system

Abstract

We provide the system. [Solution] A means of accepting business trip applications, A means of analyzing the received travel application data, Based on the analysis results, a method is provided to recommend a suitable mode of transportation for the business trip location and appointment time. A method for booking and arranging recommended transportation, Based on the analysis results, a means of recommending accommodations that meet the user's desired conditions, A method for booking recommended accommodations, A system that includes a means of notifying the user of the results of the reservation process.

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, after applying for a business trip, it was necessary to separately arrange reservations for transportation means and accommodation facilities, which posed problems of taking a lot of time and effort for users. Also, it was difficult to arrange according to the user's preferences for seats and accommodation, resulting in low satisfaction. As a result, there were problems of reduced overall work efficiency and increased stress.

Means for Solving the Problems

[0005] This invention provides a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. Specifically, the system includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended transportation, means for recommending accommodation that meets the user's preferences based on the analysis results, means for booking the recommended accommodation, and means for notifying the user of the booking results. Furthermore, by including means for recommending the user's preferred seating location and accommodation options based on the business trip request data, user satisfaction can be enhanced. This makes it possible to reduce administrative time before business trips and provide users with a comfortable business trip preparation experience.

[0006] A "business trip application" refers to an application document that contains detailed plans and information regarding a business trip.

[0007] "Analysis" refers to data processing that extracts and analyzes necessary information based on travel application data in order to provide appropriate recommendations.

[0008] "Transportation" refers to the means of transport that users use to travel to their business destination, such as bullet trains or airplanes.

[0009] "Recommendation" refers to the act of suggesting the most suitable option to the user based on analysis results.

[0010] "Booking arrangements" refers to the process of actually making reservations for recommended transportation and accommodation.

[0011] "Accommodation" refers to the place where a user stays during a business trip, such as a hotel or business hotel.

[0012] "Seat location" refers to a window seat or aisle seat on a bullet train or airplane.

[0013] "Accommodation options" refer to additional choices or services related to accommodation, such as non-smoking or smoking options, and whether or not breakfast is included.

[0014] A "user" refers to an individual or company representative who uses this system to plan, apply for, and arrange business trips. [Brief explanation of the drawing]

[0015] [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] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This 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 the 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 the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered 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.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered 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.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. The program for this system is implemented through the interaction of multiple servers, terminals, and users.

[0037] Program processing

[0038] 1. Enter and submit travel request

[0039] The user uses a terminal to submit a business trip request. They enter detailed information into the request form, including departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0040] The terminal sends the entered travel request data to the server.

[0041] 2. Receiving and analyzing travel request data

[0042] The server receives travel request data sent from the terminal. The server analyzes the received data and breaks it down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0043] 3. Recommendations for modes of transportation

[0044] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the most suitable mode of transportation from the departure point to the business trip destination. Based on the user's preference, it selects a window or aisle seat for Shinkansen travel. It also selects the most suitable flight to ensure the user arrives on time for their appointment.

[0045] For example, for a business trip from Tokyo to Osaka, the system would recommend the 9:00 AM Shinkansen "Nozomi" and suggest a window seat of the customer's choice.

[0046] 4. Accommodation Recommendations

[0047] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and include breakfast.

[0048] 5. Automated booking arrangement

[0049] The server accesses the recommended Shinkansen or airline reservation API and processes the reservation for the mode of transport. During this process, it secures seats that match the user's preferences.

[0050] Similarly, the system accesses the accommodation booking API and proceeds with booking the recommended accommodations. It also retrieves details such as the booking confirmation number and check-in / check-out times.

[0051] 6. Sending a confirmation notice

[0052] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0053] The device receives the notification and displays it to the user.

[0054] Specific example

[0055] For example, let's say Mr. Suzuki plans a business trip from Tokyo to Osaka. Mr. Suzuki enters the necessary information into a business trip application form on his terminal and submits it. The server receives and analyzes this information and recommends the Shinkansen "Nozomi" departing at 9:00 AM and a business hotel in Osaka. Once the reservations are complete, the details are notified to Mr. Suzuki's terminal.

[0056] Thus, the present invention provides a system that automates the entire process from business trip application to recommendations, booking arrangements, and notifications, enabling users to prepare for business trips smoothly and efficiently.

[0057] The following describes the processing flow.

[0058] Step 1:

[0059] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0060] Step 2:

[0061] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[0062] Step 3:

[0063] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0064] Step 4:

[0065] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches the database for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[0066] Step 5:

[0067] The server selects the most suitable mode of transportation from a list of options, reflecting the user's preferences. For example, in the case of a bullet train, it considers the user's preference for a window or aisle seat. The selection result is then saved.

[0068] Step 6:

[0069] The server accesses the accommodation database. Based on the analysis results, it selects accommodations that meet the user's desired conditions (business hotel, non-smoking room, breakfast included, etc.) from the list of recommended options.

[0070] Step 7:

[0071] The server recommends booking transportation and accommodation. Here, you access the transportation booking API to secure seats on the selected bullet train or airline.

[0072] Step 8:

[0073] The server accesses the accommodation booking API and processes the booking for the selected accommodation. It retrieves details such as the booking confirmation number and check-in / check-out times.

[0074] Step 9:

[0075] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0076] Step 10:

[0077] The device receives a notification and displays it to the user. The user can then review the reservation details and request modifications or re-recommendations as needed.

[0078] Through this series of processes, users can efficiently prepare for their business trips.

[0079] (Example 1)

[0080] 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."

[0081] Traditional business travel application and booking systems require users to manually search for and book transportation and accommodations individually, which is time-consuming and cumbersome. Furthermore, finding the optimal option that meets the user's requirements can be difficult. Additionally, errors and deficiencies in verification during the booking process can occur. Therefore, there is a need for a system that automates the entire process from user business travel application to booking arrangements, ensuring efficiency and accuracy.

[0082] 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.

[0083] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the booking procedure results, means for accessing databases of transportation and accommodation, and means for acquiring and storing booking information. This enables the user to automate and efficiently and accurately perform a series of processes from business trip requests to recommendations of transportation and accommodation, booking arrangements, and notification.

[0084] The "means for accepting business trip requests" refer to a function that receives business trip information entered by the user via a terminal and incorporates that information into the system as an initial dataset.

[0085] "Methods for analyzing received business trip application data" refers to a function that analyzes received business trip application data, breaks it down into elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions, and extracts the necessary information.

[0086] The "means of recommending transportation" is a function that suggests the optimal mode of transport from the user's departure point to their business trip destination based on analysis results. This also takes into account the user's preferences for transportation (e.g., window seats or aisle seats).

[0087] The "means of booking and arranging transportation" refers to a function that accesses a booking API for recommended transportation options, automatically performs the booking process, and sets details such as seat selection.

[0088] The "means of recommending accommodations" refer to a function that suggests the most suitable accommodations that meet the user's desired conditions based on analysis results. This also takes into account accommodation options (e.g., non-smoking rooms, breakfast included).

[0089] The "means of booking accommodations" refer to a function that accesses the booking API of recommended accommodations and automatically completes the booking process. It also retrieves the booking confirmation number and detailed information.

[0090] The "means of notifying users of the results of the booking process" refer to a function that summarizes the results of bookings for transportation and accommodation and notifies the user. The notification content includes the booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc.

[0091] "Means of accessing databases of transportation and accommodation" refers to the function of accessing databases containing information on transportation and accommodation and retrieving the necessary information. This includes calling external APIs and SQL queries.

[0092] "Means for acquiring and saving reservation information" refers to a function that securely stores reservation information obtained during the reservation process for transportation and accommodation within the system, making it accessible for later reference.

[0093] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. This system is implemented through the interaction of multiple servers, terminals, and users.

[0094] System hardware and software configuration

[0095] server:

[0096] The server has a high-performance processor (e.g., Intel Xeon), ample memory (e.g., 32GB RAM), and large-capacity storage (e.g., SSD). The server also has the following software installed:

[0097] Operating System: Linux (registered trademark) (e.g., Ubuntu 20.04)

[0098] Database: MySQL (registered trademark) or PostgreSQL

[0099] Scripting language: Python (e.g., Python 3.8)

[0100] Web server: Apache (registered trademark) or Nginx

[0101] API server: Flask or Django

[0102] Terminal:

[0103] The terminal is a device used by users to enter travel expense requests. Generally, a PC, tablet, or smartphone is used. The terminal has the following configuration:

[0104] Operating Systems: Windows, macOS®, iOS, or Android®

[0105] Web browsers: Google Chrome (registered trademark), Safari, or Edge

[0106] Network connection: Connect to the Internet

[0107] User:

[0108] The user is the person who operates the terminal to submit a travel request. The user accesses the system using a web browser and enters the necessary information.

[0109] Specific processing of the program

[0110] Entering and submitting a travel request

[0111] The user uses their device to access the business trip application form and enters the required information (e.g., departure location, departure date and time, destination, appointment time, preferred mode of transportation, and desired accommodation).

[0112] The terminal verifies the entered information in real time, and provides a submit button only after confirming that all required fields have been filled in.

[0113] After the send button is pressed, the terminal converts the input data into JSON format, encrypts it using SSL, and sends it to the server.

[0114] Receiving and analyzing travel request data

[0115] The server receives JSON data sent from the terminal.

[0116] The server analyzes the received data and extracts information such as the departure location, departure date and time, business trip destination, appointment time, preferred mode of transportation, and desired accommodation conditions.

[0117] Recommendations for transportation and accommodation

[0118] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the most suitable mode of transportation. This also takes into account the user's seating preferences.

[0119] The server accesses a database of accommodations and searches for properties that meet the user's desired criteria. Specifically, this includes options such as non-smoking rooms and breakfast included.

[0120] Automatic booking arrangement

[0121] The server accesses the booking APIs for recommended transportation and accommodations and automatically makes reservations. This includes seat selection and obtaining booking confirmation numbers.

[0122] Sending confirmation notice

[0123] The server compiles the results of the reservation process and notifies the user's terminal.

[0124] The terminal displays notifications received from the server to the user. These may include things like departure time and reservation confirmation number.

[0125] Specific example

[0126] For example, suppose a user enters the following information for a business trip:

[0127] Departure point: Tokyo

[0128] Departure date and time: December 10, 2023, 9:00 AM

[0129] Business trip destination: Osaka

[0130] Appointment time: December 10, 2023, 1:00 PM

[0131] Transportation preference: Shinkansen (bullet train), window seat

[0132] Accommodation preferences: Business hotel, non-smoking room, breakfast included

[0133] The server analyzes this data and recommends the best seats on the Shinkansen "Nozomi" and a business hotel in Osaka. Once the recommended transportation and accommodation bookings are complete, the details are notified to the user's device.

[0134] Example of a prompt

[0135] "A user is planning a business trip from Tokyo to Osaka. Please recommend transportation and accommodation based on the user's preferences and automatically make the reservations. The departure point is Tokyo, the departure date and time is 9:00 AM on December 10, 2023, the destination is Osaka, the appointment time is 1:00 PM on December 10, 2023, and the expected return date and time is 10:00 AM on December 11, 2023. The user prefers to travel by Shinkansen (bullet train), and if possible, please select a window seat. For accommodation, the user prefers a business hotel with a non-smoking room and an option for breakfast."

[0136] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0137] Step 1:

[0138] The user accesses the business trip application form using their device and enters the required information (departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation).

[0139] Input: Various travel application information entered by the user.

[0140] Output: Travel request data displayed on the terminal

[0141] Step 2:

[0142] The terminal verifies the entered information in real time, confirming that all required fields have been filled in. After verification, it provides a submit button. When the user presses the submit button, the terminal converts the travel request data into JSON format, encrypts it using SSL, and sends it to the server.

[0143] Input: Travel request data after the user presses the submit button.

[0144] Output: Encrypted JSON data sent to the server

[0145] Step 3:

[0146] The server receives JSON data sent from the terminal. After receiving the data, it first verifies the integrity and completeness of the data. Next, it parses the received JSON data and extracts the necessary information (departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions).

[0147] Input: Encrypted travel request data (JSON format)

[0148] Output: Elemental data such as departure point, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions after analysis.

[0149] Step 4:

[0150] The server accesses a database of Shinkansen (bullet train) and airline schedules and searches for the most suitable mode of transportation based on the business trip application data. The user's transportation preferences (e.g., Shinkansen, window seat) are also taken into consideration. For example, for a business trip from Tokyo to Osaka, the server recommends the 9:00 AM Shinkansen "Nozomi" train.

[0151] Input: Data on transportation methods after analysis

[0152] Output: Details of the recommended mode of transport (e.g., Shinkansen "Nozomi", window seat)

[0153] Step 5:

[0154] The server accesses a database of accommodations and, based on the analysis results, searches for and selects the most suitable accommodations that meet the user's preferences (business hotel, non-smoking room, breakfast included, etc.). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and breakfast included.

[0155] Input: Desired conditions for accommodation after analysis

[0156] Output: Details of recommended accommodations (e.g., business hotel in Osaka city, non-smoking room, breakfast included)

[0157] Step 6:

[0158] The server accesses the booking APIs for recommended transportation and accommodations and automatically processes the bookings. During this process, it sets details tailored to the user's transportation and accommodation preferences and retrieves the booking confirmation number and detailed information.

[0159] Input: Details of recommended transportation and accommodation

[0160] Output: Reservation confirmation number and reservation details

[0161] Step 7:

[0162] The server compiles the reservation process results and notifies the user's device. The notification includes the Shinkansen reservation number, departure and arrival times, hotel reservation confirmation number, and check-in and check-out times.

[0163] Enter: Reservation confirmation number and reservation details

[0164] Output: Notification data sent to the user's terminal (e.g., Shinkansen reservation number, departure / arrival times, hotel reservation confirmation number, check-in / check-out times)

[0165] Step 8:

[0166] The device interprets notification data received from the server and displays it to the user. Notifications can be pop-ups, emails, or in-app messages.

[0167] Input: Notification data sent from the server

[0168] Output: Notification content displayed to the user

[0169] (Application Example 1)

[0170] 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."

[0171] Currently, food delivery services require users to manually search for restaurants and menus and place orders one by one. This process is time-consuming and laborious, especially for busy business people, and an automated system is needed. Furthermore, there is a lack of recommendation features that take into account user preferences and past order history, and improvements are needed to enhance user satisfaction.

[0172] 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.

[0173] This invention includes a server that receives and analyzes order requests, recommends meals and restaurants based on the user's preferences, and automates the ordering process; a server that receives business trip applications; a server that analyzes business trip application data; and a server that recommends transportation suitable for the business trip location and appointment time based on the analysis results. This allows users to easily have meals that suit their preferences, as well as transportation and accommodation necessary for business trips, automatically recommended via their smartphones, and to quickly complete the booking process.

[0174] An "order request" is a request from a user regarding their preferences for meals and restaurants, made through a food delivery application.

[0175] "Recommendation" refers to suggesting the optimal option based on user input data and past behavioral data.

[0176] A "server" is a computer system that receives user input data, analyzes it, and makes necessary recommendations and arrangements.

[0177] A "business trip application" is an application form that users submit, in which they provide detailed information about their business trip (such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation and accommodation).

[0178] "Transportation" refers to the means used to get a user from their starting point to their destination (e.g., bullet train, airplane, taxi, etc.).

[0179] "Accommodation facilities" refer to hotels, inns, and other facilities where users stay during business trips.

[0180] "Analysis" is the process by which a server breaks down the data it receives and gives it meaning.

[0181] "Reservation arrangement" refers to the process of actually booking and arranging recommended transportation, accommodation, or meal orders based on customer requests.

[0182] "Notification" refers to the act of informing a user of the results of a reservation or order.

[0183] This invention provides a system that allows users to quickly and easily order food delivery through a smartphone application. It also offers a system that recommends the most suitable transportation and accommodation options to the user based on their business trip request, and automatically makes reservations. The operation of this system, which implements this application example, is described in detail below.

[0184] System Overview

[0185] This system is built using a smartphone application, a server, and external databases and APIs that work in conjunction with it.

[0186] Hardware and software

[0187] Smartphone: An iOS or Android device with the application for food delivery and travel requests installed.

[0188] Servers: AWS (Amazon Web Services) and Google Cloud are used for data reception, analysis, recommendations, booking, and notifications.

[0189] Database: MySQL or MongoDB to manage user order history, transportation schedules, accommodation information, etc.

[0190] API: Access external services such as the Foursquare API via a RESTful API to perform recommendations and booking arrangements.

[0191] Program processing

[0192] 1. Enter and submit your order request.

[0193] Users use a smartphone app to enter their order requests. These requests include details such as the type of meal, preferred restaurant, and delivery time. The smartphone then sends this information to the server.

[0194] 2. Data reception and analysis

[0195] The server analyzes the received data and determines the appropriate restaurant and menu based on the user's preferences and past order history. For example, if the user prefers Japanese food, it will recommend nearby Japanese restaurants.

[0196] 3. Recommendations and order processing

[0197] The server places orders based on recommended restaurants and menus. Orders are sent to the restaurant's ordering system via a RESTful API, and the process is automated.

[0198] 4. Sending a confirmation notice

[0199] The server compiles the order results and notifies the user's smartphone. The notification includes the order number, estimated delivery time, and price breakdown.

[0200] Furthermore, this system also handles business trip requests and performs the following processing.

[0201] Acceptance and analysis of travel expense requests

[0202] Users enter the necessary information into a business trip request form on their smartphones and submit it. The server receives and analyzes this information. It then automatically recommends transportation and accommodation options and makes the necessary reservations.

[0203] Specific example

[0204] For example, if a user wants a Japanese lunch, they enter "Japanese food" and their desired delivery time into the app and submit it. The server then searches for nearby Japanese restaurants based on this information and recommends, for example, a "salmon set meal." The server then automatically sends the order for the salmon set meal to the restaurant and sends a confirmation notification to the user.

[0205] Example of a prompt

[0206] "The user wants a Japanese lunch. The user is currently in a regional city. Recommend a suitable restaurant and automatically order the menu."

[0207] Thus, this invention provides a system that allows users to smoothly arrange food delivery and catering services.

[0208] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0209] Step 1:

[0210] Users enter their order requests using a smartphone app. This includes details such as the type of food (e.g., Japanese food), preferred restaurant, and delivery time. The entered data is stored in the smartphone's database and sent to the server.

[0211] Input: User order request data (type of meal, preferred restaurant, delivery time)

[0212] Output: Order request data sent to the server

[0213] Step 2:

[0214] The server receives order request data sent from the smartphone. It analyzes the received data and searches for a suitable restaurant based on the user's desired dining conditions (e.g., Japanese food) and past order history.

[0215] Input: Order request data

[0216] Output: Analyzed order criteria and a list of recommended restaurants.

[0217] Step 3:

[0218] The server recommends the most suitable restaurant and menu based on the analyzed data. The recommendation process involves data calculations that take into account the user's past ordering history and preferences. For example, a user who prefers Japanese food might be recommended a "salmon set meal."

[0219] Input: Analyzed order criteria and a list of recommended restaurants.

[0220] Output: List of the best restaurants and menus

[0221] Step 4:

[0222] The server processes orders based on a list of recommended restaurants and menus. Order data is sent to the recommended restaurant's ordering system via an API. For example, an order for a salmon set meal is sent using a RESTful API.

[0223] Input: List of the best restaurants and menus

[0224] Output: Order data sent to the ordering system of the recommended restaurant.

[0225] Step 5:

[0226] The server receives and compiles the order results. These results include information such as the order number, estimated delivery time, and price breakdown. This information is compiled into notification data.

[0227] Input: Order result data received from the recommended restaurant's ordering system.

[0228] Output: Compiled notification data

[0229] Step 6:

[0230] The server sends the compiled notification data to the user's smartphone. The user receives an order confirmation notification via their smartphone and can view details such as the order number, estimated delivery time, and price breakdown.

[0231] Input: Compiled notification data

[0232] Output: Notification data sent to the smartphone

[0233] Steps to process a business trip request

[0234] Step 7:

[0235] Users enter the necessary information into a business trip request form on their smartphone and submit it. This includes details such as departure location, departure date and time, destination, appointment time, expected return date and time, and preferences for transportation and accommodation.

[0236] Input: Business trip application data (departure location, departure date and time, destination, etc.)

[0237] Output: Travel request data sent to the server

[0238] Step 8:

[0239] The server receives and analyzes the travel request data. Based on the analyzed data, it breaks down the departure location, departure date and time, destination, appointment time, etc., into individual elements and clarifies the conditions for transportation and accommodation.

[0240] Input: Business trip application data

[0241] Output: Analyzed departure location, departure date and time, destination, appointment time, etc.

[0242] Step 9:

[0243] The server consults a database and recommends suitable transportation options based on the travel destination and appointment time. For example, it might query the Shinkansen (bullet train) schedule to determine the best option.

[0244] Input: Analyzed departure location, departure date and time, destination, appointment time, etc.

[0245] Output: Recommended modes of transport

[0246] Step 10:

[0247] The server automatically books and arranges recommended transportation options. Using the API, you can book Shinkansen (bullet train) tickets and your preferred seats.

[0248] Input: Recommended mode of transport

[0249] Output: Reservation confirmation data (Shinkansen train number, seat number, etc.)

[0250] Step 11:

[0251] The server searches the database for and recommends the most suitable accommodation based on the analyzed accommodation conditions (e.g., non-smoking room, breakfast included, etc.).

[0252] Input: Analysis results of accommodation facility conditions

[0253] Output: Recommended accommodations

[0254] Step 12:

[0255] The server automatically makes reservations for recommended accommodations. It utilizes a reservation API to process reservations and retrieve data such as reservation confirmation numbers.

[0256] Input: Recommended accommodations

[0257] Output: Reservation confirmation data (such as the accommodation reservation confirmation number)

[0258] Step 13:

[0259] The server compiles the booking results for transportation and accommodation and notifies the user's smartphone. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0260] Input: Booking confirmation data for transportation and accommodation.

[0261] Output: Confirmation notification sent to smartphone

[0262] In this way, through a series of steps, users can efficiently carry out all procedures related to business travel using an automated system.

[0263] 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.

[0264] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. The system's program is implemented through the interaction of multiple servers, terminals, and users.

[0265] Program processing

[0266] 1. Enter and submit travel request

[0267] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0268] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[0269] 2. Receiving and analyzing travel request data

[0270] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0271] 3. Activating the Emotion Engine and Emotion Recognition

[0272] The server activates the emotion engine and collects the user's emotional data. This emotional data is obtained from the user's input speed, input content, and biometric sensors. The emotion engine analyzes this data to recognize the user's current emotions (e.g., stress, excitement, anxiety).

[0273] 4. Recommendations for modes of transportation

[0274] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. It then lists recommended options based on the user's appointment time.

[0275] The recommendation system adjusts recommendations based on the user's emotions, as recognized by the emotion engine. For example, if a user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[0276] Save the selection results for now.

[0277] 5. Accommodation Recommendations

[0278] The server accesses a database of accommodations and searches for and selects the most suitable accommodation based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included).

[0279] The emotion engine recognizes the user's emotions and reflects them accordingly. For example, if the user is seeking relaxation, it will recommend hotels with spas or relaxation services.

[0280] 6. Automated booking arrangement

[0281] The server recommends a Shinkansen (bullet train) or airline reservation API, and the user then makes the reservation. During this process, seats are reserved according to the user's preferences.

[0282] Similarly, access the accommodation reservation API and perform the reservation procedures for the recommended accommodation facilities. Also obtain details such as the reservation confirmation number and check-in / check-out times.

[0283] 7. Sending Confirmation Notifications

[0284] The server summarizes the reservation results for transportation means and accommodation facilities and notifies the user's terminal. The notification content includes the reservation number for the bullet train, departure / arrival times, the hotel's reservation confirmation number, check-in / check-out times, etc.

[0285] The terminal receives the notification and displays it to the user.

[0286] Specific Example

[0287] For example, assume that a user plans a business trip from Tokyo to Osaka. The user inputs the necessary information into the business trip application form on the terminal and sends it. The server receives and analyzes this, and the emotion engine recognizes the user's emotion. If it is determined that the user is feeling stressed, a green car on the 9:00 am bullet train "Nozomi" is recommended, and a hotel in Osaka with a rich relaxation service is proposed. Each reservation is completed, and the details are notified to the user's terminal.

[0288] In this way, the present invention provides a system that automates the process from business trip application to recommendation, reservation arrangement, and notification in a consistent manner so that the user can smoothly and efficiently prepare for a business trip, and further uses an emotion engine to provide an optimal proposal according to the user's emotion.

[0289] The following describes the processing flow.

[0290] Step 1:

[0291] The user uses the terminal to draft a business trip application. The user inputs detailed information such as the departure location, departure date and time, business trip destination, appointment time, planned return date and time, preference for transportation means, and hope for accommodation facilities into the business trip application form.

[0292] Step 2:

[0293] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[0294] Step 3:

[0295] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0296] Step 4:

[0297] The server activates the emotion engine and collects user emotion data. This emotion data is obtained from the user's input speed and content, biometric recognition sensors, etc. The emotion engine analyzes this data to recognize the user's current emotions (stress, excitement, anxiety, etc.).

[0298] Step 5:

[0299] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[0300] Step 6:

[0301] The server selects the optimal mode of transportation from a list of options, reflecting the user's preferences and emotional data. For example, if the user is experiencing stress, the server might recommend a more spacious Green Car or a more comfortable seat in the case of a bullet train. The selection results are then saved.

[0302] Step 7:

[0303] The server accesses the accommodation facility database. Based on the analysis results, it searches for and selects the accommodation facility that best suits the user's desired conditions (such as business hotel, non-smoking room, with breakfast, etc.).

[0304] Step 8:

[0305] The server selects the optimal accommodation facility that reflects the user's preferences and sentiment data from the recommended accommodation facility candidates. For example, if the user is seeking relaxation, it recommends a hotel with a spa or relaxation services.

[0306] Step 9:

[0307] The server accesses the reservation API for the recommended bullet train or flight and conducts the reservation procedure for the means of transportation. At this time, it secures a seat that matches the user's preferences.

[0308] Step 10:

[0309] The server accesses the reservation API for the accommodation facility and conducts the reservation procedure for the recommended accommodation facility. It obtains details such as the reservation confirmation number and check-in / check-out times.

[0310] Step 11:

[0311] The server summarizes the reservation results for the means of transportation and the accommodation facility and notifies the user's terminal. Specifically, it includes the bullet train reservation number, departure / arrival times, the hotel reservation confirmation number, check-in / check-out times, etc.

[0312] Step 12:

[0313] The terminal receives the notification and displays it to the user. The user can finally confirm the reservation details and request corrections or re-recommendations if necessary.

[0314] Through this series of processes, users can efficiently prepare for business trips, and the introduction of an emotion engine allows them to receive more customized recommendations based on their mood and emotions.

[0315] (Example 2)

[0316] 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 as the "terminal".

[0317] Conventional business trip application systems recommend and automatically book transportation and accommodation based on the application details, but they do not take into account the user's emotional state when making recommendations or bookings. As a result, it is difficult to select the optimal transportation and accommodation based on the user's stress and fatigue levels, and there is a need for a system that can further improve user satisfaction.

[0318] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a business trip application, means for analyzing the received business trip application data, means for recommending a means of transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended means of transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the results of the booking procedure, means for activating an emotion recognition engine and analyzing the user's emotion data, and means for adjusting the recommendation content based on the user's emotion data. This makes it possible to automatically select and book the optimal means of transportation and accommodation according to the user's emotional state.

[0319] "Means of accepting business trip requests" refers to a function that retrieves business trip information entered by the user and imports it into a format that can be processed within the system.

[0320] "Means for analyzing business trip application data" refers to a function that analyzes the received business trip information and extracts and processes each element (departure point, destination, appointment time, etc.).

[0321] "A means of recommending a suitable mode of transportation for business trips and appointment times" refers to a function that proposes the optimal mode of transportation considering the business trip location and appointment times based on the analysis results.

[0322] "Method for booking recommended modes of transport" refers to a function that automatically executes the booking procedure for the recommended modes of transport.

[0323] "A means of recommending accommodations that meet the user's desired conditions" refers to a function that suggests accommodations that match the user's desired conditions based on the analysis results.

[0324] "Method for booking recommended accommodations" refers to a function that automatically executes the booking process for recommended accommodations.

[0325] "Means of notifying users of the results of the reservation process" refers to a function that compiles the reservation results for transportation and accommodation and notifies the user.

[0326] "A means of activating an emotion recognition engine and analyzing the user's emotional data" refers to a function that operates an emotion recognition engine and analyzes the user's emotional state (stress, excitement, anxiety, etc.).

[0327] "Means of adjusting recommendations based on user sentiment data" refers to a function that optimizes recommendations for transportation and accommodation according to the user's emotional state.

[0328] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. This system is implemented through the interaction of multiple servers, terminals, and users.

[0329] First, the user enters their travel request using a terminal. The user enters detailed information into the travel request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The terminal encodes the entered data in JSON or XML format and sends it to the server.

[0330] Next, the server analyzes the received data. Through this analysis, various elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation are extracted.

[0331] The server activates an emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, and other sources. The emotion engine analyzes this data to recognize emotional states such as stress, excitement, and anxiety.

[0332] Furthermore, the server accesses Shinkansen and airline schedule databases to search for the best mode of transportation from the departure point to the business trip destination. It lists recommended options based on the user's appointment time. The recommendations are then adjusted based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, comfortable seats and convenient flights will be recommended.

[0333] Similarly, the server accesses a database of accommodations to search for and select the accommodation that best suits the user's preferences. The user's emotions, recognized by the emotion engine, are reflected in the recommendations; for example, if the user is seeking relaxation, hotels with spas or relaxation services will be recommended.

[0334] The server accesses the recommended Shinkansen or airline reservation API to make the transportation reservation. Similarly, it accesses the accommodation reservation API to make the recommended accommodation reservation. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[0335] Finally, the server consolidates the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times. The device receives this information and displays it to the user.

[0336] Specific example

[0337] For example, consider a user planning a business trip from Tokyo to Osaka. The user enters the necessary information into a business trip application form on their device and submits it. The server receives and analyzes this information, and the emotion engine recognizes the user's emotions. If it determines that the user is feeling stressed, it recommends a Green Car seat on the 9:00 AM Shinkansen "Nozomi" and suggests a hotel in Osaka with ample relaxation services. Once the reservations are completed, the details are notified to the user's device.

[0338] Example of a prompt

[0339] "I'm on a business trip from Tokyo to Osaka, so please recommend a hotel with a Shinkansen Green Car (first class) and a spa."

[0340] This system allows users to prepare for business trips stress-free and efficiently, and to receive optimal suggestions tailored to their emotional state.

[0341] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0342] Step 1:

[0343] The user enters the necessary information into the travel request form on the terminal. Specifically, the user uses text fields and dropdown lists to enter information such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The entered data is temporarily stored in memory. (Input: User data, Output: Application data in JSON or XML format)

[0344] Step 2:

[0345] The terminal validates the entered data. For example, it checks whether required fields are filled in and whether the input format is correct. Once validation is complete, the terminal encodes the data into JSON or XML format and sends it to the server. (Input: User input data, Output: Validated JSON or XML data)

[0346] Step 3:

[0347] The server receives data sent from the terminal. It parses the received data and breaks it down into elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. This data is temporarily stored in a database. (Input: Application data in JSON or XML format; Output: Parsed application data)

[0348] Step 4:

[0349] The server activates the emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, etc. The emotion engine analyzes this data and recognizes emotional states such as stress, excitement, and anxiety. (Input: User input data and biometric sensor data; Output: Emotional data)

[0350] Step 5:

[0351] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the best mode of transportation from the departure point to the destination. For example, it uses Shinkansen timetable APIs and airline flight schedule APIs. Based on the user's input data and sentiment data, it lists recommended options. For example, it might recommend Green Car (first class) or Business Class to a user experiencing stress. (Input: Parsed application data and sentiment data; Output: List of recommended modes of transportation)

[0352] Step 6:

[0353] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences. Specifically, it uses a hotel reservation API and makes recommendations that reflect the user's sentiment data. For example, a user seeking relaxation would be recommended hotels with spas or relaxation services. (Input: Parsed application data and sentiment data; Output: List of recommended accommodations)

[0354] Step 7:

[0355] The system accesses the Shinkansen (bullet train) or airline reservation API recommended by the server and executes the booking process for transportation. During booking, the user's preferences (e.g., seat location and class) are reflected. Similarly, it accesses the accommodation reservation API and executes the booking process for recommended accommodations. It also retrieves booking confirmation numbers and check-in / check-out information. (Input: Recommended transportation and accommodation data, Output: Booking confirmation information)

[0356] Step 8:

[0357] The server integrates the booking results for transportation and accommodation and generates a notification message. This notification message is then sent to the device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc. (Input: Booking confirmation information, Output: Notification message)

[0358] Step 9:

[0359] The device receives notifications and displays them to the user. Specifically, these notifications can be in the form of pop-up notifications, email notifications, or in-app notifications. This allows the user to check reservation details and prepare for their business trip. (Input: Notification message, Output: Notification to user)

[0360] (Application Example 2)

[0361] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0362] Traditional business travel support systems failed to provide appropriate recommendations that reflected users' emotions, even in situations where they felt stressed or fatigued. As a result, users often experienced dissatisfaction because their business travel experience was not optimized. Furthermore, despite users' need for flexible responses tailored to their different emotional states, only uniform recommendations were provided.

[0363] 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.

[0364] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results and the user's emotions, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results and the user's emotions, means for booking the recommended accommodation, means for recognizing the user's emotions, means for adjusting the recommendations for transportation and accommodation based on the recognized user emotions, and means for notifying the user of the results of the booking procedure. This makes it possible to provide more personalized recommendations for transportation and accommodation that correspond to the user's emotional state.

[0365] A "business trip request" is a document or piece of information that a user submits to the system in advance regarding their travel and accommodation requests related to their work.

[0366] "Analysis" is the process of subdividing received data and extracting and identifying its meaning and characteristics.

[0367] "Transportation" refers to the means of getting around that a user can use during a business trip, including, for example, trains, airplanes, and taxis.

[0368] "Recommendation" is the act of a system suggesting the optimal option based on analysis results and user preferences.

[0369] "Reservation arrangement" refers to the process of securing actual transportation and accommodation based on recommendations.

[0370] "Accommodation facilities" refer to facilities for temporary stays during business trips or travel, and include hotels, inns, and other similar establishments.

[0371] "Emotions" primarily refers to the user's psychological state, including conditions such as stress, fatigue, excitement, and relaxation.

[0372] "Emotion recognition" is the process of identifying a user's emotional state at a given time based on their input and biometric data.

[0373] "Notifications" refer to the means by which a system communicates information to a user, specifically including reservation confirmations and recommendation results.

[0374] This invention combines a system that analyzes business trip application data, recommends transportation and accommodation based on that data, and automates the booking process with a user emotion recognition function. The system consists of a terminal that provides the user interface, a server that processes and manages the data, and an emotion engine that performs emotion recognition.

[0375] When a user submits a travel request using a smartphone or other device, the device sends the request to the server. The request data is encoded in JSON or XML format. The server parses this data and breaks it down into individual elements such as departure location, departure date and time, destination, and appointment time.

[0376] Next, the server activates the emotion engine and collects user emotion data. The emotion engine recognizes the user's current emotional state by utilizing user input speed, biometric sensors, and other factors. Generative AI models may be used for this emotion recognition.

[0377] The server uses the collected sentiment data and other travel application data to recommend transportation and accommodations. For example, if a user is feeling stressed, it will recommend hotels with more comfortable seating and relaxation services.

[0378] Once transportation and accommodation recommendations are determined, the server automatically arranges the reservations. It accesses reservation APIs for bullet trains, flights, and hotels to secure the necessary bookings. Details of these procedures are notified from the server to the user's device.

[0379] For example, if a user enters "I'm tired from work" into the app, the emotion engine recognizes the user's emotion as "stress." The server then recommends a "comfortable restaurant" suitable for relaxation, suggests accommodation with relaxation facilities, and automatically makes a reservation.

[0380] Examples of prompts to input into a generative AI model include the following:

[0381] For example, if a user enters "I'm tired from work" into the app, the system uses an emotion engine to recognize the user's emotion as "stress." The system then recommends a restaurant suitable for relaxation and automatically arranges food delivery from that restaurant. Please provide an example Python program that implements this process.

[0382] Based on the above explanation, the present invention can provide optimal transportation and accommodation recommendations tailored to the user's emotions, thereby improving the efficiency and comfort of business trip preparations.

[0383] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0384] Step 1:

[0385] The user uses a smartphone or device to enter the necessary information (departure location, departure date and time, destination, appointment time, etc.) into the business trip application form. The device encodes this input data into JSON or XML format and sends it to the server.

[0386] Input: User's business trip request data (departure location, departure date and time, destination, appointment time, etc.)

[0387] Output: Encoded application data (JSON or XML format)

[0388] Step 2:

[0389] The server receives the travel request data sent from the terminal and performs analysis. Specifically, the server parses the data and breaks it down into individual elements (such as departure location, departure date and time, destination, and appointment time).

[0390] Input: Encoded application data

[0391] Output: Travel request data broken down into individual elements

[0392] Step 3:

[0393] The server activates the emotion engine and collects user emotion data. Specifically, the generative AI model analyzes and recognizes the user's emotional state (stress, fatigue, excitement, etc.) using data from the user's input speed and biometric recognition sensors.

[0394] Input: User input data, biometric sensor data

[0395] Output: Recognized emotion data

[0396] Step 4:

[0397] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. Based on the user's appointment time, it lists possible recommendations. Furthermore, it adjusts the recommendations based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[0398] Input: Individual travel request data, recognized emotion data

[0399] Output: List of recommended modes of transport

[0400] Step 5:

[0401] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (business hotel, non-smoking room, breakfast included, etc.). Furthermore, based on recognized sentiment data, if the user is seeking relaxation, it recommends hotels with spas or relaxation services.

[0402] Input: Individual travel request data, recognized emotion data

[0403] Output: List of recommended accommodations

[0404] Step 6:

[0405] The system accesses a reservation API for Shinkansen (bullet train) or airline tickets recommended by the server and completes the booking process for transportation. During this process, seats are secured according to the user's preferences. Similarly, the system accesses a reservation API for accommodations and completes the booking process for recommended accommodations. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[0406] Input: List of recommended modes of transport, list of accommodations

[0407] Output: Booking confirmation information (transportation and accommodation)

[0408] Step 7:

[0409] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes booking numbers for Shinkansen (bullet train) and other services, departure and arrival times, hotel booking confirmation numbers, check-in and check-out times, etc. The device receives this notification and displays the necessary information to the user.

[0410] Input: Reservation confirmation information

[0411] Output: Notification to the user

[0412] 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.

[0413] 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.

[0414] 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.

[0415] [Second Embodiment]

[0416] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0417] 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.

[0418] 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).

[0419] 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.

[0420] 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.

[0421] 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).

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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".

[0428] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. The program for this system is implemented through the interaction of multiple servers, terminals, and users.

[0429] Program processing

[0430] 1. Enter and submit travel request

[0431] The user uses a terminal to submit a business trip request. They enter detailed information into the request form, including departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0432] The terminal sends the entered travel request data to the server.

[0433] 2. Receiving and analyzing travel request data

[0434] The server receives travel request data sent from the terminal. The server analyzes the received data and breaks it down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0435] 3. Recommendations for modes of transportation

[0436] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the most suitable mode of transportation from the departure point to the business trip destination. Based on the user's preference, it selects a window or aisle seat for Shinkansen travel. It also selects the most suitable flight to ensure the user arrives on time for their appointment.

[0437] For example, for a business trip from Tokyo to Osaka, the system would recommend the 9:00 AM Shinkansen "Nozomi" and suggest a window seat of the customer's choice.

[0438] 4. Accommodation Recommendations

[0439] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and include breakfast.

[0440] 5. Automated booking arrangement

[0441] The server accesses the recommended Shinkansen or airline reservation API and processes the reservation for the mode of transport. During this process, it secures seats that match the user's preferences.

[0442] Similarly, the system accesses the accommodation booking API and proceeds with booking the recommended accommodations. It also retrieves details such as the booking confirmation number and check-in / check-out times.

[0443] 6. Sending a confirmation notice

[0444] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0445] The device receives the notification and displays it to the user.

[0446] Specific example

[0447] For example, let's say Mr. Suzuki plans a business trip from Tokyo to Osaka. Mr. Suzuki enters the necessary information into a business trip application form on his terminal and submits it. The server receives and analyzes this information and recommends the Shinkansen "Nozomi" departing at 9:00 AM and a business hotel in Osaka. Once the reservations are complete, the details are notified to Mr. Suzuki's terminal.

[0448] Thus, the present invention provides a system that automates the entire process from business trip application to recommendations, booking arrangements, and notifications, enabling users to prepare for business trips smoothly and efficiently.

[0449] The following describes the processing flow.

[0450] Step 1:

[0451] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0452] Step 2:

[0453] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[0454] Step 3:

[0455] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0456] Step 4:

[0457] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches the database for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[0458] Step 5:

[0459] The server selects the most suitable mode of transportation from a list of options, reflecting the user's preferences. For example, in the case of a bullet train, it considers the user's preference for a window or aisle seat. The selection result is then saved.

[0460] Step 6:

[0461] The server accesses the accommodation database. Based on the analysis results, it selects accommodations that meet the user's desired conditions (business hotel, non-smoking room, breakfast included, etc.) from the list of recommended options.

[0462] Step 7:

[0463] The server recommends booking transportation and accommodation. Here, you access the transportation booking API to secure seats on the selected bullet train or airline.

[0464] Step 8:

[0465] The server accesses the accommodation booking API and processes the booking for the selected accommodation. It retrieves details such as the booking confirmation number and check-in / check-out times.

[0466] Step 9:

[0467] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0468] Step 10:

[0469] The device receives a notification and displays it to the user. The user can then review the reservation details and request modifications or re-recommendations as needed.

[0470] Through this series of processes, users can efficiently prepare for their business trips.

[0471] (Example 1)

[0472] 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."

[0473] Traditional business travel application and booking systems require users to manually search for and book transportation and accommodations individually, which is time-consuming and cumbersome. Furthermore, finding the optimal option that meets the user's requirements can be difficult. Additionally, errors and deficiencies in verification during the booking process can occur. Therefore, there is a need for a system that automates the entire process from user business travel application to booking arrangements, ensuring efficiency and accuracy.

[0474] 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.

[0475] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the booking procedure results, means for accessing databases of transportation and accommodation, and means for acquiring and storing booking information. This enables the user to automate and efficiently and accurately perform a series of processes from business trip requests to recommendations of transportation and accommodation, booking arrangements, and notification.

[0476] The "means for accepting business trip requests" refer to a function that receives business trip information entered by the user via a terminal and incorporates that information into the system as an initial dataset.

[0477] "Methods for analyzing received business trip application data" refers to a function that analyzes received business trip application data, breaks it down into elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions, and extracts the necessary information.

[0478] The "means of recommending transportation" is a function that suggests the optimal mode of transport from the user's departure point to their business trip destination based on analysis results. This also takes into account the user's preferences for transportation (e.g., window seats or aisle seats).

[0479] The "means of booking and arranging transportation" refers to a function that accesses a booking API for recommended transportation options, automatically performs the booking process, and sets details such as seat selection.

[0480] The "means of recommending accommodations" refer to a function that suggests the most suitable accommodations that meet the user's desired conditions based on analysis results. This also takes into account accommodation options (e.g., non-smoking rooms, breakfast included).

[0481] The "means of booking accommodations" refer to a function that accesses the booking API of recommended accommodations and automatically completes the booking process. It also retrieves the booking confirmation number and detailed information.

[0482] The "means of notifying users of the results of the booking process" refer to a function that summarizes the results of bookings for transportation and accommodation and notifies the user. The notification content includes the booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc.

[0483] "Means of accessing databases of transportation and accommodation" refers to the function of accessing databases containing information on transportation and accommodation and retrieving the necessary information. This includes calling external APIs and SQL queries.

[0484] "Means for acquiring and saving reservation information" refers to a function that securely stores reservation information obtained during the reservation process for transportation and accommodation within the system, making it accessible for later reference.

[0485] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. This system is implemented through the interaction of multiple servers, terminals, and users.

[0486] System hardware and software configuration

[0487] server:

[0488] The server has a high-performance processor (e.g., Intel Xeon), ample memory (e.g., 32GB RAM), and large-capacity storage (e.g., SSD). The server also has the following software installed:

[0489] Operating System: Linux (e.g., Ubuntu 20.04)

[0490] Database: MySQL or PostgreSQL

[0491] Scripting language: Python (e.g., Python 3.8)

[0492] Web server: Apache or Nginx

[0493] API server: Flask or Django

[0494] Terminal:

[0495] The terminal is a device used by users to enter travel expense requests. Generally, a PC, tablet, or smartphone is used. The terminal has the following configuration:

[0496] Operating Systems: Windows, macOS, iOS, or Android

[0497] Web browser: Google Chrome, Safari, or Edge

[0498] Network connection: Connect to the Internet

[0499] User:

[0500] The user is the person who operates the terminal to submit a travel request. The user accesses the system using a web browser and enters the necessary information.

[0501] Specific processing of the program

[0502] Entering and submitting a travel request

[0503] The user uses their device to access the business trip application form and enters the required information (e.g., departure location, departure date and time, destination, appointment time, preferred mode of transportation, and desired accommodation).

[0504] The terminal verifies the entered information in real time, and provides a submit button only after confirming that all required fields have been filled in.

[0505] After the send button is pressed, the terminal converts the input data into JSON format, encrypts it using SSL, and sends it to the server.

[0506] Receiving and analyzing travel request data

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

[0508] The server analyzes the received data and extracts information such as the departure location, departure date and time, business trip destination, appointment time, preferred mode of transportation, and desired accommodation conditions.

[0509] Recommendations for transportation and accommodation

[0510] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the most suitable mode of transportation. This also takes into account the user's seating preferences.

[0511] The server accesses a database of accommodations and searches for properties that meet the user's desired criteria. Specifically, this includes options such as non-smoking rooms and breakfast included.

[0512] Automatic booking arrangement

[0513] The server accesses the booking APIs for recommended transportation and accommodations and automatically makes reservations. This includes seat selection and obtaining booking confirmation numbers.

[0514] Sending confirmation notice

[0515] The server compiles the results of the reservation process and notifies the user's terminal.

[0516] The terminal displays notifications received from the server to the user. These may include things like departure time and reservation confirmation number.

[0517] Specific example

[0518] For example, suppose a user enters the following information for a business trip:

[0519] Departure point: Tokyo

[0520] Departure date and time: December 10, 2023, 9:00 AM

[0521] Business trip destination: Osaka

[0522] Appointment time: December 10, 2023, 1:00 PM

[0523] Transportation preference: Shinkansen (bullet train), window seat

[0524] Accommodation preferences: Business hotel, non-smoking room, breakfast included

[0525] The server analyzes this data and recommends the best seats on the Shinkansen "Nozomi" and a business hotel in Osaka. Once the recommended transportation and accommodation bookings are complete, the details are notified to the user's device.

[0526] Example of a prompt

[0527] "A user is planning a business trip from Tokyo to Osaka. Please recommend transportation and accommodation based on the user's preferences and automatically make the reservations. The departure point is Tokyo, the departure date and time is 9:00 AM on December 10, 2023, the destination is Osaka, the appointment time is 1:00 PM on December 10, 2023, and the expected return date and time is 10:00 AM on December 11, 2023. The user prefers to travel by Shinkansen (bullet train), and if possible, please select a window seat. For accommodation, the user prefers a business hotel with a non-smoking room and an option for breakfast."

[0528] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0529] Step 1:

[0530] The user accesses the business trip application form using their device and enters the required information (departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation).

[0531] Input: Various travel application information entered by the user.

[0532] Output: Travel request data displayed on the terminal

[0533] Step 2:

[0534] The terminal verifies the entered information in real time, confirming that all required fields have been filled in. After verification, it provides a submit button. When the user presses the submit button, the terminal converts the travel request data into JSON format, encrypts it using SSL, and sends it to the server.

[0535] Input: Travel request data after the user presses the submit button.

[0536] Output: Encrypted JSON data sent to the server

[0537] Step 3:

[0538] The server receives JSON data sent from the terminal. After receiving the data, it first verifies the integrity and completeness of the data. Next, it parses the received JSON data and extracts the necessary information (departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions).

[0539] Input: Encrypted travel request data (JSON format)

[0540] Output: Elemental data such as departure point, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions after analysis.

[0541] Step 4:

[0542] The server accesses a database of Shinkansen (bullet train) and airline schedules and searches for the most suitable mode of transportation based on the business trip application data. The user's transportation preferences (e.g., Shinkansen, window seat) are also taken into consideration. For example, for a business trip from Tokyo to Osaka, the server recommends the 9:00 AM Shinkansen "Nozomi" train.

[0543] Input: Data on transportation methods after analysis

[0544] Output: Details of the recommended mode of transport (e.g., Shinkansen "Nozomi", window seat)

[0545] Step 5:

[0546] The server accesses a database of accommodations and, based on the analysis results, searches for and selects the most suitable accommodations that meet the user's preferences (business hotel, non-smoking room, breakfast included, etc.). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and breakfast included.

[0547] Input: Desired conditions for accommodation after analysis

[0548] Output: Details of recommended accommodations (e.g., business hotel in Osaka city, non-smoking room, breakfast included)

[0549] Step 6:

[0550] The server accesses the booking APIs for recommended transportation and accommodations and automatically processes the bookings. During this process, it sets details tailored to the user's transportation and accommodation preferences and retrieves the booking confirmation number and detailed information.

[0551] Input: Details of recommended transportation and accommodation

[0552] Output: Reservation confirmation number and reservation details

[0553] Step 7:

[0554] The server compiles the reservation process results and notifies the user's device. The notification includes the Shinkansen reservation number, departure and arrival times, hotel reservation confirmation number, and check-in and check-out times.

[0555] Enter: Reservation confirmation number and reservation details

[0556] Output: Notification data sent to the user's terminal (e.g., Shinkansen reservation number, departure / arrival times, hotel reservation confirmation number, check-in / check-out times)

[0557] Step 8:

[0558] The device interprets notification data received from the server and displays it to the user. Notifications can be pop-ups, emails, or in-app messages.

[0559] Input: Notification data sent from the server

[0560] Output: Notification content displayed to the user

[0561] (Application Example 1)

[0562] 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."

[0563] Currently, food delivery services require users to manually search for restaurants and menus and place orders one by one. This process is time-consuming and laborious, especially for busy business people, and an automated system is needed. Furthermore, there is a lack of recommendation features that take into account user preferences and past order history, and improvements are needed to enhance user satisfaction.

[0564] 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.

[0565] This invention includes a server that receives and analyzes order requests, recommends meals and restaurants based on the user's preferences, and automates the ordering process; a server that receives business trip applications; a server that analyzes business trip application data; and a server that recommends transportation suitable for the business trip location and appointment time based on the analysis results. This allows users to easily have meals that suit their preferences, as well as transportation and accommodation necessary for business trips, automatically recommended via their smartphones, and to quickly complete the booking process.

[0566] An "order request" is a request from a user regarding their preferences for meals and restaurants, made through a food delivery application.

[0567] "Recommendation" refers to suggesting the optimal option based on user input data and past behavioral data.

[0568] A "server" is a computer system that receives user input data, analyzes it, and makes necessary recommendations and arrangements.

[0569] A "business trip application" is an application form that users submit, in which they provide detailed information about their business trip (such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation and accommodation).

[0570] "Transportation" refers to the means used to get a user from their starting point to their destination (e.g., bullet train, airplane, taxi, etc.).

[0571] "Accommodation facilities" refer to hotels, inns, and other facilities where users stay during business trips.

[0572] "Analysis" is the process by which a server breaks down the data it receives and gives it meaning.

[0573] "Reservation arrangement" refers to the process of actually booking and arranging recommended transportation, accommodation, or meal orders based on customer requests.

[0574] "Notification" refers to the act of informing a user of the results of a reservation or order.

[0575] This invention provides a system that allows users to quickly and easily order food delivery through a smartphone application. It also offers a system that recommends the most suitable transportation and accommodation options to the user based on their business trip request, and automatically makes reservations. The operation of this system, which implements this application example, is described in detail below.

[0576] System Overview

[0577] This system is built using a smartphone application, a server, and external databases and APIs that work in conjunction with it.

[0578] Hardware and software

[0579] Smartphone: An iOS or Android device with the application for food delivery and travel requests installed.

[0580] Servers: AWS (Amazon Web Services) and Google Cloud are used for data reception, analysis, recommendations, booking, and notifications.

[0581] Database: MySQL or MongoDB to manage user order history, transportation schedules, accommodation information, etc.

[0582] API: Access external services such as the Foursquare API via a RESTful API to perform recommendations and booking arrangements.

[0583] Program processing

[0584] 1. Enter and submit your order request.

[0585] Users use a smartphone app to enter their order requests. These requests include details such as the type of meal, preferred restaurant, and delivery time. The smartphone then sends this information to the server.

[0586] 2. Data reception and analysis

[0587] The server analyzes the received data and determines the appropriate restaurant and menu based on the user's preferences and past order history. For example, if the user prefers Japanese food, it will recommend nearby Japanese restaurants.

[0588] 3. Recommendations and order processing

[0589] The server places orders based on recommended restaurants and menus. Orders are sent to the restaurant's ordering system via a RESTful API, and the process is automated.

[0590] 4. Sending a confirmation notice

[0591] The server compiles the order results and notifies the user's smartphone. The notification includes the order number, estimated delivery time, and price breakdown.

[0592] Furthermore, this system also handles business trip requests and performs the following processing.

[0593] Acceptance and analysis of travel expense requests

[0594] Users enter the necessary information into a business trip request form on their smartphones and submit it. The server receives and analyzes this information. It then automatically recommends transportation and accommodation options and makes the necessary reservations.

[0595] Specific example

[0596] For example, if a user wants a Japanese lunch, they enter "Japanese food" and their desired delivery time into the app and submit it. The server then searches for nearby Japanese restaurants based on this information and recommends, for example, a "salmon set meal." The server then automatically sends the order for the salmon set meal to the restaurant and sends a confirmation notification to the user.

[0597] Example of a prompt

[0598] "The user wants a Japanese lunch. The user is currently in a regional city. Recommend a suitable restaurant and automatically order the menu."

[0599] Thus, this invention provides a system that allows users to smoothly arrange food delivery and catering services.

[0600] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0601] Step 1:

[0602] Users enter their order requests using a smartphone app. This includes details such as the type of food (e.g., Japanese food), preferred restaurant, and delivery time. The entered data is stored in the smartphone's database and sent to the server.

[0603] Input: User order request data (type of meal, preferred restaurant, delivery time)

[0604] Output: Order request data sent to the server

[0605] Step 2:

[0606] The server receives order request data sent from the smartphone. It analyzes the received data and searches for a suitable restaurant based on the user's desired dining conditions (e.g., Japanese food) and past order history.

[0607] Input: Order request data

[0608] Output: Analyzed order criteria and a list of recommended restaurants.

[0609] Step 3:

[0610] The server recommends the most suitable restaurant and menu based on the analyzed data. The recommendation process involves data calculations that take into account the user's past ordering history and preferences. For example, a user who prefers Japanese food might be recommended a "salmon set meal."

[0611] Input: Analyzed order criteria and a list of recommended restaurants.

[0612] Output: List of the best restaurants and menus

[0613] Step 4:

[0614] The server processes orders based on a list of recommended restaurants and menus. Order data is sent to the recommended restaurant's ordering system via an API. For example, an order for a salmon set meal is sent using a RESTful API.

[0615] Input: List of the best restaurants and menus

[0616] Output: Order data sent to the ordering system of the recommended restaurant.

[0617] Step 5:

[0618] The server receives and compiles the order results. These results include information such as the order number, estimated delivery time, and price breakdown. This information is compiled into notification data.

[0619] Input: Order result data received from the recommended restaurant's ordering system.

[0620] Output: Compiled notification data

[0621] Step 6:

[0622] The server sends the compiled notification data to the user's smartphone. The user receives an order confirmation notification via their smartphone and can view details such as the order number, estimated delivery time, and price breakdown.

[0623] Input: Compiled notification data

[0624] Output: Notification data sent to the smartphone

[0625] Steps to process a business trip request

[0626] Step 7:

[0627] Users enter the necessary information into a business trip request form on their smartphone and submit it. This includes details such as departure location, departure date and time, destination, appointment time, expected return date and time, and preferences for transportation and accommodation.

[0628] Input: Business trip application data (departure location, departure date and time, destination, etc.)

[0629] Output: Travel request data sent to the server

[0630] Step 8:

[0631] The server receives and analyzes the travel request data. Based on the analyzed data, it breaks down the departure location, departure date and time, destination, appointment time, etc., into individual elements and clarifies the conditions for transportation and accommodation.

[0632] Input: Business trip application data

[0633] Output: Analyzed departure location, departure date and time, destination, appointment time, etc.

[0634] Step 9:

[0635] The server consults a database and recommends suitable transportation options based on the travel destination and appointment time. For example, it might query the Shinkansen (bullet train) schedule to determine the best option.

[0636] Input: Analyzed departure location, departure date and time, destination, appointment time, etc.

[0637] Output: Recommended modes of transport

[0638] Step 10:

[0639] The server automatically books and arranges recommended transportation options. Using the API, you can book Shinkansen (bullet train) tickets and your preferred seats.

[0640] Input: Recommended mode of transport

[0641] Output: Reservation confirmation data (Shinkansen train number, seat number, etc.)

[0642] Step 11:

[0643] The server searches the database for and recommends the most suitable accommodation based on the analyzed accommodation conditions (e.g., non-smoking room, breakfast included, etc.).

[0644] Input: Analysis results of accommodation facility conditions

[0645] Output: Recommended accommodations

[0646] Step 12:

[0647] The server automatically makes reservations for recommended accommodations. It utilizes a reservation API to process reservations and retrieve data such as reservation confirmation numbers.

[0648] Input: Recommended accommodations

[0649] Output: Reservation confirmation data (such as the accommodation reservation confirmation number)

[0650] Step 13:

[0651] The server compiles the booking results for transportation and accommodation and notifies the user's smartphone. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0652] Input: Booking confirmation data for transportation and accommodation.

[0653] Output: Confirmation notification sent to smartphone

[0654] In this way, through a series of steps, users can efficiently carry out all procedures related to business travel using an automated system.

[0655] 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.

[0656] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. The system's program is implemented through the interaction of multiple servers, terminals, and users.

[0657] Program processing

[0658] 1. Enter and submit travel request

[0659] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0660] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[0661] 2. Receiving and analyzing travel request data

[0662] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0663] 3. Activating the Emotion Engine and Emotion Recognition

[0664] The server activates the emotion engine and collects the user's emotional data. This emotional data is obtained from the user's input speed, input content, and biometric sensors. The emotion engine analyzes this data to recognize the user's current emotions (e.g., stress, excitement, anxiety).

[0665] 4. Recommendations for modes of transportation

[0666] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. It then lists recommended options based on the user's appointment time.

[0667] The recommendation system adjusts recommendations based on the user's emotions, as recognized by the emotion engine. For example, if a user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[0668] Save the selection results for now.

[0669] 5. Accommodation Recommendations

[0670] The server accesses a database of accommodations and searches for and selects the most suitable accommodation based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included).

[0671] The emotion engine recognizes the user's emotions and reflects them accordingly. For example, if the user is seeking relaxation, it will recommend hotels with spas or relaxation services.

[0672] 6. Automated booking arrangement

[0673] The server recommends a Shinkansen (bullet train) or airline reservation API, and the user then makes the reservation. During this process, seats are reserved according to the user's preferences.

[0674] Similarly, the system accesses the accommodation booking API and proceeds with booking the recommended accommodations. It also retrieves details such as the booking confirmation number and check-in / check-out times.

[0675] 7. Sending a confirmation notice

[0676] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0677] The device receives the notification and displays it to the user.

[0678] Specific example

[0679] For example, suppose a user plans a business trip from Tokyo to Osaka. The user enters the necessary information into a business trip application form on their device and submits it. The server receives and analyzes this information, and the emotion engine recognizes the user's emotions. If it determines that the user is feeling stressed, it recommends a Green Car seat on the 9:00 AM Shinkansen "Nozomi" and suggests a hotel in Osaka with ample relaxation services. Once the reservations are completed, the details are notified to the user's device.

[0680] Thus, the present invention provides a system that automates the entire process from business trip application to recommendations, booking arrangements, and notifications, enabling users to prepare for business trips smoothly and efficiently. Furthermore, by using an emotion engine, it provides optimal suggestions tailored to the user's emotions.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0684] Step 2:

[0685] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[0686] Step 3:

[0687] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0688] Step 4:

[0689] The server activates the emotion engine and collects user emotion data. This emotion data is obtained from the user's input speed and content, biometric recognition sensors, etc. The emotion engine analyzes this data to recognize the user's current emotions (stress, excitement, anxiety, etc.).

[0690] Step 5:

[0691] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[0692] Step 6:

[0693] The server selects the optimal mode of transportation from a list of options, reflecting the user's preferences and emotional data. For example, if the user is experiencing stress, the server might recommend a more spacious Green Car or a more comfortable seat in the case of a bullet train. The selection results are then saved.

[0694] Step 7:

[0695] The server accesses the accommodation database. Based on the analysis results, it searches for and selects the accommodation that best suits the user's preferences (business hotel, non-smoking room, breakfast included, etc.).

[0696] Step 8:

[0697] The server selects the most suitable accommodation from a list of recommended options, reflecting the user's preferences and emotional data. For example, if the user is looking to relax, the server will recommend hotels with spas or relaxation services.

[0698] Step 9:

[0699] The server recommends a Shinkansen (bullet train) or airline reservation API, and the user then makes the reservation. During this process, seats are reserved according to the user's preferences.

[0700] Step 10:

[0701] The server accesses the accommodation booking API and processes the booking for the recommended accommodation. It retrieves details such as the booking confirmation number and check-in / check-out times.

[0702] Step 11:

[0703] The server compiles the booking results for transportation and accommodation and notifies the user's device. Specifically, this includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0704] Step 12:

[0705] The device receives a notification and displays it to the user. The user can then review the reservation details and request modifications or re-recommendations as needed.

[0706] Through this series of processes, users can efficiently prepare for business trips, and the introduction of an emotion engine allows them to receive more customized recommendations based on their mood and emotions.

[0707] (Example 2)

[0708] 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".

[0709] Conventional business trip application systems recommend and automatically book transportation and accommodation based on the application details, but they do not take into account the user's emotional state when making recommendations or bookings. As a result, it is difficult to select the optimal transportation and accommodation based on the user's stress and fatigue levels, and there is a need for a system that can further improve user satisfaction.

[0710] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a business trip application, means for analyzing the received business trip application data, means for recommending a means of transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended means of transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the results of the booking procedure, means for activating an emotion recognition engine and analyzing the user's emotion data, and means for adjusting the recommendation content based on the user's emotion data. This makes it possible to automatically select and book the optimal means of transportation and accommodation according to the user's emotional state.

[0711] "Means of accepting business trip requests" refers to a function that retrieves business trip information entered by the user and imports it into a format that can be processed within the system.

[0712] "Means for analyzing business trip application data" refers to a function that analyzes the received business trip information and extracts and processes each element (departure point, destination, appointment time, etc.).

[0713] "A means of recommending a suitable mode of transportation for business trips and appointment times" refers to a function that proposes the optimal mode of transportation considering the business trip location and appointment times based on the analysis results.

[0714] "Method for booking recommended modes of transport" refers to a function that automatically executes the booking procedure for the recommended modes of transport.

[0715] "A means of recommending accommodations that meet the user's desired conditions" refers to a function that suggests accommodations that match the user's desired conditions based on the analysis results.

[0716] "Method for booking recommended accommodations" refers to a function that automatically executes the booking process for recommended accommodations.

[0717] "Means of notifying users of the results of the reservation process" refers to a function that compiles the reservation results for transportation and accommodation and notifies the user.

[0718] "A means of activating an emotion recognition engine and analyzing the user's emotional data" refers to a function that operates an emotion recognition engine and analyzes the user's emotional state (stress, excitement, anxiety, etc.).

[0719] "Means of adjusting recommendations based on user sentiment data" refers to a function that optimizes recommendations for transportation and accommodation according to the user's emotional state.

[0720] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. This system is implemented through the interaction of multiple servers, terminals, and users.

[0721] First, the user enters their travel request using a terminal. The user enters detailed information into the travel request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The terminal encodes the entered data in JSON or XML format and sends it to the server.

[0722] Next, the server analyzes the received data. Through this analysis, various elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation are extracted.

[0723] The server activates an emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, and other sources. The emotion engine analyzes this data to recognize emotional states such as stress, excitement, and anxiety.

[0724] Furthermore, the server accesses Shinkansen and airline schedule databases to search for the best mode of transportation from the departure point to the business trip destination. It lists recommended options based on the user's appointment time. The recommendations are then adjusted based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, comfortable seats and convenient flights will be recommended.

[0725] Similarly, the server accesses a database of accommodations to search for and select the accommodation that best suits the user's preferences. The user's emotions, recognized by the emotion engine, are reflected in the recommendations; for example, if the user is seeking relaxation, hotels with spas or relaxation services will be recommended.

[0726] The server accesses the recommended Shinkansen or airline reservation API to make the transportation reservation. Similarly, it accesses the accommodation reservation API to make the recommended accommodation reservation. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[0727] Finally, the server consolidates the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times. The device receives this information and displays it to the user.

[0728] Specific example

[0729] For example, consider a user planning a business trip from Tokyo to Osaka. The user enters the necessary information into a business trip application form on their device and submits it. The server receives and analyzes this information, and the emotion engine recognizes the user's emotions. If it determines that the user is feeling stressed, it recommends a Green Car seat on the 9:00 AM Shinkansen "Nozomi" and suggests a hotel in Osaka with ample relaxation services. Once the reservations are completed, the details are notified to the user's device.

[0730] Example of a prompt

[0731] "I'm on a business trip from Tokyo to Osaka, so please recommend a hotel with a Shinkansen Green Car (first class) and a spa."

[0732] This system allows users to prepare for business trips stress-free and efficiently, and to receive optimal suggestions tailored to their emotional state.

[0733] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0734] Step 1:

[0735] The user enters the necessary information into the travel request form on the terminal. Specifically, the user uses text fields and dropdown lists to enter information such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The entered data is temporarily stored in memory. (Input: User data, Output: Application data in JSON or XML format)

[0736] Step 2:

[0737] The terminal validates the entered data. For example, it checks whether required fields are filled in and whether the input format is correct. Once validation is complete, the terminal encodes the data into JSON or XML format and sends it to the server. (Input: User input data, Output: Validated JSON or XML data)

[0738] Step 3:

[0739] The server receives data sent from the terminal. It parses the received data and breaks it down into elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. This data is temporarily stored in a database. (Input: Application data in JSON or XML format; Output: Parsed application data)

[0740] Step 4:

[0741] The server activates the emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, etc. The emotion engine analyzes this data and recognizes emotional states such as stress, excitement, and anxiety. (Input: User input data and biometric sensor data; Output: Emotional data)

[0742] Step 5:

[0743] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the best mode of transportation from the departure point to the destination. For example, it uses Shinkansen timetable APIs and airline flight schedule APIs. Based on the user's input data and sentiment data, it lists recommended options. For example, it might recommend Green Car (first class) or Business Class to a user experiencing stress. (Input: Parsed application data and sentiment data; Output: List of recommended modes of transportation)

[0744] Step 6:

[0745] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences. Specifically, it uses a hotel reservation API and makes recommendations that reflect the user's sentiment data. For example, a user seeking relaxation would be recommended hotels with spas or relaxation services. (Input: Parsed application data and sentiment data; Output: List of recommended accommodations)

[0746] Step 7:

[0747] The system accesses the Shinkansen (bullet train) or airline reservation API recommended by the server and executes the booking process for transportation. During booking, the user's preferences (e.g., seat location and class) are reflected. Similarly, it accesses the accommodation reservation API and executes the booking process for recommended accommodations. It also retrieves booking confirmation numbers and check-in / check-out information. (Input: Recommended transportation and accommodation data, Output: Booking confirmation information)

[0748] Step 8:

[0749] The server integrates the booking results for transportation and accommodation and generates a notification message. This notification message is then sent to the device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc. (Input: Booking confirmation information, Output: Notification message)

[0750] Step 9:

[0751] The device receives notifications and displays them to the user. Specifically, these notifications can be in the form of pop-up notifications, email notifications, or in-app notifications. This allows the user to check reservation details and prepare for their business trip. (Input: Notification message, Output: Notification to user)

[0752] (Application Example 2)

[0753] 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."

[0754] Traditional business travel support systems failed to provide appropriate recommendations that reflected users' emotions, even in situations where they felt stressed or fatigued. As a result, users often experienced dissatisfaction because their business travel experience was not optimized. Furthermore, despite users' need for flexible responses tailored to their different emotional states, only uniform recommendations were provided.

[0755] 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.

[0756] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results and the user's emotions, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results and the user's emotions, means for booking the recommended accommodation, means for recognizing the user's emotions, means for adjusting the recommendations for transportation and accommodation based on the recognized user emotions, and means for notifying the user of the results of the booking procedure. This makes it possible to provide more personalized recommendations for transportation and accommodation that correspond to the user's emotional state.

[0757] A "business trip request" is a document or piece of information that a user submits to the system in advance regarding their travel and accommodation requests related to their work.

[0758] "Analysis" is the process of subdividing received data and extracting and identifying its meaning and characteristics.

[0759] "Transportation" refers to the means of getting around that a user can use during a business trip, including, for example, trains, airplanes, and taxis.

[0760] "Recommendation" is the act of a system suggesting the optimal option based on analysis results and user preferences.

[0761] "Reservation arrangement" refers to the process of securing actual transportation and accommodation based on recommendations.

[0762] "Accommodation facilities" refer to facilities for temporary stays during business trips or travel, and include hotels, inns, and other similar establishments.

[0763] "Emotions" primarily refers to the user's psychological state, including conditions such as stress, fatigue, excitement, and relaxation.

[0764] "Emotion recognition" is the process of identifying a user's emotional state at a given time based on their input and biometric data.

[0765] "Notifications" refer to the means by which a system communicates information to a user, specifically including reservation confirmations and recommendation results.

[0766] This invention combines a system that analyzes business trip application data, recommends transportation and accommodation based on that data, and automates the booking process with a user emotion recognition function. The system consists of a terminal that provides the user interface, a server that processes and manages the data, and an emotion engine that performs emotion recognition.

[0767] When a user submits a travel request using a smartphone or other device, the device sends the request to the server. The request data is encoded in JSON or XML format. The server parses this data and breaks it down into individual elements such as departure location, departure date and time, destination, and appointment time.

[0768] Next, the server activates the emotion engine and collects user emotion data. The emotion engine recognizes the user's current emotional state by utilizing user input speed, biometric sensors, and other factors. Generative AI models may be used for this emotion recognition.

[0769] The server uses the collected sentiment data and other travel application data to recommend transportation and accommodations. For example, if a user is feeling stressed, it will recommend hotels with more comfortable seating and relaxation services.

[0770] Once transportation and accommodation recommendations are determined, the server automatically arranges the reservations. It accesses reservation APIs for bullet trains, flights, and hotels to secure the necessary bookings. Details of these procedures are notified from the server to the user's device.

[0771] For example, if a user enters "I'm tired from work" into the app, the emotion engine recognizes the user's emotion as "stress." The server then recommends a "comfortable restaurant" suitable for relaxation, suggests accommodation with relaxation facilities, and automatically makes a reservation.

[0772] Examples of prompts to input into a generative AI model include the following:

[0773] For example, if a user enters "I'm tired from work" into the app, the system uses an emotion engine to recognize the user's emotion as "stress." The system then recommends a restaurant suitable for relaxation and automatically arranges food delivery from that restaurant. Please provide an example Python program that implements this process.

[0774] Based on the above explanation, the present invention can provide optimal transportation and accommodation recommendations tailored to the user's emotions, thereby improving the efficiency and comfort of business trip preparations.

[0775] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0776] Step 1:

[0777] The user uses a smartphone or device to enter the necessary information (departure location, departure date and time, destination, appointment time, etc.) into the business trip application form. The device encodes this input data into JSON or XML format and sends it to the server.

[0778] Input: User's business trip request data (departure location, departure date and time, destination, appointment time, etc.)

[0779] Output: Encoded application data (JSON or XML format)

[0780] Step 2:

[0781] The server receives the travel request data sent from the terminal and performs analysis. Specifically, the server parses the data and breaks it down into individual elements (such as departure location, departure date and time, destination, and appointment time).

[0782] Input: Encoded application data

[0783] Output: Travel request data broken down into individual elements

[0784] Step 3:

[0785] The server activates the emotion engine and collects user emotion data. Specifically, the generative AI model analyzes and recognizes the user's emotional state (stress, fatigue, excitement, etc.) using data from the user's input speed and biometric recognition sensors.

[0786] Input: User input data, biometric sensor data

[0787] Output: Recognized emotion data

[0788] Step 4:

[0789] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. Based on the user's appointment time, it lists possible recommendations. Furthermore, it adjusts the recommendations based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[0790] Input: Individual travel request data, recognized emotion data

[0791] Output: List of recommended modes of transport

[0792] Step 5:

[0793] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (business hotel, non-smoking room, breakfast included, etc.). Furthermore, based on recognized sentiment data, if the user is seeking relaxation, it recommends hotels with spas or relaxation services.

[0794] Input: Individual travel request data, recognized emotion data

[0795] Output: List of recommended accommodations

[0796] Step 6:

[0797] The system accesses a reservation API for Shinkansen (bullet train) or airline tickets recommended by the server and completes the booking process for transportation. During this process, seats are secured according to the user's preferences. Similarly, the system accesses a reservation API for accommodations and completes the booking process for recommended accommodations. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[0798] Input: List of recommended modes of transport, list of accommodations

[0799] Output: Booking confirmation information (transportation and accommodation)

[0800] Step 7:

[0801] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes booking numbers for Shinkansen (bullet train) and other services, departure and arrival times, hotel booking confirmation numbers, check-in and check-out times, etc. The device receives this notification and displays the necessary information to the user.

[0802] Input: Reservation confirmation information

[0803] Output: Notification to the user

[0804] 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.

[0805] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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.

[0806] 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.

[0807] [Third Embodiment]

[0808] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0809] 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.

[0810] 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).

[0811] 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.

[0812] 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.

[0813] 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).

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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".

[0820] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. The program for this system is implemented through the interaction of multiple servers, terminals, and users.

[0821] Program processing

[0822] 1. Enter and submit travel request

[0823] The user uses a terminal to submit a business trip request. They enter detailed information into the request form, including departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0824] The terminal sends the entered travel request data to the server.

[0825] 2. Receiving and analyzing travel request data

[0826] The server receives travel request data sent from the terminal. The server analyzes the received data and breaks it down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0827] 3. Recommendations for modes of transportation

[0828] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the most suitable mode of transportation from the departure point to the business trip destination. Based on the user's preference, it selects a window or aisle seat for Shinkansen travel. It also selects the most suitable flight to ensure the user arrives on time for their appointment.

[0829] For example, for a business trip from Tokyo to Osaka, the system would recommend the 9:00 AM Shinkansen "Nozomi" and suggest a window seat of the customer's choice.

[0830] 4. Accommodation Recommendations

[0831] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and include breakfast.

[0832] 5. Automated booking arrangement

[0833] The server accesses the recommended Shinkansen or airline reservation API and processes the reservation for the mode of transport. During this process, it secures seats that match the user's preferences.

[0834] Similarly, the system accesses the accommodation booking API and proceeds with booking the recommended accommodations. It also retrieves details such as the booking confirmation number and check-in / check-out times.

[0835] 6. Sending a confirmation notice

[0836] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0837] The device receives the notification and displays it to the user.

[0838] Specific example

[0839] For example, let's say Mr. Suzuki plans a business trip from Tokyo to Osaka. Mr. Suzuki enters the necessary information into a business trip application form on his terminal and submits it. The server receives and analyzes this information and recommends the Shinkansen "Nozomi" departing at 9:00 AM and a business hotel in Osaka. Once the reservations are complete, the details are notified to Mr. Suzuki's terminal.

[0840] Thus, the present invention provides a system that automates the entire process from business trip application to recommendations, booking arrangements, and notifications, enabling users to prepare for business trips smoothly and efficiently.

[0841] The following describes the processing flow.

[0842] Step 1:

[0843] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[0844] Step 2:

[0845] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[0846] Step 3:

[0847] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[0848] Step 4:

[0849] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches the database for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[0850] Step 5:

[0851] The server selects the most suitable mode of transportation from a list of options, reflecting the user's preferences. For example, in the case of a bullet train, it considers the user's preference for a window or aisle seat. The selection result is then saved.

[0852] Step 6:

[0853] The server accesses the accommodation database. Based on the analysis results, it selects accommodations that meet the user's desired conditions (business hotel, non-smoking room, breakfast included, etc.) from the list of recommended options.

[0854] Step 7:

[0855] The server recommends booking transportation and accommodation. Here, you access the transportation booking API to secure seats on the selected bullet train or airline.

[0856] Step 8:

[0857] The server accesses the accommodation booking API and processes the booking for the selected accommodation. It retrieves details such as the booking confirmation number and check-in / check-out times.

[0858] Step 9:

[0859] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[0860] Step 10:

[0861] The device receives a notification and displays it to the user. The user can then review the reservation details and request modifications or re-recommendations as needed.

[0862] Through this series of processes, users can efficiently prepare for their business trips.

[0863] (Example 1)

[0864] 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."

[0865] Traditional business travel application and booking systems require users to manually search for and book transportation and accommodations individually, which is time-consuming and cumbersome. Furthermore, finding the optimal option that meets the user's requirements can be difficult. Additionally, errors and deficiencies in verification during the booking process can occur. Therefore, there is a need for a system that automates the entire process from user business travel application to booking arrangements, ensuring efficiency and accuracy.

[0866] 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.

[0867] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the booking procedure results, means for accessing databases of transportation and accommodation, and means for acquiring and storing booking information. This enables the user to automate and efficiently and accurately perform a series of processes from business trip requests to recommendations of transportation and accommodation, booking arrangements, and notification.

[0868] The "means for accepting business trip requests" refer to a function that receives business trip information entered by the user via a terminal and incorporates that information into the system as an initial dataset.

[0869] "Methods for analyzing received business trip application data" refers to a function that analyzes received business trip application data, breaks it down into elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions, and extracts the necessary information.

[0870] The "means of recommending transportation" is a function that suggests the optimal mode of transport from the user's departure point to their business trip destination based on analysis results. This also takes into account the user's preferences for transportation (e.g., window seats or aisle seats).

[0871] The "means of booking and arranging transportation" refers to a function that accesses a booking API for recommended transportation options, automatically performs the booking process, and sets details such as seat selection.

[0872] The "means of recommending accommodations" refer to a function that suggests the most suitable accommodations that meet the user's desired conditions based on analysis results. This also takes into account accommodation options (e.g., non-smoking rooms, breakfast included).

[0873] The "means of booking accommodations" refer to a function that accesses the booking API of recommended accommodations and automatically completes the booking process. It also retrieves the booking confirmation number and detailed information.

[0874] The "means of notifying users of the results of the booking process" refer to a function that summarizes the results of bookings for transportation and accommodation and notifies the user. The notification content includes the booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc.

[0875] "Means of accessing databases of transportation and accommodation" refers to the function of accessing databases containing information on transportation and accommodation and retrieving the necessary information. This includes calling external APIs and SQL queries.

[0876] "Means for acquiring and saving reservation information" refers to a function that securely stores reservation information obtained during the reservation process for transportation and accommodation within the system, making it accessible for later reference.

[0877] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. This system is implemented through the interaction of multiple servers, terminals, and users.

[0878] System hardware and software configuration

[0879] server:

[0880] The server has a high-performance processor (e.g., Intel Xeon), ample memory (e.g., 32GB RAM), and large-capacity storage (e.g., SSD). The server also has the following software installed:

[0881] Operating System: Linux (e.g., Ubuntu 20.04)

[0882] Database: MySQL or PostgreSQL

[0883] Scripting language: Python (e.g., Python 3.8)

[0884] Web server: Apache or Nginx

[0885] API server: Flask or Django

[0886] Terminal:

[0887] The terminal is a device used by users to enter travel expense requests. Generally, a PC, tablet, or smartphone is used. The terminal has the following configuration:

[0888] Operating Systems: Windows, macOS, iOS, or Android

[0889] Web browser: Google Chrome, Safari, or Edge

[0890] Network connection: Connect to the Internet

[0891] User:

[0892] The user is the person who operates the terminal to submit a travel request. The user accesses the system using a web browser and enters the necessary information.

[0893] Specific processing of the program

[0894] Entering and submitting a travel request

[0895] The user uses their device to access the business trip application form and enters the required information (e.g., departure location, departure date and time, destination, appointment time, preferred mode of transportation, and desired accommodation).

[0896] The terminal verifies the entered information in real time, and provides a submit button only after confirming that all required fields have been filled in.

[0897] After the send button is pressed, the terminal converts the input data into JSON format, encrypts it using SSL, and sends it to the server.

[0898] Receiving and analyzing travel request data

[0899] The server receives JSON data sent from the terminal.

[0900] The server analyzes the received data and extracts information such as the departure location, departure date and time, business trip destination, appointment time, preferred mode of transportation, and desired accommodation conditions.

[0901] Recommendations for transportation and accommodation

[0902] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the most suitable mode of transportation. This also takes into account the user's seating preferences.

[0903] The server accesses a database of accommodations and searches for properties that meet the user's desired criteria. Specifically, this includes options such as non-smoking rooms and breakfast included.

[0904] Automatic booking arrangement

[0905] The server accesses the booking APIs for recommended transportation and accommodations and automatically makes reservations. This includes seat selection and obtaining booking confirmation numbers.

[0906] Sending confirmation notice

[0907] The server compiles the results of the reservation process and notifies the user's terminal.

[0908] The terminal displays notifications received from the server to the user. These may include things like departure time and reservation confirmation number.

[0909] Specific example

[0910] For example, suppose a user enters the following information for a business trip:

[0911] Departure point: Tokyo

[0912] Departure date and time: December 10, 2023, 9:00 AM

[0913] Business trip destination: Osaka

[0914] Appointment time: December 10, 2023, 1:00 PM

[0915] Transportation preference: Shinkansen (bullet train), window seat

[0916] Accommodation preferences: Business hotel, non-smoking room, breakfast included

[0917] The server analyzes this data and recommends the best seats on the Shinkansen "Nozomi" and a business hotel in Osaka. Once the recommended transportation and accommodation bookings are complete, the details are notified to the user's device.

[0918] Example of a prompt

[0919] "A user is planning a business trip from Tokyo to Osaka. Please recommend transportation and accommodation based on the user's preferences and automatically make the reservations. The departure point is Tokyo, the departure date and time is 9:00 AM on December 10, 2023, the destination is Osaka, the appointment time is 1:00 PM on December 10, 2023, and the expected return date and time is 10:00 AM on December 11, 2023. The user prefers to travel by Shinkansen (bullet train), and if possible, please select a window seat. For accommodation, the user prefers a business hotel with a non-smoking room and an option for breakfast."

[0920] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0921] Step 1:

[0922] The user accesses the business trip application form using their device and enters the required information (departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation).

[0923] Input: Various travel application information entered by the user.

[0924] Output: Travel request data displayed on the terminal

[0925] Step 2:

[0926] The terminal verifies the entered information in real time, confirming that all required fields have been filled in. After verification, it provides a submit button. When the user presses the submit button, the terminal converts the travel request data into JSON format, encrypts it using SSL, and sends it to the server.

[0927] Input: Travel request data after the user presses the submit button.

[0928] Output: Encrypted JSON data sent to the server

[0929] Step 3:

[0930] The server receives JSON data sent from the terminal. After receiving the data, it first verifies the integrity and completeness of the data. Next, it parses the received JSON data and extracts the necessary information (departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions).

[0931] Input: Encrypted travel request data (JSON format)

[0932] Output: Elemental data such as departure point, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions after analysis.

[0933] Step 4:

[0934] The server accesses a database of Shinkansen (bullet train) and airline schedules and searches for the most suitable mode of transportation based on the business trip application data. The user's transportation preferences (e.g., Shinkansen, window seat) are also taken into consideration. For example, for a business trip from Tokyo to Osaka, the server recommends the 9:00 AM Shinkansen "Nozomi" train.

[0935] Input: Data on transportation methods after analysis

[0936] Output: Details of the recommended mode of transport (e.g., Shinkansen "Nozomi", window seat)

[0937] Step 5:

[0938] The server accesses a database of accommodations and, based on the analysis results, searches for and selects the most suitable accommodations that meet the user's preferences (business hotel, non-smoking room, breakfast included, etc.). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and breakfast included.

[0939] Input: Desired conditions for accommodation after analysis

[0940] Output: Details of recommended accommodations (e.g., business hotel in Osaka city, non-smoking room, breakfast included)

[0941] Step 6:

[0942] The server accesses the booking APIs for recommended transportation and accommodations and automatically processes the bookings. During this process, it sets details tailored to the user's transportation and accommodation preferences and retrieves the booking confirmation number and detailed information.

[0943] Input: Details of recommended transportation and accommodation

[0944] Output: Reservation confirmation number and reservation details

[0945] Step 7:

[0946] The server compiles the reservation process results and notifies the user's device. The notification includes the Shinkansen reservation number, departure and arrival times, hotel reservation confirmation number, and check-in and check-out times.

[0947] Enter: Reservation confirmation number and reservation details

[0948] Output: Notification data sent to the user's terminal (e.g., Shinkansen reservation number, departure / arrival times, hotel reservation confirmation number, check-in / check-out times)

[0949] Step 8:

[0950] The device interprets notification data received from the server and displays it to the user. Notifications can be pop-ups, emails, or in-app messages.

[0951] Input: Notification data sent from the server

[0952] Output: Notification content displayed to the user

[0953] (Application Example 1)

[0954] 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."

[0955] Currently, food delivery services require users to manually search for restaurants and menus and place orders one by one. This process is time-consuming and laborious, especially for busy business people, and an automated system is needed. Furthermore, there is a lack of recommendation features that take into account user preferences and past order history, and improvements are needed to enhance user satisfaction.

[0956] 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.

[0957] This invention includes a server that receives and analyzes order requests, recommends meals and restaurants based on the user's preferences, and automates the ordering process; a server that receives business trip applications; a server that analyzes business trip application data; and a server that recommends transportation suitable for the business trip location and appointment time based on the analysis results. This allows users to easily have meals that suit their preferences, as well as transportation and accommodation necessary for business trips, automatically recommended via their smartphones, and to quickly complete the booking process.

[0958] An "order request" is a request from a user regarding their preferences for meals and restaurants, made through a food delivery application.

[0959] "Recommendation" refers to suggesting the optimal option based on user input data and past behavioral data.

[0960] A "server" is a computer system that receives user input data, analyzes it, and makes necessary recommendations and arrangements.

[0961] A "business trip application" is an application form that users submit, in which they provide detailed information about their business trip (such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation and accommodation).

[0962] "Transportation" refers to the means used to get a user from their starting point to their destination (e.g., bullet train, airplane, taxi, etc.).

[0963] "Accommodation facilities" refer to hotels, inns, and other facilities where users stay during business trips.

[0964] "Analysis" is the process by which a server breaks down the data it receives and gives it meaning.

[0965] "Reservation arrangement" refers to the process of actually booking and arranging recommended transportation, accommodation, or meal orders based on customer requests.

[0966] "Notification" refers to the act of informing a user of the results of a reservation or order.

[0967] This invention provides a system that allows users to quickly and easily order food delivery through a smartphone application. It also offers a system that recommends the most suitable transportation and accommodation options to the user based on their business trip request, and automatically makes reservations. The operation of this system, which implements this application example, is described in detail below.

[0968] System Overview

[0969] This system is built using a smartphone application, a server, and external databases and APIs that work in conjunction with it.

[0970] Hardware and software

[0971] Smartphone: An iOS or Android device with the application for food delivery and travel requests installed.

[0972] Servers: AWS (Amazon Web Services) and Google Cloud are used for data reception, analysis, recommendations, booking, and notifications.

[0973] Database: MySQL or MongoDB to manage user order history, transportation schedules, accommodation information, etc.

[0974] API: Access external services such as the Foursquare API via a RESTful API to perform recommendations and booking arrangements.

[0975] Program processing

[0976] 1. Enter and submit your order request.

[0977] Users use a smartphone app to enter their order requests. These requests include details such as the type of meal, preferred restaurant, and delivery time. The smartphone then sends this information to the server.

[0978] 2. Data reception and analysis

[0979] The server analyzes the received data and determines the appropriate restaurant and menu based on the user's preferences and past order history. For example, if the user prefers Japanese food, it will recommend nearby Japanese restaurants.

[0980] 3. Recommendations and order processing

[0981] The server places orders based on recommended restaurants and menus. Orders are sent to the restaurant's ordering system via a RESTful API, and the process is automated.

[0982] 4. Sending a confirmation notice

[0983] The server compiles the order results and notifies the user's smartphone. The notification includes the order number, estimated delivery time, and price breakdown.

[0984] Furthermore, this system also handles business trip requests and performs the following processing.

[0985] Acceptance and analysis of travel expense requests

[0986] Users enter the necessary information into a business trip request form on their smartphones and submit it. The server receives and analyzes this information. It then automatically recommends transportation and accommodation options and makes the necessary reservations.

[0987] Specific example

[0988] For example, if a user wants a Japanese lunch, they enter "Japanese food" and their desired delivery time into the app and submit it. The server then searches for nearby Japanese restaurants based on this information and recommends, for example, a "salmon set meal." The server then automatically sends the order for the salmon set meal to the restaurant and sends a confirmation notification to the user.

[0989] Example of a prompt

[0990] "The user wants a Japanese lunch. The user is currently in a regional city. Recommend a suitable restaurant and automatically order the menu."

[0991] Thus, this invention provides a system that allows users to smoothly arrange food delivery and catering services.

[0992] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0993] Step 1:

[0994] Users enter their order requests using a smartphone app. This includes details such as the type of food (e.g., Japanese food), preferred restaurant, and delivery time. The entered data is stored in the smartphone's database and sent to the server.

[0995] Input: User order request data (type of meal, preferred restaurant, delivery time)

[0996] Output: Order request data sent to the server

[0997] Step 2:

[0998] The server receives order request data sent from the smartphone. It analyzes the received data and searches for a suitable restaurant based on the user's desired dining conditions (e.g., Japanese food) and past order history.

[0999] Input: Order request data

[1000] Output: Analyzed order criteria and a list of recommended restaurants.

[1001] Step 3:

[1002] The server recommends the most suitable restaurant and menu based on the analyzed data. The recommendation process involves data calculations that take into account the user's past ordering history and preferences. For example, a user who prefers Japanese food might be recommended a "salmon set meal."

[1003] Input: Analyzed order criteria and a list of recommended restaurants.

[1004] Output: List of the best restaurants and menus

[1005] Step 4:

[1006] The server processes orders based on a list of recommended restaurants and menus. Order data is sent to the recommended restaurant's ordering system via an API. For example, an order for a salmon set meal is sent using a RESTful API.

[1007] Input: List of the best restaurants and menus

[1008] Output: Order data sent to the ordering system of the recommended restaurant.

[1009] Step 5:

[1010] The server receives and compiles the order results. These results include information such as the order number, estimated delivery time, and price breakdown. This information is compiled into notification data.

[1011] Input: Order result data received from the recommended restaurant's ordering system.

[1012] Output: Compiled notification data

[1013] Step 6:

[1014] The server sends the compiled notification data to the user's smartphone. The user receives an order confirmation notification via their smartphone and can view details such as the order number, estimated delivery time, and price breakdown.

[1015] Input: Compiled notification data

[1016] Output: Notification data sent to the smartphone

[1017] Steps to process a business trip request

[1018] Step 7:

[1019] Users enter the necessary information into a business trip request form on their smartphone and submit it. This includes details such as departure location, departure date and time, destination, appointment time, expected return date and time, and preferences for transportation and accommodation.

[1020] Input: Business trip application data (departure location, departure date and time, destination, etc.)

[1021] Output: Travel request data sent to the server

[1022] Step 8:

[1023] The server receives and analyzes the travel request data. Based on the analyzed data, it breaks down the departure location, departure date and time, destination, appointment time, etc., into individual elements and clarifies the conditions for transportation and accommodation.

[1024] Input: Business trip application data

[1025] Output: Analyzed departure location, departure date and time, destination, appointment time, etc.

[1026] Step 9:

[1027] The server consults a database and recommends suitable transportation options based on the travel destination and appointment time. For example, it might query the Shinkansen (bullet train) schedule to determine the best option.

[1028] Input: Analyzed departure location, departure date and time, destination, appointment time, etc.

[1029] Output: Recommended modes of transport

[1030] Step 10:

[1031] The server automatically books and arranges recommended transportation options. Using the API, you can book Shinkansen (bullet train) tickets and your preferred seats.

[1032] Input: Recommended mode of transport

[1033] Output: Reservation confirmation data (Shinkansen train number, seat number, etc.)

[1034] Step 11:

[1035] The server searches the database for and recommends the most suitable accommodation based on the analyzed accommodation conditions (e.g., non-smoking room, breakfast included, etc.).

[1036] Input: Analysis results of accommodation facility conditions

[1037] Output: Recommended accommodations

[1038] Step 12:

[1039] The server automatically makes reservations for recommended accommodations. It utilizes a reservation API to process reservations and retrieve data such as reservation confirmation numbers.

[1040] Input: Recommended accommodations

[1041] Output: Reservation confirmation data (such as the accommodation reservation confirmation number)

[1042] Step 13:

[1043] The server compiles the booking results for transportation and accommodation and notifies the user's smartphone. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1044] Input: Booking confirmation data for transportation and accommodation.

[1045] Output: Confirmation notification sent to smartphone

[1046] In this way, through a series of steps, users can efficiently carry out all procedures related to business travel using an automated system.

[1047] 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.

[1048] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. The system's program is implemented through the interaction of multiple servers, terminals, and users.

[1049] Program processing

[1050] 1. Enter and submit travel request

[1051] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[1052] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[1053] 2. Receiving and analyzing travel request data

[1054] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[1055] 3. Activating the Emotion Engine and Emotion Recognition

[1056] The server activates the emotion engine and collects the user's emotional data. This emotional data is obtained from the user's input speed, input content, and biometric sensors. The emotion engine analyzes this data to recognize the user's current emotions (e.g., stress, excitement, anxiety).

[1057] 4. Recommendations for modes of transportation

[1058] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. It then lists recommended options based on the user's appointment time.

[1059] The recommendation system adjusts recommendations based on the user's emotions, as recognized by the emotion engine. For example, if a user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[1060] Save the selection results for now.

[1061] 5. Accommodation Recommendations

[1062] The server accesses a database of accommodations and searches for and selects the most suitable accommodation based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included).

[1063] The emotion engine recognizes the user's emotions and reflects them accordingly. For example, if the user is seeking relaxation, it will recommend hotels with spas or relaxation services.

[1064] 6. Automated booking arrangement

[1065] The server recommends a Shinkansen (bullet train) or airline reservation API, and the user then makes the reservation. During this process, seats are reserved according to the user's preferences.

[1066] Similarly, the system accesses the accommodation booking API and proceeds with booking the recommended accommodations. It also retrieves details such as the booking confirmation number and check-in / check-out times.

[1067] 7. Sending a confirmation notice

[1068] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1069] The device receives the notification and displays it to the user.

[1070] Specific example

[1071] For example, suppose a user plans a business trip from Tokyo to Osaka. The user enters the necessary information into a business trip application form on their device and submits it. The server receives and analyzes this information, and the emotion engine recognizes the user's emotions. If it determines that the user is feeling stressed, it recommends a Green Car seat on the 9:00 AM Shinkansen "Nozomi" and suggests a hotel in Osaka with ample relaxation services. Once the reservations are completed, the details are notified to the user's device.

[1072] Thus, the present invention provides a system that automates the entire process from business trip application to recommendations, booking arrangements, and notifications, enabling users to prepare for business trips smoothly and efficiently. Furthermore, by using an emotion engine, it provides optimal suggestions tailored to the user's emotions.

[1073] The following describes the processing flow.

[1074] Step 1:

[1075] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[1076] Step 2:

[1077] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[1078] Step 3:

[1079] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[1080] Step 4:

[1081] The server activates the emotion engine and collects user emotion data. This emotion data is obtained from the user's input speed and content, biometric recognition sensors, etc. The emotion engine analyzes this data to recognize the user's current emotions (stress, excitement, anxiety, etc.).

[1082] Step 5:

[1083] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[1084] Step 6:

[1085] The server selects the optimal mode of transportation from a list of options, reflecting the user's preferences and emotional data. For example, if the user is experiencing stress, the server might recommend a more spacious Green Car or a more comfortable seat in the case of a bullet train. The selection results are then saved.

[1086] Step 7:

[1087] The server accesses the accommodation database. Based on the analysis results, it searches for and selects the accommodation that best suits the user's preferences (business hotel, non-smoking room, breakfast included, etc.).

[1088] Step 8:

[1089] The server selects the most suitable accommodation from a list of recommended options, reflecting the user's preferences and emotional data. For example, if the user is looking to relax, the server will recommend hotels with spas or relaxation services.

[1090] Step 9:

[1091] The server recommends a Shinkansen (bullet train) or airline reservation API, and the user then makes the reservation. During this process, seats are reserved according to the user's preferences.

[1092] Step 10:

[1093] The server accesses the accommodation booking API and processes the booking for the recommended accommodation. It retrieves details such as the booking confirmation number and check-in / check-out times.

[1094] Step 11:

[1095] The server compiles the booking results for transportation and accommodation and notifies the user's device. Specifically, this includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1096] Step 12:

[1097] The device receives a notification and displays it to the user. The user can then review the reservation details and request modifications or re-recommendations as needed.

[1098] Through this series of processes, users can efficiently prepare for business trips, and the introduction of an emotion engine allows them to receive more customized recommendations based on their mood and emotions.

[1099] (Example 2)

[1100] 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."

[1101] Conventional business trip application systems recommend and automatically book transportation and accommodation based on the application details, but they do not take into account the user's emotional state when making recommendations or bookings. As a result, it is difficult to select the optimal transportation and accommodation based on the user's stress and fatigue levels, and there is a need for a system that can further improve user satisfaction.

[1102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a business trip application, means for analyzing the received business trip application data, means for recommending a means of transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended means of transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the results of the booking procedure, means for activating an emotion recognition engine and analyzing the user's emotion data, and means for adjusting the recommendation content based on the user's emotion data. This makes it possible to automatically select and book the optimal means of transportation and accommodation according to the user's emotional state.

[1103] "Means of accepting business trip requests" refers to a function that retrieves business trip information entered by the user and imports it into a format that can be processed within the system.

[1104] "Means for analyzing business trip application data" refers to a function that analyzes the received business trip information and extracts and processes each element (departure point, destination, appointment time, etc.).

[1105] "A means of recommending a suitable mode of transportation for business trips and appointment times" refers to a function that proposes the optimal mode of transportation considering the business trip location and appointment times based on the analysis results.

[1106] "Method for booking recommended modes of transport" refers to a function that automatically executes the booking procedure for the recommended modes of transport.

[1107] "A means of recommending accommodations that meet the user's desired conditions" refers to a function that suggests accommodations that match the user's desired conditions based on the analysis results.

[1108] "Method for booking recommended accommodations" refers to a function that automatically executes the booking process for recommended accommodations.

[1109] "Means of notifying users of the results of the reservation process" refers to a function that compiles the reservation results for transportation and accommodation and notifies the user.

[1110] "A means of activating an emotion recognition engine and analyzing the user's emotional data" refers to a function that operates an emotion recognition engine and analyzes the user's emotional state (stress, excitement, anxiety, etc.).

[1111] "Means of adjusting recommendations based on user sentiment data" refers to a function that optimizes recommendations for transportation and accommodation according to the user's emotional state.

[1112] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. This system is implemented through the interaction of multiple servers, terminals, and users.

[1113] First, the user enters their travel request using a terminal. The user enters detailed information into the travel request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The terminal encodes the entered data in JSON or XML format and sends it to the server.

[1114] Next, the server analyzes the received data. Through this analysis, various elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation are extracted.

[1115] The server activates an emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, and other sources. The emotion engine analyzes this data to recognize emotional states such as stress, excitement, and anxiety.

[1116] Furthermore, the server accesses Shinkansen and airline schedule databases to search for the best mode of transportation from the departure point to the business trip destination. It lists recommended options based on the user's appointment time. The recommendations are then adjusted based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, comfortable seats and convenient flights will be recommended.

[1117] Similarly, the server accesses a database of accommodations to search for and select the accommodation that best suits the user's preferences. The user's emotions, recognized by the emotion engine, are reflected in the recommendations; for example, if the user is seeking relaxation, hotels with spas or relaxation services will be recommended.

[1118] The server accesses the recommended Shinkansen or airline reservation API to make the transportation reservation. Similarly, it accesses the accommodation reservation API to make the recommended accommodation reservation. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[1119] Finally, the server consolidates the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times. The device receives this information and displays it to the user.

[1120] Specific example

[1121] For example, consider a user planning a business trip from Tokyo to Osaka. The user enters the necessary information into a business trip application form on their device and submits it. The server receives and analyzes this information, and the emotion engine recognizes the user's emotions. If it determines that the user is feeling stressed, it recommends a Green Car seat on the 9:00 AM Shinkansen "Nozomi" and suggests a hotel in Osaka with ample relaxation services. Once the reservations are completed, the details are notified to the user's device.

[1122] Example of a prompt

[1123] "I'm on a business trip from Tokyo to Osaka, so please recommend a hotel with a Shinkansen Green Car (first class) and a spa."

[1124] This system allows users to prepare for business trips stress-free and efficiently, and to receive optimal suggestions tailored to their emotional state.

[1125] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1126] Step 1:

[1127] The user enters the necessary information into the travel request form on the terminal. Specifically, the user uses text fields and dropdown lists to enter information such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The entered data is temporarily stored in memory. (Input: User data, Output: Application data in JSON or XML format)

[1128] Step 2:

[1129] The terminal validates the entered data. For example, it checks whether required fields are filled in and whether the input format is correct. Once validation is complete, the terminal encodes the data into JSON or XML format and sends it to the server. (Input: User input data, Output: Validated JSON or XML data)

[1130] Step 3:

[1131] The server receives data sent from the terminal. It parses the received data and breaks it down into elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. This data is temporarily stored in a database. (Input: Application data in JSON or XML format; Output: Parsed application data)

[1132] Step 4:

[1133] The server activates the emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, etc. The emotion engine analyzes this data and recognizes emotional states such as stress, excitement, and anxiety. (Input: User input data and biometric sensor data; Output: Emotional data)

[1134] Step 5:

[1135] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the best mode of transportation from the departure point to the destination. For example, it uses Shinkansen timetable APIs and airline flight schedule APIs. Based on the user's input data and sentiment data, it lists recommended options. For example, it might recommend Green Car (first class) or Business Class to a user experiencing stress. (Input: Parsed application data and sentiment data; Output: List of recommended modes of transportation)

[1136] Step 6:

[1137] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences. Specifically, it uses a hotel reservation API and makes recommendations that reflect the user's sentiment data. For example, a user seeking relaxation would be recommended hotels with spas or relaxation services. (Input: Parsed application data and sentiment data; Output: List of recommended accommodations)

[1138] Step 7:

[1139] The system accesses the Shinkansen (bullet train) or airline reservation API recommended by the server and executes the booking process for transportation. During booking, the user's preferences (e.g., seat location and class) are reflected. Similarly, it accesses the accommodation reservation API and executes the booking process for recommended accommodations. It also retrieves booking confirmation numbers and check-in / check-out information. (Input: Recommended transportation and accommodation data, Output: Booking confirmation information)

[1140] Step 8:

[1141] The server integrates the booking results for transportation and accommodation and generates a notification message. This notification message is then sent to the device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc. (Input: Booking confirmation information, Output: Notification message)

[1142] Step 9:

[1143] The device receives notifications and displays them to the user. Specifically, these notifications can be in the form of pop-up notifications, email notifications, or in-app notifications. This allows the user to check reservation details and prepare for their business trip. (Input: Notification message, Output: Notification to user)

[1144] (Application Example 2)

[1145] 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."

[1146] Traditional business travel support systems failed to provide appropriate recommendations that reflected users' emotions, even in situations where they felt stressed or fatigued. As a result, users often experienced dissatisfaction because their business travel experience was not optimized. Furthermore, despite users' need for flexible responses tailored to their different emotional states, only uniform recommendations were provided.

[1147] 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.

[1148] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results and the user's emotions, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results and the user's emotions, means for booking the recommended accommodation, means for recognizing the user's emotions, means for adjusting the recommendations for transportation and accommodation based on the recognized user emotions, and means for notifying the user of the results of the booking procedure. This makes it possible to provide more personalized recommendations for transportation and accommodation that correspond to the user's emotional state.

[1149] A "business trip request" is a document or piece of information that a user submits to the system in advance regarding their travel and accommodation requests related to their work.

[1150] "Analysis" is the process of subdividing received data and extracting and identifying its meaning and characteristics.

[1151] "Transportation" refers to the means of getting around that a user can use during a business trip, including, for example, trains, airplanes, and taxis.

[1152] "Recommendation" is the act of a system suggesting the optimal option based on analysis results and user preferences.

[1153] "Reservation arrangement" refers to the process of securing actual transportation and accommodation based on recommendations.

[1154] "Accommodation facilities" refer to facilities for temporary stays during business trips or travel, and include hotels, inns, and other similar establishments.

[1155] "Emotions" primarily refers to the user's psychological state, including conditions such as stress, fatigue, excitement, and relaxation.

[1156] "Emotion recognition" is the process of identifying a user's emotional state at a given time based on their input and biometric data.

[1157] "Notifications" refer to the means by which a system communicates information to a user, specifically including reservation confirmations and recommendation results.

[1158] This invention combines a system that analyzes business trip application data, recommends transportation and accommodation based on that data, and automates the booking process with a user emotion recognition function. The system consists of a terminal that provides the user interface, a server that processes and manages the data, and an emotion engine that performs emotion recognition.

[1159] When a user submits a travel request using a smartphone or other device, the device sends the request to the server. The request data is encoded in JSON or XML format. The server parses this data and breaks it down into individual elements such as departure location, departure date and time, destination, and appointment time.

[1160] Next, the server activates the emotion engine and collects user emotion data. The emotion engine recognizes the user's current emotional state by utilizing user input speed, biometric sensors, and other factors. Generative AI models may be used for this emotion recognition.

[1161] The server uses the collected sentiment data and other travel application data to recommend transportation and accommodations. For example, if a user is feeling stressed, it will recommend hotels with more comfortable seating and relaxation services.

[1162] Once transportation and accommodation recommendations are determined, the server automatically arranges the reservations. It accesses reservation APIs for bullet trains, flights, and hotels to secure the necessary bookings. Details of these procedures are notified from the server to the user's device.

[1163] For example, if a user enters "I'm tired from work" into the app, the emotion engine recognizes the user's emotion as "stress." The server then recommends a "comfortable restaurant" suitable for relaxation, suggests accommodation with relaxation facilities, and automatically makes a reservation.

[1164] Examples of prompts to input into a generative AI model include the following:

[1165] For example, if a user enters "I'm tired from work" into the app, the system uses an emotion engine to recognize the user's emotion as "stress." The system then recommends a restaurant suitable for relaxation and automatically arranges food delivery from that restaurant. Please provide an example Python program that implements this process.

[1166] Based on the above explanation, the present invention can provide optimal transportation and accommodation recommendations tailored to the user's emotions, thereby improving the efficiency and comfort of business trip preparations.

[1167] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1168] Step 1:

[1169] The user uses a smartphone or device to enter the necessary information (departure location, departure date and time, destination, appointment time, etc.) into the business trip application form. The device encodes this input data into JSON or XML format and sends it to the server.

[1170] Input: User's business trip request data (departure location, departure date and time, destination, appointment time, etc.)

[1171] Output: Encoded application data (JSON or XML format)

[1172] Step 2:

[1173] The server receives the travel request data sent from the terminal and performs analysis. Specifically, the server parses the data and breaks it down into individual elements (such as departure location, departure date and time, destination, and appointment time).

[1174] Input: Encoded application data

[1175] Output: Travel request data broken down into individual elements

[1176] Step 3:

[1177] The server activates the emotion engine and collects user emotion data. Specifically, the generative AI model analyzes and recognizes the user's emotional state (stress, fatigue, excitement, etc.) using data from the user's input speed and biometric recognition sensors.

[1178] Input: User input data, biometric sensor data

[1179] Output: Recognized emotion data

[1180] Step 4:

[1181] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. Based on the user's appointment time, it lists possible recommendations. Furthermore, it adjusts the recommendations based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[1182] Input: Individual travel request data, recognized emotion data

[1183] Output: List of recommended modes of transport

[1184] Step 5:

[1185] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (business hotel, non-smoking room, breakfast included, etc.). Furthermore, based on recognized sentiment data, if the user is seeking relaxation, it recommends hotels with spas or relaxation services.

[1186] Input: Individual travel request data, recognized emotion data

[1187] Output: List of recommended accommodations

[1188] Step 6:

[1189] The system accesses a reservation API for Shinkansen (bullet train) or airline tickets recommended by the server and completes the booking process for transportation. During this process, seats are secured according to the user's preferences. Similarly, the system accesses a reservation API for accommodations and completes the booking process for recommended accommodations. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[1190] Input: List of recommended modes of transport, list of accommodations

[1191] Output: Booking confirmation information (transportation and accommodation)

[1192] Step 7:

[1193] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes booking numbers for Shinkansen (bullet train) and other services, departure and arrival times, hotel booking confirmation numbers, check-in and check-out times, etc. The device receives this notification and displays the necessary information to the user.

[1194] Input: Reservation confirmation information

[1195] Output: Notification to the user

[1196] 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.

[1197] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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.

[1198] 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.

[1199] [Fourth Embodiment]

[1200] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1201] 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.

[1202] 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).

[1203] 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.

[1204] 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.

[1205] 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).

[1206] 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.

[1207] 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.

[1208] 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.

[1209] 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.

[1210] 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.

[1211] 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.

[1212] 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".

[1213] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. The program for this system is implemented through the interaction of multiple servers, terminals, and users.

[1214] Program processing

[1215] 1. Enter and submit travel request

[1216] The user uses a terminal to submit a business trip request. They enter detailed information into the request form, including departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[1217] The terminal sends the entered travel request data to the server.

[1218] 2. Receiving and analyzing travel request data

[1219] The server receives travel request data sent from the terminal. The server analyzes the received data and breaks it down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[1220] 3. Recommendations for modes of transportation

[1221] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the most suitable mode of transportation from the departure point to the business trip destination. Based on the user's preference, it selects a window or aisle seat for Shinkansen travel. It also selects the most suitable flight to ensure the user arrives on time for their appointment.

[1222] For example, for a business trip from Tokyo to Osaka, the system would recommend the 9:00 AM Shinkansen "Nozomi" and suggest a window seat of the customer's choice.

[1223] 4. Accommodation Recommendations

[1224] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and include breakfast.

[1225] 5. Automated booking arrangement

[1226] The server accesses the recommended Shinkansen or airline reservation API and processes the reservation for the mode of transport. During this process, it secures seats that match the user's preferences.

[1227] Similarly, the system accesses the accommodation booking API and proceeds with booking the recommended accommodations. It also retrieves details such as the booking confirmation number and check-in / check-out times.

[1228] 6. Sending a confirmation notice

[1229] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1230] The device receives the notification and displays it to the user.

[1231] Specific example

[1232] For example, let's say Mr. Suzuki plans a business trip from Tokyo to Osaka. Mr. Suzuki enters the necessary information into a business trip application form on his terminal and submits it. The server receives and analyzes this information and recommends the Shinkansen "Nozomi" departing at 9:00 AM and a business hotel in Osaka. Once the reservations are complete, the details are notified to Mr. Suzuki's terminal.

[1233] Thus, the present invention provides a system that automates the entire process from business trip application to recommendations, booking arrangements, and notifications, enabling users to prepare for business trips smoothly and efficiently.

[1234] The following describes the processing flow.

[1235] Step 1:

[1236] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[1237] Step 2:

[1238] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[1239] Step 3:

[1240] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[1241] Step 4:

[1242] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches the database for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[1243] Step 5:

[1244] The server selects the most suitable mode of transportation from a list of options, reflecting the user's preferences. For example, in the case of a bullet train, it considers the user's preference for a window or aisle seat. The selection result is then saved.

[1245] Step 6:

[1246] The server accesses the accommodation database. Based on the analysis results, it selects accommodations that meet the user's desired conditions (business hotel, non-smoking room, breakfast included, etc.) from the list of recommended options.

[1247] Step 7:

[1248] The server recommends booking transportation and accommodation. Here, you access the transportation booking API to secure seats on the selected bullet train or airline.

[1249] Step 8:

[1250] The server accesses the accommodation booking API and processes the booking for the selected accommodation. It retrieves details such as the booking confirmation number and check-in / check-out times.

[1251] Step 9:

[1252] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1253] Step 10:

[1254] The device receives a notification and displays it to the user. The user can then review the reservation details and request modifications or re-recommendations as needed.

[1255] Through this series of processes, users can efficiently prepare for their business trips.

[1256] (Example 1)

[1257] 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".

[1258] Traditional business travel application and booking systems require users to manually search for and book transportation and accommodations individually, which is time-consuming and cumbersome. Furthermore, finding the optimal option that meets the user's requirements can be difficult. Additionally, errors and deficiencies in verification during the booking process can occur. Therefore, there is a need for a system that automates the entire process from user business travel application to booking arrangements, ensuring efficiency and accuracy.

[1259] 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.

[1260] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the booking procedure results, means for accessing databases of transportation and accommodation, and means for acquiring and storing booking information. This enables the user to automate and efficiently and accurately perform a series of processes from business trip requests to recommendations of transportation and accommodation, booking arrangements, and notification.

[1261] The "means for accepting business trip requests" refer to a function that receives business trip information entered by the user via a terminal and incorporates that information into the system as an initial dataset.

[1262] "Methods for analyzing received business trip application data" refers to a function that analyzes received business trip application data, breaks it down into elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions, and extracts the necessary information.

[1263] The "means of recommending transportation" is a function that suggests the optimal mode of transport from the user's departure point to their business trip destination based on analysis results. This also takes into account the user's preferences for transportation (e.g., window seats or aisle seats).

[1264] The "means of booking and arranging transportation" refers to a function that accesses a booking API for recommended transportation options, automatically performs the booking process, and sets details such as seat selection.

[1265] The "means of recommending accommodations" refer to a function that suggests the most suitable accommodations that meet the user's desired conditions based on analysis results. This also takes into account accommodation options (e.g., non-smoking rooms, breakfast included).

[1266] The "means of booking accommodations" refer to a function that accesses the booking API of recommended accommodations and automatically completes the booking process. It also retrieves the booking confirmation number and detailed information.

[1267] The "means of notifying users of the results of the booking process" refer to a function that summarizes the results of bookings for transportation and accommodation and notifies the user. The notification content includes the booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc.

[1268] "Means of accessing databases of transportation and accommodation" refers to the function of accessing databases containing information on transportation and accommodation and retrieving the necessary information. This includes calling external APIs and SQL queries.

[1269] "Means for acquiring and saving reservation information" refers to a function that securely stores reservation information obtained during the reservation process for transportation and accommodation within the system, making it accessible for later reference.

[1270] This invention is a system that receives and analyzes business trip requests, recommends transportation and accommodation based on the user's preferences, and automates the booking process. This system is implemented through the interaction of multiple servers, terminals, and users.

[1271] System hardware and software configuration

[1272] server:

[1273] The server has a high-performance processor (e.g., Intel Xeon), ample memory (e.g., 32GB RAM), and large-capacity storage (e.g., SSD). The server also has the following software installed:

[1274] Operating System: Linux (e.g., Ubuntu 20.04)

[1275] Database: MySQL or PostgreSQL

[1276] Scripting language: Python (e.g., Python 3.8)

[1277] Web server: Apache or Nginx

[1278] API server: Flask or Django

[1279] Terminal:

[1280] The terminal is a device used by users to enter travel expense requests. Generally, a PC, tablet, or smartphone is used. The terminal has the following configuration:

[1281] Operating Systems: Windows, macOS, iOS, or Android

[1282] Web browser: Google Chrome, Safari, or Edge

[1283] Network connection: Connect to the Internet

[1284] User:

[1285] The user is the person who operates the terminal to submit a travel request. The user accesses the system using a web browser and enters the necessary information.

[1286] Specific processing of the program

[1287] Entering and submitting a travel request

[1288] The user uses their device to access the business trip application form and enters the required information (e.g., departure location, departure date and time, destination, appointment time, preferred mode of transportation, and desired accommodation).

[1289] The terminal verifies the entered information in real time, and provides a submit button only after confirming that all required fields have been filled in.

[1290] After the send button is pressed, the terminal converts the input data into JSON format, encrypts it using SSL, and sends it to the server.

[1291] Receiving and analyzing travel request data

[1292] The server receives JSON data sent from the terminal.

[1293] The server analyzes the received data and extracts information such as the departure location, departure date and time, business trip destination, appointment time, preferred mode of transportation, and desired accommodation conditions.

[1294] Recommendations for transportation and accommodation

[1295] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the most suitable mode of transportation. This also takes into account the user's seating preferences.

[1296] The server accesses a database of accommodations and searches for properties that meet the user's desired criteria. Specifically, this includes options such as non-smoking rooms and breakfast included.

[1297] Automatic booking arrangement

[1298] The server accesses the booking APIs for recommended transportation and accommodations and automatically makes reservations. This includes seat selection and obtaining booking confirmation numbers.

[1299] Sending confirmation notice

[1300] The server compiles the results of the reservation process and notifies the user's terminal.

[1301] The terminal displays notifications received from the server to the user. These may include things like departure time and reservation confirmation number.

[1302] Specific example

[1303] For example, suppose a user enters the following information for a business trip:

[1304] Departure point: Tokyo

[1305] Departure date and time: December 10, 2023, 9:00 AM

[1306] Business trip destination: Osaka

[1307] Appointment time: December 10, 2023, 1:00 PM

[1308] Transportation preference: Shinkansen (bullet train), window seat

[1309] Accommodation preferences: Business hotel, non-smoking room, breakfast included

[1310] The server analyzes this data and recommends the best seats on the Shinkansen "Nozomi" and a business hotel in Osaka. Once the recommended transportation and accommodation bookings are complete, the details are notified to the user's device.

[1311] Example of a prompt

[1312] "A user is planning a business trip from Tokyo to Osaka. Please recommend transportation and accommodation based on the user's preferences and automatically make the reservations. The departure point is Tokyo, the departure date and time is 9:00 AM on December 10, 2023, the destination is Osaka, the appointment time is 1:00 PM on December 10, 2023, and the expected return date and time is 10:00 AM on December 11, 2023. The user prefers to travel by Shinkansen (bullet train), and if possible, please select a window seat. For accommodation, the user prefers a business hotel with a non-smoking room and an option for breakfast."

[1313] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1314] Step 1:

[1315] The user accesses the business trip application form using their device and enters the required information (departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation).

[1316] Input: Various travel application information entered by the user.

[1317] Output: Travel request data displayed on the terminal

[1318] Step 2:

[1319] The terminal verifies the entered information in real time, confirming that all required fields have been filled in. After verification, it provides a submit button. When the user presses the submit button, the terminal converts the travel request data into JSON format, encrypts it using SSL, and sends it to the server.

[1320] Input: Travel request data after the user presses the submit button.

[1321] Output: Encrypted JSON data sent to the server

[1322] Step 3:

[1323] The server receives JSON data sent from the terminal. After receiving the data, it first verifies the integrity and completeness of the data. Next, it parses the received JSON data and extracts the necessary information (departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions).

[1324] Input: Encrypted travel request data (JSON format)

[1325] Output: Elemental data such as departure point, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and desired accommodation conditions after analysis.

[1326] Step 4:

[1327] The server accesses a database of Shinkansen (bullet train) and airline schedules and searches for the most suitable mode of transportation based on the business trip application data. The user's transportation preferences (e.g., Shinkansen, window seat) are also taken into consideration. For example, for a business trip from Tokyo to Osaka, the server recommends the 9:00 AM Shinkansen "Nozomi" train.

[1328] Input: Data on transportation methods after analysis

[1329] Output: Details of the recommended mode of transport (e.g., Shinkansen "Nozomi", window seat)

[1330] Step 5:

[1331] The server accesses a database of accommodations and, based on the analysis results, searches for and selects the most suitable accommodations that meet the user's preferences (business hotel, non-smoking room, breakfast included, etc.). For example, it might recommend business hotels in Osaka City that offer non-smoking rooms and breakfast included.

[1332] Input: Desired conditions for accommodation after analysis

[1333] Output: Details of recommended accommodations (e.g., business hotel in Osaka city, non-smoking room, breakfast included)

[1334] Step 6:

[1335] The server accesses the booking APIs for recommended transportation and accommodations and automatically processes the bookings. During this process, it sets details tailored to the user's transportation and accommodation preferences and retrieves the booking confirmation number and detailed information.

[1336] Input: Details of recommended transportation and accommodation

[1337] Output: Reservation confirmation number and reservation details

[1338] Step 7:

[1339] The server compiles the reservation process results and notifies the user's device. The notification includes the Shinkansen reservation number, departure and arrival times, hotel reservation confirmation number, and check-in and check-out times.

[1340] Enter: Reservation confirmation number and reservation details

[1341] Output: Notification data sent to the user's terminal (e.g., Shinkansen reservation number, departure / arrival times, hotel reservation confirmation number, check-in / check-out times)

[1342] Step 8:

[1343] The device interprets notification data received from the server and displays it to the user. Notifications can be pop-ups, emails, or in-app messages.

[1344] Input: Notification data sent from the server

[1345] Output: Notification content displayed to the user

[1346] (Application Example 1)

[1347] 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".

[1348] Currently, food delivery services require users to manually search for restaurants and menus and place orders one by one. This process is time-consuming and laborious, especially for busy business people, and an automated system is needed. Furthermore, there is a lack of recommendation features that take into account user preferences and past order history, and improvements are needed to enhance user satisfaction.

[1349] 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.

[1350] This invention includes a server that receives and analyzes order requests, recommends meals and restaurants based on the user's preferences, and automates the ordering process; a server that receives business trip applications; a server that analyzes business trip application data; and a server that recommends transportation suitable for the business trip location and appointment time based on the analysis results. This allows users to easily have meals that suit their preferences, as well as transportation and accommodation necessary for business trips, automatically recommended via their smartphones, and to quickly complete the booking process.

[1351] An "order request" is a request from a user regarding their preferences for meals and restaurants, made through a food delivery application.

[1352] "Recommendation" refers to suggesting the optimal option based on user input data and past behavioral data.

[1353] A "server" is a computer system that receives user input data, analyzes it, and makes necessary recommendations and arrangements.

[1354] A "business trip application" is an application form that users submit, in which they provide detailed information about their business trip (such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation and accommodation).

[1355] "Transportation" refers to the means used to get a user from their starting point to their destination (e.g., bullet train, airplane, taxi, etc.).

[1356] "Accommodation facilities" refer to hotels, inns, and other facilities where users stay during business trips.

[1357] "Analysis" is the process by which a server breaks down the data it receives and gives it meaning.

[1358] "Reservation arrangement" refers to the process of actually booking and arranging recommended transportation, accommodation, or meal orders based on customer requests.

[1359] "Notification" refers to the act of informing a user of the results of a reservation or order.

[1360] This invention provides a system that allows users to quickly and easily order food delivery through a smartphone application. It also offers a system that recommends the most suitable transportation and accommodation options to the user based on their business trip request, and automatically makes reservations. The operation of this system, which implements this application example, is described in detail below.

[1361] System Overview

[1362] This system is built using a smartphone application, a server, and external databases and APIs that work in conjunction with it.

[1363] Hardware and software

[1364] Smartphone: An iOS or Android device with the application for food delivery and travel requests installed.

[1365] Servers: AWS (Amazon Web Services) and Google Cloud are used for data reception, analysis, recommendations, booking, and notifications.

[1366] Database: MySQL or MongoDB to manage user order history, transportation schedules, accommodation information, etc.

[1367] API: Access external services such as the Foursquare API via a RESTful API to perform recommendations and booking arrangements.

[1368] Program processing

[1369] 1. Enter and submit your order request.

[1370] Users use a smartphone app to enter their order requests. These requests include details such as the type of meal, preferred restaurant, and delivery time. The smartphone then sends this information to the server.

[1371] 2. Data reception and analysis

[1372] The server analyzes the received data and determines the appropriate restaurant and menu based on the user's preferences and past order history. For example, if the user prefers Japanese food, it will recommend nearby Japanese restaurants.

[1373] 3. Recommendations and order processing

[1374] The server places orders based on recommended restaurants and menus. Orders are sent to the restaurant's ordering system via a RESTful API, and the process is automated.

[1375] 4. Sending a confirmation notice

[1376] The server compiles the order results and notifies the user's smartphone. The notification includes the order number, estimated delivery time, and price breakdown.

[1377] Furthermore, this system also handles business trip requests and performs the following processing.

[1378] Acceptance and analysis of travel expense requests

[1379] Users enter the necessary information into a business trip request form on their smartphones and submit it. The server receives and analyzes this information. It then automatically recommends transportation and accommodation options and makes the necessary reservations.

[1380] Specific example

[1381] For example, if a user wants a Japanese lunch, they enter "Japanese food" and their desired delivery time into the app and submit it. The server then searches for nearby Japanese restaurants based on this information and recommends, for example, a "salmon set meal." The server then automatically sends the order for the salmon set meal to the restaurant and sends a confirmation notification to the user.

[1382] Example of a prompt

[1383] "The user wants a Japanese lunch. The user is currently in a regional city. Recommend a suitable restaurant and automatically order the menu."

[1384] Thus, this invention provides a system that allows users to smoothly arrange food delivery and catering services.

[1385] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1386] Step 1:

[1387] Users enter their order requests using a smartphone app. This includes details such as the type of food (e.g., Japanese food), preferred restaurant, and delivery time. The entered data is stored in the smartphone's database and sent to the server.

[1388] Input: User order request data (type of meal, preferred restaurant, delivery time)

[1389] Output: Order request data sent to the server

[1390] Step 2:

[1391] The server receives order request data sent from the smartphone. It analyzes the received data and searches for a suitable restaurant based on the user's desired dining conditions (e.g., Japanese food) and past order history.

[1392] Input: Order request data

[1393] Output: Analyzed order criteria and a list of recommended restaurants.

[1394] Step 3:

[1395] The server recommends the most suitable restaurant and menu based on the analyzed data. The recommendation process involves data calculations that take into account the user's past ordering history and preferences. For example, a user who prefers Japanese food might be recommended a "salmon set meal."

[1396] Input: Analyzed order criteria and a list of recommended restaurants.

[1397] Output: List of the best restaurants and menus

[1398] Step 4:

[1399] The server processes orders based on a list of recommended restaurants and menus. Order data is sent to the recommended restaurant's ordering system via an API. For example, an order for a salmon set meal is sent using a RESTful API.

[1400] Input: List of the best restaurants and menus

[1401] Output: Order data sent to the ordering system of the recommended restaurant.

[1402] Step 5:

[1403] The server receives and compiles the order results. These results include information such as the order number, estimated delivery time, and price breakdown. This information is compiled into notification data.

[1404] Input: Order result data received from the recommended restaurant's ordering system.

[1405] Output: Compiled notification data

[1406] Step 6:

[1407] The server sends the compiled notification data to the user's smartphone. The user receives an order confirmation notification via their smartphone and can view details such as the order number, estimated delivery time, and price breakdown.

[1408] Input: Compiled notification data

[1409] Output: Notification data sent to the smartphone

[1410] Steps to process a business trip request

[1411] Step 7:

[1412] Users enter the necessary information into a business trip request form on their smartphone and submit it. This includes details such as departure location, departure date and time, destination, appointment time, expected return date and time, and preferences for transportation and accommodation.

[1413] Input: Business trip application data (departure location, departure date and time, destination, etc.)

[1414] Output: Travel request data sent to the server

[1415] Step 8:

[1416] The server receives and analyzes the travel request data. Based on the analyzed data, it breaks down the departure location, departure date and time, destination, appointment time, etc., into individual elements and clarifies the conditions for transportation and accommodation.

[1417] Input: Business trip application data

[1418] Output: Analyzed departure location, departure date and time, destination, appointment time, etc.

[1419] Step 9:

[1420] The server consults a database and recommends suitable transportation options based on the travel destination and appointment time. For example, it might query the Shinkansen (bullet train) schedule to determine the best option.

[1421] Input: Analyzed departure location, departure date and time, destination, appointment time, etc.

[1422] Output: Recommended modes of transport

[1423] Step 10:

[1424] The server automatically books and arranges recommended transportation options. Using the API, you can book Shinkansen (bullet train) tickets and your preferred seats.

[1425] Input: Recommended mode of transport

[1426] Output: Reservation confirmation data (Shinkansen train number, seat number, etc.)

[1427] Step 11:

[1428] The server searches the database for and recommends the most suitable accommodation based on the analyzed accommodation conditions (e.g., non-smoking room, breakfast included, etc.).

[1429] Input: Analysis results of accommodation facility conditions

[1430] Output: Recommended accommodations

[1431] Step 12:

[1432] The server automatically makes reservations for recommended accommodations. It utilizes a reservation API to process reservations and retrieve data such as reservation confirmation numbers.

[1433] Input: Recommended accommodations

[1434] Output: Reservation confirmation data (such as the accommodation reservation confirmation number)

[1435] Step 13:

[1436] The server compiles the booking results for transportation and accommodation and notifies the user's smartphone. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1437] Input: Booking confirmation data for transportation and accommodation.

[1438] Output: Confirmation notification sent to smartphone

[1439] In this way, through a series of steps, users can efficiently carry out all procedures related to business travel using an automated system.

[1440] 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.

[1441] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. The system's program is implemented through the interaction of multiple servers, terminals, and users.

[1442] Program processing

[1443] 1. Enter and submit travel request

[1444] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[1445] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[1446] 2. Receiving and analyzing travel request data

[1447] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[1448] 3. Activating the Emotion Engine and Emotion Recognition

[1449] The server activates the emotion engine and collects the user's emotional data. This emotional data is obtained from the user's input speed, input content, and biometric sensors. The emotion engine analyzes this data to recognize the user's current emotions (e.g., stress, excitement, anxiety).

[1450] 4. Recommendations for modes of transportation

[1451] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. It then lists recommended options based on the user's appointment time.

[1452] The recommendation system adjusts recommendations based on the user's emotions, as recognized by the emotion engine. For example, if a user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[1453] Save the selection results for now.

[1454] 5. Accommodation Recommendations

[1455] The server accesses a database of accommodations and searches for and selects the most suitable accommodation based on the user's preferences (e.g., business hotel, non-smoking room, breakfast included).

[1456] The emotion engine recognizes the user's emotions and reflects them accordingly. For example, if the user is seeking relaxation, it will recommend hotels with spas or relaxation services.

[1457] 6. Automated booking arrangement

[1458] The server recommends a Shinkansen (bullet train) or airline reservation API, and the user then makes the reservation. During this process, seats are reserved according to the user's preferences.

[1459] Similarly, the system accesses the accommodation booking API and proceeds with booking the recommended accommodations. It also retrieves details such as the booking confirmation number and check-in / check-out times.

[1460] 7. Sending a confirmation notice

[1461] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes information such as the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1462] The device receives the notification and displays it to the user.

[1463] Specific example

[1464] For example, suppose a user plans a business trip from Tokyo to Osaka. The user enters the necessary information into a business trip application form on their device and submits it. The server receives and analyzes this information, and the emotion engine recognizes the user's emotions. If it determines that the user is feeling stressed, it recommends a Green Car seat on the 9:00 AM Shinkansen "Nozomi" and suggests a hotel in Osaka with ample relaxation services. Once the reservations are completed, the details are notified to the user's device.

[1465] Thus, the present invention provides a system that automates the entire process from business trip application to recommendations, booking arrangements, and notifications, enabling users to prepare for business trips smoothly and efficiently. Furthermore, by using an emotion engine, it provides optimal suggestions tailored to the user's emotions.

[1466] The following describes the processing flow.

[1467] Step 1:

[1468] The user uses a terminal to submit a business trip request. The user enters detailed information into the business trip request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences.

[1469] Step 2:

[1470] The terminal sends the entered travel request data to the server. The transmitted data is encoded in a standard data format such as JSON or XML.

[1471] Step 3:

[1472] The server receives the travel request data sent from the terminal. The received data is parsed and broken down into individual elements such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation.

[1473] Step 4:

[1474] The server activates the emotion engine and collects user emotion data. This emotion data is obtained from the user's input speed and content, biometric recognition sensors, etc. The emotion engine analyzes this data to recognize the user's current emotions (stress, excitement, anxiety, etc.).

[1475] Step 5:

[1476] The server accesses a database of Shinkansen (bullet train) and airline schedules. It searches for the best mode of transportation from the departure point to the destination and lists recommended options based on the user's appointment time.

[1477] Step 6:

[1478] The server selects the optimal mode of transportation from a list of options, reflecting the user's preferences and emotional data. For example, if the user is experiencing stress, the server might recommend a more spacious Green Car or a more comfortable seat in the case of a bullet train. The selection results are then saved.

[1479] Step 7:

[1480] The server accesses the accommodation database. Based on the analysis results, it searches for and selects the accommodation that best suits the user's preferences (business hotel, non-smoking room, breakfast included, etc.).

[1481] Step 8:

[1482] The server selects the most suitable accommodation from a list of recommended options, reflecting the user's preferences and emotional data. For example, if the user is looking to relax, the server will recommend hotels with spas or relaxation services.

[1483] Step 9:

[1484] The server recommends a Shinkansen (bullet train) or airline reservation API, and the user then makes the reservation. During this process, seats are reserved according to the user's preferences.

[1485] Step 10:

[1486] The server accesses the accommodation booking API and processes the booking for the recommended accommodation. It retrieves details such as the booking confirmation number and check-in / check-out times.

[1487] Step 11:

[1488] The server compiles the booking results for transportation and accommodation and notifies the user's device. Specifically, this includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times.

[1489] Step 12:

[1490] The device receives a notification and displays it to the user. The user can then review the reservation details and request modifications or re-recommendations as needed.

[1491] Through this series of processes, users can efficiently prepare for business trips, and the introduction of an emotion engine allows them to receive more customized recommendations based on their mood and emotions.

[1492] (Example 2)

[1493] 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".

[1494] Conventional business trip application systems recommend and automatically book transportation and accommodation based on the application details, but they do not take into account the user's emotional state when making recommendations or bookings. As a result, it is difficult to select the optimal transportation and accommodation based on the user's stress and fatigue levels, and there is a need for a system that can further improve user satisfaction.

[1495] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a business trip application, means for analyzing the received business trip application data, means for recommending a means of transportation suitable for the business trip location and appointment time based on the analysis results, means for booking the recommended means of transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results, means for booking the recommended accommodation, means for notifying the user of the results of the booking procedure, means for activating an emotion recognition engine and analyzing the user's emotion data, and means for adjusting the recommendation content based on the user's emotion data. This makes it possible to automatically select and book the optimal means of transportation and accommodation according to the user's emotional state.

[1496] "Means of accepting business trip requests" refers to a function that retrieves business trip information entered by the user and imports it into a format that can be processed within the system.

[1497] "Means for analyzing business trip application data" refers to a function that analyzes the received business trip information and extracts and processes each element (departure point, destination, appointment time, etc.).

[1498] "A means of recommending a suitable mode of transportation for business trips and appointment times" refers to a function that proposes the optimal mode of transportation considering the business trip location and appointment times based on the analysis results.

[1499] "Method for booking recommended modes of transport" refers to a function that automatically executes the booking procedure for the recommended modes of transport.

[1500] "A means of recommending accommodations that meet the user's desired conditions" refers to a function that suggests accommodations that match the user's desired conditions based on the analysis results.

[1501] "Method for booking recommended accommodations" refers to a function that automatically executes the booking process for recommended accommodations.

[1502] "Means of notifying users of the results of the reservation process" refers to a function that compiles the reservation results for transportation and accommodation and notifies the user.

[1503] "A means of activating an emotion recognition engine and analyzing the user's emotional data" refers to a function that operates an emotion recognition engine and analyzes the user's emotional state (stress, excitement, anxiety, etc.).

[1504] "Means of adjusting recommendations based on user sentiment data" refers to a function that optimizes recommendations for transportation and accommodation according to the user's emotional state.

[1505] This invention combines a system that receives and analyzes business trip requests, recommends transportation and accommodation based on user preferences, and automates the booking process with an emotion engine that recognizes user emotions. This system is implemented through the interaction of multiple servers, terminals, and users.

[1506] First, the user enters their travel request using a terminal. The user enters detailed information into the travel request form, such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The terminal encodes the entered data in JSON or XML format and sends it to the server.

[1507] Next, the server analyzes the received data. Through this analysis, various elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and preferred accommodation are extracted.

[1508] The server activates an emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, and other sources. The emotion engine analyzes this data to recognize emotional states such as stress, excitement, and anxiety.

[1509] Furthermore, the server accesses Shinkansen and airline schedule databases to search for the best mode of transportation from the departure point to the business trip destination. It lists recommended options based on the user's appointment time. The recommendations are then adjusted based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, comfortable seats and convenient flights will be recommended.

[1510] Similarly, the server accesses a database of accommodations to search for and select the accommodation that best suits the user's preferences. The user's emotions, recognized by the emotion engine, are reflected in the recommendations; for example, if the user is seeking relaxation, hotels with spas or relaxation services will be recommended.

[1511] The server accesses the recommended Shinkansen or airline reservation API to make the transportation reservation. Similarly, it accesses the accommodation reservation API to make the recommended accommodation reservation. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[1512] Finally, the server consolidates the booking results for transportation and accommodation and notifies the user's device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, and check-in and check-out times. The device receives this information and displays it to the user.

[1513] Specific example

[1514] For example, consider a user planning a business trip from Tokyo to Osaka. The user enters the necessary information into a business trip application form on their device and submits it. The server receives and analyzes this information, and the emotion engine recognizes the user's emotions. If it determines that the user is feeling stressed, it recommends a Green Car seat on the 9:00 AM Shinkansen "Nozomi" and suggests a hotel in Osaka with ample relaxation services. Once the reservations are completed, the details are notified to the user's device.

[1515] Example of a prompt

[1516] "I'm on a business trip from Tokyo to Osaka, so please recommend a hotel with a Shinkansen Green Car (first class) and a spa."

[1517] This system allows users to prepare for business trips stress-free and efficiently, and to receive optimal suggestions tailored to their emotional state.

[1518] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1519] Step 1:

[1520] The user enters the necessary information into the travel request form on the terminal. Specifically, the user uses text fields and dropdown lists to enter information such as departure location, departure date and time, destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. The entered data is temporarily stored in memory. (Input: User data, Output: Application data in JSON or XML format)

[1521] Step 2:

[1522] The terminal validates the entered data. For example, it checks whether required fields are filled in and whether the input format is correct. Once validation is complete, the terminal encodes the data into JSON or XML format and sends it to the server. (Input: User input data, Output: Validated JSON or XML data)

[1523] Step 3:

[1524] The server receives data sent from the terminal. It parses the received data and breaks it down into elements such as departure location, departure date and time, business trip destination, appointment time, expected return date and time, preferred mode of transportation, and accommodation preferences. This data is temporarily stored in a database. (Input: Application data in JSON or XML format; Output: Parsed application data)

[1525] Step 4:

[1526] The server activates the emotion recognition engine and collects the user's emotional data. This data is obtained from the user's input speed, input content, biometric sensors, etc. The emotion engine analyzes this data and recognizes emotional states such as stress, excitement, and anxiety. (Input: User input data and biometric sensor data; Output: Emotional data)

[1527] Step 5:

[1528] The server accesses Shinkansen (bullet train) and airline schedule databases to search for the best mode of transportation from the departure point to the destination. For example, it uses Shinkansen timetable APIs and airline flight schedule APIs. Based on the user's input data and sentiment data, it lists recommended options. For example, it might recommend Green Car (first class) or Business Class to a user experiencing stress. (Input: Parsed application data and sentiment data; Output: List of recommended modes of transportation)

[1529] Step 6:

[1530] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences. Specifically, it uses a hotel reservation API and makes recommendations that reflect the user's sentiment data. For example, a user seeking relaxation would be recommended hotels with spas or relaxation services. (Input: Parsed application data and sentiment data; Output: List of recommended accommodations)

[1531] Step 7:

[1532] The system accesses the Shinkansen (bullet train) or airline reservation API recommended by the server and executes the booking process for transportation. During booking, the user's preferences (e.g., seat location and class) are reflected. Similarly, it accesses the accommodation reservation API and executes the booking process for recommended accommodations. It also retrieves booking confirmation numbers and check-in / check-out information. (Input: Recommended transportation and accommodation data, Output: Booking confirmation information)

[1533] Step 8:

[1534] The server integrates the booking results for transportation and accommodation and generates a notification message. This notification message is then sent to the device. The notification includes the Shinkansen (bullet train) booking number, departure and arrival times, hotel booking confirmation number, check-in and check-out times, etc. (Input: Booking confirmation information, Output: Notification message)

[1535] Step 9:

[1536] The device receives notifications and displays them to the user. Specifically, these notifications can be in the form of pop-up notifications, email notifications, or in-app notifications. This allows the user to check reservation details and prepare for their business trip. (Input: Notification message, Output: Notification to user)

[1537] (Application Example 2)

[1538] 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".

[1539] Traditional business travel support systems failed to provide appropriate recommendations that reflected users' emotions, even in situations where they felt stressed or fatigued. As a result, users often experienced dissatisfaction because their business travel experience was not optimized. Furthermore, despite users' need for flexible responses tailored to their different emotional states, only uniform recommendations were provided.

[1540] 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.

[1541] In this invention, the server includes means for receiving business trip requests, means for analyzing the received business trip request data, means for recommending transportation suitable for the business trip location and appointment time based on the analysis results and the user's emotions, means for booking the recommended transportation, means for recommending accommodation that meets the user's desired conditions based on the analysis results and the user's emotions, means for booking the recommended accommodation, means for recognizing the user's emotions, means for adjusting the recommendations for transportation and accommodation based on the recognized user emotions, and means for notifying the user of the results of the booking procedure. This makes it possible to provide more personalized recommendations for transportation and accommodation that correspond to the user's emotional state.

[1542] A "business trip request" is a document or piece of information that a user submits to the system in advance regarding their travel and accommodation requests related to their work.

[1543] "Analysis" is the process of subdividing received data and extracting and identifying its meaning and characteristics.

[1544] "Transportation" refers to the means of getting around that a user can use during a business trip, including, for example, trains, airplanes, and taxis.

[1545] "Recommendation" is the act of a system suggesting the optimal option based on analysis results and user preferences.

[1546] "Reservation arrangement" refers to the process of securing actual transportation and accommodation based on recommendations.

[1547] "Accommodation facilities" refer to facilities for temporary stays during business trips or travel, and include hotels, inns, and other similar establishments.

[1548] "Emotions" primarily refers to the user's psychological state, including conditions such as stress, fatigue, excitement, and relaxation.

[1549] "Emotion recognition" is the process of identifying a user's emotional state at a given time based on their input and biometric data.

[1550] "Notifications" refer to the means by which a system communicates information to a user, specifically including reservation confirmations and recommendation results.

[1551] This invention combines a system that analyzes business trip application data, recommends transportation and accommodation based on that data, and automates the booking process with a user emotion recognition function. The system consists of a terminal that provides the user interface, a server that processes and manages the data, and an emotion engine that performs emotion recognition.

[1552] When a user submits a travel request using a smartphone or other device, the device sends the request to the server. The request data is encoded in JSON or XML format. The server parses this data and breaks it down into individual elements such as departure location, departure date and time, destination, and appointment time.

[1553] Next, the server activates the emotion engine and collects user emotion data. The emotion engine recognizes the user's current emotional state by utilizing user input speed, biometric sensors, and other factors. Generative AI models may be used for this emotion recognition.

[1554] The server uses the collected sentiment data and other travel application data to recommend transportation and accommodations. For example, if a user is feeling stressed, it will recommend hotels with more comfortable seating and relaxation services.

[1555] Once transportation and accommodation recommendations are determined, the server automatically arranges the reservations. It accesses reservation APIs for bullet trains, flights, and hotels to secure the necessary bookings. Details of these procedures are notified from the server to the user's device.

[1556] For example, if a user enters "I'm tired from work" into the app, the emotion engine recognizes the user's emotion as "stress." The server then recommends a "comfortable restaurant" suitable for relaxation, suggests accommodation with relaxation facilities, and automatically makes a reservation.

[1557] Examples of prompts to input into a generative AI model include the following:

[1558] For example, if a user enters "I'm tired from work" into the app, the system uses an emotion engine to recognize the user's emotion as "stress." The system then recommends a restaurant suitable for relaxation and automatically arranges food delivery from that restaurant. Please provide an example Python program that implements this process.

[1559] Based on the above explanation, the present invention can provide optimal transportation and accommodation recommendations tailored to the user's emotions, thereby improving the efficiency and comfort of business trip preparations.

[1560] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1561] Step 1:

[1562] The user uses a smartphone or device to enter the necessary information (departure location, departure date and time, destination, appointment time, etc.) into the business trip application form. The device encodes this input data into JSON or XML format and sends it to the server.

[1563] Input: User's business trip request data (departure location, departure date and time, destination, appointment time, etc.)

[1564] Output: Encoded application data (JSON or XML format)

[1565] Step 2:

[1566] The server receives the travel request data sent from the terminal and performs analysis. Specifically, the server parses the data and breaks it down into individual elements (such as departure location, departure date and time, destination, and appointment time).

[1567] Input: Encoded application data

[1568] Output: Travel request data broken down into individual elements

[1569] Step 3:

[1570] The server activates the emotion engine and collects user emotion data. Specifically, the generative AI model analyzes and recognizes the user's emotional state (stress, fatigue, excitement, etc.) using data from the user's input speed and biometric recognition sensors.

[1571] Input: User input data, biometric sensor data

[1572] Output: Recognized emotion data

[1573] Step 4:

[1574] The server accesses a database of Shinkansen (bullet train) and airline schedules to search for the best mode of transportation from the departure point to the business trip destination. Based on the user's appointment time, it lists possible recommendations. Furthermore, it adjusts the recommendations based on the user's emotions, as recognized by the emotion engine. For example, if the user is feeling stressed, it will recommend more comfortable seats or more convenient flights.

[1575] Input: Individual travel request data, recognized emotion data

[1576] Output: List of recommended modes of transport

[1577] Step 5:

[1578] The server accesses a database of accommodations and searches for and selects the most suitable accommodations based on the user's preferences (business hotel, non-smoking room, breakfast included, etc.). Furthermore, based on recognized sentiment data, if the user is seeking relaxation, it recommends hotels with spas or relaxation services.

[1579] Input: Individual travel request data, recognized emotion data

[1580] Output: List of recommended accommodations

[1581] Step 6:

[1582] The system accesses a reservation API for Shinkansen (bullet train) or airline tickets recommended by the server and completes the booking process for transportation. During this process, seats are secured according to the user's preferences. Similarly, the system accesses a reservation API for accommodations and completes the booking process for recommended accommodations. Details such as the reservation confirmation number and check-in / check-out times are also retrieved.

[1583] Input: List of recommended modes of transport, list of accommodations

[1584] Output: Booking confirmation information (transportation and accommodation)

[1585] Step 7:

[1586] The server compiles the booking results for transportation and accommodation and notifies the user's device. The notification includes booking numbers for Shinkansen (bullet train) and other services, departure and arrival times, hotel booking confirmation numbers, check-in and check-out times, etc. The device receives this notification and displays the necessary information to the user.

[1587] Input: Reservation confirmation information

[1588] Output: Notification to the user

[1589] 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.

[1590] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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.

[1591] 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.

[1592] 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.

[1593] 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.

[1594] 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.

[1595] 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.

[1596] 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.

[1597] 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."

[1598] 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.

[1599] 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.

[1600] 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.

[1601] 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.

[1602] 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.

[1603] 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.

[1604] 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.

[1605] 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.

[1606] 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.

[1607] 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.

[1608] 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.

[1609] 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 as being incorporated by reference.

[1610] The following is further disclosed regarding the embodiments described above.

[1611] (Claim 1)

[1612] The means of accepting business trip requests,

[1613] A means of analyzing the received travel application data,

[1614] Based on the analysis results, a method is provided to recommend a suitable mode of transportation for the business trip location and appointment time.

[1615] A method for booking and arranging recommended transportation,

[1616] Based on the analysis results, a means of recommending accommodations that meet the user's desired conditions,

[1617] A method for booking recommended accommodations,

[1618] A system that includes a means of notifying the user of the results of the reservation process.

[1619] (Claim 2)

[1620] The system according to claim 1, further comprising means for recommending a seat location (window or aisle) preferred by the user based on business trip application data.

[1621] (Claim 3)

[1622] The system according to claim 1, further comprising means for recommending accommodation options (non-smoking or smoking, whether breakfast is included, etc.) based on business trip application data.

[1623] "Example 1"

[1624] (Claim 1)

[1625] The means of accepting business trip requests,

[1626] A means of analyzing the received travel application data,

[1627] Based on the analysis results, a method is provided to recommend a suitable mode of transportation for the business trip location and appointment time.

[1628] A method for booking and arranging recommended transportation,

[1629] Based on the analysis results, a means of recommending accommodations that meet the user's desired conditions,

[1630] A method for booking recommended accommodations,

[1631] A means of notifying the user of the results of the reservation process,

[1632] Means of accessing databases of transportation and accommodation,

[1633] A system that includes means for acquiring and storing reservation information.

[1634] (Claim 2)

[1635] The system according to claim 1, further comprising means for recommending a seat location (window or aisle) preferred by the user based on business trip application data.

[1636] (Claim 3)

[1637] The system according to claim 1, further comprising means for recommending accommodation options (non-smoking or smoking, whether breakfast is included, etc.) based on business trip application data.

[1638] "Application Example 1"

[1639] (Claim 1)

[1640] The means of accepting business trip requests,

[1641] A means of analyzing the received travel application data,

[1642] Based on the analysis results, a method is provided to recommend a suitable mode of transportation for the business trip location and appointment time.

[1643] A method for booking and arranging recommended transportation,

[1644] Based on the analysis results, a means of recommending accommodations that meet the user's desired conditions,

[1645] A method for booking recommended accommodations,

[1646] A means of notifying the user of the results of the reservation process,

[1647] A system that includes means for receiving and analyzing order requests, recommending meals and restaurants based on user preferences, and automating the ordering process.

[1648] (Claim 2)

[1649] The system according to claim 1, further comprising means for recommending a seat location (window or aisle) preferred by the user based on business trip application data.

[1650] (Claim 3)

[1651] The system according to claim 1, furth...

Claims

1. The means of accepting business trip applications, A means of analyzing the received travel application data, Based on the analysis results, a method is provided to recommend a suitable mode of transportation for the business trip location and appointment time. A method for booking and arranging recommended transportation, Based on the analysis results, a means of recommending accommodations that meet the user's desired conditions, A method for booking recommended accommodations, A system that includes a means of notifying the user of the results of the reservation process.

2. The system according to claim 1, further comprising means for recommending a seat location preferred by the user based on travel request data.

3. The system according to claim 1, further comprising means for recommending accommodation options based on business trip application data.

Images