificial intelligence means and emotion engine function, a saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[0441] 1. Collection of payment information

[0442] Terminal

[0443] When a user completes payment for a product or service using a smartphone payment app, a payment completion notification is sent to the user's device. The device receives the notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the device's internal database.

[0444] 2. Data household ledger registration

[0445] Terminal

[0446] The payment information stored in the terminal is sent to the server.

[0447] server

[0448] The server analyzes the received payment information, converts it into household accounting data format, and registers the analyzed information in the household accounting app database.

[0449] 3. Acquiring Emotion Data

[0450] Terminal

[0451] The device's built-in emotion engine is activated, and emotion data is acquired from the user's facial expressions, tone of voice, gestures, etc. using sensors such as a camera and microphone. The acquired emotion data is stored in a database within the device and sent to a server.

[0452] 4. Analysis by AI and emotion engine

[0453] server

[0454] The server inputs the received household accounting data and emotion data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[0455] 5. Generating Savings Advice

[0456] server

[0457] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific advice for saving money according to the user's emotional state. The generated advice is then sent to the user's device.

[0458] 6. Utilizing location information

[0459] Terminal

[0460] The device periodically acquires the user's location information and sends it to the server.

[0461] 7. Offering special offers

[0462] server

[0463] The server processes the location information received from the user and searches a database of nearby stores and facilities. It extracts special offers from the search results and filters them based on the user's current location and purchasing habits. It then sends the filtered special offers to the user's device via push notification.

[0464] Hardware and Software

[0465] Hardware: Smartphone, camera, microphone, GPS module

[0466] Software: Payment app, household accounting app, artificial intelligence engine, emotion engine, location information acquisition module, special offer information module

[0467] Specific examples

[0468] Execution scenario

[0469] A user purchases a 500 yen item at a convenience store using a common electronic payment method. The device receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired. The device sends this payment information to the server. The server analyzes the received payment information and converts it into household accounting data format as "Expenses of 500 yen at convenience store." The server registers the analyzed household accounting data in the household accounting app's database. The device activates an emotion engine to recognize the user's emotions. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice and acquires emotional data. An example would be "satisfied." The device then sends the acquired emotional data to the server. The server's AI engine processes the household accounting data and emotional data and learns the user's spending patterns and emotional tendencies. Based on this spending pattern, the server generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest buying in bulk." If the user is feeling stressed, it adds relaxation suggestions such as "Enjoy shopping within your budget." The server then sends this advice to the user's device. The device periodically acquires the user's location information and sends it to the server. The server obtains location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[0470] Prompt Sentence Examples

[0471] "Please create a program that automatically collects payment information, such as the amount of money the user spends at a convenience store, the name of the store, and the date and time. Also, please give it the ability to analyze the user's emotional data using a camera and microphone and generate money-saving advice based on that. Finally, please use location information to provide the user with information about special offers at nearby stores."

[0472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0473] Step 1:

[0474] A user purchases a product or service using a smartphone payment app. The terminal receives a payment completion notification and acquires payment information such as the purchase details, amount, purchase date and time, and store name. The acquired payment information is then temporarily stored in the terminal's database. The input is the payment information, and the output is the payment information stored in the terminal's database.

[0475] Step 2:

[0476] The device sends the temporarily saved payment information to the server. The server analyzes the received payment information and converts it into household accounting data format. The converted household accounting data is then registered in the household accounting app's database. The input is the payment information sent to the server, and the output is the information registered in the household accounting database.

[0477] Step 3:

[0478] The device starts the emotion engine and uses the camera and microphone to capture the user's facial expressions, tone of voice, gestures, etc. to obtain emotional data. The obtained emotional data is temporarily stored in the device's database and sent to the server. The input is emotional data based on the user's facial expressions and tone of voice, and the output is the emotional data sent to the server.

[0479] Step 4:

[0480] The server receives household accounting data and emotion data and inputs it into the AI ​​engine. The AI ​​engine processes the received data and learns the user's hobbies and preferences from their purchasing history, spending frequency, time of day, etc. Meanwhile, the emotion engine analyzes the emotion data and evaluates the user's psychological state. The inputs are household accounting data and emotion data, and the output is the user's hobbies and preferences and the results of the psychological state evaluation.

[0481] Step 5:

[0482] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates saving advice according to the user's emotional state and sends that advice to the user's device. The input is the output of the AI ​​engine and emotion engine, and the output is the saving advice sent to the user's device.

[0483] Step 6:

[0484] The device periodically obtains the user's location information and sends it to the server. The server processes the received location information, searches a database of nearby stores and facilities, and extracts special offer information. The special offer information is filtered based on the user's current location and purchasing habits, and is then pushed to the user's device. The input is the location information sent from the device, and the output is the special offer information pushed to the user's device.

[0485] 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.

[0486] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0487] 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.

[0488] [Second embodiment]

[0489] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0490] 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.

[0491] 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).

[0492] 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.

[0493] 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.

[0494] 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).

[0495] 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.

[0496] 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.

[0497] 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.

[0498] 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.

[0499] 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.

[0500] 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."

[0501] As an embodiment of the present invention, a system configured as follows is provided.

[0502] System Configuration

[0503] The system includes functions for collecting payment information linked to payment methods, registering household accounts, analyzing data using artificial intelligence, generating money-saving advice, acquiring location information, and providing information on special offers at nearby stores and facilities.

[0504] 1. Collection of payment information

[0505] Terminal

[0506] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[0507] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[0508] The acquired payment information is temporarily stored in a database within the terminal.

[0509] 2. Data household ledger registration

[0510] Terminal

[0511] The payment information stored in the terminal is sent to the server.

[0512] server

[0513] The server analyzes the received payment information and converts it into household accounting data format.

[0514] The analyzed information is registered in the household accounting app's database.

[0515] 3. AI-based analysis

[0516] server

[0517] The server inputs the household accounting data into an artificial intelligence (AI) engine.

[0518] The AI ​​engine analyzes patterns such as a user's purchase history, spending frequency, and time of day, and learns about the user's hobbies and preferences.

[0519] 4. Generating Savings Advice

[0520] server

[0521] The server further analyzes the user's spending patterns based on the analysis results of the AI ​​engine.

[0522] The AI ​​generates specific advice for reducing expenses, such as "Since your monthly convenience store spending is high, we suggest you buy in bulk."

[0523] The generated advice is sent to the user's terminal.

[0524] 5. Utilizing location information

[0525] Terminal

[0526] The terminal periodically acquires the user's location information.

[0527] Send location information to the server.

[0528] server

[0529] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[0530] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[0531] The filtered special offers are sent to the user's device via push notification.

[0532] Specific examples

[0533] Execution scenario

[0534] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[0535] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[0536] 3. The terminal sends this payment information to the server.

[0537] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[0538] 5. The server registers the analyzed household accounting data in the household accounting app database.

[0539] 6. The server's AI engine processes the new household accounting data and updates the user's spending patterns. For example, data such as "visiting convenience stores 15 times a month" is obtained.

[0540] 7. Based on this spending pattern, the server generates money-saving advice such as, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk."

[0541] 8. The server sends this advice to the user's device.

[0542] 9. The device periodically obtains the user's location information and sends it to the server.

[0543] 10. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[0544] This system allows users to efficiently manage their spending and receive specific advice on how to save money. Furthermore, location information is used to provide information on special offers at nearby stores, allowing for even more effective savings.

[0545] The processing flow will be explained below.

[0546] Step 1:

[0547] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[0548] Step 2:

[0549] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[0550] Step 3:

[0551] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[0552] Step 4:

[0553] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[0554] Step 5:

[0555] The server inputs household accounting data into an AI engine, which processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[0556] Step 6:

[0557] The server retrieves the AI ​​engine's learning results and further analyzes the user's spending patterns. Based on the analysis results, it generates specific advice for saving money. For example, it might suggest "Since your monthly convenience store spending is high, we suggest buying in bulk."

[0558] Step 7:

[0559] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[0560] Step 8:

[0561] The device periodically acquires the user's location information and sends it to the server.

[0562] Step 9:

[0563] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[0564] Step 10:

[0565] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[0566] In this way, the entire system works together to provide users with efficient household management and savings support.

[0567] Example 1

[0568] 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."

[0569] In modern society, users are seeking ways to efficiently manage their spending and receive specific advice on how to save money. However, existing household accounting apps and expense management systems lack the functionality to accurately analyze users' hobbies, preferences, and spending patterns and provide appropriate saving advice. Furthermore, there are also limited systems that utilize location information to provide information on special offers at nearby stores. This makes spending management cumbersome for users, making it difficult to save effectively.

[0570] 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.

[0571] In this invention, the server includes a means for converting the transmitted payment information into a household accounting data format and registering it in a household accounting database, a means for inputting the registered household accounting data into an AI engine and analyzing the user's hobbies, preferences, and spending patterns, and a means for generating and transmitting saving advice based on the analysis results to the user's terminal. This allows the user to efficiently manage their own spending and receive specific saving advice based on the AI ​​analysis results. Furthermore, by notifying the user of special offers based on location information, even more effective savings can be achieved.

[0572] "Payment Instrument" means an electronic or physical means used by a User to pay for goods or services.

[0573] "Payment information" is detailed information about the user's payment, such as the purchase details, amount, date and time, and store name.

[0574] "Server" is a central system for storing, analyzing, and processing collected data and coordinating with other components.

[0575] A "terminal" is a device that is directly operated by a user and that receives, transmits, saves, and notifies payment information.

[0576] The "household account book data format" is a data format converted into a specific format in order to centrally manage the user's income and expenditure information.

[0577] A "household account book database" is a database for storing data converted into a household account book data format.

[0578] The "AI engine" is an artificial intelligence system that analyzes users' hobbies, preferences, and spending patterns to generate specific advice.

[0579] "Savings advice" is a suggestion generated based on the analysis results, aimed at reducing the user's expenses.

[0580] "Location information" is data indicating the user's current location and movement history.

[0581] "Special offer information" is information about discounts and campaigns offered at nearby stores and facilities.

[0582] "Notification means" refers to a communication and display mechanism for providing information to the user.

[0583] The present invention provides a system that allows users to efficiently manage their spending and provides specific advice for saving money. The system has the following main functions:

[0584] 1. Collection of payment information

[0585] When a user purchases an item at a convenience store or other location, they pay using an electronic payment app on their smartphone. For example, when a user purchases a 500 yen item, they use a common electronic payment method. Once the payment is complete, the payment information (purchase details, amount, date and time, store name, etc.) is notified to the terminal.

[0586] 2. Data household ledger registration

[0587] The device temporarily stores this payment information in a database (e.g., SQLite) within the device. The device then sends the payment information to the server using an HTTPS request. The server receives the sent information, analyzes it, and converts it into a household accounting data format. The server then registers this information in the household accounting app's database (e.g., MySQL or PostgreSQL).

[0588] 3. AI-based analysis

[0589] The server inputs the household accounting data into an artificial intelligence (AI) engine. This AI engine analyzes patterns such as the user's purchase history, spending frequency, and time of day based on the household accounting data, and learns the user's hobbies and preferences. The AI ​​algorithms used include random forest and K-means clustering.

[0590] 4. Generating Savings Advice

[0591] The server further analyzes the user's spending patterns based on the AI ​​engine's analysis results. For example, for a user who frequently visits convenience stores, it generates money-saving advice such as "Since monthly convenience store spending is high, we suggest bulk purchases." This advice is then sent to the device again via an HTTPS request.

[0592] 5. Utilizing location information

[0593] The device periodically obtains the user's location information and sends it to the server using an HTTPS request. The server uses the received location information to check against a geographic database and search for special offers at nearby stores and facilities. It then filters this information and pushes special offers based on the user's purchasing habits to the device. Push notifications are sent using services such as Firebase Cloud Messaging.

[0594] Specific examples

[0595] 1. Payment Scenario

[0596] When a user purchases a 500 yen item at a convenience store, the terminal receives the payment information and stores it in an internal database. This information is then sent to the server, which converts it into household accounting data format and registers it in the database.

[0597] 2. AI analysis and advice generation

[0598] The server's AI engine uses this new data to update the user's spending patterns and detects a pattern of "visiting convenience stores 15 times a month." The server then generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest bulk purchases," and sends it to the user's device.

[0599] 3. Use of location information

[0600] The device periodically acquires the user's location information and sends it to the server. The server receives this location information, searches for special offers at nearby stores, and sends push notifications to the user's device, such as "Rice is on sale today."

[0601] Examples of prompt statements

[0602] An example of a prompt for this system is shown below:

[0603] "After purchasing a 500 yen item using a common electronic payment method, please explain the entire process that takes place using a smartphone app, from collecting payment information, registering it in a household account book, analyzing spending patterns using AI, generating money-saving advice, and providing special offers based on location information."

[0604] This allows users to efficiently manage their spending and receive specific money-saving advice based on AI analysis results. Furthermore, by utilizing location information, users can easily obtain information on special offers at nearby stores, enabling further savings.

[0605] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0606] Step 1:

[0607] A user purchases a 500 yen item at a convenience store using a common electronic payment method (such as PayPay or LINE Pay). When the user presses the payment button, the payment app processes the payment and generates a payment completion notification, which is sent to the user's device. (Input: User payment operation, Output: Payment completion notification)

[0608] Step 2:

[0609] The device receives a payment completion notification. Specifically, the device's notification system receives the notification from the payment app, extracts data including payment information (purchase details, amount, date and time, store name), and temporarily stores it in internal storage. (Input: payment completion notification, Output: temporarily stored payment information)

[0610] Step 3:

[0611] The terminal sends the temporarily saved payment information to the server using a secure communication method (HTTPS). When sending, the payment information is serialized in JSON format and sent to the server as a POST request. (Input: temporarily saved payment information, Output: sent to server)

[0612] Step 4:

[0613] The server deserializes and interprets the received payment information and converts it into a household accounting data format. This process involves data mapping and cleansing. Specifically, the received JSON data is parsed, mapped to the appropriate fields, and converted into SQL format. (Input: Submitted payment information, Output: Household accounting data format)

[0614] Step 5:

[0615] The server registers the converted household accounting data in the household accounting app's database. This is where database operations (e.g., executing an INSERT SQL statement) are performed. (Input: household accounting data format, Output: database registration completed)

[0616] Step 6:

[0617] The server inputs the registered household accounting data into an AI engine for analysis. The AI ​​engine analyzes the user's purchase history, spending frequency, time period, etc. During this process, it uses machine learning algorithms (e.g., random forest and K-means clustering) to perform pattern recognition and data clustering. (Input: household accounting data, output: analysis results)

[0618] Step 7:

[0619] Based on the AI ​​engine's analysis results, the server further analyzes the user's spending patterns and performs specific operations to generate money-saving advice. For example, if the analysis results show that the user "visits convenience stores 15 times a month," the server generates advice such as "since monthly convenience store spending is high, we suggest bulk purchases." (Input: AI engine analysis results, output: money-saving advice)

[0620] Step 8:

[0621] The server sends the generated money saving advice to the user's device. This also uses HTTPS, a secure communication method, and the advice content is serialized in JSON format and sent. (Input: Money saving advice, Output: Transmission to user device completed)

[0622] Step 9:

[0623] The device periodically obtains the user's location information. It uses a location service (e.g., Google Location Services) to collect GPS data and stores it in internal storage. (Input: Use of location service, Output: Obtained location information)

[0624] Step 10:

[0625] The location information acquired by the device is sent to the server. HTTPS is used for transmission, and the location information is serialized in JSON format and sent to the server as a POST request. (Input: acquired location information, Output: sent to server)

[0626] Step 11:

[0627] The server searches a database of nearby stores and facilities based on the location information received. It uses a geographic information system (GIS) to extract special offers around the user's current location and uses a personalized filtering algorithm to select the information that is most useful to the user. (Input: location information, output: filtered special offers)

[0628] Step 12:

[0629] The server sends the filtered special offer information to the user's device as a push notification. A service such as Firebase Cloud Messaging (FCM) is used for the push notification. (Input: filtered special offer information, Output: push notification to the user's device)

[0630] This allows users to efficiently manage their spending and receive specific advice on how to save money, as well as use their location to find out about special offers at nearby stores.

[0631] (Application example 1)

[0632] 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."

[0633] The purpose of this invention is to provide a system that, when a user uses an electronic payment method, collects expenditure information, automatically registers it in a household account book, analyzes expenditure patterns using AI and generates savings advice, and provides and notifies special offer information based on location information.Current systems have issues such as the time and effort required to manually input expenditure information, inappropriate savings advice, and missed special offer information, so these need to be resolved.

[0634] 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.

[0635] In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and learning the user's preferences, means for generating money-saving advice based on the analysis results, means for acquiring the user's location information, means for providing special offer information for nearby stores and facilities based on the acquired location information, and means for sending push notifications of the special offer information to the user, thereby enabling management of the user's spending, provision of money-saving advice, and notification of special offer information in real time.

[0636] A "payment instrument" is a method or device for making payments electronically for goods or services.

[0637] "Payment information" refers to transaction data such as the payment amount, store name, date and time when a user purchases a product or service.

[0638] A "household account book" is a record book for recording a user's daily income and expenditures and managing the financial situation of a household.

[0639] "Artificial intelligence" is a technology that allows computer systems to analyze user data and learn their needs and patterns.

[0640] "Savings advice" is advice that provides specific suggestions for cost reduction based on the user's spending patterns.

[0641] "Hobbies and preferences" refers to the types of products and services that a user is interested in and their tendencies.

[0642] "Location information" is geographical data that indicates the user's current location.

[0643] "Nearby stores and facilities" refer to stores and service providing facilities located near the user's current location.

[0644] "Special Offer Information" is information about special prices and discounts offered at nearby stores and facilities.

[0645] "Push notification" is a mechanism by which the system sends information to the user's device in real time.

[0646] This system works in conjunction with payment methods to collect payment information, automatically registers the collected information in a household account book, and analyzes the data using artificial intelligence (AI). Furthermore, it generates money-saving advice for users based on the analysis results, acquires the user's location information, and provides special offers at nearby stores and facilities. This system also includes a function to send push notifications of special offers to users.

[0647] System Configuration

[0648] 1. How payment information is collected

[0649] When a user pays for a product using an electronic payment method, a payment completion notice is sent to the smartphone terminal. This notice contains payment information such as the payment amount, store name, date and time, and this information is temporarily stored in the terminal's internal database.

[0650] 2. How to register household accounts

[0651] The payment information stored in the device is sent to a server via the Internet. The server analyzes the received information, converts it into a household accounting format, and registers it in a household accounting database.

[0652] 3. Artificial Intelligence Analysis Methods

[0653] The household accounting data registered on the server is input into an AI engine, an artificial intelligence (AI) engine. The AI ​​engine analyzes the user's purchase history and spending frequency, and learns the user's preferences. This makes it possible to generate money-saving advice based on the user's spending patterns.

[0654] 4. Means of generating saving advice

[0655] Based on the results of the analysis, the AI ​​engine generates specific money-saving advice. For example, if monthly convenience store spending is high, advice suggesting bulk purchases will be generated. This advice is sent from the server to the user's device and displayed.

[0656] 5. Location information acquisition means

[0657] The device periodically obtains the user's current location using location information services and sends this information to the server, which then uses the location information to search for special offers at nearby stores and facilities.

[0658] 6. Special Offer Information and Push Notification Methods

[0659] The server filters the special offer information based on the acquired location information and purchasing trends and sends it to the user's device via push notification, allowing the user to receive real-time information on special offers from nearby stores and facilities.

[0660] Specific examples

[0661] 1. When a user makes a 500 yen payment at a convenience store, the payment information is sent to the smartphone.

[0662] 2. The smartphone sends the payment information to the server.

[0663] 3. The server analyzes the payment information and records it in the household account book.

[0664] 4. The AI ​​engine analyzes the user's spending patterns based on the new household accounting data.

[0665] 5. The system generates a saving advice such as "Since your monthly convenience store spending is high, we suggest you buy in bulk" and notifies the user.

[0666] 6. The smartphone periodically obtains location information and sends it to the server.

[0667] 7. The server filters special offers from nearby stores and sends push notifications to the user, such as "Rice is on sale today."

[0668] Prompt Sentence Examples

[0669] Parse the following payment information and generate savings advice:

[0670] Store name: Convenience store

[0671] Price: 500 yen

[0672] Date and Time: 2023-10-03T12:00:00

[0673] Analyze your spending patterns and get advice on how to save money.

[0674] Hardware and software used

[0675] Smartphone: Receiving payment information and acquiring location information

[0676] Server: Receives and analyzes data

[0677] Database: Payment information, household accounting data storage

[0678] AI engine: Data analysis, generating savings advice

[0679] Push notification system: Providing information to users

[0680] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0681] Step 1:

[0682] Collection of payment information

[0683] When a user makes a payment using an electronic payment method at a store such as a convenience store, a payment completion notification is sent to the terminal (smartphone).

[0684] Input: Payment completion notice (payment amount, store name, date and time, etc.)

[0685] Processing: The terminal receives this notification information.

[0686] Output: Payment information temporarily stored in the device's internal database

[0687] Step 2:

[0688] Household accounting registration method

[0689] The payment information stored in the terminal is transmitted to a server via the Internet.

[0690] Input: Payment information from the device's internal database

[0691] Process: Send payment information to the server as an HTTP request

[0692] Output: Payment information received by the server

[0693] Step 3:

[0694] Conversion to household accounting data

[0695] The server analyzes the received payment information, converts it into a household accounting format, and registers it in a household accounting database.

[0696] Input: Received payment information

[0697] Processing: Analyze the data and convert it into a household accounting format

[0698] Output: Household accounting data stored in the household accounting database

[0699] Step 4:

[0700] Artificial Intelligence Analysis Methods

[0701] Household accounting data is input into an artificial intelligence (AI) engine to analyze users' spending patterns and preferences.

[0702] Input: Data from the household accounting database

[0703] Processing: AI engine analyzes data and learns spending patterns and preferences

[0704] Output: Analysis results (user spending patterns, preferences, etc.)

[0705] Step 5:

[0706] Savings advice generation method

[0707] Based on the analysis results of the AI ​​engine, saving advice is generated and sent from the server to the user's device.

[0708] Input: AI analysis results

[0709] Processing: Generate specific savings advice based on the analysis results

[0710] Output: Saving advice sent to the user's device

[0711] Step 6:

[0712] Location information acquisition means

[0713] The device periodically acquires the user's location information and sends it to the server.

[0714] Input: Device location data

[0715] Processing: The device obtains the current location using location services.

[0716] Output: Location information sent to the server

[0717] Step 7:

[0718] Special offer information and push notification methods

[0719] The server searches for nearby special offers based on the acquired location information and purchasing trends and sends a push notification to the user's device.

[0720] Input: Location information, purchasing trend data

[0721] Process: Search the database and filter the deals

[0722] Output: A push notification of the special offer sent to the user's device

[0723] 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.

[0724] As an embodiment of the present invention, a system configured as follows is provided.

[0725] System Configuration

[0726] The system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function to provide information on special offers at nearby stores and facilities.

[0727] 1. Collection of payment information

[0728] Terminal

[0729] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[0730] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[0731] The acquired payment information is temporarily stored in a database within the terminal.

[0732] 2. Data household ledger registration

[0733] Terminal

[0734] The payment information stored in the terminal is sent to the server.

[0735] server

[0736] The server analyzes the received payment information and converts it into household accounting data format.

[0737] The analyzed information is registered in the household accounting app's database.

[0738] 3. Acquiring Emotion Data

[0739] Terminal

[0740] Activate the emotion engine to recognize the user's emotions.

[0741] The emotion engine uses sensors such as a camera and microphone to obtain emotional data from the user's facial expressions, tone of voice, gestures, etc.

[0742] The acquired emotion data is stored in a database within the device and sent to a server.

[0743] 4. Analysis by AI and emotion engine

[0744] server

[0745] The server inputs the received household accounting data and emotion data into the AI ​​engine.

[0746] The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[0747] The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[0748] 5. Generating Savings Advice

[0749] server

[0750] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine.

[0751] Based on the analysis results, the system generates specific advice for saving energy depending on the user's emotional state, such as suggestions to reduce stress when stress levels are high and strong suggestions when users are relaxed.

[0752] The generated advice is sent to the user's terminal.

[0753] 6. Utilizing location information

[0754] Terminal

[0755] The terminal periodically acquires the user's location information.

[0756] Send location information to the server.

[0757] 7. Offering special offers

[0758] server

[0759] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[0760] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[0761] The filtered special offers are sent to the user's device via push notification.

[0762] Specific examples

[0763] Execution scenario

[0764] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[0765] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[0766] 3. The terminal sends this payment information to the server.

[0767] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[0768] 5. The server registers the analyzed household accounting data in the household accounting app database.

[0769] 6. The device activates an emotion engine to recognize the user's emotions.

[0770] 7. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to obtain emotion data, such as "satisfied."

[0771] 8. The device sends the acquired emotion data to the server.

[0772] 9. The server's AI engine processes the household accounting data and emotional data to learn the user's spending patterns (e.g., "visiting convenience stores 15 times a month") and emotional tendencies.

[0773] 10. Based on this spending pattern, the server generates money-saving advice such as, "Since your monthly convenience store spending is high, we suggest bulk purchases." If the user is feeling stressed, the server adds relaxation suggestions such as, "Enjoy shopping within your budget."

[0774] 11. The server sends this advice to the user's device.

[0775] 12. The device periodically obtains the user's location information and sends it to the server.

[0776] 13. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[0777] The system allows users to efficiently manage their spending, receive emotionally-driven savings advice, and utilizes location and emotional data to make purchasing more comfortable and effective.

[0778] The processing flow will be explained below.

[0779] Step 1:

[0780] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[0781] Step 2:

[0782] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[0783] Step 3:

[0784] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[0785] Step 4:

[0786] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[0787] Step 5:

[0788] The device activates an emotion engine to recognize the user's emotions. The emotion engine uses sensors such as a camera and microphone to acquire emotion data from the user's facial expressions, tone of voice, gestures, etc.

[0789] Step 6:

[0790] The device temporarily stores the acquired emotional data and transmits it to the server. The emotional data includes emotional states such as "satisfaction" and "stress."

[0791] Step 7:

[0792] The server inputs household accounting data and emotional data into the AI ​​engine, which analyzes the user's purchase history, spending frequency, time of day, etc. to learn about the user's hobbies and preferences.

[0793] Step 8:

[0794] The server combines the data analysis results of the emotion engine with the learning results of the AI ​​engine to further analyze the user's spending patterns. For example, if the user is feeling stressed, it will emphasize relaxation suggestions.

[0795] Step 9:

[0796] The server generates specific advice for saving money based on the user's emotions and spending patterns. For example, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk," and the advice is adjusted according to the user's emotional state.

[0797] Step 10:

[0798] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[0799] Step 11:

[0800] The device periodically acquires the user's location information and sends it to the server.

[0801] Step 12:

[0802] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[0803] Step 13:

[0804] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[0805] Example 2

[0806] 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."

[0807] Conventional household management systems simply record spending, but lack the ability to consider users' emotional state and provide specific savings advice. This makes it difficult for users to understand their spending patterns and find rational ways to save money. Furthermore, systems that utilize users' location information to provide relevant special offers are also lacking.

[0808] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, means for recognizing a user's emotions, means for analyzing the recognized emotional data to evaluate the user's psychological state, artificial intelligence means for analyzing the household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and psychological evaluation, means for acquiring the user's location information, and means for providing special offer information for nearby stores and facilities based on the acquired location information. This enables the user to efficiently manage their spending and receive appropriate saving advice based on their emotional state. Furthermore, providing special offer information using location information can make the user's purchasing activities more comfortable and effective.

[0809] "Payment Instrument" means an electronic instrument used by a User to pay for goods and services.

[0810] "Payment information" is data related to payments made by users, and includes information such as the purchase details, amount, date and time, and store name.

[0811] A "household account book" refers to a system or application for recording and managing a user's income and expenses.

[0812] "Artificial intelligence means" refers to machine learning algorithms and models used to analyze data and learn user preferences.

[0813] An "emotion engine" refers to a program or system that uses sensors such as cameras and microphones to acquire and analyze a user's emotional data.

[0814] "Location information" is data indicating the user's current location, and is obtained using technology such as GPS.

[0815] "Special Offer Information" refers to information about discounts and special offers offered by stores and facilities.

[0816] "Savings Advice" refers to specific suggestions or advice for reducing a user's spending.

[0817] "Database" refers to a system for systematically storing information and making it quickly searchable and accessible.

[0818] "Notification" refers to messages or alerts that inform users of important information.

[0819] "Analysis" refers to the process of examining data in detail to find useful information and patterns in it.

[0820] "Purchasing trends" refers to a user's behavioral patterns and preferences when purchasing products or services.

[0821] "Push notification" refers to a means for sending information to users in real time.

[0822] As an embodiment of the present invention, we provide a system configured as follows: This system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[0823] Collection of payment information

[0824] Terminal

[0825] When a user pays for a product or service using a smartphone payment app, a payment completion notification is sent to the terminal. The terminal receives this notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the terminal's internal database. For example, if a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed," and this information is stored in the database.

[0826] Data household ledger registration

[0827] Terminal

[0828] The terminal transmits the payment information stored in the internal database to the server.

[0829] server

[0830] The server analyzes the received payment information and converts it into household accounting data format. The analysis results are then registered in the household accounting app's database. For example, data such as "500 yen spent at a convenience store" can be converted into a format such as "Expense: convenience store, Amount: 500 yen, Date / Time: today" and saved in the household accounting database.

[0831] Acquiring emotion data

[0832] Terminal

[0833] The device activates the emotion engine and uses sensors such as a camera and microphone to acquire the user's emotional data. The acquired emotional data is stored in an internal database and sent to a server. For example, the device's camera and microphone may analyze the user's facial expressions and tone of voice, acquiring data indicating that the user is satisfied and sending it to the server.

[0834] AI and emotion engine analysis

[0835] server

[0836] The server inputs the received household accounting data and emotional data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotional engine also analyzes the emotional data to evaluate the user's psychological state. For example, based on data such as "spent 500 yen at a convenience store" and "user is satisfied," the server learns the tendency that "users visit convenience stores 15 times a month and are satisfied after each visit."

[0837] Generating Savings Advice

[0838] server

[0839] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific saving advice according to the user's emotional state. It also sends this advice to the user's device. For example, advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" is generated and sent from the server to the device.

[0840] Utilizing location information

[0841] Terminal

[0842] The device periodically acquires the user's location information and sends it to the server. When the user goes out, the device's GPS function acquires the location information and periodically sends it to the server.

[0843] Providing special offers

[0844] server

[0845] The server processes the location information received from the user and searches a database of nearby stores and facilities. Special offer information is extracted from the search results and filtered based on the user's current location and purchasing habits. The filtered special offer information is sent to the user's device via push notification. For example, information such as "Rice is on sale today" is extracted, filtered based on the user's purchasing habits, and a push notification is sent to the device.

[0846] Examples of prompt statements

[0847] Here are some example prompts to input to a generative AI model:

[0848] "I completed a 500 yen payment using an electronic payment method. Create household accounting data based on this payment, obtain emotional data, and generate savings advice."

[0849] By inputting this prompt, the AI ​​model is expected to perform actions according to the above processing steps.

[0850] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0851] Step 1:

[0852] Input: The user makes a payment using an electronic payment method.

[0853] Processing: The terminal receives a payment completion notification from the payment app and extracts payment information (purchase details, amount, date and time, store name, etc.) from the notification.

[0854] Output: Payment information is temporarily saved in the terminal's internal database.

[0855] Specific operation: When a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed." The terminal receives this notification and saves the payment information ("500 yen spent at convenience store") in the database.

[0856] Step 2:

[0857] Input: Payment information stored in the device's internal database.

[0858] Processing: The terminal sends the saved payment information to the server.

[0859] Output: Payment information is sent to the server.

[0860] Specific operation: The device sends data such as "500 yen spent at a convenience store" to the server.

[0861] Step 3:

[0862] Input: Payment information received by the server.

[0863] Processing: The server analyzes the payment information and converts it into household accounting data format.

[0864] Output: The analyzed household accounting data is registered in the household accounting app database.

[0865] Specific operation: The server receives data such as "500 yen spent at a convenience store," converts it into a format such as "Expense: convenience store, amount: 500 yen, date and time: today," and saves it in the household accounting database.

[0866] Step 4:

[0867] Input: The user picks up the device.

[0868] Processing: The device launches the emotion engine and acquires the user's emotion data using sensors such as the camera and microphone.

[0869] Output: The acquired emotion data is stored in a database within the device and sent to the server.

[0870] Specific operation: The device's camera and microphone analyze the user's facial expressions and tone of voice, obtain data indicating that the user is satisfied, and send this data to the server.

[0871] Step 5:

[0872] Input: Household accounting data and emotion data received by the server.

[0873] Processing: The server inputs household accounting data and emotional data into the AI ​​engine, processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[0874] Output: The AI ​​engine generates the learning results.

[0875] Specific operation: Based on the data "500 yen spent at a convenience store" and "user satisfaction," the server learns the tendency that "users use convenience stores 15 times a month and are satisfied after using them."

[0876] Step 6:

[0877] Input: AI engine learning results and emotion engine evaluation results.

[0878] Processing: Based on the analysis results, the server generates specific saving advice according to the user's emotional state and sends it to the user's device.

[0879] Output: The generated advice is sent to the user's terminal.

[0880] Specific operation: The server generates advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" and sends it to the device.

[0881] Step 7:

[0882] Input: User goes out.

[0883] Processing: The device periodically acquires the user's location information and sends it to the server.

[0884] Output: The obtained location information is sent to the server.

[0885] Specific operation: The device's GPS function acquires location information and periodically sends it to the server.

[0886] Step 8:

[0887] Input: The location information received by the server.

[0888] Processing: Based on the location information, the server searches a database of nearby stores and facilities, extracting and filtering special offers.

[0889] Output: The filtered special offers are pushed to the user's device.

[0890] Specific operation: The server extracts information such as "Rice is on sale today," filters it according to the user's purchasing habits, and sends a push notification to the device.

[0891] (Application example 2)

[0892] 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."

[0893] The present invention aims to provide a system that allows users to effectively reduce their spending by linking their payment information and emotional data to manage spending and providing appropriate money-saving advice and information on special offers at nearby stores based on the user's purchasing behavior and emotional state. However, while current systems collect payment information, they are limited in providing advice that takes the user's emotional state into account and information on special offers that utilize location information. Therefore, a system is needed that takes the user's emotional state and location information into account and provides personalized advice on reducing spending and information on special offers based on purchasing behavior.

[0894] 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 collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and the user's emotional state, means for acquiring the user's location information, and means for providing information on special offers at nearby stores and facilities based on the acquired location information and purchasing habits. This allows the user to receive optimal saving advice tailored to their emotional state and current location, and information on special offers at nearby stores is also provided in real time, allowing them to effectively reduce their spending.

[0895] A "Payment Instrument" is an electronic payment method used by a User to purchase goods or services.

[0896] "Payment information" refers to information related to a user's purchasing activity, such as the purchased item, amount, store name, date and time, etc.

[0897] "Household account book data" is a collection of data that records a user's income and expenses.

[0898] "Artificial intelligence means" refers to a system that has the ability to analyze large amounts of data and learn about the user's hobbies and preferences.

[0899] "Emotion data" is information about the user's emotional state obtained from facial expressions, tone of voice, gestures, and the like.

[0900] "Savings advice" refers to specific proposals and suggestions for reducing a user's spending.

[0901] "Location information" is information indicating the user's current location, and is obtained using technology such as GPS.

[0902] "Special Offer Information" refers to information about discounts and sales offered at nearby stores and facilities.

[0903] "Push notification" refers to a technology that sends information from an application to a user's device in real time.

[0904] "Purchase trends" refers to trends derived based on a user's past purchase history and spending patterns.

[0905] System Configuration

[0906] A system for implementing this invention is configured as follows: The system includes a payment information collection function linked to a payment method, a household account book registration function, an artificial intelligence means and emotion engine function, a saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[0907] 1. Collection of payment information

[0908] Terminal

[0909] When a user completes payment for a product or service using a smartphone payment app, a payment completion notification is sent to the user's device. The device receives the notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the device's internal database.

[0910] 2. Data household ledger registration

[0911] Terminal

[0912] The payment information stored in the terminal is sent to the server.

[0913] server

[0914] The server analyzes the received payment information, converts it into household accounting data format, and registers the analyzed information in the household accounting app database.

[0915] 3. Acquiring Emotion Data

[0916] Terminal

[0917] The device's built-in emotion engine is activated, and emotion data is acquired from the user's facial expressions, tone of voice, gestures, etc. using sensors such as a camera and microphone. The acquired emotion data is stored in a database within the device and sent to a server.

[0918] 4. Analysis by AI and emotion engine

[0919] server

[0920] The server inputs the received household accounting data and emotion data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[0921] 5. Generating Savings Advice

[0922] server

[0923] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific advice for saving money according to the user's emotional state. The generated advice is then sent to the user's device.

[0924] 6. Utilizing location information

[0925] Terminal

[0926] The device periodically acquires the user's location information and sends it to the server.

[0927] 7. Offering special offers

[0928] server

[0929] The server processes the location information received from the user and searches a database of nearby stores and facilities. It extracts special offers from the search results and filters them based on the user's current location and purchasing habits. It then sends the filtered special offers to the user's device via push notification.

[0930] Hardware and Software

[0931] Hardware: Smartphone, camera, microphone, GPS module

[0932] Software: Payment app, household accounting app, artificial intelligence engine, emotion engine, location information acquisition module, special offer information module

[0933] Specific examples

[0934] Execution scenario

[0935] A user purchases a 500 yen item at a convenience store using a common electronic payment method. The device receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired. The device sends this payment information to the server. The server analyzes the received payment information and converts it into household accounting data format as "Expenses of 500 yen at convenience store." The server registers the analyzed household accounting data in the household accounting app's database. The device activates an emotion engine to recognize the user's emotions. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice and acquires emotional data. An example would be "satisfied." The device then sends the acquired emotional data to the server. The server's AI engine processes the household accounting data and emotional data and learns the user's spending patterns and emotional tendencies. Based on this spending pattern, the server generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest buying in bulk." If the user is feeling stressed, it adds relaxation suggestions such as "Enjoy shopping within your budget." The server then sends this advice to the user's device. The device periodically acquires the user's location information and sends it to the server. The server obtains location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[0936] Prompt Sentence Examples

[0937] "Please create a program that automatically collects payment information, such as the amount of money the user spends at a convenience store, the name of the store, and the date and time. Also, please give it the ability to analyze the user's emotional data using a camera and microphone and generate money-saving advice based on that. Finally, please use location information to provide the user with information about special offers at nearby stores."

[0938] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0939] Step 1:

[0940] A user purchases a product or service using a smartphone payment app. The terminal receives a payment completion notification and acquires payment information such as the purchase details, amount, purchase date and time, and store name. The acquired payment information is then temporarily stored in the terminal's database. The input is the payment information, and the output is the payment information stored in the terminal's database.

[0941] Step 2:

[0942] The device sends the temporarily saved payment information to the server. The server analyzes the received payment information and converts it into household accounting data format. The converted household accounting data is then registered in the household accounting app's database. The input is the payment information sent to the server, and the output is the information registered in the household accounting database.

[0943] Step 3:

[0944] The device starts the emotion engine and uses the camera and microphone to capture the user's facial expressions, tone of voice, gestures, etc. to obtain emotional data. The obtained emotional data is temporarily stored in the device's database and sent to the server. The input is emotional data based on the user's facial expressions and tone of voice, and the output is the emotional data sent to the server.

[0945] Step 4:

[0946] The server receives household accounting data and emotion data and inputs it into the AI ​​engine. The AI ​​engine processes the received data and learns the user's hobbies and preferences from their purchasing history, spending frequency, time of day, etc. Meanwhile, the emotion engine analyzes the emotion data and evaluates the user's psychological state. The inputs are household accounting data and emotion data, and the output is the user's hobbies and preferences and the results of the psychological state evaluation.

[0947] Step 5:

[0948] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates saving advice according to the user's emotional state and sends that advice to the user's device. The input is the output of the AI ​​engine and emotion engine, and the output is the saving advice sent to the user's device.

[0949] Step 6:

[0950] The device periodically obtains the user's location information and sends it to the server. The server processes the received location information, searches a database of nearby stores and facilities, and extracts special offer information. The special offer information is filtered based on the user's current location and purchasing habits, and is then pushed to the user's device. The input is the location information sent from the device, and the output is the special offer information pushed to the user's device.

[0951] 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.

[0952] 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.

[0953] 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.

[0954] [Third embodiment]

[0955] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0956] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0957] 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).

[0958] 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.

[0959] 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.

[0960] 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).

[0961] 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.

[0962] 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.

[0963] 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.

[0964] 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.

[0965] 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.

[0966] 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."

[0967] As an embodiment of the present invention, a system configured as follows is provided.

[0968] System Configuration

[0969] The system includes functions for collecting payment information linked to payment methods, registering household accounts, analyzing data using artificial intelligence, generating money-saving advice, acquiring location information, and providing information on special offers at nearby stores and facilities.

[0970] 1. Collection of payment information

[0971] Terminal

[0972] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[0973] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[0974] The acquired payment information is temporarily stored in a database within the terminal.

[0975] 2. Data household ledger registration

[0976] Terminal

[0977] The payment information stored in the terminal is sent to the server.

[0978] server

[0979] The server analyzes the received payment information and converts it into household accounting data format.

[0980] The analyzed information is registered in the household accounting app's database.

[0981] 3. AI-based analysis

[0982] server

[0983] The server inputs the household accounting data into an artificial intelligence (AI) engine.

[0984] The AI ​​engine analyzes patterns such as a user's purchase history, spending frequency, and time of day, and learns about the user's hobbies and preferences.

[0985] 4. Generating Savings Advice

[0986] server

[0987] The server further analyzes the user's spending patterns based on the analysis results of the AI ​​engine.

[0988] The AI ​​generates specific advice for reducing expenses, such as "Since your monthly convenience store spending is high, we suggest you buy in bulk."

[0989] The generated advice is sent to the user's terminal.

[0990] 5. Utilizing location information

[0991] Terminal

[0992] The terminal periodically acquires the user's location information.

[0993] Send location information to the server.

[0994] server

[0995] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[0996] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[0997] The filtered special offers are sent to the user's device via push notification.

[0998] Specific examples

[0999] Execution scenario

[1000] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[1001] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[1002] 3. The terminal sends this payment information to the server.

[1003] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[1004] 5. The server registers the analyzed household accounting data in the household accounting app database.

[1005] 6. The server's AI engine processes the new household accounting data and updates the user's spending patterns. For example, data such as "visiting convenience stores 15 times a month" is obtained.

[1006] 7. Based on this spending pattern, the server generates money-saving advice such as, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk."

[1007] 8. The server sends this advice to the user's device.

[1008] 9. The device periodically obtains the user's location information and sends it to the server.

[1009] 10. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[1010] This system allows users to efficiently manage their spending and receive specific advice on how to save money. Furthermore, location information is used to provide information on special offers at nearby stores, allowing for even more effective savings.

[1011] The processing flow will be explained below.

[1012] Step 1:

[1013] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[1014] Step 2:

[1015] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[1016] Step 3:

[1017] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[1018] Step 4:

[1019] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[1020] Step 5:

[1021] The server inputs household accounting data into an AI engine, which processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[1022] Step 6:

[1023] The server retrieves the AI ​​engine's learning results and further analyzes the user's spending patterns. Based on the analysis results, it generates specific advice for saving money. For example, it might suggest "Since your monthly convenience store spending is high, we suggest buying in bulk."

[1024] Step 7:

[1025] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[1026] Step 8:

[1027] The device periodically acquires the user's location information and sends it to the server.

[1028] Step 9:

[1029] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[1030] Step 10:

[1031] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[1032] In this way, the entire system works together to provide users with efficient household management and savings support.

[1033] Example 1

[1034] 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."

[1035] In modern society, users are seeking ways to efficiently manage their spending and receive specific advice on how to save money. However, existing household accounting apps and expense management systems lack the functionality to accurately analyze users' hobbies, preferences, and spending patterns and provide appropriate saving advice. Furthermore, there are also limited systems that utilize location information to provide information on special offers at nearby stores. This makes spending management cumbersome for users, making it difficult to save effectively.

[1036] 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.

[1037] In this invention, the server includes a means for converting the transmitted payment information into a household accounting data format and registering it in a household accounting database, a means for inputting the registered household accounting data into an AI engine and analyzing the user's hobbies, preferences, and spending patterns, and a means for generating and transmitting saving advice based on the analysis results to the user's terminal. This allows the user to efficiently manage their own spending and receive specific saving advice based on the AI ​​analysis results. Furthermore, by notifying the user of special offers based on location information, even more effective savings can be achieved.

[1038] "Payment Instrument" means an electronic or physical means used by a User to pay for goods or services.

[1039] "Payment information" is detailed information about the user's payment, such as the purchase details, amount, date and time, and store name.

[1040] "Server" is a central system for storing, analyzing, and processing collected data and coordinating with other components.

[1041] A "terminal" is a device that is directly operated by a user and that receives, transmits, saves, and notifies payment information.

[1042] The "household account book data format" is a data format converted into a specific format in order to centrally manage the user's income and expenditure information.

[1043] A "household account book database" is a database for storing data converted into a household account book data format.

[1044] The "AI engine" is an artificial intelligence system that analyzes users' hobbies, preferences, and spending patterns to generate specific advice.

[1045] "Savings advice" is a suggestion generated based on the analysis results, aimed at reducing the user's expenses.

[1046] "Location information" is data indicating the user's current location and movement history.

[1047] "Special offer information" is information about discounts and campaigns offered at nearby stores and facilities.

[1048] "Notification means" refers to a communication and display mechanism for providing information to the user.

[1049] The present invention provides a system that allows users to efficiently manage their spending and provides specific advice for saving money. The system has the following main functions:

[1050] 1. Collection of payment information

[1051] When a user purchases an item at a convenience store or other location, they pay using an electronic payment app on their smartphone. For example, when a user purchases a 500 yen item, they use a common electronic payment method. Once the payment is complete, the payment information (purchase details, amount, date and time, store name, etc.) is notified to the terminal.

[1052] 2. Data household ledger registration

[1053] The device temporarily stores this payment information in a database (e.g., SQLite) within the device. The device then sends the payment information to the server using an HTTPS request. The server receives the sent information, analyzes it, and converts it into a household accounting data format. The server then registers this information in the household accounting app's database (e.g., MySQL or PostgreSQL).

[1054] 3. AI-based analysis

[1055] The server inputs the household accounting data into an artificial intelligence (AI) engine. This AI engine analyzes patterns such as the user's purchase history, spending frequency, and time of day based on the household accounting data, and learns the user's hobbies and preferences. The AI ​​algorithms used include random forest and K-means clustering.

[1056] 4. Generating Savings Advice

[1057] The server further analyzes the user's spending patterns based on the AI ​​engine's analysis results. For example, for a user who frequently visits convenience stores, it generates money-saving advice such as "Since monthly convenience store spending is high, we suggest bulk purchases." This advice is then sent to the device again via an HTTPS request.

[1058] 5. Utilizing location information

[1059] The device periodically obtains the user's location information and sends it to the server using an HTTPS request. The server uses the received location information to check against a geographic database and search for special offers at nearby stores and facilities. It then filters this information and pushes special offers based on the user's purchasing habits to the device. Push notifications are sent using services such as Firebase Cloud Messaging.

[1060] Specific examples

[1061] 1. Payment Scenario

[1062] When a user purchases a 500 yen item at a convenience store, the terminal receives the payment information and stores it in an internal database. This information is then sent to the server, which converts it into household accounting data format and registers it in the database.

[1063] 2. AI analysis and advice generation

[1064] The server's AI engine uses this new data to update the user's spending patterns and detects a pattern of "visiting convenience stores 15 times a month." The server then generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest bulk purchases," and sends it to the user's device.

[1065] 3. Use of location information

[1066] The device periodically acquires the user's location information and sends it to the server. The server receives this location information, searches for special offers at nearby stores, and sends push notifications to the user's device, such as "Rice is on sale today."

[1067] Examples of prompt statements

[1068] An example of a prompt for this system is shown below:

[1069] "After purchasing a 500 yen item using a common electronic payment method, please explain the entire process that takes place using a smartphone app, from collecting payment information, registering it in a household account book, analyzing spending patterns using AI, generating money-saving advice, and providing special offers based on location information."

[1070] This allows users to efficiently manage their spending and receive specific money-saving advice based on AI analysis results. Furthermore, by utilizing location information, users can easily obtain information on special offers at nearby stores, enabling further savings.

[1071] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1072] Step 1:

[1073] A user purchases a 500 yen item at a convenience store using a common electronic payment method (such as PayPay or LINE Pay). When the user presses the payment button, the payment app processes the payment and generates a payment completion notification, which is sent to the user's device. (Input: User payment operation, Output: Payment completion notification)

[1074] Step 2:

[1075] The device receives a payment completion notification. Specifically, the device's notification system receives the notification from the payment app, extracts data including payment information (purchase details, amount, date and time, store name), and temporarily stores it in internal storage. (Input: payment completion notification, Output: temporarily stored payment information)

[1076] Step 3:

[1077] The terminal sends the temporarily saved payment information to the server using a secure communication method (HTTPS). When sending, the payment information is serialized in JSON format and sent to the server as a POST request. (Input: temporarily saved payment information, Output: sent to server)

[1078] Step 4:

[1079] The server deserializes and interprets the received payment information and converts it into a household accounting data format. This process involves data mapping and cleansing. Specifically, the received JSON data is parsed, mapped to the appropriate fields, and converted into SQL format. (Input: Submitted payment information, Output: Household accounting data format)

[1080] Step 5:

[1081] The server registers the converted household accounting data in the household accounting app's database. This is where database operations (e.g., executing an INSERT SQL statement) are performed. (Input: household accounting data format, Output: database registration completed)

[1082] Step 6:

[1083] The server inputs the registered household accounting data into an AI engine for analysis. The AI ​​engine analyzes the user's purchase history, spending frequency, time period, etc. During this process, it uses machine learning algorithms (e.g., random forest and K-means clustering) to perform pattern recognition and data clustering. (Input: household accounting data, output: analysis results)

[1084] Step 7:

[1085] Based on the AI ​​engine's analysis results, the server further analyzes the user's spending patterns and performs specific operations to generate money-saving advice. For example, if the analysis results show that the user "visits convenience stores 15 times a month," the server generates advice such as "since monthly convenience store spending is high, we suggest bulk purchases." (Input: AI engine analysis results, output: money-saving advice)

[1086] Step 8:

[1087] The server sends the generated money saving advice to the user's device. This also uses HTTPS, a secure communication method, and the advice content is serialized in JSON format and sent. (Input: Money saving advice, Output: Transmission to user device completed)

[1088] Step 9:

[1089] The device periodically obtains the user's location information. It uses a location service (e.g., Google Location Services) to collect GPS data and stores it in internal storage. (Input: Use of location service, Output: Obtained location information)

[1090] Step 10:

[1091] The location information acquired by the device is sent to the server. HTTPS is used for transmission, and the location information is serialized in JSON format and sent to the server as a POST request. (Input: acquired location information, Output: sent to server)

[1092] Step 11:

[1093] The server searches a database of nearby stores and facilities based on the location information received. It uses a geographic information system (GIS) to extract special offers around the user's current location and uses a personalized filtering algorithm to select the information that is most useful to the user. (Input: location information, output: filtered special offers)

[1094] Step 12:

[1095] The server sends the filtered special offer information to the user's device as a push notification. A service such as Firebase Cloud Messaging (FCM) is used for the push notification. (Input: filtered special offer information, Output: push notification to the user's device)

[1096] This allows users to efficiently manage their spending and receive specific advice on how to save money, as well as use their location to find out about special offers at nearby stores.

[1097] (Application example 1)

[1098] 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."

[1099] The purpose of this invention is to provide a system that, when a user uses an electronic payment method, collects expenditure information, automatically registers it in a household account book, analyzes expenditure patterns using AI and generates savings advice, and provides and notifies special offer information based on location information.Current systems have issues such as the time and effort required to manually input expenditure information, inappropriate savings advice, and missed special offer information, so these need to be resolved.

[1100] 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.

[1101] In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and learning the user's preferences, means for generating money-saving advice based on the analysis results, means for acquiring the user's location information, means for providing special offer information for nearby stores and facilities based on the acquired location information, and means for sending push notifications of the special offer information to the user, thereby enabling management of the user's spending, provision of money-saving advice, and notification of special offer information in real time.

[1102] A "payment instrument" is a method or device for making payments electronically for goods or services.

[1103] "Payment information" refers to transaction data such as the payment amount, store name, date and time when a user purchases a product or service.

[1104] A "household account book" is a record book for recording a user's daily income and expenditures and managing the financial situation of a household.

[1105] "Artificial intelligence" is a technology that allows computer systems to analyze user data and learn their needs and patterns.

[1106] "Savings advice" is advice that provides specific suggestions for cost reduction based on the user's spending patterns.

[1107] "Hobbies and preferences" refers to the types of products and services that a user is interested in and their tendencies.

[1108] "Location information" is geographical data that indicates the user's current location.

[1109] "Nearby stores and facilities" refer to stores and service providing facilities located near the user's current location.

[1110] "Special Offer Information" is information about special prices and discounts offered at nearby stores and facilities.

[1111] "Push notification" is a mechanism by which the system sends information to the user's device in real time.

[1112] This system works in conjunction with payment methods to collect payment information, automatically registers the collected information in a household account book, and analyzes the data using artificial intelligence (AI). Furthermore, it generates money-saving advice for users based on the analysis results, acquires the user's location information, and provides special offers at nearby stores and facilities. This system also includes a function to send push notifications of special offers to users.

[1113] System Configuration

[1114] 1. How payment information is collected

[1115] When a user pays for a product using an electronic payment method, a payment completion notice is sent to the smartphone terminal. This notice contains payment information such as the payment amount, store name, date and time, and this information is temporarily stored in the terminal's internal database.

[1116] 2. How to register household accounts

[1117] The payment information stored in the device is sent to a server via the Internet. The server analyzes the received information, converts it into a household accounting format, and registers it in a household accounting database.

[1118] 3. Artificial Intelligence Analysis Methods

[1119] The household accounting data registered on the server is input into an AI engine, an artificial intelligence (AI) engine. The AI ​​engine analyzes the user's purchase history and spending frequency, and learns the user's preferences. This makes it possible to generate money-saving advice based on the user's spending patterns.

[1120] 4. Means of generating saving advice

[1121] Based on the results of the analysis, the AI ​​engine generates specific money-saving advice. For example, if monthly convenience store spending is high, advice suggesting bulk purchases will be generated. This advice is sent from the server to the user's device and displayed.

[1122] 5. Location information acquisition means

[1123] The device periodically obtains the user's current location using location information services and sends this information to the server, which then uses the location information to search for special offers at nearby stores and facilities.

[1124] 6. Special Offer Information and Push Notification Methods

[1125] The server filters the special offer information based on the acquired location information and purchasing trends and sends it to the user's device via push notification, allowing the user to receive real-time information on special offers from nearby stores and facilities.

[1126] Specific examples

[1127] 1. When a user makes a 500 yen payment at a convenience store, the payment information is sent to the smartphone.

[1128] 2. The smartphone sends the payment information to the server.

[1129] 3. The server analyzes the payment information and records it in the household account book.

[1130] 4. The AI ​​engine analyzes the user's spending patterns based on the new household accounting data.

[1131] 5. The system generates a saving advice such as "Since your monthly convenience store spending is high, we suggest you buy in bulk" and notifies the user.

[1132] 6. The smartphone periodically obtains location information and sends it to the server.

[1133] 7. The server filters special offers from nearby stores and sends push notifications to the user, such as "Rice is on sale today."

[1134] Prompt Sentence Examples

[1135] Parse the following payment information and generate savings advice:

[1136] Store name: Convenience store

[1137] Price: 500 yen

[1138] Date and Time: 2023-10-03T12:00:00

[1139] Analyze your spending patterns and get advice on how to save money.

[1140] Hardware and software used

[1141] Smartphone: Receiving payment information and acquiring location information

[1142] Server: Receives and analyzes data

[1143] Database: Payment information, household accounting data storage

[1144] AI engine: Data analysis, generating savings advice

[1145] Push notification system: Providing information to users

[1146] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1147] Step 1:

[1148] Collection of payment information

[1149] When a user makes a payment using an electronic payment method at a store such as a convenience store, a payment completion notification is sent to the terminal (smartphone).

[1150] Input: Payment completion notice (payment amount, store name, date and time, etc.)

[1151] Processing: The terminal receives this notification information.

[1152] Output: Payment information temporarily stored in the device's internal database

[1153] Step 2:

[1154] Household accounting registration method

[1155] The payment information stored in the terminal is transmitted to a server via the Internet.

[1156] Input: Payment information from the device's internal database

[1157] Process: Send payment information to the server as an HTTP request

[1158] Output: Payment information received by the server

[1159] Step 3:

[1160] Conversion to household accounting data

[1161] The server analyzes the received payment information, converts it into a household accounting format, and registers it in a household accounting database.

[1162] Input: Received payment information

[1163] Processing: Analyze the data and convert it into a household accounting format

[1164] Output: Household accounting data stored in the household accounting database

[1165] Step 4:

[1166] Artificial Intelligence Analysis Methods

[1167] Household accounting data is input into an artificial intelligence (AI) engine to analyze users' spending patterns and preferences.

[1168] Input: Data from the household accounting database

[1169] Processing: AI engine analyzes data and learns spending patterns and preferences

[1170] Output: Analysis results (user spending patterns, preferences, etc.)

[1171] Step 5:

[1172] Savings advice generation method

[1173] Based on the analysis results of the AI ​​engine, saving advice is generated and sent from the server to the user's device.

[1174] Input: AI analysis results

[1175] Processing: Generate specific savings advice based on the analysis results

[1176] Output: Saving advice sent to the user's device

[1177] Step 6:

[1178] Location information acquisition means

[1179] The device periodically acquires the user's location information and sends it to the server.

[1180] Input: Device location data

[1181] Processing: The device obtains the current location using location services.

[1182] Output: Location information sent to the server

[1183] Step 7:

[1184] Special offer information and push notification methods

[1185] The server searches for nearby special offers based on the acquired location information and purchasing trends and sends a push notification to the user's device.

[1186] Input: Location information, purchasing trend data

[1187] Process: Search the database and filter the deals

[1188] Output: A push notification of the special offer sent to the user's device

[1189] 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.

[1190] As an embodiment of the present invention, a system configured as follows is provided.

[1191] System Configuration

[1192] The system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function to provide information on special offers at nearby stores and facilities.

[1193] 1. Collection of payment information

[1194] Terminal

[1195] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[1196] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[1197] The acquired payment information is temporarily stored in a database within the terminal.

[1198] 2. Data household ledger registration

[1199] Terminal

[1200] The payment information stored in the terminal is sent to the server.

[1201] server

[1202] The server analyzes the received payment information and converts it into household accounting data format.

[1203] The analyzed information is registered in the household accounting app's database.

[1204] 3. Acquiring Emotion Data

[1205] Terminal

[1206] Activate the emotion engine to recognize the user's emotions.

[1207] The emotion engine uses sensors such as a camera and microphone to obtain emotional data from the user's facial expressions, tone of voice, gestures, etc.

[1208] The acquired emotion data is stored in a database within the device and sent to a server.

[1209] 4. Analysis by AI and emotion engine

[1210] server

[1211] The server inputs the received household accounting data and emotion data into the AI ​​engine.

[1212] The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[1213] The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[1214] 5. Generating Savings Advice

[1215] server

[1216] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine.

[1217] Based on the analysis results, the system generates specific advice for saving energy depending on the user's emotional state, such as suggestions to reduce stress when stress levels are high and strong suggestions when users are relaxed.

[1218] The generated advice is sent to the user's terminal.

[1219] 6. Utilizing location information

[1220] Terminal

[1221] The terminal periodically acquires the user's location information.

[1222] Send location information to the server.

[1223] 7. Offering special offers

[1224] server

[1225] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[1226] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[1227] The filtered special offers are sent to the user's device via push notification.

[1228] Specific examples

[1229] Execution scenario

[1230] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[1231] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[1232] 3. The terminal sends this payment information to the server.

[1233] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[1234] 5. The server registers the analyzed household accounting data in the household accounting app database.

[1235] 6. The device activates an emotion engine to recognize the user's emotions.

[1236] 7. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to obtain emotion data, such as "satisfied."

[1237] 8. The device sends the acquired emotion data to the server.

[1238] 9. The server's AI engine processes the household accounting data and emotional data to learn the user's spending patterns (e.g., "visiting convenience stores 15 times a month") and emotional tendencies.

[1239] 10. Based on this spending pattern, the server generates money-saving advice such as, "Since your monthly convenience store spending is high, we suggest bulk purchases." If the user is feeling stressed, the server adds relaxation suggestions such as, "Enjoy shopping within your budget."

[1240] 11. The server sends this advice to the user's device.

[1241] 12. The device periodically obtains the user's location information and sends it to the server.

[1242] 13. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[1243] The system allows users to efficiently manage their spending, receive emotionally-driven savings advice, and utilizes location and emotional data to make purchasing more comfortable and effective.

[1244] The processing flow will be explained below.

[1245] Step 1:

[1246] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[1247] Step 2:

[1248] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[1249] Step 3:

[1250] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[1251] Step 4:

[1252] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[1253] Step 5:

[1254] The device activates an emotion engine to recognize the user's emotions. The emotion engine uses sensors such as a camera and microphone to acquire emotion data from the user's facial expressions, tone of voice, gestures, etc.

[1255] Step 6:

[1256] The device temporarily stores the acquired emotional data and transmits it to the server. The emotional data includes emotional states such as "satisfaction" and "stress."

[1257] Step 7:

[1258] The server inputs household accounting data and emotional data into the AI ​​engine, which analyzes the user's purchase history, spending frequency, time of day, etc. to learn about the user's hobbies and preferences.

[1259] Step 8:

[1260] The server combines the data analysis results of the emotion engine with the learning results of the AI ​​engine to further analyze the user's spending patterns. For example, if the user is feeling stressed, it will emphasize relaxation suggestions.

[1261] Step 9:

[1262] The server generates specific advice for saving money based on the user's emotions and spending patterns. For example, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk," and the advice is adjusted according to the user's emotional state.

[1263] Step 10:

[1264] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[1265] Step 11:

[1266] The device periodically acquires the user's location information and sends it to the server.

[1267] Step 12:

[1268] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[1269] Step 13:

[1270] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[1271] Example 2

[1272] 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."

[1273] Conventional household management systems simply record spending, but lack the ability to consider users' emotional state and provide specific savings advice. This makes it difficult for users to understand their spending patterns and find rational ways to save money. Furthermore, systems that utilize users' location information to provide relevant special offers are also lacking.

[1274] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, means for recognizing a user's emotions, means for analyzing the recognized emotional data to evaluate the user's psychological state, artificial intelligence means for analyzing the household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and psychological evaluation, means for acquiring the user's location information, and means for providing special offer information for nearby stores and facilities based on the acquired location information. This enables the user to efficiently manage their spending and receive appropriate saving advice based on their emotional state. Furthermore, providing special offer information using location information can make the user's purchasing activities more comfortable and effective.

[1275] "Payment Instrument" means an electronic instrument used by a User to pay for goods and services.

[1276] "Payment information" is data related to payments made by users, and includes information such as the purchase details, amount, date and time, and store name.

[1277] A "household account book" refers to a system or application for recording and managing a user's income and expenses.

[1278] "Artificial intelligence means" refers to machine learning algorithms and models used to analyze data and learn user preferences.

[1279] An "emotion engine" refers to a program or system that uses sensors such as cameras and microphones to acquire and analyze a user's emotional data.

[1280] "Location information" is data indicating the user's current location, and is obtained using technology such as GPS.

[1281] "Special Offer Information" refers to information about discounts and special offers offered by stores and facilities.

[1282] "Savings Advice" refers to specific suggestions or advice for reducing a user's spending.

[1283] "Database" refers to a system for systematically storing information and making it quickly searchable and accessible.

[1284] "Notification" refers to messages or alerts that inform users of important information.

[1285] "Analysis" refers to the process of examining data in detail to find useful information and patterns in it.

[1286] "Purchasing trends" refers to a user's behavioral patterns and preferences when purchasing products or services.

[1287] "Push notification" refers to a means for sending information to users in real time.

[1288] As an embodiment of the present invention, we provide a system configured as follows: This system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[1289] Collection of payment information

[1290] Terminal

[1291] When a user pays for a product or service using a smartphone payment app, a payment completion notification is sent to the terminal. The terminal receives this notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the terminal's internal database. For example, if a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed," and this information is stored in the database.

[1292] Data household ledger registration

[1293] Terminal

[1294] The terminal transmits the payment information stored in the internal database to the server.

[1295] server

[1296] The server analyzes the received payment information and converts it into household accounting data format. The analysis results are then registered in the household accounting app's database. For example, data such as "500 yen spent at a convenience store" can be converted into a format such as "Expense: convenience store, Amount: 500 yen, Date / Time: today" and saved in the household accounting database.

[1297] Acquiring emotion data

[1298] Terminal

[1299] The device activates the emotion engine and uses sensors such as a camera and microphone to acquire the user's emotional data. The acquired emotional data is stored in an internal database and sent to a server. For example, the device's camera and microphone may analyze the user's facial expressions and tone of voice, acquiring data indicating that the user is satisfied and sending it to the server.

[1300] AI and emotion engine analysis

[1301] server

[1302] The server inputs the received household accounting data and emotional data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotional engine also analyzes the emotional data to evaluate the user's psychological state. For example, based on data such as "spent 500 yen at a convenience store" and "user is satisfied," the server learns the tendency that "users visit convenience stores 15 times a month and are satisfied after each visit."

[1303] Generating Savings Advice

[1304] server

[1305] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific saving advice according to the user's emotional state. It also sends this advice to the user's device. For example, advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" is generated and sent from the server to the device.

[1306] Utilizing location information

[1307] Terminal

[1308] The device periodically acquires the user's location information and sends it to the server. When the user goes out, the device's GPS function acquires the location information and periodically sends it to the server.

[1309] Providing special offers

[1310] server

[1311] The server processes the location information received from the user and searches a database of nearby stores and facilities. Special offer information is extracted from the search results and filtered based on the user's current location and purchasing habits. The filtered special offer information is sent to the user's device via push notification. For example, information such as "Rice is on sale today" is extracted, filtered based on the user's purchasing habits, and a push notification is sent to the device.

[1312] Examples of prompt statements

[1313] Here are some example prompts to input to a generative AI model:

[1314] "I completed a 500 yen payment using an electronic payment method. Create household accounting data based on this payment, obtain emotional data, and generate savings advice."

[1315] By inputting this prompt, the AI ​​model is expected to perform actions according to the above processing steps.

[1316] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1317] Step 1:

[1318] Input: The user makes a payment using an electronic payment method.

[1319] Processing: The terminal receives a payment completion notification from the payment app and extracts payment information (purchase details, amount, date and time, store name, etc.) from the notification.

[1320] Output: Payment information is temporarily saved in the terminal's internal database.

[1321] Specific operation: When a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed." The terminal receives this notification and saves the payment information ("500 yen spent at convenience store") in the database.

[1322] Step 2:

[1323] Input: Payment information stored in the device's internal database.

[1324] Processing: The terminal sends the saved payment information to the server.

[1325] Output: Payment information is sent to the server.

[1326] Specific operation: The device sends data such as "500 yen spent at a convenience store" to the server.

[1327] Step 3:

[1328] Input: Payment information received by the server.

[1329] Processing: The server analyzes the payment information and converts it into household accounting data format.

[1330] Output: The analyzed household accounting data is registered in the household accounting app database.

[1331] Specific operation: The server receives data such as "500 yen spent at a convenience store," converts it into a format such as "Expense: convenience store, amount: 500 yen, date and time: today," and saves it in the household accounting database.

[1332] Step 4:

[1333] Input: The user picks up the device.

[1334] Processing: The device launches the emotion engine and acquires the user's emotion data using sensors such as the camera and microphone.

[1335] Output: The acquired emotion data is stored in a database within the device and sent to the server.

[1336] Specific operation: The device's camera and microphone analyze the user's facial expressions and tone of voice, obtain data indicating that the user is satisfied, and send this data to the server.

[1337] Step 5:

[1338] Input: Household accounting data and emotion data received by the server.

[1339] Processing: The server inputs household accounting data and emotional data into the AI ​​engine, processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[1340] Output: The AI ​​engine generates the learning results.

[1341] Specific operation: Based on the data "500 yen spent at a convenience store" and "user satisfaction," the server learns the tendency that "users use convenience stores 15 times a month and are satisfied after using them."

[1342] Step 6:

[1343] Input: AI engine learning results and emotion engine evaluation results.

[1344] Processing: Based on the analysis results, the server generates specific saving advice according to the user's emotional state and sends it to the user's device.

[1345] Output: The generated advice is sent to the user's terminal.

[1346] Specific operation: The server generates advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" and sends it to the device.

[1347] Step 7:

[1348] Input: User goes out.

[1349] Processing: The device periodically acquires the user's location information and sends it to the server.

[1350] Output: The obtained location information is sent to the server.

[1351] Specific operation: The device's GPS function acquires location information and periodically sends it to the server.

[1352] Step 8:

[1353] Input: The location information received by the server.

[1354] Processing: Based on the location information, the server searches a database of nearby stores and facilities, extracting and filtering special offers.

[1355] Output: The filtered special offers are pushed to the user's device.

[1356] Specific operation: The server extracts information such as "Rice is on sale today," filters it according to the user's purchasing habits, and sends a push notification to the device.

[1357] (Application example 2)

[1358] 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."

[1359] The present invention aims to provide a system that allows users to effectively reduce their spending by linking their payment information and emotional data to manage spending and providing appropriate money-saving advice and information on special offers at nearby stores based on the user's purchasing behavior and emotional state. However, while current systems collect payment information, they are limited in providing advice that takes the user's emotional state into account and information on special offers that utilize location information. Therefore, a system is needed that takes the user's emotional state and location information into account and provides personalized advice on reducing spending and information on special offers based on purchasing behavior.

[1360] 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 collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and the user's emotional state, means for acquiring the user's location information, and means for providing information on special offers at nearby stores and facilities based on the acquired location information and purchasing habits. This allows the user to receive optimal saving advice tailored to their emotional state and current location, and information on special offers at nearby stores is also provided in real time, allowing them to effectively reduce their spending.

[1361] A "Payment Instrument" is an electronic payment method used by a User to purchase goods or services.

[1362] "Payment information" refers to information related to a user's purchasing activity, such as the purchased item, amount, store name, date and time, etc.

[1363] "Household account book data" is a collection of data that records a user's income and expenses.

[1364] "Artificial intelligence means" refers to a system that has the ability to analyze large amounts of data and learn about the user's hobbies and preferences.

[1365] "Emotion data" is information about the user's emotional state obtained from facial expressions, tone of voice, gestures, and the like.

[1366] "Savings advice" refers to specific proposals and suggestions for reducing a user's spending.

[1367] "Location information" is information indicating the user's current location, and is obtained using technology such as GPS.

[1368] "Special Offer Information" refers to information about discounts and sales offered at nearby stores and facilities.

[1369] "Push notification" refers to a technology that sends information from an application to a user's device in real time.

[1370] "Purchase trends" refers to trends derived based on a user's past purchase history and spending patterns.

[1371] System Configuration

[1372] A system for implementing this invention is configured as follows: The system includes a payment information collection function linked to a payment method, a household account book registration function, an artificial intelligence means and emotion engine function, a saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[1373] 1. Collection of payment information

[1374] Terminal

[1375] When a user completes payment for a product or service using a smartphone payment app, a payment completion notification is sent to the user's device. The device receives the notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the device's internal database.

[1376] 2. Data household ledger registration

[1377] Terminal

[1378] The payment information stored in the terminal is sent to the server.

[1379] server

[1380] The server analyzes the received payment information, converts it into household accounting data format, and registers the analyzed information in the household accounting app database.

[1381] 3. Acquiring Emotion Data

[1382] Terminal

[1383] The device's built-in emotion engine is activated, and emotion data is acquired from the user's facial expressions, tone of voice, gestures, etc. using sensors such as a camera and microphone. The acquired emotion data is stored in a database within the device and sent to a server.

[1384] 4. Analysis by AI and emotion engine

[1385] server

[1386] The server inputs the received household accounting data and emotion data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[1387] 5. Generating Savings Advice

[1388] server

[1389] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific advice for saving money according to the user's emotional state. The generated advice is then sent to the user's device.

[1390] 6. Utilizing location information

[1391] Terminal

[1392] The device periodically acquires the user's location information and sends it to the server.

[1393] 7. Offering special offers

[1394] server

[1395] The server processes the location information received from the user and searches a database of nearby stores and facilities. It extracts special offers from the search results and filters them based on the user's current location and purchasing habits. It then sends the filtered special offers to the user's device via push notification.

[1396] Hardware and Software

[1397] Hardware: Smartphone, camera, microphone, GPS module

[1398] Software: Payment app, household accounting app, artificial intelligence engine, emotion engine, location information acquisition module, special offer information module

[1399] Specific examples

[1400] Execution scenario

[1401] A user purchases a 500 yen item at a convenience store using a common electronic payment method. The device receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired. The device sends this payment information to the server. The server analyzes the received payment information and converts it into household accounting data format as "Expenses of 500 yen at convenience store." The server registers the analyzed household accounting data in the household accounting app's database. The device activates an emotion engine to recognize the user's emotions. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice and acquires emotional data. An example would be "satisfied." The device then sends the acquired emotional data to the server. The server's AI engine processes the household accounting data and emotional data and learns the user's spending patterns and emotional tendencies. Based on this spending pattern, the server generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest buying in bulk." If the user is feeling stressed, it adds relaxation suggestions such as "Enjoy shopping within your budget." The server then sends this advice to the user's device. The device periodically acquires the user's location information and sends it to the server. The server obtains location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[1402] Prompt Sentence Examples

[1403] "Please create a program that automatically collects payment information, such as the amount of money the user spends at a convenience store, the name of the store, and the date and time. Also, please give it the ability to analyze the user's emotional data using a camera and microphone and generate money-saving advice based on that. Finally, please use location information to provide the user with information about special offers at nearby stores."

[1404] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1405] Step 1:

[1406] A user purchases a product or service using a smartphone payment app. The terminal receives a payment completion notification and acquires payment information such as the purchase details, amount, purchase date and time, and store name. The acquired payment information is then temporarily stored in the terminal's database. The input is the payment information, and the output is the payment information stored in the terminal's database.

[1407] Step 2:

[1408] The device sends the temporarily saved payment information to the server. The server analyzes the received payment information and converts it into household accounting data format. The converted household accounting data is then registered in the household accounting app's database. The input is the payment information sent to the server, and the output is the information registered in the household accounting database.

[1409] Step 3:

[1410] The device starts the emotion engine and uses the camera and microphone to capture the user's facial expressions, tone of voice, gestures, etc. to obtain emotional data. The obtained emotional data is temporarily stored in the device's database and sent to the server. The input is emotional data based on the user's facial expressions and tone of voice, and the output is the emotional data sent to the server.

[1411] Step 4:

[1412] The server receives household accounting data and emotion data and inputs it into the AI ​​engine. The AI ​​engine processes the received data and learns the user's hobbies and preferences from their purchasing history, spending frequency, time of day, etc. Meanwhile, the emotion engine analyzes the emotion data and evaluates the user's psychological state. The inputs are household accounting data and emotion data, and the output is the user's hobbies and preferences and the results of the psychological state evaluation.

[1413] Step 5:

[1414] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates saving advice according to the user's emotional state and sends that advice to the user's device. The input is the output of the AI ​​engine and emotion engine, and the output is the saving advice sent to the user's device.

[1415] Step 6:

[1416] The device periodically obtains the user's location information and sends it to the server. The server processes the received location information, searches a database of nearby stores and facilities, and extracts special offer information. The special offer information is filtered based on the user's current location and purchasing habits, and is then pushed to the user's device. The input is the location information sent from the device, and the output is the special offer information pushed to the user's device.

[1417] 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.

[1418] 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.

[1419] 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.

[1420] [Fourth embodiment]

[1421] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1422] 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.

[1423] 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).

[1424] 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.

[1425] 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.

[1426] 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).

[1427] 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.

[1428] 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.

[1429] 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.

[1430] 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.

[1431] 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.

[1432] 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.

[1433] 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."

[1434] As an embodiment of the present invention, a system configured as follows is provided.

[1435] System Configuration

[1436] The system includes functions for collecting payment information linked to payment methods, registering household accounts, analyzing data using artificial intelligence, generating money-saving advice, acquiring location information, and providing information on special offers at nearby stores and facilities.

[1437] 1. Collection of payment information

[1438] Terminal

[1439] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[1440] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[1441] The acquired payment information is temporarily stored in a database within the terminal.

[1442] 2. Data household ledger registration

[1443] Terminal

[1444] The payment information stored in the terminal is sent to the server.

[1445] server

[1446] The server analyzes the received payment information and converts it into household accounting data format.

[1447] The analyzed information is registered in the household accounting app's database.

[1448] 3. AI-based analysis

[1449] server

[1450] The server inputs the household accounting data into an artificial intelligence (AI) engine.

[1451] The AI ​​engine analyzes patterns such as a user's purchase history, spending frequency, and time of day, and learns about the user's hobbies and preferences.

[1452] 4. Generating Savings Advice

[1453] server

[1454] The server further analyzes the user's spending patterns based on the analysis results of the AI ​​engine.

[1455] The AI ​​generates specific advice for reducing expenses, such as "Since your monthly convenience store spending is high, we suggest you buy in bulk."

[1456] The generated advice is sent to the user's terminal.

[1457] 5. Utilizing location information

[1458] Terminal

[1459] The terminal periodically acquires the user's location information.

[1460] Send location information to the server.

[1461] server

[1462] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[1463] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[1464] The filtered special offers are sent to the user's device via push notification.

[1465] Specific examples

[1466] Execution scenario

[1467] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[1468] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[1469] 3. The terminal sends this payment information to the server.

[1470] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[1471] 5. The server registers the analyzed household accounting data in the household accounting app database.

[1472] 6. The server's AI engine processes the new household accounting data and updates the user's spending patterns. For example, data such as "visiting convenience stores 15 times a month" is obtained.

[1473] 7. Based on this spending pattern, the server generates money-saving advice such as, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk."

[1474] 8. The server sends this advice to the user's device.

[1475] 9. The device periodically obtains the user's location information and sends it to the server.

[1476] 10. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[1477] This system allows users to efficiently manage their spending and receive specific advice on how to save money. Furthermore, location information is used to provide information on special offers at nearby stores, allowing for even more effective savings.

[1478] The processing flow will be explained below.

[1479] Step 1:

[1480] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[1481] Step 2:

[1482] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[1483] Step 3:

[1484] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[1485] Step 4:

[1486] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[1487] Step 5:

[1488] The server inputs household accounting data into an AI engine, which processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[1489] Step 6:

[1490] The server retrieves the AI ​​engine's learning results and further analyzes the user's spending patterns. Based on the analysis results, it generates specific advice for saving money. For example, it might suggest "Since your monthly convenience store spending is high, we suggest buying in bulk."

[1491] Step 7:

[1492] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[1493] Step 8:

[1494] The device periodically acquires the user's location information and sends it to the server.

[1495] Step 9:

[1496] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[1497] Step 10:

[1498] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[1499] In this way, the entire system works together to provide users with efficient household management and savings support.

[1500] Example 1

[1501] 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."

[1502] In modern society, users are seeking ways to efficiently manage their spending and receive specific advice on how to save money. However, existing household accounting apps and expense management systems lack the functionality to accurately analyze users' hobbies, preferences, and spending patterns and provide appropriate saving advice. Furthermore, there are also limited systems that utilize location information to provide information on special offers at nearby stores. This makes spending management cumbersome for users, making it difficult to save effectively.

[1503] 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.

[1504] In this invention, the server includes a means for converting the transmitted payment information into a household accounting data format and registering it in a household accounting database, a means for inputting the registered household accounting data into an AI engine and analyzing the user's hobbies, preferences, and spending patterns, and a means for generating and transmitting saving advice based on the analysis results to the user's terminal. This allows the user to efficiently manage their own spending and receive specific saving advice based on the AI ​​analysis results. Furthermore, by notifying the user of special offers based on location information, even more effective savings can be achieved.

[1505] "Payment Instrument" means an electronic or physical means used by a User to pay for goods or services.

[1506] "Payment information" is detailed information about the user's payment, such as the purchase details, amount, date and time, and store name.

[1507] "Server" is a central system for storing, analyzing, and processing collected data and coordinating with other components.

[1508] A "terminal" is a device that is directly operated by a user and that receives, transmits, saves, and notifies payment information.

[1509] The "household account book data format" is a data format converted into a specific format in order to centrally manage the user's income and expenditure information.

[1510] A "household account book database" is a database for storing data converted into a household account book data format.

[1511] The "AI engine" is an artificial intelligence system that analyzes users' hobbies, preferences, and spending patterns to generate specific advice.

[1512] "Savings advice" is a suggestion generated based on the analysis results, aimed at reducing the user's expenses.

[1513] "Location information" is data indicating the user's current location and movement history.

[1514] "Special offer information" is information about discounts and campaigns offered at nearby stores and facilities.

[1515] "Notification means" refers to a communication and display mechanism for providing information to the user.

[1516] The present invention provides a system that allows users to efficiently manage their spending and provides specific advice for saving money. The system has the following main functions:

[1517] 1. Collection of payment information

[1518] When a user purchases an item at a convenience store or other location, they pay using an electronic payment app on their smartphone. For example, when a user purchases a 500 yen item, they use a common electronic payment method. Once the payment is complete, the payment information (purchase details, amount, date and time, store name, etc.) is notified to the terminal.

[1519] 2. Data household ledger registration

[1520] The device temporarily stores this payment information in a database (e.g., SQLite) within the device. The device then sends the payment information to the server using an HTTPS request. The server receives the sent information, analyzes it, and converts it into a household accounting data format. The server then registers this information in the household accounting app's database (e.g., MySQL or PostgreSQL).

[1521] 3. AI-based analysis

[1522] The server inputs the household accounting data into an artificial intelligence (AI) engine. This AI engine analyzes patterns such as the user's purchase history, spending frequency, and time of day based on the household accounting data, and learns the user's hobbies and preferences. The AI ​​algorithms used include random forest and K-means clustering.

[1523] 4. Generating Savings Advice

[1524] The server further analyzes the user's spending patterns based on the AI ​​engine's analysis results. For example, for a user who frequently visits convenience stores, it generates money-saving advice such as "Since monthly convenience store spending is high, we suggest bulk purchases." This advice is then sent to the device again via an HTTPS request.

[1525] 5. Utilizing location information

[1526] The device periodically obtains the user's location information and sends it to the server using an HTTPS request. The server uses the received location information to check against a geographic database and search for special offers at nearby stores and facilities. It then filters this information and pushes special offers based on the user's purchasing habits to the device. Push notifications are sent using services such as Firebase Cloud Messaging.

[1527] Specific examples

[1528] 1. Payment Scenario

[1529] When a user purchases a 500 yen item at a convenience store, the terminal receives the payment information and stores it in an internal database. This information is then sent to the server, which converts it into household accounting data format and registers it in the database.

[1530] 2. AI analysis and advice generation

[1531] The server's AI engine uses this new data to update the user's spending patterns and detects a pattern of "visiting convenience stores 15 times a month." The server then generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest bulk purchases," and sends it to the user's device.

[1532] 3. Use of location information

[1533] The device periodically acquires the user's location information and sends it to the server. The server receives this location information, searches for special offers at nearby stores, and sends push notifications to the user's device, such as "Rice is on sale today."

[1534] Examples of prompt statements

[1535] An example of a prompt for this system is shown below:

[1536] "After purchasing a 500 yen item using a common electronic payment method, please explain the entire process that takes place using a smartphone app, from collecting payment information, registering it in a household account book, analyzing spending patterns using AI, generating money-saving advice, and providing special offers based on location information."

[1537] This allows users to efficiently manage their spending and receive specific money-saving advice based on AI analysis results. Furthermore, by utilizing location information, users can easily obtain information on special offers at nearby stores, enabling further savings.

[1538] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1539] Step 1:

[1540] A user purchases a 500 yen item at a convenience store using a common electronic payment method (such as PayPay or LINE Pay). When the user presses the payment button, the payment app processes the payment and generates a payment completion notification, which is sent to the user's device. (Input: User payment operation, Output: Payment completion notification)

[1541] Step 2:

[1542] The device receives a payment completion notification. Specifically, the device's notification system receives the notification from the payment app, extracts data including payment information (purchase details, amount, date and time, store name), and temporarily stores it in internal storage. (Input: payment completion notification, Output: temporarily stored payment information)

[1543] Step 3:

[1544] The terminal sends the temporarily saved payment information to the server using a secure communication method (HTTPS). When sending, the payment information is serialized in JSON format and sent to the server as a POST request. (Input: temporarily saved payment information, Output: sent to server)

[1545] Step 4:

[1546] The server deserializes and interprets the received payment information and converts it into a household accounting data format. This process involves data mapping and cleansing. Specifically, the received JSON data is parsed, mapped to the appropriate fields, and converted into SQL format. (Input: Submitted payment information, Output: Household accounting data format)

[1547] Step 5:

[1548] The server registers the converted household accounting data in the household accounting app's database. This is where database operations (e.g., executing an INSERT SQL statement) are performed. (Input: household accounting data format, Output: database registration completed)

[1549] Step 6:

[1550] The server inputs the registered household accounting data into an AI engine for analysis. The AI ​​engine analyzes the user's purchase history, spending frequency, time period, etc. During this process, it uses machine learning algorithms (e.g., random forest and K-means clustering) to perform pattern recognition and data clustering. (Input: household accounting data, output: analysis results)

[1551] Step 7:

[1552] Based on the AI ​​engine's analysis results, the server further analyzes the user's spending patterns and performs specific operations to generate money-saving advice. For example, if the analysis results show that the user "visits convenience stores 15 times a month," the server generates advice such as "since monthly convenience store spending is high, we suggest bulk purchases." (Input: AI engine analysis results, output: money-saving advice)

[1553] Step 8:

[1554] The server sends the generated money saving advice to the user's device. This also uses HTTPS, a secure communication method, and the advice content is serialized in JSON format and sent. (Input: Money saving advice, Output: Transmission to user device completed)

[1555] Step 9:

[1556] The device periodically obtains the user's location information. It uses a location service (e.g., Google Location Services) to collect GPS data and stores it in internal storage. (Input: Use of location service, Output: Obtained location information)

[1557] Step 10:

[1558] The location information acquired by the device is sent to the server. HTTPS is used for transmission, and the location information is serialized in JSON format and sent to the server as a POST request. (Input: acquired location information, Output: sent to server)

[1559] Step 11:

[1560] The server searches a database of nearby stores and facilities based on the location information received. It uses a geographic information system (GIS) to extract special offers around the user's current location and uses a personalized filtering algorithm to select the information that is most useful to the user. (Input: location information, output: filtered special offers)

[1561] Step 12:

[1562] The server sends the filtered special offer information to the user's device as a push notification. A service such as Firebase Cloud Messaging (FCM) is used for the push notification. (Input: filtered special offer information, Output: push notification to the user's device)

[1563] This allows users to efficiently manage their spending and receive specific advice on how to save money, as well as use their location to find out about special offers at nearby stores.

[1564] (Application example 1)

[1565] 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."

[1566] The purpose of this invention is to provide a system that, when a user uses an electronic payment method, collects expenditure information, automatically registers it in a household account book, analyzes expenditure patterns using AI and generates savings advice, and provides and notifies special offer information based on location information.Current systems have issues such as the time and effort required to manually input expenditure information, inappropriate savings advice, and missed special offer information, so these need to be resolved.

[1567] 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.

[1568] In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and learning the user's preferences, means for generating money-saving advice based on the analysis results, means for acquiring the user's location information, means for providing special offer information for nearby stores and facilities based on the acquired location information, and means for sending push notifications of the special offer information to the user, thereby enabling management of the user's spending, provision of money-saving advice, and notification of special offer information in real time.

[1569] A "payment instrument" is a method or device for making payments electronically for goods or services.

[1570] "Payment information" refers to transaction data such as the payment amount, store name, date and time when a user purchases a product or service.

[1571] A "household account book" is a record book for recording a user's daily income and expenditures and managing the financial situation of a household.

[1572] "Artificial intelligence" is a technology that allows computer systems to analyze user data and learn their needs and patterns.

[1573] "Savings advice" is advice that provides specific suggestions for cost reduction based on the user's spending patterns.

[1574] "Hobbies and preferences" refers to the types of products and services that a user is interested in and their tendencies.

[1575] "Location information" is geographical data that indicates the user's current location.

[1576] "Nearby stores and facilities" refer to stores and service providing facilities located near the user's current location.

[1577] "Special Offer Information" is information about special prices and discounts offered at nearby stores and facilities.

[1578] "Push notification" is a mechanism by which the system sends information to the user's device in real time.

[1579] This system works in conjunction with payment methods to collect payment information, automatically registers the collected information in a household account book, and analyzes the data using artificial intelligence (AI). Furthermore, it generates money-saving advice for users based on the analysis results, acquires the user's location information, and provides special offers at nearby stores and facilities. This system also includes a function to send push notifications of special offers to users.

[1580] System Configuration

[1581] 1. How payment information is collected

[1582] When a user pays for a product using an electronic payment method, a payment completion notice is sent to the smartphone terminal. This notice contains payment information such as the payment amount, store name, date and time, and this information is temporarily stored in the terminal's internal database.

[1583] 2. How to register household accounts

[1584] The payment information stored in the device is sent to a server via the Internet. The server analyzes the received information, converts it into a household accounting format, and registers it in a household accounting database.

[1585] 3. Artificial Intelligence Analysis Methods

[1586] The household accounting data registered on the server is input into an AI engine, an artificial intelligence (AI) engine. The AI ​​engine analyzes the user's purchase history and spending frequency, and learns the user's preferences. This makes it possible to generate money-saving advice based on the user's spending patterns.

[1587] 4. Means of generating saving advice

[1588] Based on the results of the analysis, the AI ​​engine generates specific money-saving advice. For example, if monthly convenience store spending is high, advice suggesting bulk purchases will be generated. This advice is sent from the server to the user's device and displayed.

[1589] 5. Location information acquisition means

[1590] The device periodically obtains the user's current location using location information services and sends this information to the server, which then uses the location information to search for special offers at nearby stores and facilities.

[1591] 6. Special Offer Information and Push Notification Methods

[1592] The server filters the special offer information based on the acquired location information and purchasing trends and sends it to the user's device via push notification, allowing the user to receive real-time information on special offers from nearby stores and facilities.

[1593] Specific examples

[1594] 1. When a user makes a 500 yen payment at a convenience store, the payment information is sent to the smartphone.

[1595] 2. The smartphone sends the payment information to the server.

[1596] 3. The server analyzes the payment information and records it in the household account book.

[1597] 4. The AI ​​engine analyzes the user's spending patterns based on the new household accounting data.

[1598] 5. The system generates a saving advice such as "Since your monthly convenience store spending is high, we suggest you buy in bulk" and notifies the user.

[1599] 6. The smartphone periodically obtains location information and sends it to the server.

[1600] 7. The server filters special offers from nearby stores and sends push notifications to the user, such as "Rice is on sale today."

[1601] Prompt Sentence Examples

[1602] Parse the following payment information and generate savings advice:

[1603] Store name: Convenience store

[1604] Price: 500 yen

[1605] Date and Time: 2023-10-03T12:00:00

[1606] Analyze your spending patterns and get advice on how to save money.

[1607] Hardware and software used

[1608] Smartphone: Receiving payment information and acquiring location information

[1609] Server: Receives and analyzes data

[1610] Database: Payment information, household accounting data storage

[1611] AI engine: Data analysis, generating savings advice

[1612] Push notification system: Providing information to users

[1613] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1614] Step 1:

[1615] Collection of payment information

[1616] When a user makes a payment using an electronic payment method at a store such as a convenience store, a payment completion notification is sent to the terminal (smartphone).

[1617] Input: Payment completion notice (payment amount, store name, date and time, etc.)

[1618] Processing: The terminal receives this notification information.

[1619] Output: Payment information temporarily stored in the device's internal database

[1620] Step 2:

[1621] Household accounting registration method

[1622] The payment information stored in the terminal is transmitted to a server via the Internet.

[1623] Input: Payment information from the device's internal database

[1624] Process: Send payment information to the server as an HTTP request

[1625] Output: Payment information received by the server

[1626] Step 3:

[1627] Conversion to household accounting data

[1628] The server analyzes the received payment information, converts it into a household accounting format, and registers it in a household accounting database.

[1629] Input: Received payment information

[1630] Processing: Analyze the data and convert it into a household accounting format

[1631] Output: Household accounting data stored in the household accounting database

[1632] Step 4:

[1633] Artificial Intelligence Analysis Methods

[1634] Household accounting data is input into an artificial intelligence (AI) engine to analyze users' spending patterns and preferences.

[1635] Input: Data from the household accounting database

[1636] Processing: AI engine analyzes data and learns spending patterns and preferences

[1637] Output: Analysis results (user spending patterns, preferences, etc.)

[1638] Step 5:

[1639] Savings advice generation method

[1640] Based on the analysis results of the AI ​​engine, saving advice is generated and sent from the server to the user's device.

[1641] Input: AI analysis results

[1642] Processing: Generate specific savings advice based on the analysis results

[1643] Output: Saving advice sent to the user's device

[1644] Step 6:

[1645] Location information acquisition means

[1646] The device periodically acquires the user's location information and sends it to the server.

[1647] Input: Device location data

[1648] Processing: The device obtains the current location using location services.

[1649] Output: Location information sent to the server

[1650] Step 7:

[1651] Special offer information and push notification methods

[1652] The server searches for nearby special offers based on the acquired location information and purchasing trends and sends a push notification to the user's device.

[1653] Input: Location information, purchasing trend data

[1654] Process: Search the database and filter the deals

[1655] Output: A push notification of the special offer sent to the user's device

[1656] 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.

[1657] As an embodiment of the present invention, a system configured as follows is provided.

[1658] System Configuration

[1659] The system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function to provide information on special offers at nearby stores and facilities.

[1660] 1. Collection of payment information

[1661] Terminal

[1662] When a user completes payment for goods or services using a smartphone payment app (e.g., a common electronic payment method), a payment completion notification is sent to the terminal.

[1663] The terminal receives the notification and obtains payment information (e.g., purchase details, amount, date and time, store name, etc.).

[1664] The acquired payment information is temporarily stored in a database within the terminal.

[1665] 2. Data household ledger registration

[1666] Terminal

[1667] The payment information stored in the terminal is sent to the server.

[1668] server

[1669] The server analyzes the received payment information and converts it into household accounting data format.

[1670] The analyzed information is registered in the household accounting app's database.

[1671] 3. Acquiring Emotion Data

[1672] Terminal

[1673] Activate the emotion engine to recognize the user's emotions.

[1674] The emotion engine uses sensors such as a camera and microphone to obtain emotional data from the user's facial expressions, tone of voice, gestures, etc.

[1675] The acquired emotion data is stored in a database within the device and sent to a server.

[1676] 4. Analysis by AI and emotion engine

[1677] server

[1678] The server inputs the received household accounting data and emotion data into the AI ​​engine.

[1679] The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[1680] The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[1681] 5. Generating Savings Advice

[1682] server

[1683] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine.

[1684] Based on the analysis results, the system generates specific advice for saving energy depending on the user's emotional state, such as suggestions to reduce stress when stress levels are high and strong suggestions when users are relaxed.

[1685] The generated advice is sent to the user's terminal.

[1686] 6. Utilizing location information

[1687] Terminal

[1688] The terminal periodically acquires the user's location information.

[1689] Send location information to the server.

[1690] 7. Offering special offers

[1691] server

[1692] The server processes the location information received from the user and searches a database of nearby stores and facilities.

[1693] Special offers are extracted from search results and filtered based on the user's location and purchasing habits.

[1694] The filtered special offers are sent to the user's device via push notification.

[1695] Specific examples

[1696] Execution scenario

[1697] 1. A user purchases a 500 yen item at a convenience store using a common electronic payment method.

[1698] 2. The terminal receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired.

[1699] 3. The terminal sends this payment information to the server.

[1700] 4. The server analyzes the payment information received and converts it into household accounting data format as "500 yen spent at convenience store."

[1701] 5. The server registers the analyzed household accounting data in the household accounting app database.

[1702] 6. The device activates an emotion engine to recognize the user's emotions.

[1703] 7. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to obtain emotion data, such as "satisfied."

[1704] 8. The device sends the acquired emotion data to the server.

[1705] 9. The server's AI engine processes the household accounting data and emotional data to learn the user's spending patterns (e.g., "visiting convenience stores 15 times a month") and emotional tendencies.

[1706] 10. Based on this spending pattern, the server generates money-saving advice such as, "Since your monthly convenience store spending is high, we suggest bulk purchases." If the user is feeling stressed, the server adds relaxation suggestions such as, "Enjoy shopping within your budget."

[1707] 11. The server sends this advice to the user's device.

[1708] 12. The device periodically obtains the user's location information and sends it to the server.

[1709] 13. The server obtains the location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[1710] The system allows users to efficiently manage their spending, receive emotionally-driven savings advice, and utilizes location and emotional data to make purchasing more comfortable and effective.

[1711] The processing flow will be explained below.

[1712] Step 1:

[1713] Users pay for goods and services using a standard electronic payment method, and once payment is complete, a payment completion notification is sent to the terminal.

[1714] Step 2:

[1715] The terminal receives the payment completion notification and acquires payment information (purchase details, amount, date and time, store name, etc.) The acquired payment information is temporarily stored in the terminal's internal database.

[1716] Step 3:

[1717] The terminal sends the temporarily saved payment information to the server. The data sent includes information such as the purchase details, amount, date and time, and store name.

[1718] Step 4:

[1719] The server analyzes the payment information received from the device, converts the analyzed information into a household accounting data format, and registers it in the household accounting app database.

[1720] Step 5:

[1721] The device activates an emotion engine to recognize the user's emotions. The emotion engine uses sensors such as a camera and microphone to acquire emotion data from the user's facial expressions, tone of voice, gestures, etc.

[1722] Step 6:

[1723] The device temporarily stores the acquired emotional data and transmits it to the server. The emotional data includes emotional states such as "satisfaction" and "stress."

[1724] Step 7:

[1725] The server inputs household accounting data and emotional data into the AI ​​engine, which analyzes the user's purchase history, spending frequency, time of day, etc. to learn about the user's hobbies and preferences.

[1726] Step 8:

[1727] The server combines the data analysis results of the emotion engine with the learning results of the AI ​​engine to further analyze the user's spending patterns. For example, if the user is feeling stressed, it will emphasize relaxation suggestions.

[1728] Step 9:

[1729] The server generates specific advice for saving money based on the user's emotions and spending patterns. For example, "Since you spend a lot at convenience stores this month, we suggest you buy in bulk," and the advice is adjusted according to the user's emotional state.

[1730] Step 10:

[1731] The server sends the generated saving advice to the user's terminal, which displays the advice in the form of a notification.

[1732] Step 11:

[1733] The device periodically acquires the user's location information and sends it to the server.

[1734] Step 12:

[1735] The server processes the location information received from the user and searches a database of nearby stores and establishments, extracting special offers from the search results and filtering them based on the user's current location and purchasing habits.

[1736] Step 13:

[1737] The server sends filtered special offer information to the user's device via push notification. By checking the notified special offer information, the user can put into practice practical savings.

[1738] Example 2

[1739] 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."

[1740] Conventional household management systems simply record spending, but lack the ability to consider users' emotional state and provide specific savings advice. This makes it difficult for users to understand their spending patterns and find rational ways to save money. Furthermore, systems that utilize users' location information to provide relevant special offers are also lacking.

[1741] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, means for recognizing a user's emotions, means for analyzing the recognized emotional data to evaluate the user's psychological state, artificial intelligence means for analyzing the household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and psychological evaluation, means for acquiring the user's location information, and means for providing special offer information for nearby stores and facilities based on the acquired location information. This enables the user to efficiently manage their spending and receive appropriate saving advice based on their emotional state. Furthermore, providing special offer information using location information can make the user's purchasing activities more comfortable and effective.

[1742] "Payment Instrument" means an electronic instrument used by a User to pay for goods and services.

[1743] "Payment information" is data related to payments made by users, and includes information such as the purchase details, amount, date and time, and store name.

[1744] A "household account book" refers to a system or application for recording and managing a user's income and expenses.

[1745] "Artificial intelligence means" refers to machine learning algorithms and models used to analyze data and learn user preferences.

[1746] An "emotion engine" refers to a program or system that uses sensors such as cameras and microphones to acquire and analyze a user's emotional data.

[1747] "Location information" is data indicating the user's current location, and is obtained using technology such as GPS.

[1748] "Special Offer Information" refers to information about discounts and special offers offered by stores and facilities.

[1749] "Savings Advice" refers to specific suggestions or advice for reducing a user's spending.

[1750] "Database" refers to a system for systematically storing information and making it quickly searchable and accessible.

[1751] "Notification" refers to messages or alerts that inform users of important information.

[1752] "Analysis" refers to the process of examining data in detail to find useful information and patterns in it.

[1753] "Purchasing trends" refers to a user's behavioral patterns and preferences when purchasing products or services.

[1754] "Push notification" refers to a means for sending information to users in real time.

[1755] As an embodiment of the present invention, we provide a system configured as follows: This system includes a payment information collection function linked to payment methods, a household account book registration function, a data analysis function using artificial intelligence, an emotion engine function, a money saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[1756] Collection of payment information

[1757] Terminal

[1758] When a user pays for a product or service using a smartphone payment app, a payment completion notification is sent to the terminal. The terminal receives this notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the terminal's internal database. For example, if a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed," and this information is stored in the database.

[1759] Data household ledger registration

[1760] Terminal

[1761] The terminal transmits the payment information stored in the internal database to the server.

[1762] server

[1763] The server analyzes the received payment information and converts it into household accounting data format. The analysis results are then registered in the household accounting app's database. For example, data such as "500 yen spent at a convenience store" can be converted into a format such as "Expense: convenience store, Amount: 500 yen, Date / Time: today" and saved in the household accounting database.

[1764] Acquiring emotion data

[1765] Terminal

[1766] The device activates the emotion engine and uses sensors such as a camera and microphone to acquire the user's emotional data. The acquired emotional data is stored in an internal database and sent to a server. For example, the device's camera and microphone may analyze the user's facial expressions and tone of voice, acquiring data indicating that the user is satisfied and sending it to the server.

[1767] AI and emotion engine analysis

[1768] server

[1769] The server inputs the received household accounting data and emotional data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotional engine also analyzes the emotional data to evaluate the user's psychological state. For example, based on data such as "spent 500 yen at a convenience store" and "user is satisfied," the server learns the tendency that "users visit convenience stores 15 times a month and are satisfied after each visit."

[1770] Generating Savings Advice

[1771] server

[1772] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific saving advice according to the user's emotional state. It also sends this advice to the user's device. For example, advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" is generated and sent from the server to the device.

[1773] Utilizing location information

[1774] Terminal

[1775] The device periodically acquires the user's location information and sends it to the server. When the user goes out, the device's GPS function acquires the location information and periodically sends it to the server.

[1776] Providing special offers

[1777] server

[1778] The server processes the location information received from the user and searches a database of nearby stores and facilities. Special offer information is extracted from the search results and filtered based on the user's current location and purchasing habits. The filtered special offer information is sent to the user's device via push notification. For example, information such as "Rice is on sale today" is extracted, filtered based on the user's purchasing habits, and a push notification is sent to the device.

[1779] Examples of prompt statements

[1780] Here are some example prompts to input to a generative AI model:

[1781] "I completed a 500 yen payment using an electronic payment method. Create household accounting data based on this payment, obtain emotional data, and generate savings advice."

[1782] By inputting this prompt, the AI ​​model is expected to perform actions according to the above processing steps.

[1783] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1784] Step 1:

[1785] Input: The user makes a payment using an electronic payment method.

[1786] Processing: The terminal receives a payment completion notification from the payment app and extracts payment information (purchase details, amount, date and time, store name, etc.) from the notification.

[1787] Output: Payment information is temporarily saved in the terminal's internal database.

[1788] Specific operation: When a user purchases a 500 yen item at a convenience store, the terminal receives a notification that "500 yen payment has been completed." The terminal receives this notification and saves the payment information ("500 yen spent at convenience store") in the database.

[1789] Step 2:

[1790] Input: Payment information stored in the device's internal database.

[1791] Processing: The terminal sends the saved payment information to the server.

[1792] Output: Payment information is sent to the server.

[1793] Specific operation: The device sends data such as "500 yen spent at a convenience store" to the server.

[1794] Step 3:

[1795] Input: Payment information received by the server.

[1796] Processing: The server analyzes the payment information and converts it into household accounting data format.

[1797] Output: The analyzed household accounting data is registered in the household accounting app database.

[1798] Specific operation: The server receives data such as "500 yen spent at a convenience store," converts it into a format such as "Expense: convenience store, amount: 500 yen, date and time: today," and saves it in the household accounting database.

[1799] Step 4:

[1800] Input: The user picks up the device.

[1801] Processing: The device launches the emotion engine and acquires the user's emotion data using sensors such as the camera and microphone.

[1802] Output: The acquired emotion data is stored in a database within the device and sent to the server.

[1803] Specific operation: The device's camera and microphone analyze the user's facial expressions and tone of voice, obtain data indicating that the user is satisfied, and send this data to the server.

[1804] Step 5:

[1805] Input: Household accounting data and emotion data received by the server.

[1806] Processing: The server inputs household accounting data and emotional data into the AI ​​engine, processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences.

[1807] Output: The AI ​​engine generates the learning results.

[1808] Specific operation: Based on the data "500 yen spent at a convenience store" and "user satisfaction," the server learns the tendency that "users use convenience stores 15 times a month and are satisfied after using them."

[1809] Step 6:

[1810] Input: AI engine learning results and emotion engine evaluation results.

[1811] Processing: Based on the analysis results, the server generates specific saving advice according to the user's emotional state and sends it to the user's device.

[1812] Output: The generated advice is sent to the user's terminal.

[1813] Specific operation: The server generates advice such as "Suggest bulk purchases" or "Enjoy shopping within your budget" and sends it to the device.

[1814] Step 7:

[1815] Input: User goes out.

[1816] Processing: The device periodically acquires the user's location information and sends it to the server.

[1817] Output: The obtained location information is sent to the server.

[1818] Specific operation: The device's GPS function acquires location information and periodically sends it to the server.

[1819] Step 8:

[1820] Input: The location information received by the server.

[1821] Processing: Based on the location information, the server searches a database of nearby stores and facilities, extracting and filtering special offers.

[1822] Output: The filtered special offers are pushed to the user's device.

[1823] Specific operation: The server extracts information such as "Rice is on sale today," filters it according to the user's purchasing habits, and sends a push notification to the device.

[1824] (Application example 2)

[1825] 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."

[1826] The present invention aims to provide a system that allows users to effectively reduce their spending by linking their payment information and emotional data to manage spending and providing appropriate money-saving advice and information on special offers at nearby stores based on the user's purchasing behavior and emotional state. However, while current systems collect payment information, they are limited in providing advice that takes the user's emotional state into account and information on special offers that utilize location information. Therefore, a system is needed that takes the user's emotional state and location information into account and provides personalized advice on reducing spending and information on special offers based on purchasing behavior.

[1827] 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 collecting payment information in conjunction with a payment means, means for automatically registering the collected payment information in a household account book, artificial intelligence means for analyzing the registered household account book data and emotional data to learn the user's hobbies and preferences, means for generating saving advice based on the analysis results and the user's emotional state, means for acquiring the user's location information, and means for providing information on special offers at nearby stores and facilities based on the acquired location information and purchasing habits. This allows the user to receive optimal saving advice tailored to their emotional state and current location, and information on special offers at nearby stores is also provided in real time, allowing them to effectively reduce their spending.

[1828] A "Payment Instrument" is an electronic payment method used by a User to purchase goods or services.

[1829] "Payment information" refers to information related to a user's purchasing activity, such as the purchased item, amount, store name, date and time, etc.

[1830] "Household account book data" is a collection of data that records a user's income and expenses.

[1831] "Artificial intelligence means" refers to a system that has the ability to analyze large amounts of data and learn about the user's hobbies and preferences.

[1832] "Emotion data" is information about the user's emotional state obtained from facial expressions, tone of voice, gestures, and the like.

[1833] "Savings advice" refers to specific proposals and suggestions for reducing a user's spending.

[1834] "Location information" is information indicating the user's current location, and is obtained using technology such as GPS.

[1835] "Special Offer Information" refers to information about discounts and sales offered at nearby stores and facilities.

[1836] "Push notification" refers to a technology that sends information from an application to a user's device in real time.

[1837] "Purchase trends" refers to trends derived based on a user's past purchase history and spending patterns.

[1838] System Configuration

[1839] A system for implementing this invention is configured as follows: The system includes a payment information collection function linked to a payment method, a household account book registration function, an artificial intelligence means and emotion engine function, a saving advice generation function, a location information acquisition function, and a function for providing information on special offers at nearby stores and facilities.

[1840] 1. Collection of payment information

[1841] Terminal

[1842] When a user completes payment for a product or service using a smartphone payment app, a payment completion notification is sent to the user's device. The device receives the notification, acquires payment information (purchase details, amount, date and time, store name, etc.), and temporarily stores it in the device's internal database.

[1843] 2. Data household ledger registration

[1844] Terminal

[1845] The payment information stored in the terminal is sent to the server.

[1846] server

[1847] The server analyzes the received payment information, converts it into household accounting data format, and registers the analyzed information in the household accounting app database.

[1848] 3. Acquiring Emotion Data

[1849] Terminal

[1850] The device's built-in emotion engine is activated, and emotion data is acquired from the user's facial expressions, tone of voice, gestures, etc. using sensors such as a camera and microphone. The acquired emotion data is stored in a database within the device and sent to a server.

[1851] 4. Analysis by AI and emotion engine

[1852] server

[1853] The server inputs the received household accounting data and emotion data into the AI ​​engine. The AI ​​engine processes data such as the user's purchase history, spending frequency, and time of day, and learns the user's hobbies and preferences. The emotion engine analyzes the emotion data and evaluates the user's psychological state.

[1854] 5. Generating Savings Advice

[1855] server

[1856] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates specific advice for saving money according to the user's emotional state. The generated advice is then sent to the user's device.

[1857] 6. Utilizing location information

[1858] Terminal

[1859] The device periodically acquires the user's location information and sends it to the server.

[1860] 7. Offering special offers

[1861] server

[1862] The server processes the location information received from the user and searches a database of nearby stores and facilities. It extracts special offers from the search results and filters them based on the user's current location and purchasing habits. It then sends the filtered special offers to the user's device via push notification.

[1863] Hardware and Software

[1864] Hardware: Smartphone, camera, microphone, GPS module

[1865] Software: Payment app, household accounting app, artificial intelligence engine, emotion engine, location information acquisition module, special offer information module

[1866] Specific examples

[1867] Execution scenario

[1868] A user purchases a 500 yen item at a convenience store using a common electronic payment method. The device receives a payment completion notification and acquires payment information. For example, "Payment of 500 yen at convenience store" is acquired. The device sends this payment information to the server. The server analyzes the received payment information and converts it into household accounting data format as "Expenses of 500 yen at convenience store." The server registers the analyzed household accounting data in the household accounting app's database. The device activates an emotion engine to recognize the user's emotions. The emotion engine uses a camera and microphone to analyze the user's facial expressions and tone of voice and acquires emotional data. An example would be "satisfied." The device then sends the acquired emotional data to the server. The server's AI engine processes the household accounting data and emotional data and learns the user's spending patterns and emotional tendencies. Based on this spending pattern, the server generates money-saving advice such as "Since your monthly convenience store spending is high, we suggest buying in bulk." If the user is feeling stressed, it adds relaxation suggestions such as "Enjoy shopping within your budget." The server then sends this advice to the user's device. The device periodically acquires the user's location information and sends it to the server. The server obtains location information, searches a database of nearby stores, extracts information such as "Rice is on sale today," and sends a push notification to the user's device.

[1869] Prompt Sentence Examples

[1870] "Please create a program that automatically collects payment information, such as the amount of money the user spends at a convenience store, the name of the store, and the date and time. Also, please give it the ability to analyze the user's emotional data using a camera and microphone and generate money-saving advice based on that. Finally, please use location information to provide the user with information about special offers at nearby stores."

[1871] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1872] Step 1:

[1873] A user purchases a product or service using a smartphone payment app. The terminal receives a payment completion notification and acquires payment information such as the purchase details, amount, purchase date and time, and store name. The acquired payment information is then temporarily stored in the terminal's database. The input is the payment information, and the output is the payment information stored in the terminal's database.

[1874] Step 2:

[1875] The device sends the temporarily saved payment information to the server. The server analyzes the received payment information and converts it into household accounting data format. The converted household accounting data is then registered in the household accounting app's database. The input is the payment information sent to the server, and the output is the information registered in the household accounting database.

[1876] Step 3:

[1877] The device starts the emotion engine and uses the camera and microphone to capture the user's facial expressions, tone of voice, gestures, etc. to obtain emotional data. The obtained emotional data is temporarily stored in the device's database and sent to the server. The input is emotional data based on the user's facial expressions and tone of voice, and the output is the emotional data sent to the server.

[1878] Step 4:

[1879] The server receives household accounting data and emotion data and inputs it into the AI ​​engine. The AI ​​engine processes the received data and learns the user's hobbies and preferences from their purchasing history, spending frequency, time of day, etc. Meanwhile, the emotion engine analyzes the emotion data and evaluates the user's psychological state. The inputs are household accounting data and emotion data, and the output is the user's hobbies and preferences and the results of the psychological state evaluation.

[1880] Step 5:

[1881] The server further analyzes the user's spending patterns based on the learning results of the AI ​​engine and the evaluation results of the emotion engine. Based on the analysis results, it generates saving advice according to the user's emotional state and sends that advice to the user's device. The input is the output of the AI ​​engine and emotion engine, and the output is the saving advice sent to the user's device.

[1882] Step 6:

[1883] The device periodically obtains the user's location information and sends it to the server. The server processes the received location information, searches a database of nearby stores and facilities, and extracts special offer information. The special offer information is filtered based on the user's current location and purchasing habits, and is then pushed to the user's device. The input is the location information sent from the device, and the output is the special offer information pushed to the user's device.

[1884] 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.

[1885] 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.

[1886] 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.

[1887] 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.

[1888] 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.

[1889] 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.

[1890] 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).

[1891] 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.

[1892] 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."

[1893] 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.

[1894] 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).

[1895] 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.

[1896] 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.

[1897] 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.

[1898] 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.

[1899] 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.

[1900] 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.

[1901] 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.

[1902] 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.

[1903] 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.

[1904] 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.

[1905] The following is further disclosed regarding the above embodiment.

[1906] (Claim 1)

[1907] A means for collecting payment information in conjunction with the payment method;

[1908] A means for automatically registering collected payment information in a household account book;

[1909] an artificial intelligence means for analyzing the registered household accounting data and learning the user's hobbies and preferences;

[1910] means for generating saving advice based on the analysis results;

[1911] A means for acquiring user location information; ...

Claims

1. A means for collecting payment information in conjunction with the payment method; A means for automatically registering collected payment information in a household account book; an artificial intelligence means for analyzing the registered household accounting data and learning the user's hobbies and preferences; means for generating saving advice based on the analysis results; A means for acquiring user location information; A means of providing special offers from nearby stores and facilities based on acquired location information A system including:

2. The system of claim 1 further comprising means for notifying the user of special offers based on location information.

3. 10. The system of claim 1, further comprising means for the artificial intelligence means to analyze the user's spending patterns and generate specific suggestions for reducing spending.

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