system

Abstract

We provide the system. [Solution] A means for analyzing reservation information received online and extracting relevant expense data from that information, A means of classifying extracted expense data and monitoring that data based on a set budget, A means of notifying users when signs of budget overruns are detected, A method to automatically calculate the total amount to be paid within the group after the trip and automate the remittance process, A means of collecting and analyzing traveler spending data and making promotional proposals to businesses or local governments, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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 Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 Managing expenses during a trip is a burden for travelers. Especially in the case of group trips, the necessary settlement processes are often complicated. Also, budget management is difficult, which causes wasteful expenses during the trip. Furthermore, there is a lack of a method for efficiently collecting and analyzing travelers' spending tendencies, so there is a problem that it is difficult for businesses and local governments to formulate appropriate promotion strategies. 【Means for Solving the Problems】 【0005】 This invention provides a system that analyzes online booking information and receipts during travel to extract expense data, classify and monitor it, and enable travelers to detect signs of budget overruns in real time. Furthermore, it streamlines settlement by automatically calculating the total amount to be paid within a group after the trip and processing the payment. It also provides a means of aggregating traveler spending data and making effective promotional proposals to businesses and local governments. 【0006】 "Online booking information" refers to detailed information about travel and accommodation reservations obtained via the internet. 【0007】 "Expense data" refers to detailed information about the expenses incurred by travelers during their trip, including amounts, dates, and purposes. 【0008】 Optical character recognition (OCR) is a technology that extracts character information from image data, and recognizes the contents of scanned documents and receipts as electronic data. 【0009】 "Signs of budget overrun" are indicators that show actual spending is exceeding the set budget, or that there is a high probability of this happening. 【0010】 "Money transfer processing" refers to the procedure for electronically moving money to a specific recipient. 【0011】 "Settlement amount" refers to the total amount each participant is responsible for paying in a group trip. 【0012】 A "promotion proposal" is a strategic recommendation made to businesses or local governments to encourage specific consumer behaviors. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【MODE FOR CARRYING OUT THE INVENTION】 【0014】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0019】 In the following embodiments, a labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc. 【0020】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0024】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0025】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0026】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0027】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0028】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30. 【0031】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0032】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0033】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0034】 One embodiment of the present invention is a system that links a traveler's device with a server located in the cloud. In this system, online reservation information and receipt images received in the traveler's email account are automatically retrieved by the server. The retrieved information is analyzed on the server using natural language processing and optical character recognition technology, and expense data such as reservation number, hotel name, date, and amount are extracted. 【0035】 The extracted expense data is sent from the server to the terminal, where a dedicated application on the terminal automatically categorizes it based on the user's itinerary. For example, hotel accommodation costs are categorized under "Accommodation," and transportation costs are categorized under "Travel." 【0036】 Users can set a budget for each category within the app before traveling. The server monitors spending in real time based on this budget information and pushes a warning message to the app on the user's device if spending approaches or exceeds the set budget. 【0037】 After the trip ends, the terminal automatically calculates the settlement amount with other participants in the group using all of the traveler's expense data stored on the server. Based on the calculation result, the user can select PayPay, bank transfer, or other electronic payment methods and send the predetermined amount to the other travelers. 【0038】 Furthermore, the server aggregates and analyzes the spending behavior of all travelers and generates effective promotional proposals for businesses and local governments based on regional consumption trends. These proposals provide businesses with a clear direction for targeting strategies to promote regional revitalization. 【0039】 This invention significantly reduces the burden of managing expenses during travel, allowing users to enjoy their trips with peace of mind, while enabling businesses and local governments to develop marketing strategies based on collected data. This system simplifies financial management during travel and provides significant value to both travelers and local communities. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 The server accesses the user's email account to verify newly arrived online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0043】 Step 2: 【0044】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. The extracted data includes information such as reservation number, date, and amount. 【0045】 Step 3: 【0046】 The server analyzes the text data extracted using natural language processing and organizes and stores the necessary expense data as structured data. 【0047】 Step 4: 【0048】 The terminal receives structured expense data from the server and displays it in a dedicated application. Here, each expense is automatically categorized based on the user's itinerary. 【0049】 Step 5: 【0050】 Users can set a budget within the application. The set budget information is sent to the server and registered in the database. 【0051】 Step 6: 【0052】 The server monitors expense data received in real time based on budget registration information and detects signs of exceeding the set budget. If an overrun is anticipated, a warning message is pushed to the user's device. 【0053】 Step 7: 【0054】 After the trip ends, the terminal automatically calculates the settlement amount for each group participant using all expense data stored on the server. 【0055】 Step 8: 【0056】 Based on the calculated settlement amount, the user selects an electronic payment system through the application and completes the transfer to the other traveler. 【0057】 Step 9: 【0058】 The server aggregates spending data collected from travelers and analyzes their spending trends. Based on this analysis, it generates promotional proposals for businesses and local governments and provides them as reports. 【0059】 (Example 1) 【0060】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0061】 In modern travel, travelers are burdened with the need to manage various booking and spending data. Furthermore, efficiently managing budgets and settling group expenses during trips is difficult, often resulting in traveler stress. Additionally, there is a lack of mechanisms to accurately understand the impact of spending on local areas and provide useful information to businesses and public institutions. 【0062】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0063】 In this invention, the server includes means for acquiring information from the user's communication device, analyzing the information, and extracting relevant expense data; means for classifying the data transmitted via the communication device and monitoring the data in real time based on the user's set budget; and means for notifying the user's communication device when an overspending of the budget is expected. This enables travelers to efficiently manage their spending, and allows businesses and public institutions to develop strategies based on consumer behavior patterns. 【0064】 "User's communication device" refers to a device such as a mobile phone, tablet, or computer that a traveler uses to manage and verify their own information. 【0065】 "Acquiring and analyzing information" refers to the act of automatically collecting reservation information and receipts from electronic data such as emails and images, and then analyzing that data to extract necessary expense information. 【0066】 "Extracting expense data" is the process of identifying and organizing specific expenditure details such as date, amount, and category from the acquired information. 【0067】 "Monitoring data based on budget" is a process that tracks spending limits for each category set by the user in real time, and helps with budget management. 【0068】 "Means of notification" refers to messaging functions used to inform users of the possibility of budget overruns, and typically utilizes push notifications or email. 【0069】 "Automatically calculating and processing settlements" refers to providing a procedure that simplifies payment by calculating each person's share of expenses based on all expenses incurred within the group after the trip has ended. 【0070】 "Collecting and analyzing spending patterns" is the process of aggregating data such as purchase history during travel, identifying trends and patterns, and generating strategic information based on that. 【0071】 This invention provides a system that enables travelers to efficiently manage their expenses during their trip and stay within their budget. The system functions by linking the user's communication device with a server located in the cloud. 【0072】 The server connects to email accounts registered on the user's communication device and automatically retrieves reservation information and receipt images. This utilizes email service APIs (e.g., email provider APIs). From the retrieved data, the server uses natural language processing tools (e.g., natural language processing toolkits) and optical character recognition technology (e.g., character recognition services) to extract data related to expenses. This allows for the efficient collection of information such as reservation numbers, hotel names, dates, and amounts. 【0073】 Next, the server stores this extracted data in the cloud and, if necessary, transmits it to the user's communication device using encrypted communication. The communication device has a dedicated application installed that displays and categorizes the data based on the user's itinerary. The application can categorize expenses according to categories such as "accommodation" and "transportation." 【0074】 Before traveling, users can use this application to set a travel budget for each category. The server monitors spending in real time based on this budget information and sends push notifications as the user approaches the budget. 【0075】 Furthermore, the server aggregates and analyzes spending data from all travelers and automatically generates promotional proposals for businesses or public institutions based on local consumption trends. These proposals enable businesses to receive targeted strategies aimed at revitalizing their local areas. 【0076】 As a concrete example, consider a traveler planning a trip to a certain country and managing various expenses (accommodation, transportation, etc.) during the trip. By using this system, they can prevent exceeding their budget and enjoy their trip with peace of mind. An example of a prompt would be, "Suggest ways to help with travel budget management. In particular, focus on ways to streamline the management of accommodation and transportation expenses during the trip." 【0077】 This system not only reduces the burden on users but also brings data-driven value to the local economy. 【0078】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0079】 Step 1: 【0080】 The user sets up an email account on their communication device (smartphone or computer). The configured account information is sent to the server. This allows the server to obtain authentication information to access the user's email data. 【0081】 Step 2: 【0082】 The server uses the acquired authentication information to connect to the email service API and check for new emails. It filters the emails to find those containing keywords related to reservations or expenses (e.g., "reservation confirmation" or "receipt"). The detected emails and their attachments are selected for the next processing. 【0083】 Step 3: 【0084】 The server applies natural language processing tools and optical character recognition (OCR) technology to the selected emails and attachments. The input data is analyzed, and relevant data such as amounts, dates, and reservation numbers are extracted. This generates structured expense data. 【0085】 Step 4: 【0086】 The server stores the extracted data in a cloud database. The stored data is protected from unauthorized access using encryption technology, thus ensuring user privacy. 【0087】 Step 5: 【0088】 The server transmits data stored in the cloud to the user's communication device using a secure communication method. A dedicated application on the user's communication device receives the data and prepares it for visualization and organization. 【0089】 Step 6: 【0090】 The terminal categorizes the received data within the application. The input is data received from the server, and the output is information organized by categories such as "accommodation" and "meals." This categorization makes it easy for users to visually review their expenses. 【0091】 Step 7: 【0092】 Users set budgets for each category using the application. This allows the server to monitor spending in real time. 【0093】 Step 8: 【0094】 The server sends an alert notification to the communication device when a user's spending approaches their set budget. This allows the user to review their spending and plan to stay within their budget. 【0095】 Step 9: 【0096】 After the trip ends, the terminal automatically settles accounts among the group using all expense data stored on the server. Based on the entered data, the settlement calculation is performed, and the output shows each user's share of the expenses. 【0097】 Step 10: 【0098】 The server aggregates and analyzes spending data from all users. Based on the results, it generates and outputs promotional proposals for companies and local governments. This enables effective marketing that takes into account local consumer behavior. 【0099】 (Application Example 1) 【0100】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0101】 There is a problem in that travelers have difficulty effectively managing and settling their expenses during and after their trips. Furthermore, there is the challenge of the considerable effort and time required to accurately understand local consumption trends and use that information for targeted marketing. 【0102】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0103】 This invention includes a server that includes means for analyzing reservation information received online and extracting relevant expense data from that information; means for classifying the extracted expense data and monitoring the data based on a set budget; means for notifying the user when signs of budget overrun are detected; means for automatically calculating the settlement amount within the group after the trip and automating the remittance process; means for aggregating and analyzing travelers' spending data and making promotional proposals to businesses or local governments; means for facilitating smooth payments using electronic payment methods based on consumption trend data; and means for automatically analyzing spending history and predicting future spending trends before issuing budget overrun warnings. This enables efficient management of spending during travel, streamlining settlement processing, and effective marketing based on local consumption trends. 【0104】 "Reservation information" refers to information issued when using online services such as travel or accommodation, which includes details such as the date, time, location, and price. 【0105】 "Expense data" refers to data related to expenses incurred in connection with travel, and includes information such as hotel accommodation fees and transportation costs. 【0106】 "Classification" is the act of dividing extracted expense data into specific categories, a technique that makes management and analysis easier. 【0107】 "Budget monitoring" is the process of tracking how much actual spending is progressing based on a budget set in advance by the user, in order to prevent budget overruns. 【0108】 "Notification" is the act of informing a user of information, and is often used as a means to provide warnings or confirmations in real time. 【0109】 The "settlement amount" is the value obtained after reviewing the allocation of expenses at the end of the trip and calculating the amount each person in the group should bear. 【0110】 "Money transfer" refers to the process of sending money to another user or service provider, and includes the use of digital payment methods. 【0111】 "Expense data aggregation" refers to the act of compiling all expenses incurred during a trip and organizing them into a series of data. 【0112】 "Promotional proposals" refer to the act of proposing marketing strategies to businesses and local governments based on collected and analyzed data. 【0113】 "Payment methods" is a general term for the methods and means used by users to pay for goods or services, and includes electronic methods. 【0114】 "Consumption history" refers to a record of a user's past spending and is fundamental information for predicting future spending trends. 【0115】 To realize this invention, the system mainly consists of a server and a user terminal. The server is equipped with a program that analyzes reservation information received online and extracts expense data. This program uses Python's natural language processing library (NLTK) and optical character recognition tool (Tesseract OCR) to analyze the necessary data from emails and images. The analyzed data is stored in a database in real time using Firebase. The server analyzes this data, monitors how far spending has progressed based on the user's budget settings, and sends push notifications as needed. 【0116】 On the terminal side, users can input their budget through a dedicated application and monitor expenses in real time based on that budget. This app also has a function to warn users if they are about to exceed their budget and to predict future spending based on their spending history. After the trip is over, the system uses server data to automatically calculate settlements within the group and allows payment to be made using a specific electronic payment method. 【0117】 As a concrete example, when a user checks into a hotel during a trip, the reservation confirmation email is automatically processed on the server, and the accommodation cost is categorized into the "Accommodation" category in the app. The application then runs on the device, displaying real-time warnings before the budget is exceeded. While reviewing the spending data, the user can enter prompts into the app, such as "Which category does this expense fall into?" or "Please tell me my travel spending status for this month," and receive immediate feedback from the system. 【0118】 Through this system, users can easily manage their travel expenses and enjoy peace of mind and efficiency while traveling by seamlessly settling accounts and making payments after their trip. 【0119】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0120】 Step 1: 【0121】 The server receives user reservation information and images from online sources as input. This information includes emails and scanned receipt images. The server uses a natural language processing library (NLTK) and an optical character recognition tool (Tesseract OCR) to output expense data such as reservation number, hotel name, date, and amount in text format. 【0122】 Step 2: 【0123】 The server stores the extracted expense data in a database for classification. This process involves the server accessing a real-time database (Firebase) and organizing the data by category. For example, accommodation expenses are categorized under "accommodation" and stored in the database as data related to that category. 【0124】 Step 3: 【0125】 The server monitors expense data in real time based on budget information entered by the user in advance. The server compares the budget with actual spending, and if an overspending is anticipated, it sends a warning to the device using a push notification function. This makes budget management easy for users. 【0126】 Step 4: 【0127】 The terminal receives all expense data from the server after the trip ends. The user then uses the application to initiate settlement within the group. The terminal aggregates each participant's expenses, calculates the total settlement amount, and displays the result. This allows the user to view detailed data for settlement. 【0128】 Step 5: 【0129】 The user makes an electronic payment based on the result displayed after settlement. The terminal makes the payment to the other user via the selected payment method (e.g., an electronic payment system). In this step, the terminal quickly transfers the required amount and notifies that the payment is complete. 【0130】 Step 6: 【0131】 The server aggregates spending data from all travelers and generates promotional proposals for businesses and local governments. At this stage, the server analyzes consumer trends and creates reports to derive effective marketing strategies. This output is used by businesses and local governments as a guide for regional revitalization. 【0132】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0133】 In embodiments of the present invention, a system is provided that integrates a terminal owned by the traveler, a server located in the cloud, and an emotion engine. This system accesses the user's email account to retrieve newly received online reservation information and receipt images on the server. The retrieved information is analyzed on the server using optical character recognition (OCR) to extract expense data such as reservation number, amount, and date. 【0134】 The server analyzes the extracted expense data using natural language processing and stores it as structured data. This structured data is sent to the terminal, where a dedicated application automatically categorizes the expenses according to the user's itinerary. 【0135】 In the expense management application, users enter their budget for each category before traveling. Based on this, the server monitors the expense data in real time and sends a warning notification to the user's device if it detects a potential budget overrun. 【0136】 This notification is optimized according to the user's emotional state. The emotion engine analyzes the user's voice input and past behavioral data to estimate their emotional state. For example, if the user is in a relaxed emotional state, the notification message can be composed in a calm tone. 【0137】 After the trip ends, the device uses expense data stored on the server to automatically calculate the settlement amount within the group and presents payment methods. Users can utilize this function to easily complete the payment process. 【0138】 Furthermore, the server aggregates and analyzes traveler spending and emotional data to understand consumption trends. This allows for the generation of emotionally-based promotional suggestions for businesses and local governments, enabling the formation of more effective marketing strategies. 【0139】 This invention aims to improve user satisfaction by integrating expense management with an understanding of emotions, thereby providing users with a more personalized travel experience. Furthermore, it aims to contribute to the revitalization of businesses and local governments through promotions that enhance their contribution to the local community. 【0140】 The following describes the processing flow. 【0141】 Step 1: 【0142】 The server accesses the user's email account to verify newly received online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0143】 Step 2: 【0144】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. This text data includes reservation numbers, amounts, dates, and other information. 【0145】 Step 3: 【0146】 The server applies natural language processing to the extracted text data for analysis, organizes the necessary expense data as structured data, and stores it in the database. 【0147】 Step 4: 【0148】 The terminal receives structured expense data from the server and displays it in a dedicated application. This application automatically categorizes each expense based on the user's itinerary. 【0149】 Step 5: 【0150】 Users set budgets for each expenditure category within the application on their device. This budget information is sent to the server and used as a basis for expense monitoring. 【0151】 Step 6: 【0152】 The device provides the user's voice input and behavioral data to the emotion engine. The emotion engine uses this data to estimate the user's emotional state. 【0153】 Step 7: 【0154】 The server monitors expense data in real time based on the set budget and sends a notification to the user's device if it detects a potential budget overrun. The content and tone of this notification are adjusted based on the results of the sentiment engine. 【0155】 Step 8: 【0156】 At the end of the trip, the device retrieves all expense data from the server and automatically calculates the settlement amount for each group participant. Users can easily complete the payment process through the recommended payment method on the device. 【0157】 Step 9: 【0158】 The server aggregates traveler spending and sentiment data to generate promotional suggestions for businesses and local governments. These suggestions take into account consumption trends based on the aggregated sentiment states. 【0159】 (Example 2) 【0160】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0161】 This invention relates to a system for efficiently managing travel expenses, and more particularly to supporting users' budget management in real time and reducing the risk of exceeding the budget. Conventional systems have problems with budget management becoming complicated due to insufficient optimization of expense classification and notifications. In addition, there is a lack of notification systems that take into account the emotional state of travelers, which limits the improvement of the user experience. 【0162】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0163】 In this invention, the server includes means for analyzing received reservation information and extracting relevant cost data, means for classifying the extracted cost data and monitoring the data based on a set budget, and means for analyzing the user's emotional state and optimizing notification content according to that emotion. This makes it possible to streamline user budget management, reduce the risk of exceeding the budget, and provide notifications that are sensitive to the user's emotions. 【0164】 "Received reservation information" refers to electronic data containing reservation details related to travel, which is used to analyze expense data. 【0165】 "Expense data" refers to data containing information about various travel expenses, including elements such as reservation number, amount, and date. 【0166】 A "classification method" is a function for dividing extracted cost data into categories based on specific criteria. 【0167】 "Means of notifying users" refers to a function that sends warnings or information to users when signs of budget overruns are detected. 【0168】 "Means for analyzing emotional state" refers to a function that estimates the user's current emotional state based on their words, actions, and past behavior. 【0169】 "Method for automatically calculating settlement figures" refers to a function that automatically calculates the amount needed to settle expenses between travelers after the trip is completed. 【0170】 "Means of automating the remittance process" refers to a function that allows users to easily complete the remittance process based on the settled amount. 【0171】 "Means for aggregating and analyzing consumption data" refers to a function that collects and analyzes travelers' spending information to reveal consumption trends and behavioral patterns. 【0172】 "Means of proposing promotions" refers to a function that proposes effective sales activities and marketing strategies to businesses and local governments based on aggregated data. 【0173】 This invention provides a system for efficiently managing travel expenses. It mainly consists of a traveler's terminal, a server located in the cloud, and an emotion engine that analyzes the user's emotional state. 【0174】 The server analyzes reservation information and receipt images received by the user via their terminal using optical character recognition software. Specifically, it uses software such as "Tesseract" to extract expense data such as reservation numbers, amounts, and dates from email text and images. This extracted data is then analyzed using natural language processing libraries such as "spaCy" and "NLTK". Based on these analysis results, the server generates structured data and sends it to the terminal. 【0175】 The terminal is operated through a dedicated application that automatically categorizes expenses according to the user's itinerary based on the structured data received. Furthermore, the user can enter a budget for each expense category in this application before the trip. Based on this configured budget information, the server monitors the expense data in real time, and if there are signs of budget overrun, the emotion engine analyzes the user's current emotional state and sends a warning notification in an appropriate tone. 【0176】 When the user is relaxed, notification messages are delivered in a calm tone. Furthermore, once the trip is complete, the device uses expense data stored on the server to automatically calculate the total amount due within the group and presents the appropriate payment procedure. This allows the user to process payments quickly and easily. 【0177】 Furthermore, the server can analyze the collected traveler consumption and sentiment data, and based on the results, it can provide a platform for implementing promotional proposals to businesses and local governments, thereby supporting more effective marketing strategies. 【0178】 As a concrete example, one could collect expense information along with emotional records of shopping experiences a user had during a trip, and then use that data to suggest discount promotions at stores. An example of a prompt to the generating AI model would be, "Organize the expense data for my New York trip and optimize warning notifications about potential budget overruns." This prompt would allow the system to perform detailed processing to improve the user experience. 【0179】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0180】 Step 1: 【0181】 The user receives travel-related booking information via email using their device. Input includes the email content and attachments. The device sends this information to a server in the cloud, filtering the email subject, body, and attachments to identify relevant information. The output is the booking data extracted and sent to the server. 【0182】 Step 2: 【0183】 The server analyzes received email information using optical character recognition (OCR) software. Input includes both email text and images. Specifically, it uses OCR tools such as "Tesseract" to extract text data from emails and images. The output includes expense data such as reservation numbers, amounts, and dates. 【0184】 Step 3: 【0185】 The server analyzes the extracted cost data using natural language processing techniques. The input is raw text data obtained through OCR. Natural language processing libraries such as "spaCy" and "NLTK" are used to structure the data and divide it into semantic categories. The output is structured cost data. 【0186】 Step 4: 【0187】 The server sends the generated structured data to the terminal. The input is structured expense data. This data is transmitted using a secure protocol (e.g., SSL / TLS). The output is the secure transmission of data to the terminal. 【0188】 Step 5: 【0189】 The terminal categorizes the received expense data using a dedicated application. The input is structured expense data. In practice, it automatically categorizes expenses by comparing them with past travel data. The output displays the categorized expense items. 【0190】 Step 6: 【0191】 Before traveling, users enter a budget for each expense category. The input is a numerical budget value. Based on the terminal application, the budget for each category is set. The set budget information is then sent to the server as output. 【0192】 Step 7: 【0193】 The server monitors expense data in real time and, when it detects signs of budget overruns, sends a notification to the device that takes the user's emotional state into account. Inputs include categorized expense data, a set budget, and the user's emotional state. An emotional engine is used to analyze the emotional state and optimize the notification message. The output is an emotionally appropriate warning notification displayed on the device. 【0194】 Step 8: 【0195】 After the trip ends, the terminal automatically calculates the settlement amount for the group using expense data stored on the server. The input is all expense data from the trip. A calculation algorithm is used to determine the payment amount for each user. The settlement results are presented as output. 【0196】 Step 9: 【0197】 The server aggregates and analyzes traveler spending and sentiment data, providing it to businesses and local governments as a basis for promotional proposals. Input includes all expense and sentiment data. Business intelligence tools are used to analyze data patterns. The output is the data analysis results, which are then used in marketing strategies. 【0198】 (Application Example 2) 【0199】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0200】 There are challenges in ensuring that travelers can smoothly manage their expenses during their trips and enjoy their travels with peace of mind within their budget. Furthermore, it is necessary to improve travel satisfaction by providing information tailored to their emotional state in real time during their trips and offering personalized travel experiences. Additionally, there is a need for businesses and local governments to provide appropriate information to implement effective marketing based on travelers' spending trends. 【0201】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0202】 This invention includes a server that analyzes reservation information received online and extracts relevant expense data from that information; a server that classifies the extracted expense data and monitors the data based on a set budget; and a server that provides users with information optimized based on their emotional state. This makes it easier for travelers to manage their spending within their budget and improves their travel satisfaction by receiving information optimized to their individual emotional state. It also enables businesses and local governments to make promotional proposals based on travelers' spending data. 【0203】 "Online reservation information" refers to data related to travel and service reservations that are received by the user's digital device via electronic communication. 【0204】 "Expense data" refers to numerical or textual data containing information about expenses incurred during travel or service use. 【0205】 "Information optimized based on emotional state" refers to content and notifications that are individually tailored to take into account the user's psychological and emotional state. 【0206】 "Monitoring data based on a budget" refers to the process of evaluating and verifying actual spending in real time based on financial limits set by the user in advance. 【0207】 "Input for estimating emotional state" refers to biometric or behavioral information used for emotion estimation, such as user voice and behavioral data. 【0208】 "Making a promotional proposal" refers to the act of proposing sales promotion activities or special offers to target audiences based on predictions and analysis. 【0209】 The system to realize this application is built by integrating a traveler's device, a server located in the cloud, and an emotion engine. The server has a program that processes booking information received online, accessing the traveler's email account to retrieve booking information and receipt images. The retrieved information is analyzed using OCR technology to extract expense data such as booking numbers, amounts, and dates. Optical character recognition tools such as AWS® Textract are used in this process. 【0210】 The extracted expense data is converted into structured data using a Python script on AWS Lambda and stored in DynamoDB. The data is monitored in real time based on the set budget, and notifications are sent to the user via Firebase. The notifications are optimized based on the user's emotional state. Emotion estimation is performed by analyzing the emotional state from voice input and text data using Google Cloud's Speech-to-Text and Azure's Text Analytics. 【0211】 Furthermore, after the trip ends, the system automatically calculates the total amount settled within the group on the terminal and presents the result to the user, enabling quick payment. In addition, the server aggregates and analyzes travelers' spending and sentiment data to generate promotional suggestions for businesses and local governments based on their spending trends. As a result, the user's travel experience becomes more personalized and satisfaction levels increase. 【0212】 For example, if a user uploads photos taken during a trip to the application, relevant tourist information will be provided in real time. Furthermore, a generative AI model will recommend tourist destinations and events that take the user's mood into consideration. An example of a prompt might be, "Please recommend tourist destinations to visit when I am feeling relaxed." 【0213】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0214】 Step 1: 【0215】 The server accesses the user's email account and retrieves newly received reservation information and receipt images. Based on this input data, it saves the reservation information to a database and prepares it for OCR processing. 【0216】 Step 2: 【0217】 The server analyzes the receipt image acquired using OCR technology. During this process, character recognition tools such as AWS Textract are used to extract expense data such as reservation number, amount, and date from the image. This result is output as text data and passed on to the next processing step. 【0218】 Step 3: 【0219】 The terminal processes the text data received from the server using a Python script executed on AWS Lambda, converting it into structured data. This organizes the expense data by category and stores it in DynamoDB. Obtaining structured data makes it easier for users to view expenses for each category. 【0220】 Step 4: 【0221】 The device monitors spending in real time, referencing the user's set budget and structured data stored on the server. If a potential budget overrun is detected, the device sends a notification to the user. This notification is sent using Firebase, allowing the user to instantly understand their spending situation. 【0222】 Step 5: 【0223】 The server analyzes the user's voice input using Google Cloud's Speech-to-Text and estimates their emotional state using Azure's Text Analytics. Based on the estimated emotional data and structured data, an AI model is used to generate notifications optimized for expense management, which are then provided to the user according to the prompt (e.g., "If I want to relax, please recommend a cafe."). 【0224】 Step 6: 【0225】 After the trip ends, the device downloads all expenditure data from the server and automatically calculates the settlement amount within the group. This calculation can be viewed on the user's smartphone, enabling quick remittances. The user can choose the most suitable remittance method from the presented options. 【0226】 Step 7: 【0227】 The server analyzes aggregated spending and sentiment data, and based on this, generates promotional suggestions for businesses and local governments that are tailored to consumer trends. This enables businesses and local governments to develop more effective marketing strategies. 【0228】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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. 【0229】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0230】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0231】 [Second Embodiment] 【0232】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0233】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0234】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0235】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0236】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0237】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0238】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0239】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0240】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0241】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0242】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0243】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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". 【0244】 One embodiment of the present invention is a system that links a traveler's device with a server located in the cloud. In this system, online reservation information and receipt images received in the traveler's email account are automatically retrieved by the server. The retrieved information is analyzed on the server using natural language processing and optical character recognition technology, and expense data such as reservation number, hotel name, date, and amount are extracted. 【0245】 The extracted expense data is sent from the server to the terminal, where a dedicated application on the terminal automatically categorizes it based on the user's itinerary. For example, hotel accommodation costs are categorized under "Accommodation," and transportation costs are categorized under "Travel." 【0246】 Users can set a budget for each category within the app before traveling. The server monitors spending in real time based on this budget information and pushes a warning message to the app on the user's device if spending approaches or exceeds the set budget. 【0247】 After the trip ends, the terminal automatically calculates the settlement amount with other participants in the group using all of the traveler's expense data stored on the server. Based on the calculation result, the user can select PayPay, bank transfer, or other electronic payment methods and send the predetermined amount to the other travelers. 【0248】 Furthermore, the server aggregates and analyzes the spending behavior of all travelers and generates effective promotional proposals for businesses and local governments based on regional consumption trends. These proposals provide businesses with a clear direction for targeting strategies to promote regional revitalization. 【0249】 This invention significantly reduces the burden of managing expenses during travel, allowing users to enjoy their trips with peace of mind, while enabling businesses and local governments to develop marketing strategies based on collected data. This system simplifies financial management during travel and provides significant value to both travelers and local communities. 【0250】 The following describes the processing flow. 【0251】 Step 1: 【0252】 The server accesses the user's email account to verify newly arrived online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0253】 Step 2: 【0254】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. The extracted data includes information such as reservation number, date, and amount. 【0255】 Step 3: 【0256】 The server analyzes the text data extracted using natural language processing and organizes and stores the necessary expense data as structured data. 【0257】 Step 4: 【0258】 The terminal receives structured expense data from the server and displays it in a dedicated application. Here, each expense is automatically categorized based on the user's itinerary. 【0259】 Step 5: 【0260】 Users can set a budget within the application. The set budget information is sent to the server and registered in the database. 【0261】 Step 6: 【0262】 The server monitors expense data received in real time based on budget registration information and detects signs of exceeding the set budget. If an overrun is anticipated, a warning message is pushed to the user's device. 【0263】 Step 7: 【0264】 After the trip ends, the terminal automatically calculates the settlement amount for each group participant using all expense data stored on the server. 【0265】 Step 8: 【0266】 Based on the calculated settlement amount, the user selects an electronic payment system through the application and completes the transfer to the other traveler. 【0267】 Step 9: 【0268】 The server aggregates spending data collected from travelers and analyzes their spending trends. Based on this analysis, it generates promotional proposals for businesses and local governments and provides them as reports. 【0269】 (Example 1) 【0270】 Next, we will describe Example 1. 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." 【0271】 In modern travel, travelers are burdened with the need to manage various booking and spending data. Furthermore, efficiently managing budgets and settling group expenses during trips is difficult, often resulting in traveler stress. Additionally, there is a lack of mechanisms to accurately understand the impact of spending on local areas and provide useful information to businesses and public institutions. 【0272】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0273】 In this invention, the server includes means for acquiring information from the user's communication device, analyzing the information, and extracting relevant expense data; means for classifying the data transmitted via the communication device and monitoring the data in real time based on the user's set budget; and means for notifying the user's communication device when an overspending of the budget is expected. This enables travelers to efficiently manage their spending, and allows businesses and public institutions to develop strategies based on consumer behavior patterns. 【0274】 "User's communication device" refers to a device such as a mobile phone, tablet, or computer that a traveler uses to manage and verify their own information. 【0275】 "Acquiring and analyzing information" refers to the act of automatically collecting reservation information and receipts from electronic data such as emails and images, and then analyzing that data to extract necessary expense information. 【0276】 "Extracting expense data" is the process of identifying and organizing specific expenditure details such as date, amount, and category from the acquired information. 【0277】 "Monitoring data based on budget" is a process that tracks spending limits for each category set by the user in real time, and helps with budget management. 【0278】 "Means of notification" refers to messaging functions used to inform users of the possibility of budget overruns, and typically utilizes push notifications or email. 【0279】 "Automatically calculating and processing settlements" refers to providing a procedure that simplifies payment by calculating each person's share of expenses based on all expenses incurred within the group after the trip has ended. 【0280】 "Collecting and analyzing spending patterns" is the process of aggregating data such as purchase history during travel, identifying trends and patterns, and generating strategic information based on that. 【0281】 This invention provides a system that enables travelers to efficiently manage their expenses during their trip and stay within their budget. The system functions by linking the user's communication device with a server located in the cloud. 【0282】 The server connects to the email accounts registered on the communication devices owned by users and automatically obtains reservation information and receipt images. For this, it uses a mail service API (e.g., the API of the mail provider). From the obtained data, the server utilizes natural language processing tools (e.g., natural language processing toolkits) and optical character recognition technology (e.g., character recognition services) to extract data related to expenses. As a result, information such as reservation numbers, hotel names, dates, amounts, etc. can be efficiently collected. 【0283】 Next, the server stores these extracted data in the cloud and sends them to the user's communication device using encrypted communication if necessary. A dedicated application for displaying and classifying data based on the user's itinerary is installed on the communication device. The application can classify expenses according to categories such as "accommodation" and "travel", for example. 【0284】 Before the trip, the user can use this application to set a travel budget for each category. The server monitors the expenditures in real time based on this budget information and sends a warning as a push notification when approaching the budget. 【0285】 In addition, the server aggregates and analyzes the expenditure data of all travelers and automatically generates promotion proposals based on the consumption trends in the region for enterprises or public institutions. This proposal can provide businesses with a targeting strategy aimed at activating the region. 【0286】 As a specific example, consider the case where a traveler plans a trip to a certain country and manages various expenses (such as accommodation fees and transportation fees) during the trip. By using this system, it is possible to prevent exceeding the budget and enjoy the trip with peace of mind. An example of a prompt sentence is "Please propose a method to support travel budget management. In particular, focus on methods to efficiently manage accommodation fees and transportation fees during the trip." 【0287】 This system not only reduces the burden on users but also brings data-driven value to the local economy. 【0288】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0289】 Step 1: 【0290】 The user sets up an email account on their communication device (smartphone or computer). The configured account information is sent to the server. This allows the server to obtain authentication information to access the user's email data. 【0291】 Step 2: 【0292】 The server uses the acquired authentication information to connect to the email service API and check for new emails. It filters the emails to find those containing keywords related to reservations or expenses (e.g., "reservation confirmation" or "receipt"). The detected emails and their attachments are selected for the next processing. 【0293】 Step 3: 【0294】 The server applies natural language processing tools and optical character recognition (OCR) technology to the selected emails and attachments. The input data is analyzed, and relevant data such as amounts, dates, and reservation numbers are extracted. This generates structured expense data. 【0295】 Step 4: 【0296】 The server stores the extracted data in a cloud database. The stored data is protected from unauthorized access using encryption technology, thus ensuring user privacy. 【0297】 Step 5: 【0298】 The server sends the data stored in the cloud to the user's communication device via secure communication means. A dedicated application on the user's communication device receives the data and prepares it for visualization and organization. 【0299】 Step 6: 【0300】 The terminal classifies the received data by category within the application. The input is the received data from the server, and the output is information organized by category such as "accommodation" and "meals". This classification makes it easier for the user to visually confirm their expenses. 【0301】 Step 7: 【0302】 The user sets a budget for each category using the application. This enables the server to monitor the spending situation in real time. 【0303】 Step 8: 【0304】 When the user's spending approaches the set budget, the server sends a warning notification to the communication device. This allows the user to review their spending and make plans to stay within the budget. 【0305】 Step 9: 【0306】 After the trip ends, the terminal automatically conducts settlement among groups using all the expense data stored in the server. Settlement calculations are performed based on the input data, and the amount each user is responsible for is shown as the output. 【0307】 Step 10: 【0308】 The server aggregates and analyzes the spending data of all users. Based on the results, it generates and outputs promotion proposals for companies and local governments. This enables effective marketing that understands the consumption behavior of the region. 【0309】 (Application Example 1) 【0310】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0311】 There is a problem in that travelers have difficulty effectively managing and settling their expenses during and after their trips. Furthermore, there is the challenge of the considerable effort and time required to accurately understand local consumption trends and use that information for targeted marketing. 【0312】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0313】 This invention includes a server that includes means for analyzing reservation information received online and extracting relevant expense data from that information; means for classifying the extracted expense data and monitoring the data based on a set budget; means for notifying the user when signs of budget overrun are detected; means for automatically calculating the settlement amount within the group after the trip and automating the remittance process; means for aggregating and analyzing travelers' spending data and making promotional proposals to businesses or local governments; means for facilitating smooth payments using electronic payment methods based on consumption trend data; and means for automatically analyzing spending history and predicting future spending trends before issuing budget overrun warnings. This enables efficient management of spending during travel, streamlining settlement processing, and effective marketing based on local consumption trends. 【0314】 "Reservation information" refers to information issued when using online services such as travel or accommodation, which includes details such as the date, time, location, and price. 【0315】 "Expense data" refers to data related to expenses incurred in connection with travel, and includes information such as hotel accommodation fees and transportation costs. 【0316】 "Classification" is the act of dividing extracted expense data into specific categories, a technique that makes management and analysis easier. 【0317】 "Budget monitoring" is the process of tracking how much actual spending is progressing based on a budget set in advance by the user, in order to prevent budget overruns. 【0318】 "Notification" is the act of informing a user of information, and is often used as a means to provide warnings or confirmations in real time. 【0319】 The "settlement amount" is the value obtained after reviewing the allocation of expenses at the end of the trip and calculating the amount each person in the group should bear. 【0320】 "Money transfer" refers to the process of sending money to another user or service provider, and includes the use of digital payment methods. 【0321】 "Expense data aggregation" refers to the act of compiling all expenses incurred during a trip and organizing them into a series of data. 【0322】 "Promotional proposals" refer to the act of proposing marketing strategies to businesses and local governments based on collected and analyzed data. 【0323】 "Payment methods" is a general term for the methods and means used by users to pay for goods or services, and includes electronic methods. 【0324】 "Consumption history" refers to a record of a user's past spending and is fundamental information for predicting future spending trends. 【0325】 To realize this invention, the system mainly consists of a server and a user terminal. The server is equipped with a program that analyzes reservation information received online and extracts expense data. This program uses Python's natural language processing library (NLTK) and optical character recognition tool (Tesseract OCR) to analyze the necessary data from emails and images. The analyzed data is stored in a database in real time using Firebase. The server analyzes this data, monitors how far spending has progressed based on the user's budget settings, and sends push notifications as needed. 【0326】 On the terminal side, users can input their budget through a dedicated application and monitor expenses in real time based on that budget. This app also has a function to warn users if they are about to exceed their budget and to predict future spending based on their spending history. After the trip is over, the system uses server data to automatically calculate settlements within the group and allows payment to be made using a specific electronic payment method. 【0327】 As a concrete example, when a user checks into a hotel during a trip, the reservation confirmation email is automatically processed on the server, and the accommodation cost is categorized into the "Accommodation" category in the app. The application then runs on the device, displaying real-time warnings before the budget is exceeded. While reviewing the spending data, the user can enter prompts into the app, such as "Which category does this expense fall into?" or "Please tell me my travel spending status for this month," and receive immediate feedback from the system. 【0328】 Through this system, users can easily manage their travel expenses and enjoy peace of mind and efficiency while traveling by seamlessly settling accounts and making payments after their trip. 【0329】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0330】 Step 1: 【0331】 The server receives user reservation information and images from online sources as input. This information includes emails and scanned receipt images. The server uses a natural language processing library (NLTK) and an optical character recognition tool (Tesseract OCR) to output expense data such as reservation number, hotel name, date, and amount in text format. 【0332】 Step 2: 【0333】 The server stores the extracted expense data in a database for classification. This process involves the server accessing a real-time database (Firebase) and organizing the data by category. For example, accommodation expenses are categorized under "accommodation" and stored in the database as data related to that category. 【0334】 Step 3: 【0335】 The server monitors expense data in real time based on budget information entered by the user in advance. The server compares the budget with actual spending, and if an overspending is anticipated, it sends a warning to the device using a push notification function. This makes budget management easy for users. 【0336】 Step 4: 【0337】 The terminal receives all expense data from the server after the trip ends. The user then uses the application to initiate settlement within the group. The terminal aggregates each participant's expenses, calculates the total settlement amount, and displays the result. This allows the user to view detailed data for settlement. 【0338】 Step 5: 【0339】 The user makes an electronic payment based on the result displayed after settlement. The terminal makes the payment to the other user via the selected payment method (e.g., an electronic payment system). In this step, the terminal quickly transfers the required amount and notifies that the payment is complete. 【0340】 Step 6: 【0341】 The server aggregates spending data from all travelers and generates promotional proposals for businesses and local governments. At this stage, the server analyzes consumer trends and creates reports to derive effective marketing strategies. This output is used by businesses and local governments as a guide for regional revitalization. 【0342】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0343】 In embodiments of the present invention, a system is provided that integrates a terminal owned by the traveler, a server located in the cloud, and an emotion engine. This system accesses the user's email account to retrieve newly received online reservation information and receipt images on the server. The retrieved information is analyzed on the server using optical character recognition (OCR) to extract expense data such as reservation number, amount, and date. 【0344】 The server analyzes the extracted expense data using natural language processing and stores it as structured data. This structured data is sent to the terminal, where a dedicated application automatically categorizes the expenses according to the user's itinerary. 【0345】 In the expense management application, users enter their budget for each category before traveling. Based on this, the server monitors the expense data in real time and sends a warning notification to the user's device if it detects a potential budget overrun. 【0346】 This notification is optimized according to the user's emotional state. The emotion engine analyzes the user's voice input and past behavioral data to estimate their emotional state. For example, if the user is in a relaxed emotional state, the notification message can be composed in a calm tone. 【0347】 After the trip ends, the device uses expense data stored on the server to automatically calculate the settlement amount within the group and presents payment methods. Users can utilize this function to easily complete the payment process. 【0348】 Furthermore, the server aggregates and analyzes traveler spending and emotional data to understand consumption trends. This allows for the generation of emotionally-based promotional suggestions for businesses and local governments, enabling the formation of more effective marketing strategies. 【0349】 This invention aims to improve user satisfaction by integrating expense management with an understanding of emotions, thereby providing users with a more personalized travel experience. Furthermore, it aims to contribute to the revitalization of businesses and local governments through promotions that enhance their contribution to the local community. 【0350】 The following describes the processing flow. 【0351】 Step 1: 【0352】 The server accesses the user's email account to verify newly received online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0353】 Step 2: 【0354】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. This text data includes reservation numbers, amounts, dates, and other information. 【0355】 Step 3: 【0356】 The server applies natural language processing to the extracted text data for analysis, organizes the necessary expense data as structured data, and stores it in the database. 【0357】 Step 4: 【0358】 The terminal receives structured expense data from the server and displays it in a dedicated application. This application automatically categorizes each expense based on the user's itinerary. 【0359】 Step 5: 【0360】 Users set budgets for each expenditure category within the application on their device. This budget information is sent to the server and used as a basis for expense monitoring. 【0361】 Step 6: 【0362】 The device provides the user's voice input and behavioral data to the emotion engine. The emotion engine uses this data to estimate the user's emotional state. 【0363】 Step 7: 【0364】 The server monitors expense data in real time based on the set budget and sends a notification to the user's device if it detects a potential budget overrun. The content and tone of this notification are adjusted based on the results of the sentiment engine. 【0365】 Step 8: 【0366】 At the end of the trip, the device retrieves all expense data from the server and automatically calculates the settlement amount for each group participant. Users can easily complete the payment process through the recommended payment method on the device. 【0367】 Step 9: 【0368】 The server aggregates traveler spending and sentiment data to generate promotional suggestions for businesses and local governments. These suggestions take into account consumption trends based on the aggregated sentiment states. 【0369】 (Example 2) 【0370】 Next, we will describe Example 2. 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". 【0371】 This invention relates to a system for efficiently managing travel expenses, and more particularly to supporting users' budget management in real time and reducing the risk of exceeding the budget. Conventional systems have problems with budget management becoming complicated due to insufficient optimization of expense classification and notifications. In addition, there is a lack of notification systems that take into account the emotional state of travelers, which limits the improvement of the user experience. 【0372】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0373】 In this invention, the server includes means for analyzing received reservation information and extracting relevant cost data, means for classifying the extracted cost data and monitoring the data based on a set budget, and means for analyzing the user's emotional state and optimizing notification content according to that emotion. This makes it possible to streamline user budget management, reduce the risk of exceeding the budget, and provide notifications that are sensitive to the user's emotions. 【0374】 "Received reservation information" refers to electronic data containing reservation details related to travel, which is used to analyze expense data. 【0375】 "Expense data" refers to data containing information about various travel expenses, including elements such as reservation number, amount, and date. 【0376】 A "classification method" is a function for dividing extracted cost data into categories based on specific criteria. 【0377】 "Means of notifying users" refers to a function that sends warnings or information to users when signs of budget overruns are detected. 【0378】 "Means for analyzing emotional state" refers to a function that estimates the user's current emotional state based on their words, actions, and past behavior. 【0379】 "Method for automatically calculating settlement figures" refers to a function that automatically calculates the amount needed to settle expenses between travelers after the trip is completed. 【0380】 "Means of automating the remittance process" refers to a function that allows users to easily complete the remittance process based on the settled amount. 【0381】 "Means for aggregating and analyzing consumption data" refers to a function that collects and analyzes travelers' spending information to reveal consumption trends and behavioral patterns. 【0382】 "Means of proposing promotions" refers to a function that proposes effective sales activities and marketing strategies to businesses and local governments based on aggregated data. 【0383】 This invention provides a system for efficiently managing travel expenses. It mainly consists of a traveler's terminal, a server located in the cloud, and an emotion engine that analyzes the user's emotional state. 【0384】 The server analyzes reservation information and receipt images received by the user via their terminal using optical character recognition software. Specifically, it uses software such as "Tesseract" to extract expense data such as reservation numbers, amounts, and dates from email text and images. This extracted data is then analyzed using natural language processing libraries such as "spaCy" and "NLTK". Based on these analysis results, the server generates structured data and sends it to the terminal. 【0385】 The terminal is operated through a dedicated application that automatically categorizes expenses according to the user's itinerary based on the structured data received. Furthermore, the user can enter a budget for each expense category in this application before the trip. Based on this configured budget information, the server monitors the expense data in real time, and if there are signs of budget overrun, the emotion engine analyzes the user's current emotional state and sends a warning notification in an appropriate tone. 【0386】 When the user is relaxed, notification messages are delivered in a calm tone. Furthermore, once the trip is complete, the device uses expense data stored on the server to automatically calculate the total amount due within the group and presents the appropriate payment procedure. This allows the user to process payments quickly and easily. 【0387】 Furthermore, the server can analyze the collected traveler consumption and sentiment data, and based on the results, it can provide a platform for implementing promotional proposals to businesses and local governments, thereby supporting more effective marketing strategies. 【0388】 As a concrete example, one could collect expense information along with emotional records of shopping experiences a user had during a trip, and then use that data to suggest discount promotions at stores. An example of a prompt to the generating AI model would be, "Organize the expense data for my New York trip and optimize warning notifications about potential budget overruns." This prompt would allow the system to perform detailed processing to improve the user experience. 【0389】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0390】 Step 1: 【0391】 The user receives travel-related booking information via email using their device. Input includes the email content and attachments. The device sends this information to a server in the cloud, filtering the email subject, body, and attachments to identify relevant information. The output is the booking data extracted and sent to the server. 【0392】 Step 2: 【0393】 The server analyzes received email information using optical character recognition (OCR) software. Input includes both email text and images. Specifically, it uses OCR tools such as "Tesseract" to extract text data from emails and images. The output includes expense data such as reservation numbers, amounts, and dates. 【0394】 Step 3: 【0395】 The server analyzes the extracted cost data using natural language processing techniques. The input is raw text data obtained through OCR. Natural language processing libraries such as "spaCy" and "NLTK" are used to structure the data and divide it into semantic categories. The output is structured cost data. 【0396】 Step 4: 【0397】 The server sends the generated structured data to the terminal. The input is structured expense data. This data is transmitted using a secure protocol (e.g., SSL / TLS). The output is the secure transmission of data to the terminal. 【0398】 Step 5: 【0399】 The terminal categorizes the received expense data using a dedicated application. The input is structured expense data. In practice, it automatically categorizes expenses by comparing them with past travel data. The output displays the categorized expense items. 【0400】 Step 6: 【0401】 Before traveling, users enter a budget for each expense category. The input is a numerical budget value. Based on the terminal application, the budget for each category is set. The set budget information is then sent to the server as output. 【0402】 Step 7: 【0403】 The server monitors expense data in real time and, when it detects signs of budget overruns, sends a notification to the device that takes the user's emotional state into account. Inputs include categorized expense data, a set budget, and the user's emotional state. An emotional engine is used to analyze the emotional state and optimize the notification message. The output is an emotionally appropriate warning notification displayed on the device. 【0404】 Step 8: 【0405】 After the trip ends, the terminal automatically calculates the settlement amount for the group using expense data stored on the server. The input is all expense data from the trip. A calculation algorithm is used to determine the payment amount for each user. The settlement results are presented as output. 【0406】 Step 9: 【0407】 The server aggregates and analyzes traveler spending and sentiment data, providing it to businesses and local governments as a basis for promotional proposals. Input includes all expense and sentiment data. Business intelligence tools are used to analyze data patterns. The output is the data analysis results, which are then used in marketing strategies. 【0408】 (Application Example 2) 【0409】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0410】 There are challenges in ensuring that travelers can smoothly manage their expenses during their trips and enjoy their travels with peace of mind within their budget. Furthermore, it is necessary to improve travel satisfaction by providing information tailored to their emotional state in real time during their trips and offering personalized travel experiences. Additionally, there is a need for businesses and local governments to provide appropriate information to implement effective marketing based on travelers' spending trends. 【0411】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0412】 This invention includes a server that analyzes reservation information received online and extracts relevant expense data from that information; a server that classifies the extracted expense data and monitors the data based on a set budget; and a server that provides users with information optimized based on their emotional state. This makes it easier for travelers to manage their spending within their budget and improves their travel satisfaction by receiving information optimized to their individual emotional state. It also enables businesses and local governments to make promotional proposals based on travelers' spending data. 【0413】 "Online reservation information" refers to data related to travel and service reservations that are received by the user's digital device via electronic communication. 【0414】 "Expense data" refers to numerical or textual data containing information about expenses incurred during travel or service use. 【0415】 "Information optimized based on emotional state" refers to content and notifications that are individually tailored to take into account the user's psychological and emotional state. 【0416】 "Monitoring data based on a budget" refers to the process of evaluating and verifying actual spending in real time based on financial limits set by the user in advance. 【0417】 "Input for estimating emotional state" refers to biometric or behavioral information used for emotion estimation, such as user voice and behavioral data. 【0418】 "Making a promotional proposal" refers to the act of proposing sales promotion activities or special offers to target audiences based on predictions and analysis. 【0419】 The system to realize this application is built by integrating a traveler's device, a server located in the cloud, and an emotion engine. The server has a program that processes booking information received online, accessing the traveler's email account to retrieve booking information and receipt images. The retrieved information is analyzed using OCR technology to extract expense data such as booking numbers, amounts, and dates. Optical character recognition tools such as AWS Textract are used in this process. 【0420】 The extracted expense data is converted into structured data using a Python script on AWS Lambda and stored in DynamoDB. The data is monitored in real time based on the set budget, and notifications are sent to the user via Firebase. The notifications are optimized based on the user's emotional state. Emotion estimation is performed by analyzing the emotional state from speech input and text data using Google Cloud's Speech-to-Text and Azure's Text Analytics. 【0421】 Furthermore, after the trip ends, the system automatically calculates the total amount settled within the group on the terminal and presents the result to the user, enabling quick payment. In addition, the server aggregates and analyzes travelers' spending and sentiment data to generate promotional suggestions for businesses and local governments based on their spending trends. As a result, the user's travel experience becomes more personalized and satisfaction levels increase. 【0422】 For example, if a user uploads photos taken during a trip to the application, relevant tourist information will be provided in real time. Furthermore, a generative AI model will recommend tourist destinations and events that take the user's mood into consideration. An example of a prompt might be, "Please recommend tourist destinations to visit when I am feeling relaxed." 【0423】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0424】 Step 1: 【0425】 The server accesses the user's email account and retrieves newly received reservation information and receipt images. Based on this input data, it saves the reservation information to a database and prepares it for OCR processing. 【0426】 Step 2: 【0427】 The server analyzes the receipt image acquired using OCR technology. During this process, character recognition tools such as AWS Textract are used to extract expense data such as reservation number, amount, and date from the image. This result is output as text data and passed on to the next processing step. 【0428】 Step 3: 【0429】 The terminal processes the text data received from the server using a Python script executed on AWS Lambda, converting it into structured data. This organizes the expense data by category and stores it in DynamoDB. Obtaining structured data makes it easier for users to view expenses for each category. 【0430】 Step 4: 【0431】 The device monitors spending in real time, referencing the user's set budget and structured data stored on the server. If a potential budget overrun is detected, the device sends a notification to the user. This notification is sent using Firebase, allowing the user to instantly understand their spending situation. 【0432】 Step 5: 【0433】 The server analyzes the user's voice input using Google Cloud's Speech-to-Text and estimates their emotional state using Azure's Text Analytics. Based on the estimated emotional data and structured data, an AI model is used to generate notifications optimized for expense management, which are then provided to the user according to the prompt (e.g., "If I want to relax, please recommend a cafe."). 【0434】 Step 6: 【0435】 After the trip ends, the device downloads all expenditure data from the server and automatically calculates the settlement amount within the group. This calculation can be viewed on the user's smartphone, enabling quick remittances. The user can choose the most suitable remittance method from the presented options. 【0436】 Step 7: 【0437】 The server analyzes aggregated spending and sentiment data, and based on this, generates promotional suggestions for businesses and local governments that are tailored to consumer trends. This enables businesses and local governments to develop more effective marketing strategies. 【0438】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0439】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0440】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0441】 [Third Embodiment] 【0442】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0443】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0444】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0445】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0446】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0447】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0448】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0449】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0450】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0451】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0452】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0453】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0454】 One embodiment of the present invention is a system that links a traveler's device with a server located in the cloud. In this system, online reservation information and receipt images received in the traveler's email account are automatically retrieved by the server. The retrieved information is analyzed on the server using natural language processing and optical character recognition technology, and expense data such as reservation number, hotel name, date, and amount are extracted. 【0455】 The extracted expense data is sent from the server to the terminal, where a dedicated application on the terminal automatically categorizes it based on the user's itinerary. For example, hotel accommodation costs are categorized under "Accommodation," and transportation costs are categorized under "Travel." 【0456】 Users can set a budget for each category within the app before traveling. The server monitors spending in real time based on this budget information and pushes a warning message to the app on the user's device if spending approaches or exceeds the set budget. 【0457】 After the trip ends, the terminal automatically calculates the settlement amount with other participants in the group using all of the traveler's expense data stored on the server. Based on the calculation result, the user can select PayPay, bank transfer, or other electronic payment methods and send the predetermined amount to the other travelers. 【0458】 Furthermore, the server aggregates and analyzes the spending behavior of all travelers and generates effective promotional proposals for businesses and local governments based on regional consumption trends. These proposals provide businesses with a clear direction for targeting strategies to promote regional revitalization. 【0459】 This invention significantly reduces the burden of managing expenses during travel, allowing users to enjoy their trips with peace of mind, while enabling businesses and local governments to develop marketing strategies based on collected data. This system simplifies financial management during travel and provides significant value to both travelers and local communities. 【0460】 The following describes the processing flow. 【0461】 Step 1: 【0462】 The server accesses the user's email account to verify newly arrived online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0463】 Step 2: 【0464】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. The extracted data includes information such as reservation number, date, and amount. 【0465】 Step 3: 【0466】 The server analyzes the text data extracted using natural language processing and organizes and stores the necessary expense data as structured data. 【0467】 Step 4: 【0468】 The terminal receives structured expense data from the server and displays it in a dedicated application. Here, each expense is automatically categorized based on the user's itinerary. 【0469】 Step 5: 【0470】 Users can set a budget within the application. The set budget information is sent to the server and registered in the database. 【0471】 Step 6: 【0472】 The server monitors expense data received in real time based on budget registration information and detects signs of exceeding the set budget. If an overrun is anticipated, a warning message is pushed to the user's device. 【0473】 Step 7: 【0474】 After the trip ends, the terminal automatically calculates the settlement amount for each group participant using all expense data stored on the server. 【0475】 Step 8: 【0476】 Based on the calculated settlement amount, the user selects an electronic payment system through the application and completes the transfer to the other traveler. 【0477】 Step 9: 【0478】 The server aggregates spending data collected from travelers and analyzes their spending trends. Based on this analysis, it generates promotional proposals for businesses and local governments and provides them as reports. 【0479】 (Example 1) 【0480】 Next, we will describe Example 1. 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." 【0481】 In modern travel, travelers are burdened with the need to manage various booking and spending data. Furthermore, efficiently managing budgets and settling group expenses during trips is difficult, often resulting in traveler stress. Additionally, there is a lack of mechanisms to accurately understand the impact of spending on local areas and provide useful information to businesses and public institutions. 【0482】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0483】 In this invention, the server includes means for acquiring information from the user's communication device, analyzing the information, and extracting relevant expense data; means for classifying the data transmitted via the communication device and monitoring the data in real time based on the user's set budget; and means for notifying the user's communication device when an overspending of the budget is expected. This enables travelers to efficiently manage their spending, and allows businesses and public institutions to develop strategies based on consumer behavior patterns. 【0484】 "User's communication device" refers to a device such as a mobile phone, tablet, or computer that a traveler uses to manage and verify their own information. 【0485】 "Acquiring and analyzing information" refers to the act of automatically collecting reservation information and receipts from electronic data such as emails and images, and then analyzing that data to extract necessary expense information. 【0486】 "Extracting expense data" is the process of identifying and organizing specific expenditure details such as date, amount, and category from the acquired information. 【0487】 "Monitoring data based on budget" is a process that tracks spending limits for each category set by the user in real time, and helps with budget management. 【0488】 "Means of notification" refers to messaging functions used to inform users of the possibility of budget overruns, and typically utilizes push notifications or email. 【0489】 "Automatically calculating and processing settlements" refers to providing a procedure that simplifies payment by calculating each person's share of expenses based on all expenses incurred within the group after the trip has ended. 【0490】 "Collecting and analyzing spending patterns" is the process of aggregating data such as purchase history during travel, identifying trends and patterns, and generating strategic information based on that. 【0491】 This invention provides a system that enables travelers to efficiently manage their expenses during their trip and stay within their budget. The system functions by linking the user's communication device with a server located in the cloud. 【0492】 The server connects to email accounts registered on the user's communication device and automatically retrieves reservation information and receipt images. This utilizes email service APIs (e.g., email provider APIs). From the retrieved data, the server uses natural language processing tools (e.g., natural language processing toolkits) and optical character recognition technology (e.g., character recognition services) to extract data related to expenses. This allows for the efficient collection of information such as reservation numbers, hotel names, dates, and amounts. 【0493】 Next, the server stores this extracted data in the cloud and, if necessary, transmits it to the user's communication device using encrypted communication. The communication device has a dedicated application installed that displays and categorizes the data based on the user's itinerary. The application can categorize expenses according to categories such as "accommodation" and "transportation." 【0494】 Before traveling, users can use this application to set a travel budget for each category. The server monitors spending in real time based on this budget information and sends push notifications as the user approaches the budget. 【0495】 Furthermore, the server aggregates and analyzes spending data from all travelers and automatically generates promotional proposals for businesses or public institutions based on local consumption trends. These proposals enable businesses to receive targeted strategies aimed at revitalizing their local areas. 【0496】 As a concrete example, consider a traveler planning a trip to a certain country and managing various expenses (accommodation, transportation, etc.) during the trip. By using this system, they can prevent exceeding their budget and enjoy their trip with peace of mind. An example of a prompt would be, "Suggest ways to help with travel budget management. In particular, focus on ways to streamline the management of accommodation and transportation expenses during the trip." 【0497】 This system not only reduces the burden on users but also brings data-driven value to the local economy. 【0498】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0499】 Step 1: 【0500】 The user sets up an email account on their communication device (smartphone or computer). The configured account information is sent to the server. This allows the server to obtain authentication information to access the user's email data. 【0501】 Step 2: 【0502】 The server uses the acquired authentication information to connect to the email service API and check for new emails. It filters the emails to find those containing keywords related to reservations or expenses (e.g., "reservation confirmation" or "receipt"). The detected emails and their attachments are selected for the next processing. 【0503】 Step 3: 【0504】 The server applies natural language processing tools and optical character recognition (OCR) technology to the selected emails and attachments. The input data is analyzed, and relevant data such as amounts, dates, and reservation numbers are extracted. This generates structured expense data. 【0505】 Step 4: 【0506】 The server stores the extracted data in a cloud database. The stored data is protected from unauthorized access using encryption technology, thus ensuring user privacy. 【0507】 Step 5: 【0508】 The server transmits data stored in the cloud to the user's communication device using a secure communication method. A dedicated application on the user's communication device receives the data and prepares it for visualization and organization. 【0509】 Step 6: 【0510】 The terminal categorizes the received data within the application. The input is data received from the server, and the output is information organized by categories such as "accommodation" and "meals." This categorization makes it easy for users to visually review their expenses. 【0511】 Step 7: 【0512】 Users set budgets for each category using the application. This allows the server to monitor spending in real time. 【0513】 Step 8: 【0514】 The server sends an alert notification to the communication device when a user's spending approaches their set budget. This allows the user to review their spending and plan to stay within their budget. 【0515】 Step 9: 【0516】 After the trip ends, the terminal automatically settles accounts among the group using all expense data stored on the server. Based on the entered data, the settlement calculation is performed, and the output shows each user's share of the expenses. 【0517】 Step 10: 【0518】 The server aggregates and analyzes spending data from all users. Based on the results, it generates and outputs promotional proposals for companies and local governments. This enables effective marketing that takes into account local consumer behavior. 【0519】 (Application Example 1) 【0520】 Next, we will explain Application Example 1. In the following explanation, 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." 【0521】 There is a problem in that travelers have difficulty effectively managing and settling their expenses during and after their trips. Furthermore, there is the challenge of the considerable effort and time required to accurately understand local consumption trends and use that information for targeted marketing. 【0522】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0523】 This invention includes a server that includes means for analyzing reservation information received online and extracting relevant expense data from that information; means for classifying the extracted expense data and monitoring the data based on a set budget; means for notifying the user when signs of budget overrun are detected; means for automatically calculating the settlement amount within the group after the trip and automating the remittance process; means for aggregating and analyzing travelers' spending data and making promotional proposals to businesses or local governments; means for facilitating smooth payments using electronic payment methods based on consumption trend data; and means for automatically analyzing spending history and predicting future spending trends before issuing budget overrun warnings. This enables efficient management of spending during travel, streamlining settlement processing, and effective marketing based on local consumption trends. 【0524】 "Reservation information" refers to information issued when using online services such as travel or accommodation, which includes details such as the date, time, location, and price. 【0525】 "Expense data" refers to data related to expenses incurred in connection with travel, and includes information such as hotel accommodation fees and transportation costs. 【0526】 "Classification" is the act of dividing extracted expense data into specific categories, a technique that makes management and analysis easier. 【0527】 "Budget monitoring" is the process of tracking how much actual spending is progressing based on a budget set in advance by the user, in order to prevent budget overruns. 【0528】 "Notification" is the act of informing a user of information, and is often used as a means to provide warnings or confirmations in real time. 【0529】 The "settlement amount" is the value obtained after reviewing the allocation of expenses at the end of the trip and calculating the amount each person in the group should bear. 【0530】 "Money transfer" refers to the process of sending money to another user or service provider, and includes the use of digital payment methods. 【0531】 "Expense data aggregation" refers to the act of compiling all expenses incurred during a trip and organizing them into a series of data. 【0532】 "Promotional proposals" refer to the act of proposing marketing strategies to businesses and local governments based on collected and analyzed data. 【0533】 "Payment methods" is a general term for the methods and means used by users to pay for goods or services, and includes electronic methods. 【0534】 "Consumption history" refers to a record of a user's past spending and is fundamental information for predicting future spending trends. 【0535】 To realize this invention, the system mainly consists of a server and a user terminal. The server is equipped with a program that analyzes reservation information received online and extracts expense data. This program uses Python's natural language processing library (NLTK) and optical character recognition tool (Tesseract OCR) to analyze the necessary data from emails and images. The analyzed data is stored in a database in real time using Firebase. The server analyzes this data, monitors how far spending has progressed based on the user's budget settings, and sends push notifications as needed. 【0536】 On the terminal side, users can input their budget through a dedicated application and monitor expenses in real time based on that budget. This app also has a function to warn users if they are about to exceed their budget and to predict future spending based on their spending history. After the trip is over, the system uses server data to automatically calculate settlements within the group and allows payment to be made using a specific electronic payment method. 【0537】 As a concrete example, when a user checks into a hotel during a trip, the reservation confirmation email is automatically processed on the server, and the accommodation cost is categorized into the "Accommodation" category in the app. The application then runs on the device, displaying real-time warnings before the budget is exceeded. While reviewing the spending data, the user can enter prompts into the app, such as "Which category does this expense fall into?" or "Please tell me my travel spending status for this month," and receive immediate feedback from the system. 【0538】 Through this system, users can easily manage their travel expenses and enjoy peace of mind and efficiency while traveling by seamlessly settling accounts and making payments after their trip. 【0539】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0540】 Step 1: 【0541】 The server receives user reservation information and images from online sources as input. This information includes emails and scanned receipt images. The server uses a natural language processing library (NLTK) and an optical character recognition tool (Tesseract OCR) to output expense data such as reservation number, hotel name, date, and amount in text format. 【0542】 Step 2: 【0543】 The server stores the extracted expense data in a database for classification. This process involves the server accessing a real-time database (Firebase) and organizing the data by category. For example, accommodation expenses are categorized under "accommodation" and stored in the database as data related to that category. 【0544】 Step 3: 【0545】 The server monitors expense data in real time based on budget information entered by the user in advance. The server compares the budget with actual spending, and if an overspending is anticipated, it sends a warning to the device using a push notification function. This makes budget management easy for users. 【0546】 Step 4: 【0547】 The terminal receives all expense data from the server after the trip ends. The user then uses the application to initiate settlement within the group. The terminal aggregates each participant's expenses, calculates the total settlement amount, and displays the result. This allows the user to view detailed data for settlement. 【0548】 Step 5: 【0549】 The user makes an electronic payment based on the result displayed after settlement. The terminal makes the payment to the other user via the selected payment method (e.g., an electronic payment system). In this step, the terminal quickly transfers the required amount and notifies that the payment is complete. 【0550】 Step 6: 【0551】 The server aggregates spending data from all travelers and generates promotional proposals for businesses and local governments. At this stage, the server analyzes consumer trends and creates reports to derive effective marketing strategies. This output is used by businesses and local governments as a guide for regional revitalization. 【0552】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0553】 In embodiments of the present invention, a system is provided that integrates a terminal owned by the traveler, a server located in the cloud, and an emotion engine. This system accesses the user's email account to retrieve newly received online reservation information and receipt images on the server. The retrieved information is analyzed on the server using optical character recognition (OCR) to extract expense data such as reservation number, amount, and date. 【0554】 The server analyzes the extracted expense data using natural language processing and stores it as structured data. This structured data is sent to the terminal, where a dedicated application automatically categorizes the expenses according to the user's itinerary. 【0555】 In the expense management application, users enter their budget for each category before traveling. Based on this, the server monitors the expense data in real time and sends a warning notification to the user's device if it detects a potential budget overrun. 【0556】 This notification is optimized according to the user's emotional state. The emotion engine analyzes the user's voice input and past behavioral data to estimate their emotional state. For example, if the user is in a relaxed emotional state, the notification message can be composed in a calm tone. 【0557】 After the trip ends, the device uses expense data stored on the server to automatically calculate the settlement amount within the group and presents payment methods. Users can utilize this function to easily complete the payment process. 【0558】 Furthermore, the server aggregates and analyzes traveler spending and emotional data to understand consumption trends. This allows for the generation of emotionally-based promotional suggestions for businesses and local governments, enabling the formation of more effective marketing strategies. 【0559】 This invention aims to improve user satisfaction by integrating expense management with an understanding of emotions, thereby providing users with a more personalized travel experience. Furthermore, it aims to contribute to the revitalization of businesses and local governments through promotions that enhance their contribution to the local community. 【0560】 The following describes the processing flow. 【0561】 Step 1: 【0562】 The server accesses the user's email account to verify newly received online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0563】 Step 2: 【0564】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. This text data includes reservation numbers, amounts, dates, and other information. 【0565】 Step 3: 【0566】 The server applies natural language processing to the extracted text data for analysis, organizes the necessary expense data as structured data, and stores it in the database. 【0567】 Step 4: 【0568】 The terminal receives structured expense data from the server and displays it in a dedicated application. This application automatically categorizes each expense based on the user's itinerary. 【0569】 Step 5: 【0570】 Users set budgets for each expenditure category within the application on their device. This budget information is sent to the server and used as a basis for expense monitoring. 【0571】 Step 6: 【0572】 The device provides the user's voice input and behavioral data to the emotion engine. The emotion engine uses this data to estimate the user's emotional state. 【0573】 Step 7: 【0574】 The server monitors expense data in real time based on the set budget and sends a notification to the user's device if it detects a potential budget overrun. The content and tone of this notification are adjusted based on the results of the sentiment engine. 【0575】 Step 8: 【0576】 At the end of the trip, the device retrieves all expense data from the server and automatically calculates the settlement amount for each group participant. Users can easily complete the payment process through the recommended payment method on the device. 【0577】 Step 9: 【0578】 The server aggregates traveler spending and sentiment data to generate promotional suggestions for businesses and local governments. These suggestions take into account consumption trends based on the aggregated sentiment states. 【0579】 (Example 2) 【0580】 Next, we will describe Example 2. 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." 【0581】 This invention relates to a system for efficiently managing travel expenses, and more particularly to supporting users' budget management in real time and reducing the risk of exceeding the budget. Conventional systems have problems with budget management becoming complicated due to insufficient optimization of expense classification and notifications. In addition, there is a lack of notification systems that take into account the emotional state of travelers, which limits the improvement of the user experience. 【0582】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0583】 In this invention, the server includes means for analyzing received reservation information and extracting relevant cost data, means for classifying the extracted cost data and monitoring the data based on a set budget, and means for analyzing the user's emotional state and optimizing notification content according to that emotion. This makes it possible to streamline user budget management, reduce the risk of exceeding the budget, and provide notifications that are sensitive to the user's emotions. 【0584】 "Received reservation information" refers to electronic data containing reservation details related to travel, which is used to analyze expense data. 【0585】 "Expense data" refers to data containing information about various travel expenses, including elements such as reservation number, amount, and date. 【0586】 A "classification method" is a function for dividing extracted cost data into categories based on specific criteria. 【0587】 "Means of notifying users" refers to a function that sends warnings or information to users when signs of budget overruns are detected. 【0588】 "Means for analyzing emotional state" refers to a function that estimates the user's current emotional state based on their words, actions, and past behavior. 【0589】 "Method for automatically calculating settlement figures" refers to a function that automatically calculates the amount needed to settle expenses between travelers after the trip is completed. 【0590】 "Means of automating the remittance process" refers to a function that allows users to easily complete the remittance process based on the settled amount. 【0591】 "Means for aggregating and analyzing consumption data" refers to a function that collects and analyzes travelers' spending information to reveal consumption trends and behavioral patterns. 【0592】 "Means of proposing promotions" refers to a function that proposes effective sales activities and marketing strategies to businesses and local governments based on aggregated data. 【0593】 This invention provides a system for efficiently managing travel expenses. It mainly consists of a traveler's terminal, a server located in the cloud, and an emotion engine that analyzes the user's emotional state. 【0594】 The server analyzes reservation information and receipt images received by the user via their terminal using optical character recognition software. Specifically, it uses software such as "Tesseract" to extract expense data such as reservation numbers, amounts, and dates from email text and images. This extracted data is then analyzed using natural language processing libraries such as "spaCy" and "NLTK". Based on these analysis results, the server generates structured data and sends it to the terminal. 【0595】 The terminal is operated through a dedicated application that automatically categorizes expenses according to the user's itinerary based on the structured data received. Furthermore, the user can enter a budget for each expense category in this application before the trip. Based on this configured budget information, the server monitors the expense data in real time, and if there are signs of budget overrun, the emotion engine analyzes the user's current emotional state and sends a warning notification in an appropriate tone. 【0596】 When the user is relaxed, notification messages are delivered in a calm tone. Furthermore, once the trip is complete, the device uses expense data stored on the server to automatically calculate the total amount due within the group and presents the appropriate payment procedure. This allows the user to process payments quickly and easily. 【0597】 Furthermore, the server can analyze the collected traveler consumption and sentiment data, and based on the results, it can provide a platform for implementing promotional proposals to businesses and local governments, thereby supporting more effective marketing strategies. 【0598】 As a concrete example, one could collect expense information along with emotional records of shopping experiences a user had during a trip, and then use that data to suggest discount promotions at stores. An example of a prompt to the generating AI model would be, "Organize the expense data for my New York trip and optimize warning notifications about potential budget overruns." This prompt would allow the system to perform detailed processing to improve the user experience. 【0599】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0600】 Step 1: 【0601】 The user receives travel-related booking information via email using their device. Input includes the email content and attachments. The device sends this information to a server in the cloud, filtering the email subject, body, and attachments to identify relevant information. The output is the booking data extracted and sent to the server. 【0602】 Step 2: 【0603】 The server analyzes received email information using optical character recognition (OCR) software. Input includes both email text and images. Specifically, it uses OCR tools such as "Tesseract" to extract text data from emails and images. The output includes expense data such as reservation numbers, amounts, and dates. 【0604】 Step 3: 【0605】 The server analyzes the extracted cost data using natural language processing techniques. The input is raw text data obtained through OCR. Natural language processing libraries such as "spaCy" and "NLTK" are used to structure the data and divide it into semantic categories. The output is structured cost data. 【0606】 Step 4: 【0607】 The server sends the generated structured data to the terminal. The input is structured expense data. This data is transmitted using a secure protocol (e.g., SSL / TLS). The output is the secure transmission of data to the terminal. 【0608】 Step 5: 【0609】 The terminal categorizes the received expense data using a dedicated application. The input is structured expense data. In practice, it automatically categorizes expenses by comparing them with past travel data. The output displays the categorized expense items. 【0610】 Step 6: 【0611】 Before traveling, users enter a budget for each expense category. The input is a numerical budget value. Based on the terminal application, the budget for each category is set. The set budget information is then sent to the server as output. 【0612】 Step 7: 【0613】 The server monitors expense data in real time and, when it detects signs of budget overruns, sends a notification to the device that takes the user's emotional state into account. Inputs include categorized expense data, a set budget, and the user's emotional state. An emotional engine is used to analyze the emotional state and optimize the notification message. The output is an emotionally appropriate warning notification displayed on the device. 【0614】 Step 8: 【0615】 After the trip ends, the terminal automatically calculates the settlement amount for the group using expense data stored on the server. The input is all expense data from the trip. A calculation algorithm is used to determine the payment amount for each user. The settlement results are presented as output. 【0616】 Step 9: 【0617】 The server aggregates and analyzes traveler spending and sentiment data, providing it to businesses and local governments as a basis for promotional proposals. Input includes all expense and sentiment data. Business intelligence tools are used to analyze data patterns. The output is the data analysis results, which are then used in marketing strategies. 【0618】 (Application Example 2) 【0619】 Next, we will explain application example 2. In the following explanation, 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." 【0620】 There are challenges in ensuring that travelers can smoothly manage their expenses during their trips and enjoy their travels with peace of mind within their budget. Furthermore, it is necessary to improve travel satisfaction by providing information tailored to their emotional state in real time during their trips and offering personalized travel experiences. Additionally, there is a need for businesses and local governments to provide appropriate information to implement effective marketing based on travelers' spending trends. 【0621】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0622】 This invention includes a server that analyzes reservation information received online and extracts relevant expense data from that information; a server that classifies the extracted expense data and monitors the data based on a set budget; and a server that provides users with information optimized based on their emotional state. This makes it easier for travelers to manage their spending within their budget and improves their travel satisfaction by receiving information optimized to their individual emotional state. It also enables businesses and local governments to make promotional proposals based on travelers' spending data. 【0623】 "Online reservation information" refers to data related to travel and service reservations that are received by the user's digital device via electronic communication. 【0624】 "Expense data" refers to numerical or textual data containing information about expenses incurred during travel or service use. 【0625】 "Information optimized based on emotional state" refers to content and notifications that are individually tailored to take into account the user's psychological and emotional state. 【0626】 "Monitoring data based on a budget" refers to the process of evaluating and verifying actual spending in real time based on financial limits set by the user in advance. 【0627】 "Input for estimating emotional state" refers to biometric or behavioral information used for emotion estimation, such as user voice and behavioral data. 【0628】 "Making a promotional proposal" refers to the act of proposing sales promotion activities or special offers to target audiences based on predictions and analysis. 【0629】 The system to realize this application is built by integrating a traveler's device, a server located in the cloud, and an emotion engine. The server has a program that processes booking information received online, accessing the traveler's email account to retrieve booking information and receipt images. The retrieved information is analyzed using OCR technology to extract expense data such as booking numbers, amounts, and dates. Optical character recognition tools such as AWS Textract are used in this process. 【0630】 The extracted expense data is converted into structured data using a Python script on AWS Lambda and stored in DynamoDB. The data is monitored in real time based on the set budget, and notifications are sent to the user via Firebase. The notifications are optimized based on the user's emotional state. Emotion estimation is performed by analyzing the emotional state from speech input and text data using Google Cloud's Speech-to-Text and Azure's Text Analytics. 【0631】 Furthermore, after the trip ends, the system automatically calculates the total amount settled within the group on the terminal and presents the result to the user, enabling quick payment. In addition, the server aggregates and analyzes travelers' spending and sentiment data to generate promotional suggestions for businesses and local governments based on their spending trends. As a result, the user's travel experience becomes more personalized and satisfaction levels increase. 【0632】 For example, if a user uploads photos taken during a trip to the application, relevant tourist information will be provided in real time. Furthermore, a generative AI model will recommend tourist destinations and events that take the user's mood into consideration. An example of a prompt might be, "Please recommend tourist destinations to visit when I am feeling relaxed." 【0633】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0634】 Step 1: 【0635】 The server accesses the user's email account and retrieves newly received reservation information and receipt images. Based on this input data, it saves the reservation information to a database and prepares it for OCR processing. 【0636】 Step 2: 【0637】 The server analyzes the receipt image acquired using OCR technology. During this process, character recognition tools such as AWS Textract are used to extract expense data such as reservation number, amount, and date from the image. This result is output as text data and passed on to the next processing step. 【0638】 Step 3: 【0639】 The terminal processes the text data received from the server using a Python script executed on AWS Lambda, converting it into structured data. This organizes the expense data by category and stores it in DynamoDB. Obtaining structured data makes it easier for users to view expenses for each category. 【0640】 Step 4: 【0641】 The device monitors spending in real time, referencing the user's set budget and structured data stored on the server. If a potential budget overrun is detected, the device sends a notification to the user. This notification is sent using Firebase, allowing the user to instantly understand their spending situation. 【0642】 Step 5: 【0643】 The server analyzes the user's voice input using Google Cloud's Speech-to-Text and estimates their emotional state using Azure's Text Analytics. Based on the estimated emotional data and structured data, an AI model is used to generate notifications optimized for expense management, which are then provided to the user according to the prompt (e.g., "If I want to relax, please recommend a cafe."). 【0644】 Step 6: 【0645】 After the trip ends, the device downloads all expenditure data from the server and automatically calculates the settlement amount within the group. This calculation can be viewed on the user's smartphone, enabling quick remittances. The user can choose the most suitable remittance method from the presented options. 【0646】 Step 7: 【0647】 The server analyzes aggregated spending and sentiment data, and based on this, generates promotional suggestions for businesses and local governments that are tailored to consumer trends. This enables businesses and local governments to develop more effective marketing strategies. 【0648】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0649】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0650】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0651】 [Fourth Embodiment] 【0652】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0653】 As shown in Figure 7, the 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. 【0654】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0655】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0656】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0657】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0658】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0659】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0660】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0661】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0662】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0663】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0664】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0665】 One embodiment of the present invention is a system that links a traveler's device with a server located in the cloud. In this system, online reservation information and receipt images received in the traveler's email account are automatically retrieved by the server. The retrieved information is analyzed on the server using natural language processing and optical character recognition technology, and expense data such as reservation number, hotel name, date, and amount are extracted. 【0666】 The extracted expense data is sent from the server to the terminal, where a dedicated application on the terminal automatically categorizes it based on the user's itinerary. For example, hotel accommodation costs are categorized under "Accommodation," and transportation costs are categorized under "Travel." 【0667】 Users can set a budget for each category within the app before traveling. The server monitors spending in real time based on this budget information and pushes a warning message to the app on the user's device if spending approaches or exceeds the set budget. 【0668】 After the trip ends, the terminal automatically calculates the settlement amount with other participants in the group using all of the traveler's expense data stored on the server. Based on the calculation result, the user can select PayPay, bank transfer, or other electronic payment methods and send the predetermined amount to the other travelers. 【0669】 Furthermore, the server aggregates and analyzes the spending behavior of all travelers and generates effective promotional proposals for businesses and local governments based on regional consumption trends. These proposals provide businesses with a clear direction for targeting strategies to promote regional revitalization. 【0670】 This invention significantly reduces the burden of managing expenses during travel, allowing users to enjoy their trips with peace of mind, while enabling businesses and local governments to develop marketing strategies based on collected data. This system simplifies financial management during travel and provides significant value to both travelers and local communities. 【0671】 The following describes the processing flow. 【0672】 Step 1: 【0673】 The server accesses the user's email account to verify newly arrived online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0674】 Step 2: 【0675】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. The extracted data includes information such as reservation number, date, and amount. 【0676】 Step 3: 【0677】 The server analyzes the text data extracted using natural language processing and organizes and stores the necessary expense data as structured data. 【0678】 Step 4: 【0679】 The terminal receives structured expense data from the server and displays it in a dedicated application. Here, each expense is automatically categorized based on the user's itinerary. 【0680】 Step 5: 【0681】 Users can set a budget within the application. The set budget information is sent to the server and registered in the database. 【0682】 Step 6: 【0683】 The server monitors expense data received in real time based on budget registration information and detects signs of exceeding the set budget. If an overrun is anticipated, a warning message is pushed to the user's device. 【0684】 Step 7: 【0685】 After the trip ends, the terminal automatically calculates the settlement amount for each group participant using all expense data stored on the server. 【0686】 Step 8: 【0687】 Based on the calculated settlement amount, the user selects an electronic payment system through the application and completes the transfer to the other traveler. 【0688】 Step 9: 【0689】 The server aggregates spending data collected from travelers and analyzes their spending trends. Based on this analysis, it generates promotional proposals for businesses and local governments and provides them as reports. 【0690】 (Example 1) 【0691】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0692】 In modern travel, travelers are burdened with the need to manage various booking and spending data. Furthermore, efficiently managing budgets and settling group expenses during trips is difficult, often resulting in traveler stress. Additionally, there is a lack of mechanisms to accurately understand the impact of spending on local areas and provide useful information to businesses and public institutions. 【0693】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0694】 In this invention, the server includes means for acquiring information from the user's communication device, analyzing the information, and extracting relevant expense data; means for classifying the data transmitted via the communication device and monitoring the data in real time based on the user's set budget; and means for notifying the user's communication device when an overspending of the budget is expected. This enables travelers to efficiently manage their spending, and allows businesses and public institutions to develop strategies based on consumer behavior patterns. 【0695】 "User's communication device" refers to a device such as a mobile phone, tablet, or computer that a traveler uses to manage and verify their own information. 【0696】 "Acquiring and analyzing information" refers to the act of automatically collecting reservation information and receipts from electronic data such as emails and images, and then analyzing that data to extract necessary expense information. 【0697】 "Extracting expense data" is the process of identifying and organizing specific expenditure details such as date, amount, and category from the acquired information. 【0698】 "Monitoring data based on budget" is a process that tracks spending limits for each category set by the user in real time, and helps with budget management. 【0699】 "Means of notification" refers to messaging functions used to inform users of the possibility of budget overruns, and typically utilizes push notifications or email. 【0700】 "Automatically calculating and processing settlements" refers to providing a procedure that simplifies payment by calculating each person's share of expenses based on all expenses incurred within the group after the trip has ended. 【0701】 "Collecting and analyzing spending patterns" is the process of aggregating data such as purchase history during travel, identifying trends and patterns, and generating strategic information based on that. 【0702】 This invention provides a system that enables travelers to efficiently manage their expenses during their trip and stay within their budget. The system functions by linking the user's communication device with a server located in the cloud. 【0703】 The server connects to email accounts registered on the user's communication device and automatically retrieves reservation information and receipt images. This utilizes email service APIs (e.g., email provider APIs). From the retrieved data, the server uses natural language processing tools (e.g., natural language processing toolkits) and optical character recognition technology (e.g., character recognition services) to extract data related to expenses. This allows for the efficient collection of information such as reservation numbers, hotel names, dates, and amounts. 【0704】 Next, the server stores this extracted data in the cloud and, if necessary, transmits it to the user's communication device using encrypted communication. The communication device has a dedicated application installed that displays and categorizes the data based on the user's itinerary. The application can categorize expenses according to categories such as "accommodation" and "transportation." 【0705】 Before traveling, users can use this application to set a travel budget for each category. The server monitors spending in real time based on this budget information and sends push notifications as the user approaches the budget. 【0706】 Furthermore, the server aggregates and analyzes spending data from all travelers and automatically generates promotional proposals for businesses or public institutions based on local consumption trends. These proposals enable businesses to receive targeted strategies aimed at revitalizing their local areas. 【0707】 As a concrete example, consider a traveler planning a trip to a certain country and managing various expenses (accommodation, transportation, etc.) during the trip. By using this system, they can prevent exceeding their budget and enjoy their trip with peace of mind. An example of a prompt would be, "Suggest ways to help with travel budget management. In particular, focus on ways to streamline the management of accommodation and transportation expenses during the trip." 【0708】 This system not only reduces the burden on users but also brings data-driven value to the local economy. 【0709】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0710】 Step 1: 【0711】 The user sets up an email account on their communication device (smartphone or computer). The configured account information is sent to the server. This allows the server to obtain authentication information to access the user's email data. 【0712】 Step 2: 【0713】 The server uses the acquired authentication information to connect to the email service API and check for new emails. It filters the emails to find those containing keywords related to reservations or expenses (e.g., "reservation confirmation" or "receipt"). The detected emails and their attachments are selected for the next processing. 【0714】 Step 3: 【0715】 The server applies natural language processing tools and optical character recognition (OCR) technology to the selected emails and attachments. The input data is analyzed, and relevant data such as amounts, dates, and reservation numbers are extracted. This generates structured expense data. 【0716】 Step 4: 【0717】 The server stores the extracted data in a cloud database. The stored data is protected from unauthorized access using encryption technology, thus ensuring user privacy. 【0718】 Step 5: 【0719】 The server transmits data stored in the cloud to the user's communication device using a secure communication method. A dedicated application on the user's communication device receives the data and prepares it for visualization and organization. 【0720】 Step 6: 【0721】 The terminal categorizes the received data within the application. The input is data received from the server, and the output is information organized by categories such as "accommodation" and "meals." This categorization makes it easy for users to visually review their expenses. 【0722】 Step 7: 【0723】 Users set budgets for each category using the application. This allows the server to monitor spending in real time. 【0724】 Step 8: 【0725】 The server sends an alert notification to the communication device when a user's spending approaches their set budget. This allows the user to review their spending and plan to stay within their budget. 【0726】 Step 9: 【0727】 After the trip ends, the terminal automatically settles accounts among the group using all expense data stored on the server. Based on the entered data, the settlement calculation is performed, and the output shows each user's share of the expenses. 【0728】 Step 10: 【0729】 The server aggregates and analyzes spending data from all users. Based on the results, it generates and outputs promotional proposals for companies and local governments. This enables effective marketing that takes into account local consumer behavior. 【0730】 (Application Example 1) 【0731】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0732】 There is a problem in that travelers have difficulty effectively managing and settling their expenses during and after their trips. Furthermore, there is the challenge of the considerable effort and time required to accurately understand local consumption trends and use that information for targeted marketing. 【0733】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0734】 This invention includes a server that includes means for analyzing reservation information received online and extracting relevant expense data from that information; means for classifying the extracted expense data and monitoring the data based on a set budget; means for notifying the user when signs of budget overrun are detected; means for automatically calculating the settlement amount within the group after the trip and automating the remittance process; means for aggregating and analyzing travelers' spending data and making promotional proposals to businesses or local governments; means for facilitating smooth payments using electronic payment methods based on consumption trend data; and means for automatically analyzing spending history and predicting future spending trends before issuing budget overrun warnings. This enables efficient management of spending during travel, streamlining settlement processing, and effective marketing based on local consumption trends. 【0735】 "Reservation information" refers to information issued when using online services such as travel or accommodation, which includes details such as the date, time, location, and price. 【0736】 "Expense data" refers to data related to expenses incurred in connection with travel, and includes information such as hotel accommodation fees and transportation costs. 【0737】 "Classification" is the act of dividing extracted expense data into specific categories, a technique that makes management and analysis easier. 【0738】 "Budget monitoring" is the process of tracking how much actual spending is progressing based on a budget set in advance by the user, in order to prevent budget overruns. 【0739】 "Notification" is the act of informing a user of information, and is often used as a means to provide warnings or confirmations in real time. 【0740】 The "settlement amount" is the value obtained after reviewing the allocation of expenses at the end of the trip and calculating the amount each person in the group should bear. 【0741】 "Money transfer" refers to the process of sending money to another user or service provider, and includes the use of digital payment methods. 【0742】 "Expense data aggregation" refers to the act of compiling all expenses incurred during a trip and organizing them into a series of data. 【0743】 "Promotional proposals" refer to the act of proposing marketing strategies to businesses and local governments based on collected and analyzed data. 【0744】 "Payment methods" is a general term for the methods and means used by users to pay for goods or services, and includes electronic methods. 【0745】 "Consumption history" refers to a record of a user's past spending and is fundamental information for predicting future spending trends. 【0746】 To realize this invention, the system mainly consists of a server and a user terminal. The server is equipped with a program that analyzes reservation information received online and extracts expense data. This program uses Python's natural language processing library (NLTK) and optical character recognition tool (Tesseract OCR) to analyze the necessary data from emails and images. The analyzed data is stored in a database in real time using Firebase. The server analyzes this data, monitors how far spending has progressed based on the user's budget settings, and sends push notifications as needed. 【0747】 On the terminal side, users can input their budget through a dedicated application and monitor expenses in real time based on that budget. This app also has a function to warn users if they are about to exceed their budget and to predict future spending based on their spending history. After the trip is over, the system uses server data to automatically calculate settlements within the group and allows payment to be made using a specific electronic payment method. 【0748】 As a concrete example, when a user checks into a hotel during a trip, the reservation confirmation email is automatically processed on the server, and the accommodation cost is categorized into the "Accommodation" category in the app. The application then runs on the device, displaying real-time warnings before the budget is exceeded. While reviewing the spending data, the user can enter prompts into the app, such as "Which category does this expense fall into?" or "Please tell me my travel spending status for this month," and receive immediate feedback from the system. 【0749】 Through this system, users can easily manage their travel expenses and enjoy peace of mind and efficiency while traveling by seamlessly settling accounts and making payments after their trip. 【0750】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0751】 Step 1: 【0752】 The server receives user reservation information and images from online sources as input. This information includes emails and scanned receipt images. The server uses a natural language processing library (NLTK) and an optical character recognition tool (Tesseract OCR) to output expense data such as reservation number, hotel name, date, and amount in text format. 【0753】 Step 2: 【0754】 The server stores the extracted expense data in a database for classification. This process involves the server accessing a real-time database (Firebase) and organizing the data by category. For example, accommodation expenses are categorized under "accommodation" and stored in the database as data related to that category. 【0755】 Step 3: 【0756】 The server monitors expense data in real time based on budget information entered by the user in advance. The server compares the budget with actual spending, and if an overspending is anticipated, it sends a warning to the device using a push notification function. This makes budget management easy for users. 【0757】 Step 4: 【0758】 The terminal receives all expense data from the server after the trip ends. The user then uses the application to initiate settlement within the group. The terminal aggregates each participant's expenses, calculates the total settlement amount, and displays the result. This allows the user to view detailed data for settlement. 【0759】 Step 5: 【0760】 The user makes an electronic payment based on the result displayed after settlement. The terminal makes the payment to the other user via the selected payment method (e.g., an electronic payment system). In this step, the terminal quickly transfers the required amount and notifies that the payment is complete. 【0761】 Step 6: 【0762】 The server aggregates spending data from all travelers and generates promotional proposals for businesses and local governments. At this stage, the server analyzes consumer trends and creates reports to derive effective marketing strategies. This output is used by businesses and local governments as a guide for regional revitalization. 【0763】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0764】 In embodiments of the present invention, a system is provided that integrates a terminal owned by the traveler, a server located in the cloud, and an emotion engine. This system accesses the user's email account to retrieve newly received online reservation information and receipt images on the server. The retrieved information is analyzed on the server using optical character recognition (OCR) to extract expense data such as reservation number, amount, and date. 【0765】 The server analyzes the extracted expense data using natural language processing and stores it as structured data. This structured data is sent to the terminal, where a dedicated application automatically categorizes the expenses according to the user's itinerary. 【0766】 In the expense management application, users enter their budget for each category before traveling. Based on this, the server monitors the expense data in real time and sends a warning notification to the user's device if it detects a potential budget overrun. 【0767】 This notification is optimized according to the user's emotional state. The emotion engine analyzes the user's voice input and past behavioral data to estimate their emotional state. For example, if the user is in a relaxed emotional state, the notification message can be composed in a calm tone. 【0768】 After the trip ends, the device uses expense data stored on the server to automatically calculate the settlement amount within the group and presents payment methods. Users can utilize this function to easily complete the payment process. 【0769】 Furthermore, the server aggregates and analyzes traveler spending and emotional data to understand consumption trends. This allows for the generation of emotionally-based promotional suggestions for businesses and local governments, enabling the formation of more effective marketing strategies. 【0770】 This invention aims to improve user satisfaction by integrating expense management with an understanding of emotions, thereby providing users with a more personalized travel experience. Furthermore, it aims to contribute to the revitalization of businesses and local governments through promotions that enhance their contribution to the local community. 【0771】 The following describes the processing flow. 【0772】 Step 1: 【0773】 The server accesses the user's email account to verify newly received online reservation information and receipt images. The verified information is automatically downloaded to the server. 【0774】 Step 2: 【0775】 The server uses optical character recognition (OCR) technology to extract text data from the downloaded information. This text data includes reservation numbers, amounts, dates, and other information. 【0776】 Step 3: 【0777】 The server applies natural language processing to the extracted text data for analysis, organizes the necessary expense data as structured data, and stores it in the database. 【0778】 Step 4: 【0779】 The terminal receives structured expense data from the server and displays it in a dedicated application. This application automatically categorizes each expense based on the user's itinerary. 【0780】 Step 5: 【0781】 Users set budgets for each expenditure category within the application on their device. This budget information is sent to the server and used as a basis for expense monitoring. 【0782】 Step 6: 【0783】 The device provides the user's voice input and behavioral data to the emotion engine. The emotion engine uses this data to estimate the user's emotional state. 【0784】 Step 7: 【0785】 The server monitors expense data in real time based on the set budget and sends a notification to the user's device if it detects a potential budget overrun. The content and tone of this notification are adjusted based on the results of the sentiment engine. 【0786】 Step 8: 【0787】 At the end of the trip, the device retrieves all expense data from the server and automatically calculates the settlement amount for each group participant. Users can easily complete the payment process through the recommended payment method on the device. 【0788】 Step 9: 【0789】 The server aggregates traveler spending and sentiment data to generate promotional suggestions for businesses and local governments. These suggestions take into account consumption trends based on the aggregated sentiment states. 【0790】 (Example 2) 【0791】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0792】 This invention relates to a system for efficiently managing travel expenses, and more particularly to supporting users' budget management in real time and reducing the risk of exceeding the budget. Conventional systems have problems with budget management becoming complicated due to insufficient optimization of expense classification and notifications. In addition, there is a lack of notification systems that take into account the emotional state of travelers, which limits the improvement of the user experience. 【0793】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0794】 In this invention, the server includes means for analyzing received reservation information and extracting relevant cost data, means for classifying the extracted cost data and monitoring the data based on a set budget, and means for analyzing the user's emotional state and optimizing notification content according to that emotion. This makes it possible to streamline user budget management, reduce the risk of exceeding the budget, and provide notifications that are sensitive to the user's emotions. 【0795】 "Received reservation information" refers to electronic data containing reservation details related to travel, which is used to analyze expense data. 【0796】 "Expense data" refers to data containing information about various travel expenses, including elements such as reservation number, amount, and date. 【0797】 A "classification method" is a function for dividing extracted cost data into categories based on specific criteria. 【0798】 "Means of notifying users" refers to a function that sends warnings or information to users when signs of budget overruns are detected. 【0799】 "Means for analyzing emotional state" refers to a function that estimates the user's current emotional state based on their words, actions, and past behavior. 【0800】 "Method for automatically calculating settlement figures" refers to a function that automatically calculates the amount needed to settle expenses between travelers after the trip is completed. 【0801】 "Means of automating the remittance process" refers to a function that allows users to easily complete the remittance process based on the settled amount. 【0802】 "Means for aggregating and analyzing consumption data" refers to a function that collects and analyzes travelers' spending information to reveal consumption trends and behavioral patterns. 【0803】 "Means of proposing promotions" refers to a function that proposes effective sales activities and marketing strategies to businesses and local governments based on aggregated data. 【0804】 This invention provides a system for efficiently managing travel expenses. It mainly consists of a traveler's terminal, a server located in the cloud, and an emotion engine that analyzes the user's emotional state. 【0805】 The server analyzes reservation information and receipt images received by the user via their terminal using optical character recognition software. Specifically, it uses software such as "Tesseract" to extract expense data such as reservation numbers, amounts, and dates from email text and images. This extracted data is then analyzed using natural language processing libraries such as "spaCy" and "NLTK". Based on these analysis results, the server generates structured data and sends it to the terminal. 【0806】 The terminal is operated through a dedicated application that automatically categorizes expenses according to the user's itinerary based on the structured data received. Furthermore, the user can enter a budget for each expense category in this application before the trip. Based on this configured budget information, the server monitors the expense data in real time, and if there are signs of budget overrun, the emotion engine analyzes the user's current emotional state and sends a warning notification in an appropriate tone. 【0807】 When the user is relaxed, notification messages are delivered in a calm tone. Furthermore, once the trip is complete, the device uses expense data stored on the server to automatically calculate the total amount due within the group and presents the appropriate payment procedure. This allows the user to process payments quickly and easily. 【0808】 Furthermore, the server can analyze the collected traveler consumption and sentiment data, and based on the results, it can provide a platform for implementing promotional proposals to businesses and local governments, thereby supporting more effective marketing strategies. 【0809】 As a concrete example, one could collect expense information along with emotional records of shopping experiences a user had during a trip, and then use that data to suggest discount promotions at stores. An example of a prompt to the generating AI model would be, "Organize the expense data for my New York trip and optimize warning notifications about potential budget overruns." This prompt would allow the system to perform detailed processing to improve the user experience. 【0810】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0811】 Step 1: 【0812】 The user receives travel-related booking information via email using their device. Input includes the email content and attachments. The device sends this information to a server in the cloud, filtering the email subject, body, and attachments to identify relevant information. The output is the booking data extracted and sent to the server. 【0813】 Step 2: 【0814】 The server analyzes received email information using optical character recognition (OCR) software. Input includes both email text and images. Specifically, it uses OCR tools such as "Tesseract" to extract text data from emails and images. The output includes expense data such as reservation numbers, amounts, and dates. 【0815】 Step 3: 【0816】 The server analyzes the extracted cost data using natural language processing techniques. The input is raw text data obtained through OCR. Natural language processing libraries such as "spaCy" and "NLTK" are used to structure the data and divide it into semantic categories. The output is structured cost data. 【0817】 Step 4: 【0818】 The server sends the generated structured data to the terminal. The input is structured expense data. This data is transmitted using a secure protocol (e.g., SSL / TLS). The output is the secure transmission of data to the terminal. 【0819】 Step 5: 【0820】 The terminal categorizes the received expense data using a dedicated application. The input is structured expense data. In practice, it automatically categorizes expenses by comparing them with past travel data. The output displays the categorized expense items. 【0821】 Step 6: 【0822】 Before traveling, users enter a budget for each expense category. The input is a numerical budget value. Based on the terminal application, the budget for each category is set. The set budget information is then sent to the server as output. 【0823】 Step 7: 【0824】 The server monitors expense data in real time and, when it detects signs of budget overruns, sends a notification to the device that takes the user's emotional state into account. Inputs include categorized expense data, a set budget, and the user's emotional state. An emotional engine is used to analyze the emotional state and optimize the notification message. The output is an emotionally appropriate warning notification displayed on the device. 【0825】 Step 8: 【0826】 After the trip ends, the terminal automatically calculates the settlement amount for the group using expense data stored on the server. The input is all expense data from the trip. A calculation algorithm is used to determine the payment amount for each user. The settlement results are presented as output. 【0827】 Step 9: 【0828】 The server aggregates and analyzes traveler spending and sentiment data, providing it to businesses and local governments as a basis for promotional proposals. Input includes all expense and sentiment data. Business intelligence tools are used to analyze data patterns. The output is the data analysis results, which are then used in marketing strategies. 【0829】 (Application Example 2) 【0830】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0831】 There are challenges in ensuring that travelers can smoothly manage their expenses during their trips and enjoy their travels with peace of mind within their budget. Furthermore, it is necessary to improve travel satisfaction by providing information tailored to their emotional state in real time during their trips and offering personalized travel experiences. Additionally, there is a need for businesses and local governments to provide appropriate information to implement effective marketing based on travelers' spending trends. 【0832】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0833】 This invention includes a server that analyzes reservation information received online and extracts relevant expense data from that information; a server that classifies the extracted expense data and monitors the data based on a set budget; and a server that provides users with information optimized based on their emotional state. This makes it easier for travelers to manage their spending within their budget and improves their travel satisfaction by receiving information optimized to their individual emotional state. It also enables businesses and local governments to make promotional proposals based on travelers' spending data. 【0834】 "Online reservation information" refers to data related to travel and service reservations that are received by the user's digital device via electronic communication. 【0835】 "Expense data" refers to numerical or textual data containing information about expenses incurred during travel or service use. 【0836】 "Information optimized based on emotional state" refers to content and notifications that are individually tailored to take into account the user's psychological and emotional state. 【0837】 "Monitoring data based on a budget" refers to the process of evaluating and verifying actual spending in real time based on financial limits set by the user in advance. 【0838】 "Input for estimating emotional state" refers to biometric or behavioral information used for emotion estimation, such as user voice and behavioral data. 【0839】 "Making a promotional proposal" refers to the act of proposing sales promotion activities or special offers to target audiences based on predictions and analysis. 【0840】 The system to realize this application is built by integrating a traveler's device, a server located in the cloud, and an emotion engine. The server has a program that processes booking information received online, accessing the traveler's email account to retrieve booking information and receipt images. The retrieved information is analyzed using OCR technology to extract expense data such as booking numbers, amounts, and dates. Optical character recognition tools such as AWS Textract are used in this process. 【0841】 The extracted expense data is converted into structured data using a Python script on AWS Lambda and stored in DynamoDB. The data is monitored in real time based on the set budget, and notifications are sent to the user via Firebase. The notifications are optimized based on the user's emotional state. Emotion estimation is performed by analyzing the emotional state from speech input and text data using Google Cloud's Speech-to-Text and Azure's Text Analytics. 【0842】 Furthermore, after the trip ends, the system automatically calculates the total amount settled within the group on the terminal and presents the result to the user, enabling quick payment. In addition, the server aggregates and analyzes travelers' spending and sentiment data to generate promotional suggestions for businesses and local governments based on their spending trends. As a result, the user's travel experience becomes more personalized and satisfaction levels increase. 【0843】 For example, if a user uploads photos taken during a trip to the application, relevant tourist information will be provided in real time. Furthermore, a generative AI model will recommend tourist destinations and events that take the user's mood into consideration. An example of a prompt might be, "Please recommend tourist destinations to visit when I am feeling relaxed." 【0844】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0845】 Step 1: 【0846】 The server accesses the user's email account and retrieves newly received reservation information and receipt images. Based on this input data, it saves the reservation information to a database and prepares it for OCR processing. 【0847】 Step 2: 【0848】 The server analyzes the receipt image acquired using OCR technology. During this process, character recognition tools such as AWS Textract are used to extract expense data such as reservation number, amount, and date from the image. This result is output as text data and passed on to the next processing step. 【0849】 Step 3: 【0850】 The terminal processes the text data received from the server using a Python script executed on AWS Lambda, converting it into structured data. This organizes the expense data by category and stores it in DynamoDB. Obtaining structured data makes it easier for users to view expenses for each category. 【0851】 Step 4: 【0852】 The device monitors spending in real time, referencing the user's set budget and structured data stored on the server. If a potential budget overrun is detected, the device sends a notification to the user. This notification is sent using Firebase, allowing the user to instantly understand their spending situation. 【0853】 Step 5: 【0854】 The server analyzes the user's voice input using Google Cloud's Speech-to-Text and estimates their emotional state using Azure's Text Analytics. Based on the estimated emotional data and structured data, an AI model is used to generate notifications optimized for expense management, which are then provided to the user according to the prompt (e.g., "If I want to relax, please recommend a cafe."). 【0855】 Step 6: 【0856】 After the trip ends, the device downloads all expenditure data from the server and automatically calculates the settlement amount within the group. This calculation can be viewed on the user's smartphone, enabling quick remittances. The user can choose the most suitable remittance method from the presented options. 【0857】 Step 7: 【0858】 The server analyzes aggregated spending and sentiment data, and based on this, generates promotional suggestions for businesses and local governments that are tailored to consumer trends. This enables businesses and local governments to develop more effective marketing strategies. 【0859】 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0860】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0861】 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0862】 Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0863】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0864】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0865】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0866】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0867】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0868】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0869】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0870】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0871】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0872】 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. 【0873】 Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0874】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0875】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0876】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0877】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0878】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0879】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0880】 The following is further disclosed regarding the embodiments described above. 【0881】 (Claim 1) 【0882】 A means for analyzing reservation information received online and extracting relevant expense data from that information, 【0883】 A means of classifying extracted expense data and monitoring that data based on a set budget, 【0884】 A means of notifying users when signs of budget overruns are detected, 【0885】 A method to automatically calculate the total amount to be paid within the group after the trip and automate the remittance process, 【0886】 A means of collecting and analyzing traveler spending data and making promotional proposals to businesses or local governments, 【0887】 A system that includes this. 【0888】 (Claim 2) 【0889】 The system according to claim 1, which extracts expense data from received emails or images using optical character recognition. 【0890】 (Claim 3) 【0891】 The system according to claim 1, which includes a means for having the user input a budget setting and monitoring expenditures in real time based on that budget. 【0892】 "Example 1" 【0893】 (Claim 1) 【0894】 A means for acquiring information from the user's communication device, analyzing that information, and extracting related cost data, 【0895】 A means of classifying data transmitted via communication equipment and monitoring that data in real time based on a user-defined budget, 【0896】 A means of notifying users' communication devices when an overrun is expected, 【0897】 A means to automatically calculate expenses after the trip ends and facilitate electronic payment processing, 【0898】 A means of aggregating travelers' spending patterns and providing information and suggestions to companies or public institutions based on the analysis results, 【0899】 A system that includes this. 【0900】 (Claim 2) 【0901】 The system according to claim 1, which extracts cost data from analyzed electronic communications or images using character recognition. 【0902】 (Claim 3) 【0903】 The system according to claim 1, which includes a means for allowing users to set a predetermined budget and for monitoring expenditures in real time using a communication device based on that setting. 【0904】 "Application Example 1" 【0905】 (Claim 1) 【0906】 A means for analyzing reservation information received online and extracting relevant expense data from that information, 【0907】 A means of classifying extracted expense data and monitoring that data based on a set budget, 【0908】 A means of notifying users when signs of budget overruns are detected, 【0909】 A method to automatically calculate the total amount to be paid within the group after the trip and automate the remittance process, 【0910】 A means of collecting and analyzing traveler spending data and making promotional proposals to businesses or local governments, 【0911】 Based on consumer trend data, a means to enable smooth payments using electronic payment methods, 【0912】 Before issuing a budget overrun warning, a means to automatically analyze consumption history and predict future spending trends is provided. 【0913】 A system that includes this. 【0914】 (Claim 2) 【0915】 The system according to claim 1, which extracts expense data from received emails or images using optical character recognition. 【0916】 (Claim 3) 【0917】 The system according to claim 1, which includes means for having the user input a budget setting, monitoring expenditures in real time based on that budget, and predicting future expenses and notifying warnings. 【0918】 "Example 2 of combining an emotion engine" 【0919】 (Claim 1) 【0920】 A means for analyzing received reservation information and extracting relevant cost data from that information, 【0921】 A means of classifying extracted cost data and monitoring that data based on a set budget, 【0922】 A means of notifying users when signs of budget overruns are detected, 【0923】 A means to analyze the user's emotional state and optimize notification content according to that emotion, 【0924】 A method to automatically calculate the settlement amount within the group after the trip ends and automate the remittance process, 【0925】 A means of collecting and analyzing traveler spending data and making promotional proposals to organizations or local governments, 【0926】 A system that includes this. 【0927】 (Claim 2) 【0928】 The system according to claim 1, which extracts cost data from received electronic messages or visual data using optical character recognition. 【0929】 (Claim 3) 【0930】 The system according to claim 1, which includes a means for having the user input a budget setting and monitoring consumption in real time based on that budget. 【0931】 "Application example 2 when combining with an emotional engine" 【0932】 (Claim 1) 【0933】 A means for analyzing reservation information received online and extracting relevant expense data from that information, 【0934】 A means of classifying extracted expense data and monitoring that data based on a set budget, 【0935】 A means of notifying users when signs of budget overruns are detected, 【0936】 A method to automatically calculate the total amount to be paid within the group after the trip and automate the remittance process, 【0937】 A means of collecting and analyzing traveler spending data and making promotional proposals to businesses or local governments, 【0938】 A means of providing users with information optimized based on their emotional state, 【0939】 A means for analyzing input to estimate the user's emotional state, 【0940】 A system that includes this. 【0941】 (Claim 2) 【0942】 The system according to claim 1, which extracts expense data from received electronic communications or images using character recognition technology. 【0943】 (Claim 3) 【0944】 The system according to claim 1, which includes means for having the user input a budget setting, monitoring expenditures in real time based on that budget, and generating notifications that respond to emotions. [Explanation of Symbols] 【0945】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means for analyzing reservation information received online and extracting relevant expense data from that information, A means of classifying extracted expense data and monitoring that data based on a set budget, A means of notifying users when signs of budget overruns are detected, A method to automatically calculate the total amount to be paid within the group after the trip and automate the remittance process, A means of collecting and analyzing traveler spending data and making promotional proposals to businesses or local governments, A system that includes this. [Claim 2] The system according to claim 1, which extracts expense data from a received email or image using optical character recognition. [Claim 3] The system according to claim 1, which includes a means for having the user input a budget setting and monitoring expenditures in real time based on that budget.

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