system

Abstract

We provide the system. [Solution] A means for receiving travel destination information and length of stay information entered by the user, A means for generating the optimal itinerary for a trip based on the input information, A means of collecting transportation and accommodation reservation information in bulk based on the optimal itinerary, A means for presenting the generated tour order and reservation information to the user, A system that includes this.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] When making a business trip plan, there is a problem that it takes a great deal of effort and time to collect travel routes and travel times to multiple destinations and to optimize the tour order considering the stay time. In addition, reservations for transportation and accommodation facilities need to be made individually, making it difficult to efficiently create a plan and perform the reservation procedures. As a result, there is a problem that the convenience in performing business is impaired and limited time cannot be effectively utilized.

Means for Solving the Problems

[0005] This invention provides a system that automatically generates an optimal travel sequence based on the user's input of destination and length of stay information when traveling for business, and collects transportation and accommodation reservation information in bulk based on that sequence. Furthermore, by including functions to handle transportation and accommodation reservation procedures on behalf of the user based on the plan selected by the user, and functions to obtain the latest operational information and room availability from external sources, the system enables users to create and execute business trip plans efficiently and quickly.

[0006] A "user" is an individual or legal entity that uses the system to create a travel plan.

[0007] "Travel destination information" refers to geographical information about the destination you plan to visit during your business trip.

[0008] "Length of stay information" refers to information indicating the planned duration of stay at each travel destination.

[0009] "Travel order" refers to the sequence in which you visit destinations most efficiently during your trip.

[0010] "Transportation" refers to an organization or system that provides means of getting around, such as airplanes, trains, and buses.

[0011] "Accommodation facilities" refers to hotels, inns, and other accommodations where one can stay during a business trip.

[0012] "Reservation information" refers to detailed information regarding transportation tickets and accommodation reservations.

[0013] "External information sources" refer to third-party data platforms that provide information such as transportation service status and accommodation availability.

[0014] A "business trip plan" is an overall travel schedule that includes multiple destinations, the order in which they will be visited, and related booking information. [Brief explanation of the drawing]

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a 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, the 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, the 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, the 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 implemented as a system that allows users to efficiently create business trip plans by inputting travel destination information and length of stay information. This system uses a terminal, a server, and a generating AI to propose an optimal itinerary to the user and support its execution.

[0037] The system's program includes several key functions. First, the user inputs their travel destinations and the duration of each stay into the system via a terminal. The terminal then prepares to send the input information to the server. Next, the server analyzes the received information and uses a generative AI to calculate the optimal itinerary. This AI employs algorithms such as the traveling salesperson problem to find efficient routes.

[0038] Subsequently, the server collects information on transportation services and accommodation availability from external sources based on an optimal patrol order. In this process, API access and web scraping techniques are employed to obtain the latest data. This makes it possible to present users with multiple travel plans.

[0039] The user selects the plan that best suits their needs from the presented options. Once the selection is complete, the server handles transportation reservations and accommodation arrangements based on the chosen plan. If necessary, electronic tickets and confirmation emails are automatically generated through integration with ticketless service providers.

[0040] For example, if a user plans a business trip to Tokyo, Osaka, and Nagoya, with stays of 3 hours, 5 hours, and 2 hours in each city, the system will present several optimal travel plans accordingly. The server will present a draft schedule, such as "depart for Tokyo in the morning, travel to Osaka in the afternoon, and visit Nagoya on the final day," and simultaneously display options for transportation and accommodation required for each leg of the journey. The user can then select the most convenient plan and complete the booking, allowing them to smoothly execute their business trip.

[0041] Thus, the present invention can significantly improve the efficiency of creating and managing business trip plans, providing users with a simple and comprehensive solution.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user enters travel destination and length of stay information using a device. In addition to the destination and length of stay at each location, the user enters the departure date and time and any requests regarding specific modes of transportation.

[0045] Step 2:

[0046] The terminal organizes the input information and prepares it for transmission to the server. The terminal packages the information in a specific format (e.g., JSON format) and sends it to the server.

[0047] Step 3:

[0048] The server analyzes the information received from the terminal and uses a generation AI to generate the optimal patrol order. The server calculates an efficient route considering the distance and travel time between destinations.

[0049] Step 4:

[0050] Based on a calculated patrol order, the server collects the latest transportation timetables and accommodation availability from external sources. The server uses web APIs and scraping techniques to obtain the necessary data.

[0051] Step 5:

[0052] Based on the information collected by the server, multiple travel plans are created and sent to the terminal. The server provides detailed plan information, including the mode of transportation, duration, and cost for each plan.

[0053] Step 6:

[0054] The user selects their preferred plan from those presented on their device. The user compares travel time, costs, and accommodation conditions to choose the best plan.

[0055] Step 7:

[0056] The server executes the booking process for transportation and accommodation in a single operation based on the selected plan. The server sends the necessary data to each booking system and verifies the process.

[0057] Step 8:

[0058] The terminal displays completed booking information to the user. The terminal shows electronic tickets and booking confirmation documents, allowing the user to proceed with travel preparations.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] In typical travel planning, creating efficient routes and making all transportation and accommodation reservations at once is extremely time-consuming and laborious. Furthermore, manually handling many steps, such as managing reservation information and presenting multiple travel plans, is inefficient and carries the risk of inaccurate information. To address these challenges, there is a need for a way to automate travel planning efficiently and accurately, thereby reducing the burden on users.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel route based on the entered information, and means for calculating the travel route using a generation AI model and presenting an efficient travel plan. This enables the automatic generation of an efficient and accurate travel plan based on the information entered by the user, as well as the centralized management of booking procedures.

[0064] "User" refers to an individual or group that uses this system to plan their trip.

[0065] "Destination information" refers to information about the place the user plans to visit, including place names and facility names.

[0066] "Length of stay information" refers to information indicating how long a user plans to spend at each destination.

[0067] A "travel route" refers to the sequence and route of movement when visiting multiple destinations.

[0068] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to calculate the optimal travel route.

[0069] "Transportation" refers to public transportation and rental services, including the means of transport used by travelers to move between destinations.

[0070] "Accommodation facilities" refer to facilities such as hotels, inns, and private lodgings where travelers stay.

[0071] "Reservation information" refers to the information necessary for users to secure services from transportation and accommodation providers, and includes details such as dates and prices.

[0072] "Information sources" refer to databases, websites, and other resources used to obtain the latest information on transportation and accommodation.

[0073] "Integrated management" refers to improving efficiency by integrating and processing / managing multiple processes or tasks at once.

[0074] This invention is a system for users to efficiently plan their trips. The system utilizes a terminal, a server, and a generative AI model. First, the user inputs destination and length of stay information into the terminal. The terminal uses devices such as smartphones, tablets, and personal computers, allowing users to input information through an interface.

[0075] Next, the terminal sends the entered information to the server. The server analyzes the received data and runs a generating AI model to calculate the optimal travel route. This AI model uses data processing software and algorithms to generate an efficient travel plan based on the conditions entered by the user.

[0076] For this calculation, the server is designed to use high-performance hardware to process large amounts of data quickly. It also accesses external information sources via the internet to obtain transportation service status and accommodation availability. This ensures that users are always provided with the most up-to-date information.

[0077] For example, if a user plans to "visit Tokyo, Osaka, and Nagoya, staying for 3 hours, 5 hours, and 2 hours in each city," the system will generate and present multiple travel plans accordingly. As an example of a prompt, we will use the sentence, "Please suggest the optimal travel schedule based on the destinations and purpose of your trip."

[0078] This system also provides the ability to select from multiple travel plans via a terminal. Once the user completes their selection, the server makes bulk reservations for transportation and accommodation based on the selected plan. Finally, an electronic ticket and confirmation email are automatically generated and sent to the user. This allows users to efficiently and quickly implement their travel plans.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The user enters destination and length of stay information using their device. Specifically, they access a dedicated application or web form on their device and enter the "destination" and "length of stay" separately. This becomes the input data. When the user presses the "submit" button, the input is complete and ready to proceed to the next processing step.

[0082] Step 2:

[0083] The terminal sends destination and length of stay information entered by the user to the server. The terminal converts this information into a data format such as JSON and sends an HTTP request to the appropriate API endpoint. This process uses the SSL / TLS protocol to ensure data consistency and security. This allows the server to receive user data in an organized format.

[0084] Step 3:

[0085] The server analyzes destination and length of stay information received from the terminal. Using a generative AI model, the server calculates the optimal travel route based on the input information. This model leverages algorithms to solve the traveling salesman problem, outputting plans that consider transportation convenience and time efficiency. As a result of this process, multiple efficient travel plans are generated.

[0086] Step 4:

[0087] Based on the generated travel route, the server retrieves information on transportation service status and accommodation availability from external sources. This is done using API access and web scraping to collect real-time data. Using this collected data, the server complements the details of each travel plan and generates a list of available transportation options and accommodations.

[0088] Step 5:

[0089] The server sends the generated multiple travel plans and associated information to the terminal and presents them to the user. The information is displayed in a visually easy-to-understand manner, allowing the user to compare the travel time, cost, and convenience of each plan. This is done based on prompt messages generated by the server, providing the user with the information needed to make a decision.

[0090] Step 6:

[0091] The user selects the travel plan that best suits their needs from the presented options and sends their selection to the server via their device. After making their selection, the user presses the "Complete Booking" button to officially begin the process based on their chosen plan.

[0092] Step 7:

[0093] The server handles transportation bookings and accommodation arrangements in a single process based on the user's selected travel plan. The server automatically integrates with the booking system and sends necessary e-tickets and confirmation emails to the user. This entire process ensures an efficient and stress-free travel plan for the user.

[0094] (Application Example 1)

[0095] 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."

[0096] In food delivery services, efficiently delivering goods to multiple destinations requires quickly determining the optimal delivery order and route. Current systems often involve manual route setting, which can lead to increased delivery times and wasted resources. A sophisticated system is needed to solve these problems.

[0097] 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.

[0098] In this invention, the server includes means for receiving delivery destination information and time information, means for generating an optimal delivery order based on the input information, and means for calculating and presenting a route that takes travel time into consideration. This enables optimal route planning and efficient delivery in deliveries.

[0099] "Delivery information" refers to geographical information about the delivery destination of the product, including the address and destination of the item to be delivered.

[0100] "Time information" refers to information related to the delivery schedule and duration, including the estimated start and end times of the delivery.

[0101] The "optimal delivery order" is the calculated arrival sequence for efficiently delivering goods to multiple destinations, and is designed to minimize travel time.

[0102] A "route that takes travel time into consideration" refers to the most efficient driving route, generated by evaluating factors such as traffic conditions and distance.

[0103] "Route information" refers to detailed information about the route referenced during the delivery process, including specific roads and intermediate stops.

[0104] This invention is a system for improving delivery efficiency, particularly in delivery services. A server receives delivery destination and time information from the user and generates an optimal delivery sequence using a generative AI model. This process includes calculations to select an efficient route, combined with an algorithm for solving the traveling salesman problem. Based on the generated sequence, the server calculates a route that takes travel time into account and presents the route information to the user.

[0105] This system utilizes optimization libraries such as Google® OR-Tools to determine the most efficient delivery route based on the distance and travel time between entered points. Data processing is performed on the server, and only the generated results are sent to the user's terminal. After the user reviews and selects a route, the system automatically executes the delivery plan.

[0106] As a concrete example, consider a scenario where a restaurant delivers food to multiple customers. The server receives address information for each delivery destination, considers the estimated delivery time for each, and suggests the optimal delivery order. This allows the delivery vehicles to deliver all the food in the shortest possible time.

[0107] An example of a prompt to the generating AI is: "Calculate the optimal delivery order and suggest an efficient route based on the travel time information between the following locations. The locations are as follows: [List of locations]". Through this prompt, the AI ​​quickly calculates the most efficient delivery route.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The user uses a terminal to enter the delivery address and desired delivery time. This information is then transmitted as input data to the system.

[0111] Step 2:

[0112] The server stores the delivery address and time information received from the user in a database. At this stage, the integrity and completeness of the data format are verified. The information is retained in preparation for optimization processing.

[0113] Step 3:

[0114] The server uses a generated AI model to solve the Traveling Salesperson Problem and calculate the optimal delivery order. This calculation generates an order that minimizes travel time by evaluating the distance and time between delivery locations. The output is an optimized delivery route.

[0115] Step 4:

[0116] The server calculates a detailed route based on the optimal route, taking travel time into consideration. During this process, it utilizes external data such as traffic information to optimize the route in real time. As a result of the calculation, specific route information is generated.

[0117] Step 5:

[0118] The server sends the optimal delivery order and route information it generates to the user's terminal. The user reviews the route on the terminal and chooses whether to start executing the delivery plan. Upon user approval, the next automated delivery step is executed.

[0119] Step 6:

[0120] Based on the user's selection, the system automatically issues a movement command to the delivery vehicle. The vehicle is then instructed to begin deliveries along the route according to the optimal sequence in Step 3.

[0121] Step 7:

[0122] The server monitors the delivery status and reports the delivery progress to the user in real time. Routes are re-optimized as needed, and updated information is notified to both the vehicle and the user. This ensures efficient delivery completion.

[0123] 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.

[0124] This invention allows users to input travel destination and length of stay information, and the system then efficiently creates a business trip plan based on that information. By combining this with an emotion engine, the system recognizes the user's emotions and proposes a travel plan accordingly.

[0125] The system functions by combining a terminal, a server, and an emotion engine. First, the user uses the terminal to input their travel destination and length of stay. As the user inputs their preferences through the system interface, the emotion engine detects emotions from the user's facial expressions, voice, input speed, etc.

[0126] The terminal sends detected emotional data along with the user's input information to the server. The server uses a generative AI to generate the optimal itinerary for the trip, taking the user's emotional data into consideration. This system can provide emotionally tailored plans, such as suggesting a plan with more sightseeing spots and rest time if the user is seeking relaxation.

[0127] Furthermore, the server collects transportation schedules and accommodation availability from external sources and incorporates them into the optimized plan. This process utilizes APIs and web scraping technologies to ensure real-time updates. It can also dynamically adjust the priority of choices based on feedback from an emotion engine.

[0128] For example, if a user inputs "I want to visit Tokyo, Osaka, and Nagoya" and also detects a relaxed mood, the system will prioritize suggesting plans that include relaxing facilities and tourist attractions. It can also suggest more comfortable class options for transportation.

[0129] After the user obtains a plan tailored to their emotions on their device, the server handles the booking process for transportation and accommodation based on the selected plan. Once the booking is complete, the device provides the user with an electronic ticket and confirmation email, supporting a smooth travel plan execution.

[0130] Thus, the present invention enables efficient creation and management of business trip plans, and makes it possible to provide plans that are more satisfying in accordance with the user's feelings.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The user uses a device to input travel destination and length of stay information. The device collects the entered data and simultaneously acquires sentiment data through the user interface.

[0134] Step 2:

[0135] The terminal sends user input data and emotional data to the server. Emotional data includes the results of voice and facial expression analysis and is information that quantifies the user's emotional state.

[0136] Step 3:

[0137] The server analyzes destination information, length of stay information, and emotion data received by the user. Using a generative AI, it calculates the optimal sightseeing order and customizes the plan according to the user's emotions. If the emotional state is "relaxed," it considers a plan that includes many tourist spots.

[0138] Step 4:

[0139] The server collects transportation timetables and accommodation availability information from external sources. The server uses APIs and scraping techniques to obtain the latest data and incorporate it into the generated plan.

[0140] Step 5:

[0141] The server creates multiple plans and sends information to the terminal, including a plan that has been adjusted based on the user's emotions. Each plan includes the mode of transport, duration, and cost.

[0142] Step 6:

[0143] The user selects the plan that best suits their needs from those presented on their device. The user can then see how the plan has been tailored to their emotional needs.

[0144] Step 7:

[0145] The server automatically makes reservations for transportation and accommodation based on the user's choices. Emotion-based adjustments are reflected in the reservation priority and class selection.

[0146] Step 8:

[0147] The terminal displays completed reservation information to the user and provides reservation confirmation documents and electronic tickets. This allows the user to proceed smoothly with their business trip planning.

[0148] (Example 2)

[0149] 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".

[0150] Traditional travel planning systems often provide standardized travel plans based solely on user input, making it difficult to generate plans that cater to individual user emotions and needs. Furthermore, they fail to provide plans that reflect the latest real-time transportation and accommodation information, posing a challenge to improving user satisfaction.

[0151] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0152] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel sequence based on emotions using a generating AI, and means for acquiring and incorporating transportation timetables and accommodation availability information from external resources. This makes it possible to generate highly satisfying travel plans based on the user's individual emotions and up-to-date information.

[0153] "Destination information" refers to the geographical location selected by the user as their travel destination and related information.

[0154] "Length of stay information" refers to information about the duration of a user's planned stay at a specific travel destination.

[0155] "Generative AI" is an artificial intelligence technology that generates information and plans based on given data and specified prompts.

[0156] An "emotion engine" is a technology that analyzes the user's facial expressions, voice, input speed, etc., to detect the user's emotional state.

[0157] A "public transport timetable" is information about the departure and arrival times and operating schedules of public transportation.

[0158] "Accommodation room availability information" refers to information showing the availability of rooms in accommodation facilities such as hotels and inns.

[0159] The "optimal travel sequence" is a sequence of steps that determines an efficient and satisfying travel route based on user input and emotions.

[0160] This invention is implemented using a system that efficiently creates travel plans planned by users and provides plans tailored to their individual emotions. The system mainly consists of a terminal, a server, and an emotion engine.

[0161] The user first enters travel destination and length of stay information using the terminal. During this process, the terminal uses an emotion engine to detect the user's emotions based on their facial expressions, voice, and input speed. The emotion engine utilizes various sensors and a microphone to analyze the user's emotional state.

[0162] The terminal sends the entered information and emotional data to the server. The server uses a generative AI model to generate an optimal travel plan based on the user's emotional data. The generative AI model can use prompts to generate information according to instructions. For example, if the server detects that the user wants to visit Tokyo, Osaka, and Nagoya, along with the emotion of wanting to relax, it can generate a plan that includes relaxing facilities and tourist spots. An example of a prompt would be, "I want to travel to Tokyo, Osaka, and Nagoya with a relaxing plan. Please suggest a plan that includes the latest transportation information."

[0163] Furthermore, the server utilizes APIs and web scraping technologies to collect real-time information on transportation schedules and accommodation availability, and incorporates it into the generated travel plans. This acquisition of external data makes it possible to always provide the most up-to-date information.

[0164] Once the user selects their final travel plan, the server automatically handles the booking of transportation and accommodation. The terminal then notifies the user of booking confirmations, e-tickets, and other relevant information, supporting a smooth execution of their travel plan. This system enables a personalized travel experience that enhances user satisfaction.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The user enters travel destination and length of stay information through the device. During input, the device uses its camera and microphone to record the user's facial expressions and voice, and detects emotional data through an emotion engine. At this point, the input data includes destination information, length of stay information, and emotional data. The device temporarily stores this data.

[0168] Step 2:

[0169] The device sends saved destination information, length of stay information, and sentiment data to the server. The server activates a generative AI model based on the received data to generate a travel plan. Specifically, it provides prompt messages to the generative AI model to create a travel plan tailored to the user's sentiment. As a result, the generated travel plan is output to the server.

[0170] Step 3:

[0171] The server utilizes external APIs and web scraping techniques to obtain necessary information such as transportation schedules and accommodation availability for the generated travel plan. The input is a request for relevant information based on the travel plan, and the output is a detailed travel plan reconstructed on the server, including the latest service and availability information.

[0172] Step 4:

[0173] The server sends an optimized travel plan to the device. The device then presents the received travel plan to the user on an intuitive screen. The screen display includes an overview of the travel plan, a schedule, and recommended points. The output displays a travel plan that is clearly organized and easy for the user to understand.

[0174] Step 5:

[0175] The user selects their preferred travel plan from the displayed options. The device then sends information about the selected plan back to the server. The output is information about the selected plan, reflecting the user's preferences.

[0176] Step 6:

[0177] The server automatically makes reservations for transportation and accommodation based on the user's selected plan. This is a process that accesses the reservation system via the internet and secures the necessary reservations. As output, confirmation information is generated if the reservation confirmation is successful.

[0178] Step 7:

[0179] The terminal receives booking confirmation information from the server and provides it to the user as an electronic ticket or booking confirmation email. As a final output, the user obtains all the necessary documents for their trip, completing their travel planning smoothly.

[0180] (Application Example 2)

[0181] 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".

[0182] Modern travelers want to plan their trips efficiently and comfortably, but traditional travel planning systems fail to consider user emotions and only offer standard itineraries. Furthermore, booking transportation and accommodations manually is time-consuming and laborious. Additionally, there is a lack of means to ensure that the destinations and experiences travelers actually visit align with their emotional needs.

[0183] 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.

[0184] In this invention, the server includes means for performing emotion recognition to analyze the user's emotional state, means for generating an optimal travel itinerary based on the input information and emotional state, and means for obtaining the latest transportation operation information and accommodation availability in real time from external sources. This makes it possible to propose a more satisfying travel plan that is tailored to the user's emotions and to streamline the booking process.

[0185] A "user" is the person who inputs travel destination and length of stay information, and whose emotional state is analyzed by the system.

[0186] "Emotion recognition" is the process by which an emotion engine determines the user's emotional state at a given moment based on input data such as facial expressions and voice.

[0187] The "optimal itinerary" is a sequence of visits generated based on the travel destination information, length of stay, and emotional state entered by the user, ensuring an efficient and satisfying trip.

[0188] "External information sources" refer to third-party databases or services that provide information on transportation and accommodation, and that are capable of updating information in real time.

[0189] "Transportation" refers to the vehicles and methods of travel used by the user to move between specified travel destinations, and users can choose based on comfort and convenience.

[0190] "Accommodation facilities" are facilities where travelers stay, and reservations are made based on real-time room availability.

[0191] A "display device" is a device that constitutes part of a terminal that visually provides users with generated tour order, reservation information, and suggested content.

[0192] This invention aims to enable users to efficiently plan their trips, and for those plans to be tailored to the user's emotions. The system mainly consists of a terminal, a server, and an emotion engine. The terminal refers to a device such as smart glasses or a smartphone, which the user uses to input travel destination information and length of stay information. Once the user inputs the information, the emotion engine, which performs emotion recognition, detects emotional data from the user's facial expressions and voice. This data is transmitted to the server.

[0193] The server uses a generative AI model to generate the optimal itinerary based on user-specified travel destination information and emotional data. This allows for the suggestion of plans tailored to the user's emotional state, such as including scenic tourist spots and rest areas when the user is relaxed. APIs and web scraping techniques are used to obtain real-time information on transportation and accommodations from external sources and incorporate it into the plan.

[0194] The terminal's display visually shows the generated itinerary, reservation information, and suggestions, allowing the user to browse and make selections. Once selections are made, the server automatically handles the booking process for transportation and accommodation, and sends the necessary information back to the terminal. Finally, the terminal provides the user with an electronic ticket and confirmation email, supporting them in executing their travel plan without stress.

[0195] For example, if a user specifies that they "want to visit Tokyo, Osaka, and Nagoya," and the emotion engine detects a feeling of relaxation, the server will create a plan that includes suitable tourist destinations and facilities, and suggest comfortable transportation options. Another example of a generative AI model is a prompt that can be used: "The user has requested 'Kyoto' as their travel destination, and the emotion engine's analysis has detected 'joy.' Please suggest a relaxing sightseeing plan for this user."

[0196] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0197] Step 1:

[0198] The terminal obtains travel destination and length of stay information from the user. The user enters this information using an input device, and the terminal receives that input. The input data is formatted into a format that can be used for subsequent processing.

[0199] Step 2:

[0200] The device requests the emotion engine to analyze the user's emotions. The user's facial expressions and voice data are sent to the emotion engine as input, and the emotion engine identifies the emotional state through facial recognition and voice analysis. This process outputs the user's emotional data.

[0201] Step 3:

[0202] The terminal sends the entered travel destination information, length of stay information, and sentiment data to the server. The server receives this data as input and prepares to store it in the appropriate database.

[0203] Step 4:

[0204] The server uses a generative AI model to generate the optimal itinerary. Based on the user's travel destinations, length of stay, and emotional state, the generative AI model devises the best itinerary. This model learns from prompts and outputs tourist spots and travel routes as needed.

[0205] Step 5:

[0206] The server obtains real-time information on transportation and accommodation from external sources. It collects transportation service status and accommodation availability information via API and integrates it into the generated itinerary.

[0207] Step 6:

[0208] The server sends the generated tour order and reservation information to the terminal. The terminal presents this data to the user as visual / audio information. The user can review the displayed plan and make selections or changes as needed.

[0209] Step 7:

[0210] The server handles the booking process for transportation and accommodation based on the user's selection. It automates the booking process via API, outputting necessary confirmation information according to the details of the selected plan.

[0211] Step 8:

[0212] The device sends booking confirmations and e-tickets to the user, providing all the necessary travel information. Finally, the user can check this information on their smart glasses or smartphone and complete their travel plan.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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".

[0229] This invention is implemented as a system that allows users to efficiently create business trip plans by inputting travel destination information and length of stay information. This system uses a terminal, a server, and a generating AI to propose an optimal itinerary to the user and support its execution.

[0230] The system's program includes several key functions. First, the user inputs their travel destinations and the duration of each stay into the system via a terminal. The terminal then prepares to send the input information to the server. Next, the server analyzes the received information and uses a generative AI to calculate the optimal itinerary. This AI employs algorithms such as the traveling salesperson problem to find efficient routes.

[0231] Subsequently, the server collects information on transportation services and accommodation availability from external sources based on an optimal patrol order. In this process, API access and web scraping techniques are employed to obtain the latest data. This makes it possible to present users with multiple travel plans.

[0232] The user selects the plan that best suits their needs from the presented options. Once the selection is complete, the server handles transportation reservations and accommodation arrangements based on the chosen plan. If necessary, electronic tickets and confirmation emails are automatically generated through integration with ticketless service providers.

[0233] For example, if a user plans a business trip to Tokyo, Osaka, and Nagoya, with stays of 3 hours, 5 hours, and 2 hours in each city, the system will present several optimal travel plans accordingly. The server will present a draft schedule, such as "depart for Tokyo in the morning, travel to Osaka in the afternoon, and visit Nagoya on the final day," and simultaneously display options for transportation and accommodation required for each leg of the journey. The user can then select the most convenient plan and complete the booking, allowing them to smoothly execute their business trip.

[0234] Thus, the present invention can significantly improve the efficiency of creating and managing business trip plans, providing users with a simple and comprehensive solution.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The user enters travel destination and length of stay information using a device. In addition to the destination and length of stay at each location, the user enters the departure date and time and any requests regarding specific modes of transportation.

[0238] Step 2:

[0239] The terminal organizes the input information and prepares it for transmission to the server. The terminal packages the information in a specific format (e.g., JSON format) and sends it to the server.

[0240] Step 3:

[0241] The server analyzes the information received from the terminal and uses a generation AI to generate the optimal patrol order. The server calculates an efficient route considering the distance and travel time between destinations.

[0242] Step 4:

[0243] Based on a calculated patrol order, the server collects the latest transportation timetables and accommodation availability from external sources. The server uses web APIs and scraping techniques to obtain the necessary data.

[0244] Step 5:

[0245] Based on the information collected by the server, multiple travel plans are created and sent to the terminal. The server provides detailed plan information, including the mode of transportation, duration, and cost for each plan.

[0246] Step 6:

[0247] The user selects their preferred plan from those presented on their device. The user compares travel time, costs, and accommodation conditions to choose the best plan.

[0248] Step 7:

[0249] The server executes the booking process for transportation and accommodation in a single operation based on the selected plan. The server sends the necessary data to each booking system and verifies the process.

[0250] Step 8:

[0251] The terminal displays completed booking information to the user. The terminal shows electronic tickets and booking confirmation documents, allowing the user to proceed with travel preparations.

[0252] (Example 1)

[0253] 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."

[0254] In typical travel planning, creating efficient routes and making all transportation and accommodation reservations at once is extremely time-consuming and laborious. Furthermore, manually handling many steps, such as managing reservation information and presenting multiple travel plans, is inefficient and carries the risk of inaccurate information. To address these challenges, there is a need for a way to automate travel planning efficiently and accurately, thereby reducing the burden on users.

[0255] 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.

[0256] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel route based on the entered information, and means for calculating the travel route using a generation AI model and presenting an efficient travel plan. This enables the automatic generation of an efficient and accurate travel plan based on the information entered by the user, as well as the centralized management of booking procedures.

[0257] "User" refers to an individual or group that uses this system to plan their trip.

[0258] "Destination information" refers to information about the place the user plans to visit, including place names and facility names.

[0259] "Length of stay information" refers to information indicating how long a user plans to spend at each destination.

[0260] A "travel route" refers to the sequence and route of movement when visiting multiple destinations.

[0261] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to calculate the optimal travel route.

[0262] "Transportation" refers to public transportation and rental services, including the means of transport used by travelers to move between destinations.

[0263] "Accommodation facilities" refer to facilities such as hotels, inns, and private lodgings where travelers stay.

[0264] "Reservation information" refers to the information necessary for users to secure services from transportation and accommodation providers, and includes details such as dates and prices.

[0265] "Information sources" refer to databases, websites, and other resources used to obtain the latest information on transportation and accommodation.

[0266] "Integrated management" refers to improving efficiency by integrating and processing / managing multiple processes or tasks at once.

[0267] This invention is a system for users to efficiently plan their trips. The system utilizes a terminal, a server, and a generative AI model. First, the user inputs destination and length of stay information into the terminal. The terminal uses devices such as smartphones, tablets, and personal computers, allowing users to input information through an interface.

[0268] Next, the terminal sends the entered information to the server. The server analyzes the received data and runs a generating AI model to calculate the optimal travel route. This AI model uses data processing software and algorithms to generate an efficient travel plan based on the conditions entered by the user.

[0269] For this calculation, the server is designed to use high-performance hardware to process large amounts of data quickly. It also accesses external information sources via the internet to obtain transportation service status and accommodation availability. This ensures that users are always provided with the most up-to-date information.

[0270] For example, if a user plans to "visit Tokyo, Osaka, and Nagoya, staying for 3 hours, 5 hours, and 2 hours in each city," the system will generate and present multiple travel plans accordingly. As an example of a prompt, we will use the sentence, "Please suggest the optimal travel schedule based on the destinations and purpose of your trip."

[0271] This system also provides the ability to select from multiple travel plans via a terminal. Once the user completes their selection, the server makes bulk reservations for transportation and accommodation based on the selected plan. Finally, an electronic ticket and confirmation email are automatically generated and sent to the user. This allows users to efficiently and quickly implement their travel plans.

[0272] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0273] Step 1:

[0274] The user enters destination and length of stay information using their device. Specifically, they access a dedicated application or web form on their device and enter the "destination" and "length of stay" separately. This becomes the input data. When the user presses the "submit" button, the input is complete and ready to proceed to the next processing step.

[0275] Step 2:

[0276] The terminal sends destination and length of stay information entered by the user to the server. The terminal converts this information into a data format such as JSON and sends an HTTP request to the appropriate API endpoint. This process uses the SSL / TLS protocol to ensure data consistency and security. This allows the server to receive user data in an organized format.

[0277] Step 3:

[0278] The server analyzes destination and length of stay information received from the terminal. Using a generative AI model, the server calculates the optimal travel route based on the input information. This model leverages algorithms to solve the traveling salesman problem, outputting plans that consider transportation convenience and time efficiency. As a result of this process, multiple efficient travel plans are generated.

[0279] Step 4:

[0280] Based on the generated travel route, the server retrieves information on transportation service status and accommodation availability from external sources. This is done using API access and web scraping to collect real-time data. Using this collected data, the server complements the details of each travel plan and generates a list of available transportation options and accommodations.

[0281] Step 5:

[0282] The server transmits the generated plurality of travel plans and the information attached thereto to the terminal and presents them to the user. The information is displayed visually and clearly, and the user can compare and consider the travel time, cost, and convenience of each plan. This is done based on the prompt text generated by the server, providing the user with materials for making a decision.

[0283] Step 6:

[0284] The user selects the travel plan that best suits their needs from the presented travel plans and transmits the selection to the server through the terminal. After the selection, the user presses the "Reservation Procedure Completed" button to officially start the procedure based on the selected plan.

[0285] Step 7:

[0286] The server makes a reservation for transportation and arranges accommodation facilities in one go based on the travel plan selected by the user. The server automatically cooperates with the reservation system and transmits the necessary e-tickets and confirmation emails to the user. Through this series of processes, an efficient and stress-free travel plan is completed for the user.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] In the food delivery service, in order to efficiently deliver goods to multiple destinations, it is necessary to quickly determine the optimal delivery order and route. In the current system, there are many cases where the route is set manually, which may lead to an increase in delivery time and waste of resources. An advanced system to solve such problems is required.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0291] In this invention, the server includes means for receiving delivery destination information and time information, means for generating an optimal delivery order based on the input information, and means for calculating and presenting a route that takes travel time into consideration. This enables optimal route planning and efficient delivery in deliveries.

[0292] "Delivery information" refers to geographical information about the delivery destination of the product, including the address and destination of the item to be delivered.

[0293] "Time information" refers to information related to the delivery schedule and duration, including the estimated start and end times of the delivery.

[0294] The "optimal delivery order" is the calculated arrival sequence for efficiently delivering goods to multiple destinations, and is designed to minimize travel time.

[0295] A "route that takes travel time into consideration" refers to the most efficient driving route, generated by evaluating factors such as traffic conditions and distance.

[0296] "Route information" refers to detailed information about the route referenced during the delivery process, including specific roads and intermediate stops.

[0297] This invention is a system for improving delivery efficiency, particularly in delivery services. A server receives delivery destination and time information from the user and generates an optimal delivery sequence using a generative AI model. This process includes calculations to select an efficient route, combined with an algorithm for solving the traveling salesman problem. Based on the generated sequence, the server calculates a route that takes travel time into account and presents the route information to the user.

[0298] This system utilizes optimization libraries such as Google OR-Tools to determine the most efficient delivery route based on the distance and travel time between entered points. Data processing takes place on the server, and only the generated results are sent to the user's terminal. After the user reviews and selects a route, the system automatically executes the delivery plan.

[0299] As a concrete example, consider a scenario where a restaurant delivers food to multiple customers. The server receives address information for each delivery destination, considers the estimated delivery time for each, and suggests the optimal delivery order. This allows the delivery vehicles to deliver all the food in the shortest possible time.

[0300] An example of a prompt to the generating AI is: "Calculate the optimal delivery order and suggest an efficient route based on the travel time information between the following locations. The locations are as follows: [List of locations]". Through this prompt, the AI ​​quickly calculates the most efficient delivery route.

[0301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0302] Step 1:

[0303] The user uses a terminal to enter the delivery address and desired delivery time. This information is then transmitted as input data to the system.

[0304] Step 2:

[0305] The server stores the delivery address and time information received from the user in a database. At this stage, the integrity and completeness of the data format are verified. The information is retained in preparation for optimization processing.

[0306] Step 3:

[0307] The server uses a generative AI model to solve the traveling salesman problem and calculate the optimal order of deliveries. This calculation generates an order that minimizes travel time by evaluating the distances and times between delivery destinations. An optimized delivery route is obtained as the output.

[0308] Step 4:

[0309] The server calculates a detailed driving route considering travel time based on the optimal route. At this time, external data such as traffic information is utilized to optimize the route in real time. Specific route information is generated as the calculation result.

[0310] Step 5:

[0311] The server transmits the optimal delivery order and route information generated to the user terminal. The user checks the route on the terminal and selects whether to start the execution of the delivery plan. With the user's approval, the next automatic delivery step is executed.

[0312] Step 6:

[0313] Based on the user's selection, the system automatically transmits a movement command to the delivery vehicle. A communication command is sent to the vehicle to start delivery along the route according to the optimal order in Step 3.

[0314] Step 7:

[0315] The server monitors the delivery status and reports the delivery progress to the user in real time. If necessary, the route is re-optimized and updated information is notified to the vehicle and the user. As a result, the delivery is completed efficiently.

[0316] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0317] This invention allows users to input travel destination and length of stay information, and the system then efficiently creates a business trip plan based on that information. By combining this with an emotion engine, the system recognizes the user's emotions and proposes a travel plan accordingly.

[0318] The system functions by combining a terminal, a server, and an emotion engine. First, the user uses the terminal to input their travel destination and length of stay. As the user inputs their preferences through the system interface, the emotion engine detects emotions from the user's facial expressions, voice, input speed, etc.

[0319] The terminal sends detected emotional data along with the user's input information to the server. The server uses a generative AI to generate the optimal itinerary for the trip, taking the user's emotional data into consideration. This system can provide emotionally tailored plans, such as suggesting a plan with more sightseeing spots and rest time if the user is seeking relaxation.

[0320] Furthermore, the server collects transportation schedules and accommodation availability from external sources and incorporates them into the optimized plan. This process utilizes APIs and web scraping technologies to ensure real-time updates. It can also dynamically adjust the priority of choices based on feedback from an emotion engine.

[0321] For example, if a user inputs "I want to visit Tokyo, Osaka, and Nagoya" and also detects a relaxed mood, the system will prioritize suggesting plans that include relaxing facilities and tourist attractions. It can also suggest more comfortable class options for transportation.

[0322] After the user obtains a plan tailored to their emotions on their device, the server handles the booking process for transportation and accommodation based on the selected plan. Once the booking is complete, the device provides the user with an electronic ticket and confirmation email, supporting a smooth travel plan execution.

[0323] Thus, the present invention enables efficient creation and management of business trip plans, and makes it possible to provide plans that are more satisfying in accordance with the user's feelings.

[0324] The following describes the processing flow.

[0325] Step 1:

[0326] The user uses a device to input travel destination and length of stay information. The device collects the entered data and simultaneously acquires sentiment data through the user interface.

[0327] Step 2:

[0328] The terminal sends user input data and emotional data to the server. Emotional data includes the results of voice and facial expression analysis and is information that quantifies the user's emotional state.

[0329] Step 3:

[0330] The server analyzes destination information, length of stay information, and emotion data received by the user. Using a generative AI, it calculates the optimal sightseeing order and customizes the plan according to the user's emotions. If the emotional state is "relaxed," it considers a plan that includes many tourist spots.

[0331] Step 4:

[0332] The server collects transportation timetables and accommodation availability information from external sources. The server uses APIs and scraping techniques to obtain the latest data and incorporate it into the generated plan.

[0333] Step 5:

[0334] The server creates multiple plans and sends information to the terminal, including a plan that has been adjusted based on the user's emotions. Each plan includes the mode of transport, duration, and cost.

[0335] Step 6:

[0336] The user selects the plan that best suits their needs from those presented on their device. The user can then see how the plan has been tailored to their emotional needs.

[0337] Step 7:

[0338] The server automatically makes reservations for transportation and accommodation based on the user's choices. Emotion-based adjustments are reflected in the reservation priority and class selection.

[0339] Step 8:

[0340] The terminal displays completed reservation information to the user and provides reservation confirmation documents and electronic tickets. This allows the user to proceed smoothly with their business trip planning.

[0341] (Example 2)

[0342] 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".

[0343] Traditional travel planning systems often provide standardized travel plans based solely on user input, making it difficult to generate plans that cater to individual user emotions and needs. Furthermore, they fail to provide plans that reflect the latest real-time transportation and accommodation information, posing a challenge to improving user satisfaction.

[0344] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0345] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel sequence based on emotions using a generating AI, and means for acquiring and incorporating transportation timetables and accommodation availability information from external resources. This makes it possible to generate highly satisfying travel plans based on the user's individual emotions and up-to-date information.

[0346] "Destination information" refers to the geographical location selected by the user as their travel destination and related information.

[0347] "Length of stay information" refers to information about the duration of a user's planned stay at a specific travel destination.

[0348] "Generative AI" is an artificial intelligence technology that generates information and plans based on given data and specified prompts.

[0349] An "emotion engine" is a technology that analyzes the user's facial expressions, voice, input speed, etc., to detect the user's emotional state.

[0350] A "public transport timetable" is information about the departure and arrival times and operating schedules of public transportation.

[0351] "Accommodation room availability information" refers to information showing the availability of rooms in accommodation facilities such as hotels and inns.

[0352] The "optimal travel sequence" is a sequence of steps that determines an efficient and satisfying travel route based on user input and emotions.

[0353] This invention is implemented using a system that efficiently creates travel plans planned by users and provides plans tailored to their individual emotions. The system mainly consists of a terminal, a server, and an emotion engine.

[0354] The user first enters travel destination and length of stay information using the terminal. During this process, the terminal uses an emotion engine to detect the user's emotions based on their facial expressions, voice, and input speed. The emotion engine utilizes various sensors and a microphone to analyze the user's emotional state.

[0355] The terminal sends the entered information and emotional data to the server. The server uses a generative AI model to generate an optimal travel plan based on the user's emotional data. The generative AI model can use prompts to generate information according to instructions. For example, if the server detects that the user wants to visit Tokyo, Osaka, and Nagoya, along with the emotion of wanting to relax, it can generate a plan that includes relaxing facilities and tourist spots. An example of a prompt would be, "I want to travel to Tokyo, Osaka, and Nagoya with a relaxing plan. Please suggest a plan that includes the latest transportation information."

[0356] Furthermore, the server utilizes APIs and web scraping technologies to collect real-time information on transportation schedules and accommodation availability, and incorporates it into the generated travel plans. This acquisition of external data makes it possible to always provide the most up-to-date information.

[0357] Once the user selects their final travel plan, the server automatically handles the booking of transportation and accommodation. The terminal then notifies the user of booking confirmations, e-tickets, and other relevant information, supporting a smooth execution of their travel plan. This system enables a personalized travel experience that enhances user satisfaction.

[0358] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0359] Step 1:

[0360] The user enters travel destination and length of stay information through the device. During input, the device uses its camera and microphone to record the user's facial expressions and voice, and detects emotional data through an emotion engine. At this point, the input data includes destination information, length of stay information, and emotional data. The device temporarily stores this data.

[0361] Step 2:

[0362] The device sends saved destination information, length of stay information, and sentiment data to the server. The server activates a generative AI model based on the received data to generate a travel plan. Specifically, it provides prompt messages to the generative AI model to create a travel plan tailored to the user's sentiment. As a result, the generated travel plan is output to the server.

[0363] Step 3:

[0364] The server utilizes external APIs and web scraping techniques to obtain necessary information such as transportation schedules and accommodation availability for the generated travel plan. The input is a request for relevant information based on the travel plan, and the output is a detailed travel plan reconstructed on the server, including the latest service and availability information.

[0365] Step 4:

[0366] The server sends an optimized travel plan to the device. The device then presents the received travel plan to the user on an intuitive screen. The screen display includes an overview of the travel plan, a schedule, and recommended points. The output displays a travel plan that is clearly organized and easy for the user to understand.

[0367] Step 5:

[0368] The user selects their preferred travel plan from the displayed options. The device then sends information about the selected plan back to the server. The output is information about the selected plan, reflecting the user's preferences.

[0369] Step 6:

[0370] The server automatically makes reservations for transportation and accommodation based on the user's selected plan. This is a process that accesses the reservation system via the internet and secures the necessary reservations. As output, confirmation information is generated if the reservation confirmation is successful.

[0371] Step 7:

[0372] The terminal receives booking confirmation information from the server and provides it to the user as an electronic ticket or booking confirmation email. As a final output, the user obtains all the necessary documents for their trip, completing their travel planning smoothly.

[0373] (Application Example 2)

[0374] 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."

[0375] Modern travelers want to plan their trips efficiently and comfortably, but traditional travel planning systems fail to consider user emotions and only offer standard itineraries. Furthermore, booking transportation and accommodations manually is time-consuming and laborious. Additionally, there is a lack of means to ensure that the destinations and experiences travelers actually visit align with their emotional needs.

[0376] 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.

[0377] In this invention, the server includes means for performing emotion recognition to analyze the user's emotional state, means for generating an optimal travel itinerary based on the input information and emotional state, and means for obtaining the latest transportation operation information and accommodation availability in real time from external sources. This makes it possible to propose a more satisfying travel plan that is tailored to the user's emotions and to streamline the booking process.

[0378] A "user" is the person who inputs travel destination and length of stay information, and whose emotional state is analyzed by the system.

[0379] "Emotion recognition" is the process by which an emotion engine determines the user's emotional state at a given moment based on input data such as facial expressions and voice.

[0380] The "optimal itinerary" is a sequence of visits generated based on the travel destination information, length of stay, and emotional state entered by the user, ensuring an efficient and satisfying trip.

[0381] "External information sources" refer to third-party databases or services that provide information on transportation and accommodation, and that are capable of updating information in real time.

[0382] "Transportation" refers to the vehicles and methods of travel used by the user to move between specified travel destinations, and users can choose based on comfort and convenience.

[0383] "Accommodation facilities" are facilities where travelers stay, and reservations are made based on real-time room availability.

[0384] A "display device" is a device that constitutes part of a terminal that visually provides users with generated tour order, reservation information, and suggested content.

[0385] This invention aims to enable users to efficiently plan their trips, and for those plans to be tailored to the user's emotions. The system mainly consists of a terminal, a server, and an emotion engine. The terminal refers to a device such as smart glasses or a smartphone, which the user uses to input travel destination information and length of stay information. Once the user inputs the information, the emotion engine, which performs emotion recognition, detects emotional data from the user's facial expressions and voice. This data is transmitted to the server.

[0386] The server uses a generative AI model to generate the optimal itinerary based on user-specified travel destination information and emotional data. This allows for the suggestion of plans tailored to the user's emotional state, such as including scenic tourist spots and rest areas when the user is relaxed. APIs and web scraping techniques are used to obtain real-time information on transportation and accommodations from external sources and incorporate it into the plan.

[0387] The terminal's display visually shows the generated itinerary, reservation information, and suggestions, allowing the user to browse and make selections. Once selections are made, the server automatically handles the booking process for transportation and accommodation, and sends the necessary information back to the terminal. Finally, the terminal provides the user with an electronic ticket and confirmation email, supporting them in executing their travel plan without stress.

[0388] For example, if a user specifies that they "want to visit Tokyo, Osaka, and Nagoya," and the emotion engine detects a feeling of relaxation, the server will create a plan that includes suitable tourist destinations and facilities, and suggest comfortable transportation options. Another example of a generative AI model is a prompt that can be used: "The user has requested 'Kyoto' as their travel destination, and the emotion engine's analysis has detected 'joy.' Please suggest a relaxing sightseeing plan for this user."

[0389] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0390] Step 1:

[0391] The terminal obtains travel destination and length of stay information from the user. The user enters this information using an input device, and the terminal receives that input. The input data is formatted into a format that can be used for subsequent processing.

[0392] Step 2:

[0393] The device requests the emotion engine to analyze the user's emotions. The user's facial expressions and voice data are sent to the emotion engine as input, and the emotion engine identifies the emotional state through facial recognition and voice analysis. This process outputs the user's emotional data.

[0394] Step 3:

[0395] The terminal sends the entered travel destination information, length of stay information, and sentiment data to the server. The server receives this data as input and prepares to store it in the appropriate database.

[0396] Step 4:

[0397] The server uses a generative AI model to generate the optimal itinerary. Based on the user's travel destinations, length of stay, and emotional state, the generative AI model devises the best itinerary. This model learns from prompts and outputs tourist spots and travel routes as needed.

[0398] Step 5:

[0399] The server obtains real-time information on transportation and accommodation from external sources. It collects transportation service status and accommodation availability information via API and integrates it into the generated itinerary.

[0400] Step 6:

[0401] The server sends the generated tour order and reservation information to the terminal. The terminal presents this data to the user as visual / audio information. The user can review the displayed plan and make selections or changes as needed.

[0402] Step 7:

[0403] The server handles the booking process for transportation and accommodation based on the user's selection. It automates the booking process via API, outputting necessary confirmation information according to the details of the selected plan.

[0404] Step 8:

[0405] The device sends booking confirmations and e-tickets to the user, providing all the necessary travel information. Finally, the user can check this information on their smart glasses or smartphone and complete their travel plan.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] [Third Embodiment]

[0410] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0411] 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.

[0412] 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).

[0413] 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.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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".

[0422] This invention is implemented as a system that allows users to efficiently create business trip plans by inputting travel destination information and length of stay information. This system uses a terminal, a server, and a generating AI to propose an optimal itinerary to the user and support its execution.

[0423] The system's program includes several key functions. First, the user inputs their travel destinations and the duration of each stay into the system via a terminal. The terminal then prepares to send the input information to the server. Next, the server analyzes the received information and uses a generative AI to calculate the optimal itinerary. This AI employs algorithms such as the traveling salesperson problem to find efficient routes.

[0424] Subsequently, the server collects information on transportation services and accommodation availability from external sources based on an optimal patrol order. In this process, API access and web scraping techniques are employed to obtain the latest data. This makes it possible to present users with multiple travel plans.

[0425] The user selects the plan that best suits their needs from the presented options. Once the selection is complete, the server handles transportation reservations and accommodation arrangements based on the chosen plan. If necessary, electronic tickets and confirmation emails are automatically generated through integration with ticketless service providers.

[0426] For example, if a user plans a business trip to Tokyo, Osaka, and Nagoya, with stays of 3 hours, 5 hours, and 2 hours in each city, the system will present several optimal travel plans accordingly. The server will present a draft schedule, such as "depart for Tokyo in the morning, travel to Osaka in the afternoon, and visit Nagoya on the final day," and simultaneously display options for transportation and accommodation required for each leg of the journey. The user can then select the most convenient plan and complete the booking, allowing them to smoothly execute their business trip.

[0427] Thus, the present invention can significantly improve the efficiency of creating and managing business trip plans, providing users with a simple and comprehensive solution.

[0428] The following describes the processing flow.

[0429] Step 1:

[0430] The user enters travel destination and length of stay information using a device. In addition to the destination and length of stay at each location, the user enters the departure date and time and any requests regarding specific modes of transportation.

[0431] Step 2:

[0432] The terminal organizes the input information and prepares it for transmission to the server. The terminal packages the information in a specific format (e.g., JSON format) and sends it to the server.

[0433] Step 3:

[0434] The server analyzes the information received from the terminal and uses a generation AI to generate the optimal patrol order. The server calculates an efficient route considering the distance and travel time between destinations.

[0435] Step 4:

[0436] Based on a calculated patrol order, the server collects the latest transportation timetables and accommodation availability from external sources. The server uses web APIs and scraping techniques to obtain the necessary data.

[0437] Step 5:

[0438] Based on the information collected by the server, multiple travel plans are created and sent to the terminal. The server provides detailed plan information, including the mode of transportation, duration, and cost for each plan.

[0439] Step 6:

[0440] The user selects their preferred plan from those presented on their device. The user compares travel time, costs, and accommodation conditions to choose the best plan.

[0441] Step 7:

[0442] The server executes the booking process for transportation and accommodation in a single operation based on the selected plan. The server sends the necessary data to each booking system and verifies the process.

[0443] Step 8:

[0444] The terminal displays completed booking information to the user. The terminal shows electronic tickets and booking confirmation documents, allowing the user to proceed with travel preparations.

[0445] (Example 1)

[0446] 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."

[0447] In typical travel planning, creating efficient routes and making all transportation and accommodation reservations at once is extremely time-consuming and laborious. Furthermore, manually handling many steps, such as managing reservation information and presenting multiple travel plans, is inefficient and carries the risk of inaccurate information. To address these challenges, there is a need for a way to automate travel planning efficiently and accurately, thereby reducing the burden on users.

[0448] 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.

[0449] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel route based on the entered information, and means for calculating the travel route using a generation AI model and presenting an efficient travel plan. This enables the automatic generation of an efficient and accurate travel plan based on the information entered by the user, as well as the centralized management of booking procedures.

[0450] "User" refers to an individual or group that uses this system to plan their trip.

[0451] "Destination information" refers to information about the place the user plans to visit, including place names and facility names.

[0452] "Length of stay information" refers to information indicating how long a user plans to spend at each destination.

[0453] A "travel route" refers to the sequence and route of movement when visiting multiple destinations.

[0454] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to calculate the optimal travel route.

[0455] "Transportation" refers to public transportation and rental services, including the means of transport used by travelers to move between destinations.

[0456] "Accommodation facilities" refer to facilities such as hotels, inns, and private lodgings where travelers stay.

[0457] "Reservation information" refers to the information necessary for users to secure services from transportation and accommodation providers, and includes details such as dates and prices.

[0458] "Information sources" refer to databases, websites, and other resources used to obtain the latest information on transportation and accommodation.

[0459] "Integrated management" refers to improving efficiency by integrating and processing / managing multiple processes or tasks at once.

[0460] This invention is a system for users to efficiently plan their trips. The system utilizes a terminal, a server, and a generative AI model. First, the user inputs destination and length of stay information into the terminal. The terminal uses devices such as smartphones, tablets, and personal computers, allowing users to input information through an interface.

[0461] Next, the terminal sends the entered information to the server. The server analyzes the received data and runs a generating AI model to calculate the optimal travel route. This AI model uses data processing software and algorithms to generate an efficient travel plan based on the conditions entered by the user.

[0462] For this calculation, the server is designed to use high-performance hardware to process large amounts of data quickly. It also accesses external information sources via the internet to obtain transportation service status and accommodation availability. This ensures that users are always provided with the most up-to-date information.

[0463] For example, if a user plans to "visit Tokyo, Osaka, and Nagoya, staying for 3 hours, 5 hours, and 2 hours in each city," the system will generate and present multiple travel plans accordingly. As an example of a prompt, we will use the sentence, "Please suggest the optimal travel schedule based on the destinations and purpose of your trip."

[0464] This system also provides the ability to select from multiple travel plans via a terminal. Once the user completes their selection, the server makes bulk reservations for transportation and accommodation based on the selected plan. Finally, an electronic ticket and confirmation email are automatically generated and sent to the user. This allows users to efficiently and quickly implement their travel plans.

[0465] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0466] Step 1:

[0467] The user enters destination and length of stay information using their device. Specifically, they access a dedicated application or web form on their device and enter the "destination" and "length of stay" separately. This becomes the input data. When the user presses the "submit" button, the input is complete and ready to proceed to the next processing step.

[0468] Step 2:

[0469] The terminal sends destination and length of stay information entered by the user to the server. The terminal converts this information into a data format such as JSON and sends an HTTP request to the appropriate API endpoint. This process uses the SSL / TLS protocol to ensure data consistency and security. This allows the server to receive user data in an organized format.

[0470] Step 3:

[0471] The server analyzes destination and length of stay information received from the terminal. Using a generative AI model, the server calculates the optimal travel route based on the input information. This model leverages algorithms to solve the traveling salesman problem, outputting plans that consider transportation convenience and time efficiency. As a result of this process, multiple efficient travel plans are generated.

[0472] Step 4:

[0473] Based on the generated travel route, the server retrieves information on transportation service status and accommodation availability from external sources. This is done using API access and web scraping to collect real-time data. Using this collected data, the server complements the details of each travel plan and generates a list of available transportation options and accommodations.

[0474] Step 5:

[0475] The server sends the generated multiple travel plans and associated information to the terminal and presents them to the user. The information is displayed in a visually easy-to-understand manner, allowing the user to compare the travel time, cost, and convenience of each plan. This is done based on prompt messages generated by the server, providing the user with the information needed to make a decision.

[0476] Step 6:

[0477] The user selects the travel plan that best suits their needs from the presented options and sends their selection to the server via their device. After making their selection, the user presses the "Complete Booking" button to officially begin the process based on their chosen plan.

[0478] Step 7:

[0479] The server handles transportation bookings and accommodation arrangements in a single process based on the user's selected travel plan. The server automatically integrates with the booking system and sends necessary e-tickets and confirmation emails to the user. This entire process ensures an efficient and stress-free travel plan for the user.

[0480] (Application Example 1)

[0481] 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."

[0482] In food delivery services, efficiently delivering goods to multiple destinations requires quickly determining the optimal delivery order and route. Current systems often involve manual route setting, which can lead to increased delivery times and wasted resources. A sophisticated system is needed to solve these problems.

[0483] 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.

[0484] In this invention, the server includes means for receiving delivery destination information and time information, means for generating an optimal delivery order based on the input information, and means for calculating and presenting a route that takes travel time into consideration. This enables optimal route planning and efficient delivery in deliveries.

[0485] "Delivery information" refers to geographical information about the delivery destination of the product, including the address and destination of the item to be delivered.

[0486] "Time information" refers to information related to the delivery schedule and duration, including the estimated start and end times of the delivery.

[0487] The "optimal delivery order" is the calculated arrival sequence for efficiently delivering goods to multiple destinations, and is designed to minimize travel time.

[0488] A "route that takes travel time into consideration" refers to the most efficient driving route, generated by evaluating factors such as traffic conditions and distance.

[0489] "Route information" refers to detailed information about the route referenced during the delivery process, including specific roads and intermediate stops.

[0490] This invention is a system for improving delivery efficiency, particularly in delivery services. A server receives delivery destination and time information from the user and generates an optimal delivery sequence using a generative AI model. This process includes calculations to select an efficient route, combined with an algorithm for solving the traveling salesman problem. Based on the generated sequence, the server calculates a route that takes travel time into account and presents the route information to the user.

[0491] This system utilizes optimization libraries such as Google OR-Tools to determine the most efficient delivery route based on the distance and travel time between entered points. Data processing takes place on the server, and only the generated results are sent to the user's terminal. After the user reviews and selects a route, the system automatically executes the delivery plan.

[0492] As a concrete example, consider a scenario where a restaurant delivers food to multiple customers. The server receives address information for each delivery destination, considers the estimated delivery time for each, and suggests the optimal delivery order. This allows the delivery vehicles to deliver all the food in the shortest possible time.

[0493] An example of a prompt to the generating AI is: "Calculate the optimal delivery order and suggest an efficient route based on the travel time information between the following locations. The locations are as follows: [List of locations]". Through this prompt, the AI ​​quickly calculates the most efficient delivery route.

[0494] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0495] Step 1:

[0496] The user uses a terminal to enter the delivery address and desired delivery time. This information is then transmitted as input data to the system.

[0497] Step 2:

[0498] The server stores the delivery address and time information received from the user in a database. At this stage, the integrity and completeness of the data format are verified. The information is retained in preparation for optimization processing.

[0499] Step 3:

[0500] The server uses a generated AI model to solve the Traveling Salesperson Problem and calculate the optimal delivery order. This calculation generates an order that minimizes travel time by evaluating the distance and time between delivery locations. The output is an optimized delivery route.

[0501] Step 4:

[0502] The server calculates a detailed route based on the optimal route, taking travel time into consideration. During this process, it utilizes external data such as traffic information to optimize the route in real time. As a result of the calculation, specific route information is generated.

[0503] Step 5:

[0504] The server sends the optimal delivery order and route information it generates to the user's terminal. The user reviews the route on the terminal and chooses whether to start executing the delivery plan. Upon user approval, the next automated delivery step is executed.

[0505] Step 6:

[0506] Based on the user's selection, the system automatically issues a movement command to the delivery vehicle. The vehicle is then instructed to begin deliveries along the route according to the optimal sequence in Step 3.

[0507] Step 7:

[0508] The server monitors the delivery status and reports the delivery progress to the user in real time. Routes are re-optimized as needed, and updated information is notified to both the vehicle and the user. This ensures efficient delivery completion.

[0509] 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.

[0510] This invention allows users to input travel destination and length of stay information, and the system then efficiently creates a business trip plan based on that information. By combining this with an emotion engine, the system recognizes the user's emotions and proposes a travel plan accordingly.

[0511] The system functions by combining a terminal, a server, and an emotion engine. First, the user uses the terminal to input their travel destination and length of stay. As the user inputs their preferences through the system interface, the emotion engine detects emotions from the user's facial expressions, voice, input speed, etc.

[0512] The terminal sends detected emotional data along with the user's input information to the server. The server uses a generative AI to generate the optimal itinerary for the trip, taking the user's emotional data into consideration. This system can provide emotionally tailored plans, such as suggesting a plan with more sightseeing spots and rest time if the user is seeking relaxation.

[0513] Furthermore, the server collects transportation schedules and accommodation availability from external sources and incorporates them into the optimized plan. This process utilizes APIs and web scraping technologies to ensure real-time updates. It can also dynamically adjust the priority of choices based on feedback from an emotion engine.

[0514] For example, if a user inputs "I want to visit Tokyo, Osaka, and Nagoya" and also detects a relaxed mood, the system will prioritize suggesting plans that include relaxing facilities and tourist attractions. It can also suggest more comfortable class options for transportation.

[0515] After the user obtains a plan tailored to their emotions on their device, the server handles the booking process for transportation and accommodation based on the selected plan. Once the booking is complete, the device provides the user with an electronic ticket and confirmation email, supporting a smooth travel plan execution.

[0516] Thus, the present invention enables efficient creation and management of business trip plans, and makes it possible to provide plans that are more satisfying in accordance with the user's feelings.

[0517] The following describes the processing flow.

[0518] Step 1:

[0519] The user uses a device to input travel destination and length of stay information. The device collects the entered data and simultaneously acquires sentiment data through the user interface.

[0520] Step 2:

[0521] The terminal sends user input data and emotional data to the server. Emotional data includes the results of voice and facial expression analysis and is information that quantifies the user's emotional state.

[0522] Step 3:

[0523] The server analyzes destination information, length of stay information, and emotion data received by the user. Using a generative AI, it calculates the optimal sightseeing order and customizes the plan according to the user's emotions. If the emotional state is "relaxed," it considers a plan that includes many tourist spots.

[0524] Step 4:

[0525] The server collects transportation timetables and accommodation availability information from external sources. The server uses APIs and scraping techniques to obtain the latest data and incorporate it into the generated plan.

[0526] Step 5:

[0527] The server creates multiple plans and sends information to the terminal, including a plan that has been adjusted based on the user's emotions. Each plan includes the mode of transport, duration, and cost.

[0528] Step 6:

[0529] The user selects the plan that best suits their needs from those presented on their device. The user can then see how the plan has been tailored to their emotional needs.

[0530] Step 7:

[0531] The server automatically makes reservations for transportation and accommodation based on the user's choices. Emotion-based adjustments are reflected in the reservation priority and class selection.

[0532] Step 8:

[0533] The terminal displays completed reservation information to the user and provides reservation confirmation documents and electronic tickets. This allows the user to proceed smoothly with their business trip planning.

[0534] (Example 2)

[0535] 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."

[0536] Traditional travel planning systems often provide standardized travel plans based solely on user input, making it difficult to generate plans that cater to individual user emotions and needs. Furthermore, they fail to provide plans that reflect the latest real-time transportation and accommodation information, posing a challenge to improving user satisfaction.

[0537] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0538] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel sequence based on emotions using a generating AI, and means for acquiring and incorporating transportation timetables and accommodation availability information from external resources. This makes it possible to generate highly satisfying travel plans based on the user's individual emotions and up-to-date information.

[0539] "Destination information" refers to the geographical location selected by the user as their travel destination and related information.

[0540] "Length of stay information" refers to information about the duration of a user's planned stay at a specific travel destination.

[0541] "Generative AI" is an artificial intelligence technology that generates information and plans based on given data and specified prompts.

[0542] An "emotion engine" is a technology that analyzes the user's facial expressions, voice, input speed, etc., to detect the user's emotional state.

[0543] A "public transport timetable" is information about the departure and arrival times and operating schedules of public transportation.

[0544] "Accommodation room availability information" refers to information showing the availability of rooms in accommodation facilities such as hotels and inns.

[0545] The "optimal travel sequence" is a sequence of steps that determines an efficient and satisfying travel route based on user input and emotions.

[0546] This invention is implemented using a system that efficiently creates travel plans planned by users and provides plans tailored to their individual emotions. The system mainly consists of a terminal, a server, and an emotion engine.

[0547] The user first enters travel destination and length of stay information using the terminal. During this process, the terminal uses an emotion engine to detect the user's emotions based on their facial expressions, voice, and input speed. The emotion engine utilizes various sensors and a microphone to analyze the user's emotional state.

[0548] The terminal sends the entered information and emotional data to the server. The server uses a generative AI model to generate an optimal travel plan based on the user's emotional data. The generative AI model can use prompts to generate information according to instructions. For example, if the server detects that the user wants to visit Tokyo, Osaka, and Nagoya, along with the emotion of wanting to relax, it can generate a plan that includes relaxing facilities and tourist spots. An example of a prompt would be, "I want to travel to Tokyo, Osaka, and Nagoya with a relaxing plan. Please suggest a plan that includes the latest transportation information."

[0549] Furthermore, the server utilizes APIs and web scraping technologies to collect real-time information on transportation schedules and accommodation availability, and incorporates it into the generated travel plans. This acquisition of external data makes it possible to always provide the most up-to-date information.

[0550] Once the user selects their final travel plan, the server automatically handles the booking of transportation and accommodation. The terminal then notifies the user of booking confirmations, e-tickets, and other relevant information, supporting a smooth execution of their travel plan. This system enables a personalized travel experience that enhances user satisfaction.

[0551] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0552] Step 1:

[0553] The user enters travel destination and length of stay information through the device. During input, the device uses its camera and microphone to record the user's facial expressions and voice, and detects emotional data through an emotion engine. At this point, the input data includes destination information, length of stay information, and emotional data. The device temporarily stores this data.

[0554] Step 2:

[0555] The device sends saved destination information, length of stay information, and sentiment data to the server. The server activates a generative AI model based on the received data to generate a travel plan. Specifically, it provides prompt messages to the generative AI model to create a travel plan tailored to the user's sentiment. As a result, the generated travel plan is output to the server.

[0556] Step 3:

[0557] The server utilizes external APIs and web scraping techniques to obtain necessary information such as transportation schedules and accommodation availability for the generated travel plan. The input is a request for relevant information based on the travel plan, and the output is a detailed travel plan reconstructed on the server, including the latest service and availability information.

[0558] Step 4:

[0559] The server sends an optimized travel plan to the device. The device then presents the received travel plan to the user on an intuitive screen. The screen display includes an overview of the travel plan, a schedule, and recommended points. The output displays a travel plan that is clearly organized and easy for the user to understand.

[0560] Step 5:

[0561] The user selects their preferred travel plan from the displayed options. The device then sends information about the selected plan back to the server. The output is information about the selected plan, reflecting the user's preferences.

[0562] Step 6:

[0563] The server automatically makes reservations for transportation and accommodation based on the user's selected plan. This is a process that accesses the reservation system via the internet and secures the necessary reservations. As output, confirmation information is generated if the reservation confirmation is successful.

[0564] Step 7:

[0565] The terminal receives booking confirmation information from the server and provides it to the user as an electronic ticket or booking confirmation email. As a final output, the user obtains all the necessary documents for their trip, completing their travel planning smoothly.

[0566] (Application Example 2)

[0567] 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."

[0568] Modern travelers want to plan their trips efficiently and comfortably, but traditional travel planning systems fail to consider user emotions and only offer standard itineraries. Furthermore, booking transportation and accommodations manually is time-consuming and laborious. Additionally, there is a lack of means to ensure that the destinations and experiences travelers actually visit align with their emotional needs.

[0569] 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.

[0570] In this invention, the server includes means for performing emotion recognition to analyze the user's emotional state, means for generating an optimal travel itinerary based on the input information and emotional state, and means for obtaining the latest transportation operation information and accommodation availability in real time from external sources. This makes it possible to propose a more satisfying travel plan that is tailored to the user's emotions and to streamline the booking process.

[0571] A "user" is the person who inputs travel destination and length of stay information, and whose emotional state is analyzed by the system.

[0572] "Emotion recognition" is the process by which an emotion engine determines the user's emotional state at a given moment based on input data such as facial expressions and voice.

[0573] The "optimal itinerary" is a sequence of visits generated based on the travel destination information, length of stay, and emotional state entered by the user, ensuring an efficient and satisfying trip.

[0574] "External information sources" refer to third-party databases or services that provide information on transportation and accommodation, and that are capable of updating information in real time.

[0575] "Transportation" refers to the vehicles and methods of travel used by the user to move between specified travel destinations, and users can choose based on comfort and convenience.

[0576] "Accommodation facilities" are facilities where travelers stay, and reservations are made based on real-time room availability.

[0577] A "display device" is a device that constitutes part of a terminal that visually provides users with generated tour order, reservation information, and suggested content.

[0578] This invention aims to enable users to efficiently plan their trips, and for those plans to be tailored to the user's emotions. The system mainly consists of a terminal, a server, and an emotion engine. The terminal refers to a device such as smart glasses or a smartphone, which the user uses to input travel destination information and length of stay information. Once the user inputs the information, the emotion engine, which performs emotion recognition, detects emotional data from the user's facial expressions and voice. This data is transmitted to the server.

[0579] The server uses a generative AI model to generate the optimal itinerary based on user-specified travel destination information and emotional data. This allows for the suggestion of plans tailored to the user's emotional state, such as including scenic tourist spots and rest areas when the user is relaxed. APIs and web scraping techniques are used to obtain real-time information on transportation and accommodations from external sources and incorporate it into the plan.

[0580] The terminal's display visually shows the generated itinerary, reservation information, and suggestions, allowing the user to browse and make selections. Once selections are made, the server automatically handles the booking process for transportation and accommodation, and sends the necessary information back to the terminal. Finally, the terminal provides the user with an electronic ticket and confirmation email, supporting them in executing their travel plan without stress.

[0581] For example, if a user specifies that they "want to visit Tokyo, Osaka, and Nagoya," and the emotion engine detects a feeling of relaxation, the server will create a plan that includes suitable tourist destinations and facilities, and suggest comfortable transportation options. Another example of a generative AI model is a prompt that can be used: "The user has requested 'Kyoto' as their travel destination, and the emotion engine's analysis has detected 'joy.' Please suggest a relaxing sightseeing plan for this user."

[0582] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0583] Step 1:

[0584] The terminal obtains travel destination and length of stay information from the user. The user enters this information using an input device, and the terminal receives that input. The input data is formatted into a format that can be used for subsequent processing.

[0585] Step 2:

[0586] The device requests the emotion engine to analyze the user's emotions. The user's facial expressions and voice data are sent to the emotion engine as input, and the emotion engine identifies the emotional state through facial recognition and voice analysis. This process outputs the user's emotional data.

[0587] Step 3:

[0588] The terminal sends the entered travel destination information, length of stay information, and sentiment data to the server. The server receives this data as input and prepares to store it in the appropriate database.

[0589] Step 4:

[0590] The server uses a generative AI model to generate the optimal itinerary. Based on the user's travel destinations, length of stay, and emotional state, the generative AI model devises the best itinerary. This model learns from prompts and outputs tourist spots and travel routes as needed.

[0591] Step 5:

[0592] The server obtains real-time information on transportation and accommodation from external sources. It collects transportation service status and accommodation availability information via API and integrates it into the generated itinerary.

[0593] Step 6:

[0594] The server sends the generated tour order and reservation information to the terminal. The terminal presents this data to the user as visual / audio information. The user can review the displayed plan and make selections or changes as needed.

[0595] Step 7:

[0596] The server handles the booking process for transportation and accommodation based on the user's selection. It automates the booking process via API, outputting necessary confirmation information according to the details of the selected plan.

[0597] Step 8:

[0598] The device sends booking confirmations and e-tickets to the user, providing all the necessary travel information. Finally, the user can check this information on their smart glasses or smartphone and complete their travel plan.

[0599] 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.

[0600] 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.

[0601] 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.

[0602] [Fourth Embodiment]

[0603] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0604] 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.

[0605] 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).

[0606] 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.

[0607] 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.

[0608] 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).

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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".

[0616] This invention is implemented as a system that allows users to efficiently create business trip plans by inputting travel destination information and length of stay information. This system uses a terminal, a server, and a generating AI to propose an optimal itinerary to the user and support its execution.

[0617] The system's program includes several key functions. First, the user inputs their travel destinations and the duration of each stay into the system via a terminal. The terminal then prepares to send the input information to the server. Next, the server analyzes the received information and uses a generative AI to calculate the optimal itinerary. This AI employs algorithms such as the traveling salesperson problem to find efficient routes.

[0618] Subsequently, the server collects information on transportation services and accommodation availability from external sources based on an optimal patrol order. In this process, API access and web scraping techniques are employed to obtain the latest data. This makes it possible to present users with multiple travel plans.

[0619] The user selects the plan that best suits their needs from the presented options. Once the selection is complete, the server handles transportation reservations and accommodation arrangements based on the chosen plan. If necessary, electronic tickets and confirmation emails are automatically generated through integration with ticketless service providers.

[0620] For example, if a user plans a business trip to Tokyo, Osaka, and Nagoya, with stays of 3 hours, 5 hours, and 2 hours in each city, the system will present several optimal travel plans accordingly. The server will present a draft schedule, such as "depart for Tokyo in the morning, travel to Osaka in the afternoon, and visit Nagoya on the final day," and simultaneously display options for transportation and accommodation required for each leg of the journey. The user can then select the most convenient plan and complete the booking, allowing them to smoothly execute their business trip.

[0621] Thus, the present invention can significantly improve the efficiency of creating and managing business trip plans, providing users with a simple and comprehensive solution.

[0622] The following describes the processing flow.

[0623] Step 1:

[0624] The user enters travel destination and length of stay information using a device. In addition to the destination and length of stay at each location, the user enters the departure date and time and any requests regarding specific modes of transportation.

[0625] Step 2:

[0626] The terminal organizes the input information and prepares it for transmission to the server. The terminal packages the information in a specific format (e.g., JSON format) and sends it to the server.

[0627] Step 3:

[0628] The server analyzes the information received from the terminal and uses a generation AI to generate the optimal patrol order. The server calculates an efficient route considering the distance and travel time between destinations.

[0629] Step 4:

[0630] Based on a calculated patrol order, the server collects the latest transportation timetables and accommodation availability from external sources. The server uses web APIs and scraping techniques to obtain the necessary data.

[0631] Step 5:

[0632] Based on the information collected by the server, multiple travel plans are created and sent to the terminal. The server provides detailed plan information, including the mode of transportation, duration, and cost for each plan.

[0633] Step 6:

[0634] The user selects their preferred plan from those presented on their device. The user compares travel time, costs, and accommodation conditions to choose the best plan.

[0635] Step 7:

[0636] The server executes the booking process for transportation and accommodation in a single operation based on the selected plan. The server sends the necessary data to each booking system and verifies the process.

[0637] Step 8:

[0638] The terminal displays completed booking information to the user. The terminal shows electronic tickets and booking confirmation documents, allowing the user to proceed with travel preparations.

[0639] (Example 1)

[0640] 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".

[0641] In typical travel planning, creating efficient routes and making all transportation and accommodation reservations at once is extremely time-consuming and laborious. Furthermore, manually handling many steps, such as managing reservation information and presenting multiple travel plans, is inefficient and carries the risk of inaccurate information. To address these challenges, there is a need for a way to automate travel planning efficiently and accurately, thereby reducing the burden on users.

[0642] 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.

[0643] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel route based on the entered information, and means for calculating the travel route using a generation AI model and presenting an efficient travel plan. This enables the automatic generation of an efficient and accurate travel plan based on the information entered by the user, as well as the centralized management of booking procedures.

[0644] "User" refers to an individual or group that uses this system to plan their trip.

[0645] "Destination information" refers to information about the place the user plans to visit, including place names and facility names.

[0646] "Length of stay information" refers to information indicating how long a user plans to spend at each destination.

[0647] A "travel route" refers to the sequence and route of movement when visiting multiple destinations.

[0648] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to calculate the optimal travel route.

[0649] "Transportation" refers to public transportation and rental services, including the means of transport used by travelers to move between destinations.

[0650] "Accommodation facilities" refer to facilities such as hotels, inns, and private lodgings where travelers stay.

[0651] "Reservation information" refers to the information necessary for users to secure services from transportation and accommodation providers, and includes details such as dates and prices.

[0652] "Information sources" refer to databases, websites, and other resources used to obtain the latest information on transportation and accommodation.

[0653] "Integrated management" refers to improving efficiency by integrating and processing / managing multiple processes or tasks at once.

[0654] This invention is a system for users to efficiently plan their trips. The system utilizes a terminal, a server, and a generative AI model. First, the user inputs destination and length of stay information into the terminal. The terminal uses devices such as smartphones, tablets, and personal computers, allowing users to input information through an interface.

[0655] Next, the terminal sends the entered information to the server. The server analyzes the received data and runs a generating AI model to calculate the optimal travel route. This AI model uses data processing software and algorithms to generate an efficient travel plan based on the conditions entered by the user.

[0656] For this calculation, the server is designed to use high-performance hardware to process large amounts of data quickly. It also accesses external information sources via the internet to obtain transportation service status and accommodation availability. This ensures that users are always provided with the most up-to-date information.

[0657] For example, if a user plans to "visit Tokyo, Osaka, and Nagoya, staying for 3 hours, 5 hours, and 2 hours in each city," the system will generate and present multiple travel plans accordingly. As an example of a prompt, we will use the sentence, "Please suggest the optimal travel schedule based on the destinations and purpose of your trip."

[0658] This system also provides the ability to select from multiple travel plans via a terminal. Once the user completes their selection, the server makes bulk reservations for transportation and accommodation based on the selected plan. Finally, an electronic ticket and confirmation email are automatically generated and sent to the user. This allows users to efficiently and quickly implement their travel plans.

[0659] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0660] Step 1:

[0661] The user enters destination and length of stay information using their device. Specifically, they access a dedicated application or web form on their device and enter the "destination" and "length of stay" separately. This becomes the input data. When the user presses the "submit" button, the input is complete and ready to proceed to the next processing step.

[0662] Step 2:

[0663] The terminal sends destination and length of stay information entered by the user to the server. The terminal converts this information into a data format such as JSON and sends an HTTP request to the appropriate API endpoint. This process uses the SSL / TLS protocol to ensure data consistency and security. This allows the server to receive user data in an organized format.

[0664] Step 3:

[0665] The server analyzes destination and length of stay information received from the terminal. Using a generative AI model, the server calculates the optimal travel route based on the input information. This model leverages algorithms to solve the traveling salesman problem, outputting plans that consider transportation convenience and time efficiency. As a result of this process, multiple efficient travel plans are generated.

[0666] Step 4:

[0667] Based on the generated travel route, the server retrieves information on transportation service status and accommodation availability from external sources. This is done using API access and web scraping to collect real-time data. Using this collected data, the server complements the details of each travel plan and generates a list of available transportation options and accommodations.

[0668] Step 5:

[0669] The server sends the generated multiple travel plans and associated information to the terminal and presents them to the user. The information is displayed in a visually easy-to-understand manner, allowing the user to compare the travel time, cost, and convenience of each plan. This is done based on prompt messages generated by the server, providing the user with the information needed to make a decision.

[0670] Step 6:

[0671] The user selects the travel plan that best suits their needs from the presented options and sends their selection to the server via their device. After making their selection, the user presses the "Complete Booking" button to officially begin the process based on their chosen plan.

[0672] Step 7:

[0673] The server handles transportation bookings and accommodation arrangements in a single process based on the user's selected travel plan. The server automatically integrates with the booking system and sends necessary e-tickets and confirmation emails to the user. This entire process ensures an efficient and stress-free travel plan for the user.

[0674] (Application Example 1)

[0675] 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".

[0676] In food delivery services, efficiently delivering goods to multiple destinations requires quickly determining the optimal delivery order and route. Current systems often involve manual route setting, which can lead to increased delivery times and wasted resources. A sophisticated system is needed to solve these problems.

[0677] 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.

[0678] In this invention, the server includes means for receiving delivery destination information and time information, means for generating an optimal delivery order based on the input information, and means for calculating and presenting a route that takes travel time into consideration. This enables optimal route planning and efficient delivery in deliveries.

[0679] "Delivery information" refers to geographical information about the delivery destination of the product, including the address and destination of the item to be delivered.

[0680] "Time information" refers to information related to the delivery schedule and duration, including the estimated start and end times of the delivery.

[0681] The "optimal delivery order" is the calculated arrival sequence for efficiently delivering goods to multiple destinations, and is designed to minimize travel time.

[0682] A "route that takes travel time into consideration" refers to the most efficient driving route, generated by evaluating factors such as traffic conditions and distance.

[0683] "Route information" refers to detailed information about the route referenced during the delivery process, including specific roads and intermediate stops.

[0684] This invention is a system for improving delivery efficiency, particularly in delivery services. A server receives delivery destination and time information from the user and generates an optimal delivery sequence using a generative AI model. This process includes calculations to select an efficient route, combined with an algorithm for solving the traveling salesman problem. Based on the generated sequence, the server calculates a route that takes travel time into account and presents the route information to the user.

[0685] This system utilizes optimization libraries such as Google OR-Tools to determine the most efficient delivery route based on the distance and travel time between entered points. Data processing takes place on the server, and only the generated results are sent to the user's terminal. After the user reviews and selects a route, the system automatically executes the delivery plan.

[0686] As a concrete example, consider a scenario where a restaurant delivers food to multiple customers. The server receives address information for each delivery destination, considers the estimated delivery time for each, and suggests the optimal delivery order. This allows the delivery vehicles to deliver all the food in the shortest possible time.

[0687] An example of a prompt to the generating AI is: "Calculate the optimal delivery order and suggest an efficient route based on the travel time information between the following locations. The locations are as follows: [List of locations]". Through this prompt, the AI ​​quickly calculates the most efficient delivery route.

[0688] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0689] Step 1:

[0690] The user uses a terminal to enter the delivery address and desired delivery time. This information is then transmitted as input data to the system.

[0691] Step 2:

[0692] The server stores the delivery address and time information received from the user in a database. At this stage, the integrity and completeness of the data format are verified. The information is retained in preparation for optimization processing.

[0693] Step 3:

[0694] The server uses a generated AI model to solve the Traveling Salesperson Problem and calculate the optimal delivery order. This calculation generates an order that minimizes travel time by evaluating the distance and time between delivery locations. The output is an optimized delivery route.

[0695] Step 4:

[0696] The server calculates a detailed route based on the optimal route, taking travel time into consideration. During this process, it utilizes external data such as traffic information to optimize the route in real time. As a result of the calculation, specific route information is generated.

[0697] Step 5:

[0698] The server sends the optimal delivery order and route information it generates to the user's terminal. The user reviews the route on the terminal and chooses whether to start executing the delivery plan. Upon user approval, the next automated delivery step is executed.

[0699] Step 6:

[0700] Based on the user's selection, the system automatically issues a movement command to the delivery vehicle. The vehicle is then instructed to begin deliveries along the route according to the optimal sequence in Step 3.

[0701] Step 7:

[0702] The server monitors the delivery status and reports the delivery progress to the user in real time. Routes are re-optimized as needed, and updated information is notified to both the vehicle and the user. This ensures efficient delivery completion.

[0703] 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.

[0704] This invention allows users to input travel destination and length of stay information, and the system then efficiently creates a business trip plan based on that information. By combining this with an emotion engine, the system recognizes the user's emotions and proposes a travel plan accordingly.

[0705] The system functions by combining a terminal, a server, and an emotion engine. First, the user uses the terminal to input their travel destination and length of stay. As the user inputs their preferences through the system interface, the emotion engine detects emotions from the user's facial expressions, voice, input speed, etc.

[0706] The terminal sends detected emotional data along with the user's input information to the server. The server uses a generative AI to generate the optimal itinerary for the trip, taking the user's emotional data into consideration. This system can provide emotionally tailored plans, such as suggesting a plan with more sightseeing spots and rest time if the user is seeking relaxation.

[0707] Furthermore, the server collects transportation schedules and accommodation availability from external sources and incorporates them into the optimized plan. This process utilizes APIs and web scraping technologies to ensure real-time updates. It can also dynamically adjust the priority of choices based on feedback from an emotion engine.

[0708] For example, if a user inputs "I want to visit Tokyo, Osaka, and Nagoya" and also detects a relaxed mood, the system will prioritize suggesting plans that include relaxing facilities and tourist attractions. It can also suggest more comfortable class options for transportation.

[0709] After the user obtains a plan tailored to their emotions on their device, the server handles the booking process for transportation and accommodation based on the selected plan. Once the booking is complete, the device provides the user with an electronic ticket and confirmation email, supporting a smooth travel plan execution.

[0710] Thus, the present invention enables efficient creation and management of business trip plans, and makes it possible to provide plans that are more satisfying in accordance with the user's feelings.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] The user uses a device to input travel destination and length of stay information. The device collects the entered data and simultaneously acquires sentiment data through the user interface.

[0714] Step 2:

[0715] The terminal sends user input data and emotional data to the server. Emotional data includes the results of voice and facial expression analysis and is information that quantifies the user's emotional state.

[0716] Step 3:

[0717] The server analyzes destination information, length of stay information, and emotion data received by the user. Using a generative AI, it calculates the optimal sightseeing order and customizes the plan according to the user's emotions. If the emotional state is "relaxed," it considers a plan that includes many tourist spots.

[0718] Step 4:

[0719] The server collects transportation timetables and accommodation availability information from external sources. The server uses APIs and scraping techniques to obtain the latest data and incorporate it into the generated plan.

[0720] Step 5:

[0721] The server creates multiple plans and sends information to the terminal, including a plan that has been adjusted based on the user's emotions. Each plan includes the mode of transport, duration, and cost.

[0722] Step 6:

[0723] The user selects the plan that best suits their needs from those presented on their device. The user can then see how the plan has been tailored to their emotional needs.

[0724] Step 7:

[0725] The server automatically makes reservations for transportation and accommodation based on the user's choices. Emotion-based adjustments are reflected in the reservation priority and class selection.

[0726] Step 8:

[0727] The terminal displays completed reservation information to the user and provides reservation confirmation documents and electronic tickets. This allows the user to proceed smoothly with their business trip planning.

[0728] (Example 2)

[0729] 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".

[0730] Traditional travel planning systems often provide standardized travel plans based solely on user input, making it difficult to generate plans that cater to individual user emotions and needs. Furthermore, they fail to provide plans that reflect the latest real-time transportation and accommodation information, posing a challenge to improving user satisfaction.

[0731] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0732] In this invention, the server includes means for receiving destination information and length of stay information entered by the user, means for generating an optimal travel sequence based on emotions using a generating AI, and means for acquiring and incorporating transportation timetables and accommodation availability information from external resources. This makes it possible to generate highly satisfying travel plans based on the user's individual emotions and up-to-date information.

[0733] "Destination information" refers to the geographical location selected by the user as their travel destination and related information.

[0734] "Length of stay information" refers to information about the duration of a user's planned stay at a specific travel destination.

[0735] "Generative AI" is an artificial intelligence technology that generates information and plans based on given data and specified prompts.

[0736] An "emotion engine" is a technology that analyzes the user's facial expressions, voice, input speed, etc., to detect the user's emotional state.

[0737] A "public transport timetable" is information about the departure and arrival times and operating schedules of public transportation.

[0738] "Accommodation room availability information" refers to information showing the availability of rooms in accommodation facilities such as hotels and inns.

[0739] The "optimal travel sequence" is a sequence of steps that determines an efficient and satisfying travel route based on user input and emotions.

[0740] This invention is implemented using a system that efficiently creates travel plans planned by users and provides plans tailored to their individual emotions. The system mainly consists of a terminal, a server, and an emotion engine.

[0741] The user first enters travel destination and length of stay information using the terminal. During this process, the terminal uses an emotion engine to detect the user's emotions based on their facial expressions, voice, and input speed. The emotion engine utilizes various sensors and a microphone to analyze the user's emotional state.

[0742] The terminal sends the entered information and emotional data to the server. The server uses a generative AI model to generate an optimal travel plan based on the user's emotional data. The generative AI model can use prompts to generate information according to instructions. For example, if the server detects that the user wants to visit Tokyo, Osaka, and Nagoya, along with the emotion of wanting to relax, it can generate a plan that includes relaxing facilities and tourist spots. An example of a prompt would be, "I want to travel to Tokyo, Osaka, and Nagoya with a relaxing plan. Please suggest a plan that includes the latest transportation information."

[0743] Furthermore, the server utilizes APIs and web scraping technologies to collect real-time information on transportation schedules and accommodation availability, and incorporates it into the generated travel plans. This acquisition of external data makes it possible to always provide the most up-to-date information.

[0744] Once the user selects their final travel plan, the server automatically handles the booking of transportation and accommodation. The terminal then notifies the user of booking confirmations, e-tickets, and other relevant information, supporting a smooth execution of their travel plan. This system enables a personalized travel experience that enhances user satisfaction.

[0745] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0746] Step 1:

[0747] The user enters travel destination and length of stay information through the device. During input, the device uses its camera and microphone to record the user's facial expressions and voice, and detects emotional data through an emotion engine. At this point, the input data includes destination information, length of stay information, and emotional data. The device temporarily stores this data.

[0748] Step 2:

[0749] The device sends saved destination information, length of stay information, and sentiment data to the server. The server activates a generative AI model based on the received data to generate a travel plan. Specifically, it provides prompt messages to the generative AI model to create a travel plan tailored to the user's sentiment. As a result, the generated travel plan is output to the server.

[0750] Step 3:

[0751] The server utilizes external APIs and web scraping techniques to obtain necessary information such as transportation schedules and accommodation availability for the generated travel plan. The input is a request for relevant information based on the travel plan, and the output is a detailed travel plan reconstructed on the server, including the latest service and availability information.

[0752] Step 4:

[0753] The server sends an optimized travel plan to the device. The device then presents the received travel plan to the user on an intuitive screen. The screen display includes an overview of the travel plan, a schedule, and recommended points. The output displays a travel plan that is clearly organized and easy for the user to understand.

[0754] Step 5:

[0755] The user selects their preferred travel plan from the displayed options. The device then sends information about the selected plan back to the server. The output is information about the selected plan, reflecting the user's preferences.

[0756] Step 6:

[0757] The server automatically makes reservations for transportation and accommodation based on the user's selected plan. This is a process that accesses the reservation system via the internet and secures the necessary reservations. As output, confirmation information is generated if the reservation confirmation is successful.

[0758] Step 7:

[0759] The terminal receives booking confirmation information from the server and provides it to the user as an electronic ticket or booking confirmation email. As a final output, the user obtains all the necessary documents for their trip, completing their travel planning smoothly.

[0760] (Application Example 2)

[0761] 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".

[0762] Modern travelers want to plan their trips efficiently and comfortably, but traditional travel planning systems fail to consider user emotions and only offer standard itineraries. Furthermore, booking transportation and accommodations manually is time-consuming and laborious. Additionally, there is a lack of means to ensure that the destinations and experiences travelers actually visit align with their emotional needs.

[0763] 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.

[0764] In this invention, the server includes means for performing emotion recognition to analyze the user's emotional state, means for generating an optimal travel itinerary based on the input information and emotional state, and means for obtaining the latest transportation operation information and accommodation availability in real time from external sources. This makes it possible to propose a more satisfying travel plan that is tailored to the user's emotions and to streamline the booking process.

[0765] A "user" is the person who inputs travel destination and length of stay information, and whose emotional state is analyzed by the system.

[0766] "Emotion recognition" is the process by which an emotion engine determines the user's emotional state at a given moment based on input data such as facial expressions and voice.

[0767] The "optimal itinerary" is a sequence of visits generated based on the travel destination information, length of stay, and emotional state entered by the user, ensuring an efficient and satisfying trip.

[0768] "External information sources" refer to third-party databases or services that provide information on transportation and accommodation, and that are capable of updating information in real time.

[0769] "Transportation" refers to the vehicles and methods of travel used by the user to move between specified travel destinations, and users can choose based on comfort and convenience.

[0770] "Accommodation facilities" are facilities where travelers stay, and reservations are made based on real-time room availability.

[0771] A "display device" is a device that constitutes part of a terminal that visually provides users with generated tour order, reservation information, and suggested content.

[0772] This invention aims to enable users to efficiently plan their trips, and for those plans to be tailored to the user's emotions. The system mainly consists of a terminal, a server, and an emotion engine. The terminal refers to a device such as smart glasses or a smartphone, which the user uses to input travel destination information and length of stay information. Once the user inputs the information, the emotion engine, which performs emotion recognition, detects emotional data from the user's facial expressions and voice. This data is transmitted to the server.

[0773] The server uses a generative AI model to generate the optimal itinerary based on user-specified travel destination information and emotional data. This allows for the suggestion of plans tailored to the user's emotional state, such as including scenic tourist spots and rest areas when the user is relaxed. APIs and web scraping techniques are used to obtain real-time information on transportation and accommodations from external sources and incorporate it into the plan.

[0774] The terminal's display visually shows the generated itinerary, reservation information, and suggestions, allowing the user to browse and make selections. Once selections are made, the server automatically handles the booking process for transportation and accommodation, and sends the necessary information back to the terminal. Finally, the terminal provides the user with an electronic ticket and confirmation email, supporting them in executing their travel plan without stress.

[0775] For example, if a user specifies that they "want to visit Tokyo, Osaka, and Nagoya," and the emotion engine detects a feeling of relaxation, the server will create a plan that includes suitable tourist destinations and facilities, and suggest comfortable transportation options. Another example of a generative AI model is a prompt that can be used: "The user has requested 'Kyoto' as their travel destination, and the emotion engine's analysis has detected 'joy.' Please suggest a relaxing sightseeing plan for this user."

[0776] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0777] Step 1:

[0778] The terminal obtains travel destination and length of stay information from the user. The user enters this information using an input device, and the terminal receives that input. The input data is formatted into a format that can be used for subsequent processing.

[0779] Step 2:

[0780] The device requests the emotion engine to analyze the user's emotions. The user's facial expressions and voice data are sent to the emotion engine as input, and the emotion engine identifies the emotional state through facial recognition and voice analysis. This process outputs the user's emotional data.

[0781] Step 3:

[0782] The terminal sends the entered travel destination information, length of stay information, and sentiment data to the server. The server receives this data as input and prepares to store it in the appropriate database.

[0783] Step 4:

[0784] The server uses a generative AI model to generate the optimal itinerary. Based on the user's travel destinations, length of stay, and emotional state, the generative AI model devises the best itinerary. This model learns from prompts and outputs tourist spots and travel routes as needed.

[0785] Step 5:

[0786] The server obtains real-time information on transportation and accommodation from external sources. It collects transportation service status and accommodation availability information via API and integrates it into the generated itinerary.

[0787] Step 6:

[0788] The server sends the generated tour order and reservation information to the terminal. The terminal presents this data to the user as visual / audio information. The user can review the displayed plan and make selections or changes as needed.

[0789] Step 7:

[0790] The server handles the booking process for transportation and accommodation based on the user's selection. It automates the booking process via API, outputting necessary confirmation information according to the details of the selected plan.

[0791] Step 8:

[0792] The device sends booking confirmations and e-tickets to the user, providing all the necessary travel information. Finally, the user can check this information on their smart glasses or smartphone and complete their travel plan.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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."

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0814] The following is further disclosed regarding the embodiments described above.

[0815] (Claim 1)

[0816] A means for receiving travel destination information and length of stay information entered by the user,

[0817] A means for generating the optimal itinerary for a trip based on the input information,

[0818] A means of collecting transportation and accommodation reservation information in bulk based on the optimal itinerary,

[0819] A means for presenting the generated tour order and reservation information to the user,

[0820] A system that includes this.

[0821] (Claim 2)

[0822] The system according to claim 1, further comprising means for making reservations for transportation and accommodation based on the itinerary selected by the user.

[0823] (Claim 3)

[0824] The system according to claim 1, further comprising means for obtaining the latest transportation service information and accommodation availability from external sources.

[0825] "Example 1"

[0826] (Claim 1)

[0827] A means for receiving destination information and length of stay information entered by the user,

[0828] A means for generating the optimal travel route based on the input information,

[0829] A means of collecting reservation information for transportation and accommodation facilities in bulk based on the optimal travel route,

[0830] A means of presenting the generated travel route and reservation information to the user,

[0831] A means of calculating travel routes using a generative AI model and presenting an efficient travel plan,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, further comprising means for handling the reservation procedures for transportation and accommodation based on the travel route selected by the user.

[0835] (Claim 3)

[0836] The system according to claim 1, further comprising means for obtaining the latest transportation service information and accommodation availability information from external sources.

[0837] "Application Example 1"

[0838] (Claim 1)

[0839] A means for receiving delivery address and time information entered by the user,

[0840] A means for generating the optimal delivery order based on the input information,

[0841] A means of calculating and presenting a route that takes travel time into consideration, based on the optimal delivery order,

[0842] A means for presenting the generated delivery order and route information to the user,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] The system according to claim 1, further comprising means for automatically executing a travel plan based on a delivery order selected by the user.

[0846] (Claim 3)

[0847] The system according to claim 1, further comprising means for obtaining the latest traffic conditions and delivery destination status from external sources.

[0848] "Example 2 of combining an emotion engine"

[0849] (Claim 1)

[0850] A means for receiving destination information and length of stay information entered by the user,

[0851] A means for generating the optimal travel sequence using a generative AI based on the input information and detected emotions,

[0852] A means for obtaining transportation timetables and accommodation availability information from external resources and incorporating them into the aforementioned optimal order,

[0853] A means of presenting the generated travel plan and booking information to the user,

[0854] A system that includes this.

[0855] (Claim 2)

[0856] The system according to claim 1, further comprising means for handling the booking procedures for transportation and accommodation based on the travel plan selected by the user.

[0857] (Claim 3)

[0858] The system according to claim 1, further comprising means for analyzing the user's emotions using an emotion engine and reflecting that analysis in the proposed plan.

[0859] "Application example 2 when combining with an emotional engine"

[0860] (Claim 1)

[0861] A means for receiving travel destination information and length of stay information entered by the user,

[0862] A means of performing emotion recognition in order to analyze the emotional state of the user,

[0863] A means for generating the optimal itinerary for a trip based on input information and emotional state,

[0864] A means of obtaining the latest transportation service information and accommodation availability in real time from external sources,

[0865] A means of collecting transportation and accommodation reservation information in bulk based on the optimal itinerary,

[0866] A means for displaying the generated tour order, reservation information, and suggested content on a display device,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, further comprising means for making reservations for transportation and accommodation based on the itinerary selected by the user.

[0870] (Claim 3)

[0871] The system according to claim 1, further comprising means for suggesting tourist destinations and experiences that correspond to emotions, using the results of emotion recognition. [Explanation of Symbols]

[0872] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving travel destination information and length of stay information entered by the user, A means for generating the optimal itinerary for a trip based on the input information, A means of collecting transportation and accommodation reservation information in bulk based on the optimal itinerary, A means for presenting the generated tour order and reservation information to the user, A system that includes this.

2. The system according to claim 1, further comprising means for making reservations for transportation and accommodation based on the itinerary selected by the user.

3. The system according to claim 1, further comprising means for obtaining the latest transportation service information and accommodation availability from external sources.

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