system

Abstract

We provide the system. [Solution] A means of receiving user input information and analyzing it using natural language processing technology, A means of obtaining information from external databases and APIs to generate travel plans based on analysis results, A method for selecting the most suitable travel plan from multiple generated plans based on the user's conditions and optimizing the itinerary in real time, A means of monitoring the user's location and surrounding environment during travel, and dynamically redesigning the route as needed, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, with the diversification of travelers' needs, customization of travel plans suitable for individual travelers has been demanded. However, the complexity of travel plans and the impact of overtourism in popular tourist destinations on the environment and local communities are increasing. Therefore, a system that balances travelers' needs and regional sustainability is required.

Means for Solving the Problems

[0005] This invention provides a means for obtaining information from external databases and APIs to generate appropriate travel plans by analyzing user input information using natural language processing technology. This makes it possible to generate travel plans tailored to individual needs, select the best one from multiple plans, and optimize the itinerary in real time. Furthermore, it provides a means for dynamically redesigning routes by monitoring the user's location information and surrounding environment during travel, and for contributing to the local economy by promoting local tourism resources and utilizing local currency systems.

[0006] "User input information" refers to travel preferences, budget, and activities of interest, and is data that the system analyzes to create a travel plan.

[0007] "Natural language processing technology" refers to techniques that enable computers to understand and process human language, and are methods used to analyze user input information.

[0008] "External databases and APIs" are external sources of information that are accessed to obtain the information necessary when generating travel plans.

[0009] A "travel plan" is a plan created based on the user's needs, which includes destinations, modes of transportation, schedules, and other elements.

[0010] "Optimizing your itinerary in real time" means dynamically adjusting destinations and routes in response to changing circumstances during your trip.

[0011] "Overtourism" is a phenomenon in which the number of visitors to a tourist destination exceeds the local capacity, negatively impacting the environment and the local community.

[0012] "Promoting local tourism resources" refers to activities that actively introduce the culture, sights, and events of a destination to travelers and increase their awareness.

[0013] A "local currency system" refers to a unique currency or payment method used within a specific region, and is introduced with the aim of revitalizing the local economy. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] 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.

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

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

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

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0029] 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.

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

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a system that allows users to customize and optimize their travel plans using their own device. First, the user inputs basic travel information, such as their budget, cities they want to visit, and tourist destinations of interest, into the device. This device uses natural language processing technology to analyze the user's input and clarify their needs.

[0036] The analysis results are sent to a server, which uses external databases and APIs to generate travel plans in real time. This includes information such as the crowd situation at the destination, the weather, and recommended tourist attractions. For example, if a user specifies that they want a relaxing hot spring trip with a budget of 100,000 yen, the server will create a list of hot spring resorts that fit within that budget and suggest the most suitable destination from that list.

[0037] During your trip, the server interacts with your device to monitor your progress in real time. This allows the server to consider traffic conditions and facility congestion, and, if necessary, suggest new routes or alternative tourist destinations. For example, if your planned tourist destination is crowded, the server will recommend nearby tourist destinations to your device.

[0038] Furthermore, it has the functionality to promote local tourism resources and contribute to the local economy by utilizing a local currency system. The server introduces local specialties and events of the visited area to users, enhancing the appeal of travel and contributing to regional revitalization.

[0039] In this way, by providing travel plans that match users' preferences and conditions, and by responding to diverse situations at the destination, it is possible to create a system that provides a fulfilling travel experience while giving back to the local community.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The terminal displays an interface for the user to input information about their travel purpose, budget, and desired destinations. The user enters this information through this interface.

[0043] Step 2:

[0044] The device analyzes information entered by the user using a natural language processing engine. The analysis results identify the user's travel needs and preferences.

[0045] Step 3:

[0046] The device sends the analysis results as data to the server. This prepares the server for creating the travel plan in the next step.

[0047] Step 4:

[0048] The server extracts user criteria based on data received from the terminal. It retrieves necessary tourist information, congestion status, and weather data from available external databases and APIs.

[0049] Step 5:

[0050] The server applies an AI model and generates multiple travel plans using the acquired information. Each plan is specialized based on the user's conditions.

[0051] Step 6:

[0052] The server selects the most suitable travel plan for the user from the generated options and optimizes the itinerary to be efficient and appealing.

[0053] Step 7:

[0054] The server sends an optimized travel plan to the device. The device displays this plan and presents it to the user.

[0055] Step 8:

[0056] The server monitors the user's location and surrounding environment in real time during their trip. If necessary, it redesigns the travel route, taking into account traffic and congestion conditions.

[0057] Step 9:

[0058] The server conducts promotional activities using local tourism resources and the local currency system, and notifies users' devices of local specialties and event information. This promotes contributions to the local economy.

[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 planning travel itineraries, it is difficult for users to gather a large amount of information on their own and create the optimal plan, and it is also difficult to maintain an optimal plan in real time as the situation changes during the trip. In addition, there is the problem that they cannot effectively contribute to the local economy of the travel destination.

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

[0063] In this invention, the server includes means for acquiring user input information and analyzing it using lexical analysis technology, means for acquiring information for creating an itinerary based on the analysis results from external information sources and data acquisition means, and means for selecting the plan best suited to the user's requirements from a plurality of generated itineraries and optimizing the travel itinerary in real time. This enables users to efficiently and effectively plan their trips, and to make an economic contribution to the destination region while continuing to optimize the plan in real time during the trip.

[0064] "User input information" refers to data such as budget, destinations, and activities of interest that users provide in order to plan their trip.

[0065] "Vocabulary analysis technology" is a technique that uses natural language processing technology to analyze the intent and requests of users from the information they input.

[0066] A "travel itinerary" refers to a detailed travel schedule that includes destinations, activities, and time allocations.

[0067] "External information sources" refer to external databases or APIs that the server connects to in order to generate travel itineraries, and are sources from which real-time information is obtained.

[0068] "Data acquisition methods" refer to the processes and technologies used to obtain necessary information from external sources.

[0069] "Real-time optimization" means adjusting the itinerary in real time according to changes in the user's environment and circumstances during their trip, always maintaining the optimal state.

[0070] "Environmental information" refers to factors that affect a user's trip, such as weather, traffic, and congestion at tourist spots.

[0071] "Contributing to the local economy" refers to actions and impacts that promote local economic activity, such as users purchasing local products or participating in local events during their travels.

[0072] "Artificial intelligence technology" refers to technologies that utilize machine learning and data analysis capabilities to generate itinerary plans tailored to user needs.

[0073] The embodiment for carrying out this invention is configured as follows: First, the user inputs information necessary for travel planning using their own terminal. Specifically, they input their budget, cities and countries to visit, activities and tourist destinations of interest, etc. The terminal collects this information and uses vocabulary analysis technology to analyze the user's requests in detail.

[0074] The analyzed information is sent to the server via the network. Based on this received information, the server accesses external information sources such as databases and APIs to obtain data such as congestion levels at the destination, weather information, and the latest events and exhibitions at tourist spots.

[0075] The server integrates the acquired information and uses artificial intelligence technology to generate an optimal travel itinerary that matches the user's requests. This itinerary generation uses an AI model that analyzes and optimizes data in real time. For example, it may adjust the order of destinations based on factors such as congestion levels.

[0076] The generated travel itinerary is sent to the device, where the user can review it on the screen and make changes or adjustments as needed. During the trip, the user's location and environmental information is sent to the server via the device, and the server dynamically redesigns the route based on this information. For example, if a planned tourist destination is crowded, the server will suggest a different nearby tourist destination.

[0077] Furthermore, the server suggests to users purchasing local products or participating in local events to promote contributions to the local economy of their travel destination. This creates benefits not only for the traveler but also for the region they visit.

[0078] An example of a prompt message is, "Please plan a budget-friendly museum tour in Tokyo. Please take into account crowd information and weather forecasts." In this way, the present invention aims to comprehensively support the user's travel experience and contribute to the local community.

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

[0080] Step 1:

[0081] The user uses a terminal to input information necessary for travel planning. This input information includes budget, cities to visit, and tourist attractions and activities of interest. The terminal receives this information and prepares it for analysis using lexical analysis technology. The input text data is analyzed using natural language processing technology to clarify the user's intent. As a result of the analysis, the user's desired travel conditions are clarified. A specific example of this process is when the user inputs "I want to enjoy a relaxing hot spring trip" into the terminal, and the terminal analyzes that information.

[0082] Step 2:

[0083] The terminal sends the analysis results to the server. During this process, data processing takes place, involving the transmission of the generated analysis results data over the network. Based on the received analysis data, the server prepares to access external databases and APIs that serve as information sources. It receives the analysis results as input and proceeds with preparations for acquiring external data. A concrete example of this operation is when the terminal sends the analysis result "hot spring trip" to the server.

[0084] Step 3:

[0085] The server retrieves travel-related data from external databases and APIs. It obtains the latest information necessary for travel planning, such as congestion levels, weather, and special event information for planned destinations. This process involves data collection from external sources and data processing to obtain context related to user requests. As output, various travel-related data is aggregated on the server. Specifically, the server collects the latest weather information related to "hot springs in Tokyo."

[0086] Step 4:

[0087] The server uses artificial intelligence technology to generate a travel plan based on the acquired data. This generating AI model is used to design an optimal travel schedule that takes into account congestion information and weather. Using data acquired from external sources as input, the AI ​​model performs data calculations to generate the travel plan. The output is a travel itinerary customized for the user. Specifically, the server uses AI to suggest a relaxing hot spring schedule that avoids congestion at the destination.

[0088] Step 5:

[0089] The server sends the generated travel itinerary to the user's device. The device receives this data and prepares to visually present the information to the user. The generated itinerary data is received from the server as input and processed to be displayed in a format that the user can confirm. Specifically, the server can then display the completed hot spring trip schedule on the device screen.

[0090] Step 6:

[0091] During travel, the server continuously receives location and environmental information through the user's device. Based on this information, the server optimizes the itinerary in real time and dynamically redesigns the route as needed. It takes real-time location information as input and performs data calculations to recalculate the optimal itinerary. The output is an updated itinerary plan. A concrete example of this operation is when the server proposes a new route that avoids traffic congestion while the user is traveling.

[0092] Step 7:

[0093] The server suggests actions to users that encourage economic contribution by utilizing local resources at their travel destination. It prepares to provide information on local specialties and events that can be accessed on the device. The data output presents information on local specialties and local events that users can participate in, encouraging actions that contribute to the economy. Specifically, the server sends users information about participating in a local festival held in a hot spring resort.

[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 recent years, meal delivery services have faced the problem of insufficient support for users to select appropriate suppliers based on their preferences and budget, resulting in a lack of improved user experience. Furthermore, there is a lack of optimal supply planning that takes into account real-time congestion and delivery times, highlighting the need to improve supply efficiency. Additionally, effectively promoting local food resources and contributing to the local economy is crucial.

[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 user input information and analyzing it using natural language processing technology, means for obtaining information from an external database and API for generating a meal supply plan based on the analysis results, means for selecting the plan best suited to the user's conditions from among the generated meal supply plans and optimizing the delivery route in real time, and means for selecting the optimal supplier considering delivery time and congestion status obtained from an external API. This enables the optimization of meal supply plans based on user preferences, realizes efficient supply considering congestion status and delivery time, and promotes the revitalization of the local economy by utilizing local food resources.

[0099] "A means of receiving user input information and analyzing it using natural language processing technology" refers to a process of receiving information such as the user's specified food preferences and budget from a terminal, analyzing that information using natural language processing technology, and clarifying the user's needs.

[0100] "Means for obtaining information from external databases and APIs to generate a meal supply plan based on analysis results" refers to a method that utilizes analyzed user information to obtain real-time menu and supplier information from external databases and APIs, and generates appropriate meal supply options.

[0101] "A means of selecting the optimal meal supply plan from multiple generated plans that best suits the user's conditions and optimizing the delivery route in real time" refers to a function that selects the optimal plan that matches the user's desired conditions from among pre-generated supply plans and dynamically adjusts the delivery route and time based on that selection.

[0102] "A method for selecting the optimal supplier by considering delivery time and congestion status obtained from external APIs" refers to a method of evaluating delivery time and the degree of congestion at suppliers obtained using external APIs, and determining the optimal supplier for rapid and efficient delivery.

[0103] The system implementing this invention is comprised of communication between a user's terminal and a server. When the user inputs their preferred food genre and budget into the terminal, this information is analyzed using natural language processing technology. For the analysis, a natural language processing model using the Hugging Face Transformers library is utilized to reveal detailed needs regarding the user's preferences.

[0104] The server retrieves real-time data from external APIs (such as restaurant database APIs and map service APIs) based on the analyzed information and generates an optimal meal delivery plan. At this stage, Python frameworks such as Flask or Django can be used. The retrieved data is dynamically optimized, taking into account delivery times and congestion levels, and presented to the user on a smartphone application developed with Flutter®.

[0105] For example, if a user enters "I want to eat spicy food for 3000 yen" into the terminal, the system will search for restaurants serving spicy food in the vicinity, taking into account the user's location, and recommend restaurants based on factors such as waiting times and discount information. In this process, it is possible to suggest the restaurant and menu that best suits the user's criteria.

[0106] By using a generative AI model, prompts like the following can be used to instruct the system to derive the optimal plan from user input: "Based on the text entered by the user, generate a plan that suggests the best restaurant and menu in real time. Take into account the user's location, budget, and culinary preferences, and retrieve and process the necessary information from an external API."

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The user enters their preferred food genre and budget into the device. This user input is collected in text format on the device. This serves as the initial input for the program.

[0110] Step 2:

[0111] The device analyzes the collected text information using natural language processing technology. Using the Hugging Face Transformers library, it analyzes the user's input text and extracts the user's specific wishes and conditions. This result is output as analyzed data.

[0112] Step 3:

[0113] The server retrieves real-time data from external APIs based on the analysis results. Based on the analyzed needs, it accesses restaurant database APIs and map service APIs to obtain supplier and delivery information. The input is the analyzed needs, and the output is the retrieved data.

[0114] Step 4:

[0115] The server generates and optimizes a meal supply plan based on the acquired data. It creates a list of target restaurants and menus, evaluates delivery times and congestion levels, and dynamically adjusts the plan. The input is the acquired data, and the optimized supply plan is output.

[0116] Step 5:

[0117] The server sends an optimized meal delivery plan to the terminal. Through a smartphone app developed with Flutter, the user can review and select the proposed plan. The output is user-facing display data.

[0118] Step 6:

[0119] The user selects their preferred option from the presented choices and places an order. The selected plan is recorded within the application via taps or clicks and output as the final order data.

[0120] 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.

[0121] This invention is a system that combines an emotion engine to further enhance the user's travel experience. The user inputs their travel wishes and interests into the terminal. At this point, the terminal uses a natural language processing engine to analyze this input information and understand the user's basic needs.

[0122] Furthermore, the device incorporates an emotion engine that infers the user's emotional state from the tone of the words they type and the conditions they select. For example, if a user types, "I'm stressed and want to go somewhere relaxing," the emotion engine will determine that the user prioritizes relaxation.

[0123] The analyzed information is sent to a server, which then generates a travel plan optimized for the user's needs and emotions based on tourism information obtained from external databases and APIs. For example, if the user wants to relax, quiet hot spring resorts with little crowding or peaceful, nature-rich locations will be suggested.

[0124] During the trip, the server utilizes an emotion engine to monitor the user's emotional state in real time. If the user expresses, for example, excitement or dissatisfaction, the server will re-select sightseeing destinations or suggest events accordingly. This makes it possible to provide an experience that fits the user's emotions.

[0125] Furthermore, the server promotes local tourism resources and contributes to the revitalization of the local economy by utilizing a local currency system. Based on the user's emotions indicated by the emotion engine, it provides personalized information on local products and events, creating an attractive local experience for the user.

[0126] In this way, this system optimizes travel plans that take user emotions into consideration and adjusts the travel experience in real time, thereby realizing more personalized travel and simultaneously promoting integration with local communities.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The user inputs information about their travel preferences, budget, and destination region through the device. The device provides an interface for collecting this information.

[0130] Step 2:

[0131] The device uses natural language processing technology to analyze user input and extract basic travel needs and conditions. The analyzed information is used as data to clarify the user's intentions.

[0132] Step 3:

[0133] The device operates an emotion engine based on user input to detect the user's emotional state. For example, it analyzes word choices and tone to infer emotions such as wanting to relax or seeking stimulation.

[0134] Step 4:

[0135] The terminal sends the analyzed data and detected emotion data to the server. The server receives this data and uses it for processing.

[0136] Step 5:

[0137] The server collects tourism information from external databases and APIs based on the received data, and generates travel plans that match the user's needs and preferences. The plans take into account factors such as the level of crowding at the destinations and the weather.

[0138] Step 6:

[0139] The server creates several travel plans and selects the one best suited to the user. The selection is based on the user's emotional state.

[0140] Step 7:

[0141] The server sends the selected travel plan to the terminal. The terminal then presents the plan to the user, allowing the user to confirm it.

[0142] Step 8:

[0143] During the trip, the server utilizes an emotion engine to continuously monitor the user's emotional state. Based on changes in emotions, the plan is readjusted as needed.

[0144] Step 9:

[0145] The server promotes local tourism resources and contributes to economic revitalization through a local currency system. It provides users with emotionally-driven information on local specialties and events.

[0146] (Example 2)

[0147] 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".

[0148] In planning user trips, conventional systems failed to adequately consider users' emotions and individual preferences, resulting in a low degree of personalization. Furthermore, it was difficult to readjust the plan to reflect changes in users' emotions during the trip, leading to insufficient utilization of local tourism resources and inadequate contributions to the local community.

[0149] 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.

[0150] In this invention, the server includes natural language processing means for analyzing user input information, emotion analysis means for inferring the user's emotional state, and travel plan generation means based on the analysis results and emotional state. This enables the provision of detailed travel plans that take into account the user's individual emotions, the optimization of the real-time experience based on the user's emotional state during the trip, and further contributes to the local economy.

[0151] "User input information" refers to data that encapsulates the user's wishes and interests regarding travel, and is information in text format expressed in natural language.

[0152] "Natural language processing technology" refers to techniques that enable computers to understand and analyze human language, employing methods that include morphological analysis and semantic analysis.

[0153] "Emotional analysis methods" refer to technologies that infer emotional states from user input based on tone and word choices, and utilize emotion recognition algorithms.

[0154] "External databases and APIs" refer to repositories and application interfaces that provide data such as tourism information and weather information that can be accessed via the internet.

[0155] "Travel plan generation method" refers to the process of creating an optimal travel plan that reflects the user's needs and emotions, and is performed by the system based on data acquired from external sources.

[0156] "Real-time optimization" refers to operations that instantly readjust travel plans and itineraries in response to changes in the user's current location and emotional state, providing an experience tailored to the user.

[0157] "Travel monitoring" is a process of constantly observing the user's behavior and emotional state as they progress through their trip, and restructuring the plan as needed.

[0158] "Contributing to the local economy" refers to activities that aim to revitalize the region through tourism by promoting local culture and specialty products, thereby contributing to the development of the local economy.

[0159] A "local monetary system" refers to the local currency and payment methods used by travelers, and is a mechanism that has a direct impact on the local economy.

[0160] The system of this invention aims to optimize the user's travel experience and has a configuration that combines natural language processing technology and sentiment analysis means. Its embodiments are described in detail below.

[0161] First, the user enters their travel preferences and interests into their device. The entered data is analyzed via a natural language processing engine, and based on this analysis, the user's basic needs are understood. Furthermore, the device has a built-in emotion engine that analyzes the tone and selected words from the user's input to infer the user's emotional state. This allows the system to identify emotional needs, such as the user's desire for relaxation.

[0162] The analyzed information is sent to a server via the internet. The server accesses external databases and APIs to collect travel information and then generates a travel plan that best fits the user's needs and preferences. This plan suggests tourist destinations and activities tailored to the user's tastes. For example, a user seeking relaxation might be recommended less crowded hot spring resorts or quiet natural areas.

[0163] Furthermore, during the trip, the server monitors the user's emotional state in real time. It utilizes the user's smartphone app to collect feedback and recognize changes in their emotional state. Based on these changes, the server adjusts the selection of tourist destinations and suggests events in real time. This ensures that users continuously receive a travel experience tailored to their individual emotions and needs.

[0164] To contribute to the revitalization of the local economy, the server promotes local tourist resources and provides information on specialty products and events based on user sentiment. In this way, travelers are delivered attractive local experiences, and a sense of connection with the region is fostered.

[0165] For example, if a user inputs "I want to relax in a quiet place away from the hustle and bustle of the city," the system analyzes this need and suggests places like nature-rich retreats or quiet beaches. Furthermore, if the user provides feedback during their trip indicating a desire to "learn more about the local culture," the system will provide additional information such as traditional festivals or local craft experiences.

[0166] Examples of prompts include: "Please recommend a relaxing travel destination. Conditions: Stress relief, quiet environment" or "Please suggest tourist spots where I can experience the local culture. Interests: Hands-on experiences, traditional festivals."

[0167] This system allows users to enjoy flexible and personalized travel experiences tailored to their emotions and desires. Furthermore, it contributes to local communities through initiatives that utilize local resources.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user inputs their travel preferences and interests into the device. This input includes specific information such as the travel destination, purpose, duration, budget, and emotional state the user wants to express. The device analyzes this information using natural language processing technology to understand the user's basic needs and emotional state. For example, it might receive input such as, "I want to go to a quiet place with abundant nature." The output obtained here is a list of standardized needs and an estimated emotional state.

[0171] Step 2:

[0172] The terminal sends the analyzed information to the server. The input includes estimated data on the user's needs and emotions. The server retrieves tourist information from external databases and APIs. Specifically, the server aggregates relevant information such as the characteristics of tourist destinations, seasonal information, and recommended activities. The output here is foundational data for travel plans that may suit the user's needs.

[0173] Step 3:

[0174] The server matches collected tourist information with user needs and sentiment data to generate the optimal travel plan. This process utilizes an AI model to generate and output multiple travel plans optimized for the user's conditions. For example, for a user seeking relaxation, it might suggest uncrowded hot spring resorts or quiet nature parks. The output here is a list of specific itineraries and potential destinations.

[0175] Step 4:

[0176] During the trip, the user's emotional state is monitored in real time by the device. The device receives user feedback as input and uses an emotion engine to detect changes in emotion. For example, if the user provides feedback such as "I want to do more active activities," this becomes the input. As output, suggestions for tourist destinations and activities that have been re-selected based on the emotional state are generated.

[0177] Step 5:

[0178] The server leverages local tourism resources to provide personalized information on local products and events based on the user's emotions. This stage includes the integration of local product promotions and a local currency system. Inputs are user emotion data and local promotional information, while output is a suggestion of engaging local experiences for the user.

[0179] In this way, this system uses natural language processing and sentiment analysis, starting with user input, to optimize the travel experience in real time. It can also strengthen relationships with local communities.

[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 the "server," and the smart device 14 will be referred to as the "terminal."

[0182] For travelers, creating an optimal travel plan tailored to their individual needs and emotions is a challenging task. Furthermore, systems capable of flexibly responding to unexpected situations during travel are limited. Additionally, mechanisms for receiving real-time suggestions that respond to changing emotions are insufficient. Addressing these challenges is necessary to further personalize the user's travel experience and promote integration between local communities and travelers.

[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 receiving user input information and analyzing it using natural language processing technology, means for inferring the user's emotional state using an emotion engine and reflecting that information in the travel plan, and means for monitoring the user's location information and surrounding environment during the trip and dynamically redesigning the route in response to changes in the emotional state. This enables the optimization of the travel plan according to the user's needs and real-time sightseeing suggestions that are appropriate to their emotions.

[0185] "User input information" refers to text data such as travel preferences and interests that travelers enter into their devices.

[0186] "Natural language processing technology" is a technology that allows computers to analyze and understand human language, extracting meaning and intent from user input information.

[0187] An "emotion engine" is a technology that infers an emotional state from the words a user inputs or the conditions they select, and uses that information to process the system.

[0188] A "travel plan" is a plan of itineraries and destinations suggested based on the user's needs and interests.

[0189] "External databases and APIs" refer to external sources of information and interfaces that the system uses to retrieve tourist information and surrounding data.

[0190] "Real-time optimization" means instantly readjusting the travel plan in response to changes in the user's situation and emotions during their trip.

[0191] "Location information" refers to geographical data about the user's current location.

[0192] "Surrounding environment" refers to facilities, natural environments, or conditions that exist in the vicinity of the place the user is visiting.

[0193] "Emotion-responsive tourist information" refers to information about tourist spots and events that are appropriate for the user's emotional state.

[0194] This invention is a system that utilizes an emotion engine to enhance the user's travel experience. This system acquires user input information using devices such as smartphones and smart glasses. When the user inputs their travel wishes and interests, this information is analyzed using natural language processing technology. For the analysis, Python's natural language processing libraries NLTK and spaCy are used. The emotion engine utilizes an API for Sentiment Analysis to infer the user's emotional state from the tone and selection of the input words.

[0195] Based on these analysis results, the server retrieves tourist information from external databases using the Google Places API and other services. It then optimizes the generated travel plan to match the user's emotions and dynamically redesigns the route in real time based on location information. During this process, cloud database services such as Firebase are used to keep the information instantly up-to-date.

[0196] For example, if a user enters a desire to "relax in a peaceful natural setting," the emotion engine will determine that the user is seeking relaxation and suggest information about quiet nature parks or hot spring resorts. During the trip, if the system detects an emotion such as "I want to avoid crowds today," it will redesign the route to avoid crowds and guide the user to peaceful spots.

[0197] An example of a prompt to input into a generative AI model is: "Design an application that suggests the optimal travel and sightseeing plan based on the user's emotions and interests, and provides a real-time, emotionally resonant experience."

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] The terminal receives text input from the user regarding their travel preferences and interests. This input information is then analyzed using natural language processing techniques. Specifically, the meaning of words and phrases is extracted using Python libraries such as NLTK and spaCy to identify the user's basic needs. The input for this step is the user's free-form text, and the output is the analyzed keywords and sentences.

[0201] Step 2:

[0202] The device uses an emotion engine to infer the user's emotional state based on the analyzed information, including the tone of voice and selected conditions. Using an API for Sentiment Analysis, it can determine, for example, that the user prioritizes relaxation from an input such as "I want to relax." The input for this step is the analysis results obtained in step 1, and the output is an evaluation of the user's emotional state.

[0203] Step 3:

[0204] The server retrieves tourist information from sources such as the Google Places API based on the user's needs and emotional state. It accesses external databases to collect tourist destinations and events that are suitable for the user. The input for this step is the emotional state and needs output from step 2, and the output is a list of recommended tourist information.

[0205] Step 4:

[0206] The server generates a series of travel plans based on the acquired tourist information. This includes optimizing the order of visits, estimating transportation methods and travel times. A generation AI model is used to create the plan that best matches the individual conditions. The input for this step is the list of tourist information from step 3, and the output is the optimized travel plan.

[0207] Step 5:

[0208] The device monitors the user's location during travel, checking changes in the surrounding environment and the user's emotional state in real time. It dynamically redesigns the route and suggests a new plan based on the emotional changes. A database service such as Firebase is used to enable real-time updates. The input for this step is the current location and the user's emotional state, and the output is the redesigned route or suggestion.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] 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.

[0215] 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).

[0216] 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.

[0217] 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.

[0218] 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).

[0219] 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.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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".

[0225] This invention is a system that allows users to customize and optimize their travel plans using their own device. First, the user inputs basic travel information, such as their budget, cities they want to visit, and tourist destinations of interest, into the device. This device uses natural language processing technology to analyze the user's input and clarify their needs.

[0226] The analysis results are sent to a server, which uses external databases and APIs to generate travel plans in real time. This includes information such as the crowd situation at the destination, the weather, and recommended tourist attractions. For example, if a user specifies that they want a relaxing hot spring trip with a budget of 100,000 yen, the server will create a list of hot spring resorts that fit within that budget and suggest the most suitable destination from that list.

[0227] During your trip, the server interacts with your device to monitor your progress in real time. This allows the server to consider traffic conditions and facility congestion, and, if necessary, suggest new routes or alternative tourist destinations. For example, if your planned tourist destination is crowded, the server will recommend nearby tourist destinations to your device.

[0228] Furthermore, it has the functionality to promote local tourism resources and contribute to the local economy by utilizing a local currency system. The server introduces local specialties and events of the visited area to users, enhancing the appeal of travel and contributing to regional revitalization.

[0229] In this way, by providing travel plans that match users' preferences and conditions, and by responding to diverse situations at the destination, it is possible to create a system that provides a fulfilling travel experience while giving back to the local community.

[0230] The following describes the processing flow.

[0231] Step 1:

[0232] The terminal displays an interface for the user to input information about their travel purpose, budget, and desired destinations. The user enters this information through this interface.

[0233] Step 2:

[0234] The device analyzes information entered by the user using a natural language processing engine. The analysis results identify the user's travel needs and preferences.

[0235] Step 3:

[0236] The device sends the analysis results as data to the server. This prepares the server for creating the travel plan in the next step.

[0237] Step 4:

[0238] The server extracts user criteria based on data received from the terminal. It retrieves necessary tourist information, congestion status, and weather data from available external databases and APIs.

[0239] Step 5:

[0240] The server applies an AI model and generates multiple travel plans using the acquired information. Each plan is specialized based on the user's conditions.

[0241] Step 6:

[0242] The server selects the most suitable travel plan for the user from the generated options and optimizes the itinerary to be efficient and appealing.

[0243] Step 7:

[0244] The server sends an optimized travel plan to the device. The device displays this plan and presents it to the user.

[0245] Step 8:

[0246] The server monitors the user's location and surrounding environment in real time during their trip. If necessary, it redesigns the travel route, taking into account traffic and congestion conditions.

[0247] Step 9:

[0248] The server conducts promotional activities using local tourism resources and the local currency system, and notifies users' devices of local specialties and event information. This promotes contributions to the local economy.

[0249] (Example 1)

[0250] 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."

[0251] In planning travel itineraries, it is difficult for users to gather a large amount of information on their own and create the optimal plan, and it is also difficult to maintain an optimal plan in real time as the situation changes during the trip. In addition, there is the problem that they cannot effectively contribute to the local economy of the travel destination.

[0252] 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.

[0253] In this invention, the server includes means for acquiring user input information and analyzing it using lexical analysis technology, means for acquiring information for creating an itinerary based on the analysis results from external information sources and data acquisition means, and means for selecting the plan best suited to the user's requirements from a plurality of generated itineraries and optimizing the travel itinerary in real time. This enables users to efficiently and effectively plan their trips, and to make an economic contribution to the destination region while continuing to optimize the plan in real time during the trip.

[0254] "User input information" refers to data such as budget, destinations, and activities of interest that users provide in order to plan their trip.

[0255] "Vocabulary analysis technology" is a technique that uses natural language processing technology to analyze the intent and requests of users from the information they input.

[0256] A "travel itinerary" refers to a detailed travel schedule that includes destinations, activities, and time allocations.

[0257] "External information sources" refer to external databases or APIs that the server connects to in order to generate travel itineraries, and are sources from which real-time information is obtained.

[0258] "Data acquisition methods" refer to the processes and technologies used to obtain necessary information from external sources.

[0259] "Real-time optimization" means adjusting the itinerary in real time according to changes in the user's environment and circumstances during their trip, always maintaining the optimal state.

[0260] "Environmental information" refers to factors that affect a user's trip, such as weather, traffic, and congestion at tourist spots.

[0261] "Contributing to the local economy" refers to actions and impacts that promote local economic activity, such as users purchasing local products or participating in local events during their travels.

[0262] "Artificial intelligence technology" refers to technologies that utilize machine learning and data analysis capabilities to generate itinerary plans tailored to user needs.

[0263] The embodiment for carrying out this invention is configured as follows: First, the user inputs information necessary for travel planning using their own terminal. Specifically, they input their budget, cities and countries to visit, activities and tourist destinations of interest, etc. The terminal collects this information and uses vocabulary analysis technology to analyze the user's requests in detail.

[0264] The analyzed information is sent to the server via the network. Based on this received information, the server accesses external information sources such as databases and APIs to obtain data such as congestion levels at the destination, weather information, and the latest events and exhibitions at tourist spots.

[0265] The server integrates the acquired information and uses artificial intelligence technology to generate an optimal travel itinerary that matches the user's requests. This itinerary generation uses an AI model that analyzes and optimizes data in real time. For example, it may adjust the order of destinations based on factors such as congestion levels.

[0266] The generated travel itinerary is sent to the device, where the user can review it on the screen and make changes or adjustments as needed. During the trip, the user's location and environmental information is sent to the server via the device, and the server dynamically redesigns the route based on this information. For example, if a planned tourist destination is crowded, the server will suggest a different nearby tourist destination.

[0267] Furthermore, the server suggests to users purchasing local products or participating in local events to promote contributions to the local economy of their travel destination. This creates benefits not only for the traveler but also for the region they visit.

[0268] An example of a prompt message is, "Please plan a budget-friendly museum tour in Tokyo. Please take into account crowd information and weather forecasts." In this way, the present invention aims to comprehensively support the user's travel experience and contribute to the local community.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] The user uses a terminal to input information necessary for travel planning. This input information includes budget, cities to visit, and tourist attractions and activities of interest. The terminal receives this information and prepares it for analysis using lexical analysis technology. The input text data is analyzed using natural language processing technology to clarify the user's intent. As a result of the analysis, the user's desired travel conditions are clarified. A specific example of this process is when the user inputs "I want to enjoy a relaxing hot spring trip" into the terminal, and the terminal analyzes that information.

[0272] Step 2:

[0273] The terminal sends the analysis results to the server. During this process, data processing takes place, involving the transmission of the generated analysis results data over the network. Based on the received analysis data, the server prepares to access external databases and APIs that serve as information sources. It receives the analysis results as input and proceeds with preparations for acquiring external data. A concrete example of this operation is when the terminal sends the analysis result "hot spring trip" to the server.

[0274] Step 3:

[0275] The server retrieves travel-related data from external databases and APIs. It obtains the latest information necessary for travel planning, such as congestion levels, weather, and special event information for planned destinations. This process involves data collection from external sources and data processing to obtain context related to user requests. As output, various travel-related data is aggregated on the server. Specifically, the server collects the latest weather information related to "hot springs in Tokyo."

[0276] Step 4:

[0277] The server uses artificial intelligence technology to generate a travel plan based on the acquired data. This generating AI model is used to design an optimal travel schedule that takes into account congestion information and weather. Using data acquired from external sources as input, the AI ​​model performs data calculations to generate the travel plan. The output is a travel itinerary customized for the user. Specifically, the server uses AI to suggest a relaxing hot spring schedule that avoids congestion at the destination.

[0278] Step 5:

[0279] The server sends the generated travel itinerary to the user's device. The device receives this data and prepares to visually present the information to the user. The generated itinerary data is received from the server as input and processed to be displayed in a format that the user can confirm. Specifically, the server can then display the completed hot spring trip schedule on the device screen.

[0280] Step 6:

[0281] During travel, the server continuously receives location and environmental information through the user's device. Based on this information, the server optimizes the itinerary in real time and dynamically redesigns the route as needed. It takes real-time location information as input and performs data calculations to recalculate the optimal itinerary. The output is an updated itinerary plan. A concrete example of this operation is when the server proposes a new route that avoids traffic congestion while the user is traveling.

[0282] Step 7:

[0283] The server suggests actions to users that encourage economic contribution by utilizing local resources at their travel destination. It prepares to provide information on local specialties and events that can be accessed on the device. The data output presents information on local specialties and local events that users can participate in, encouraging actions that contribute to the economy. Specifically, the server sends users information about participating in a local festival held in a hot spring resort.

[0284] (Application Example 1)

[0285] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0286] In recent years' meal supply services, there is a problem that the user experience does not improve because there is insufficient support for users to select an appropriate supplier according to their preferences and budget. Also, there is a lack of an optimal supply plan considering real-time congestion and delivery time, and it is required to improve these supply efficiencies. Furthermore, it is also important to contribute to the regional economy by effectively promoting the food resources in the region.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0288] In this invention, the server includes means for receiving the user's input information and analyzing it using natural language processing technology, means for obtaining information for generating a meal supply plan from an external database and API based on the analysis result, means for selecting the plan optimal for the user's conditions from the generated multiple meal supply plans and optimizing the delivery route in real time, and means for selecting an optimal supplier considering the delivery time and congestion situation obtained from an external API. Thereby, it becomes possible to optimize the meal supply plan based on the user's preferences, realize efficient supply considering congestion and delivery time, and also promote the activation of the regional economy by utilizing the food resources in the region.

[0289] The means of "receiving the user's input information and analyzing it using natural language processing technology" is a process of receiving information such as the user's preferences and budget for meals specified from the terminal, analyzing the information by natural language processing technology, and clarifying the user's needs.

[0290] "Means for obtaining information from external databases and APIs to generate a meal supply plan based on analysis results" refers to a method that utilizes analyzed user information to obtain real-time menu and supplier information from external databases and APIs, and generates appropriate meal supply options.

[0291] "A means of selecting the optimal meal supply plan from multiple generated plans that best suits the user's conditions and optimizing the delivery route in real time" refers to a function that selects the optimal plan that matches the user's desired conditions from among pre-generated supply plans and dynamically adjusts the delivery route and time based on that selection.

[0292] "A method for selecting the optimal supplier by considering delivery time and congestion status obtained from external APIs" refers to a method of evaluating delivery time and the degree of congestion at suppliers obtained using external APIs, and determining the optimal supplier for rapid and efficient delivery.

[0293] The system implementing this invention is comprised of communication between a user's terminal and a server. When the user inputs their preferred food genre and budget into the terminal, this information is analyzed using natural language processing technology. For the analysis, a natural language processing model using the Hugging Face Transformers library is utilized to reveal detailed needs regarding the user's preferences.

[0294] The server retrieves real-time data from external APIs (such as restaurant database APIs and map service APIs) based on the analyzed information and generates an optimal meal delivery plan. At this stage, Python frameworks like Flask or Django can be used. The retrieved data is dynamically optimized, taking into account delivery times and congestion levels, and presented to the user on a smartphone application developed with Flutter.

[0295] For example, if a user enters "I want to eat spicy food for 3000 yen" into the terminal, the system will search for restaurants serving spicy food in the vicinity, taking into account the user's location, and recommend restaurants based on factors such as waiting times and discount information. In this process, it is possible to suggest the restaurant and menu that best suits the user's criteria.

[0296] By using a generative AI model, prompts like the following can be used to instruct the system to derive the optimal plan from user input: "Based on the text entered by the user, generate a plan that suggests the best restaurant and menu in real time. Take into account the user's location, budget, and culinary preferences, and retrieve and process the necessary information from an external API."

[0297] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0298] Step 1:

[0299] The user enters their preferred food genre and budget into the device. This user input is collected in text format on the device. This serves as the initial input for the program.

[0300] Step 2:

[0301] The device analyzes the collected text information using natural language processing technology. Using the Hugging Face Transformers library, it analyzes the user's input text and extracts the user's specific wishes and conditions. This result is output as analyzed data.

[0302] Step 3:

[0303] The server retrieves real-time data from external APIs based on the analysis results. Based on the analyzed needs, it accesses restaurant database APIs and map service APIs to obtain supplier and delivery information. The input is the analyzed needs, and the output is the retrieved data.

[0304] Step 4:

[0305] The server generates and optimizes a meal supply plan based on the acquired data. It creates a list of target restaurants and menus, evaluates delivery times and congestion situations, and dynamically adjusts the plan. The input is the acquired data, and the optimized supply plan is output.

[0306] Step 5:

[0307] The server sends the optimized meal supply plan to the terminal. Through a smartphone app developed in Flutter, the user can view and select the proposed plan. The output is display data for the user.

[0308] Step 6:

[0309] The user selects their preferences from the presented options and places an order. The selected plan is recorded within the application by tapping or clicking and output as the final order data.

[0310] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0311] The present invention is a system that combines an emotion engine to further enrich the user's travel experience. The user inputs their wishes and interests regarding the trip into the terminal. At this point, the terminal analyzes this input information using a natural language processing engine to grasp the user's basic needs.

[0312] Furthermore, the device incorporates an emotion engine that infers the user's emotional state from the tone of the words they type and the conditions they select. For example, if a user types, "I'm stressed and want to go somewhere relaxing," the emotion engine will determine that the user prioritizes relaxation.

[0313] The analyzed information is sent to a server, which then generates a travel plan optimized for the user's needs and emotions based on tourism information obtained from external databases and APIs. For example, if the user wants to relax, quiet hot spring resorts with little crowding or peaceful, nature-rich locations will be suggested.

[0314] During the trip, the server utilizes an emotion engine to monitor the user's emotional state in real time. If the user expresses, for example, excitement or dissatisfaction, the server will re-select sightseeing destinations or suggest events accordingly. This makes it possible to provide an experience that fits the user's emotions.

[0315] Furthermore, the server promotes local tourism resources and contributes to the revitalization of the local economy by utilizing a local currency system. Based on the user's emotions indicated by the emotion engine, it provides personalized information on local products and events, creating an attractive local experience for the user.

[0316] In this way, this system optimizes travel plans that take user emotions into consideration and adjusts the travel experience in real time, thereby realizing more personalized travel and simultaneously promoting integration with local communities.

[0317] The following describes the processing flow.

[0318] Step 1:

[0319] The user inputs information about their travel preferences, budget, and destination region through the device. The device provides an interface for collecting this information.

[0320] Step 2:

[0321] The device uses natural language processing technology to analyze user input and extract basic travel needs and conditions. The analyzed information is used as data to clarify the user's intentions.

[0322] Step 3:

[0323] The device operates an emotion engine based on user input to detect the user's emotional state. For example, it analyzes word choices and tone to infer emotions such as wanting to relax or seeking stimulation.

[0324] Step 4:

[0325] The terminal sends the analyzed data and detected emotion data to the server. The server receives this data and uses it for processing.

[0326] Step 5:

[0327] The server collects tourism information from external databases and APIs based on the received data, and generates travel plans that match the user's needs and preferences. The plans take into account factors such as the level of crowding at the destinations and the weather.

[0328] Step 6:

[0329] The server creates several travel plans and selects the one best suited to the user. The selection is based on the user's emotional state.

[0330] Step 7:

[0331] The server sends the selected travel plan to the terminal. The terminal then presents the plan to the user, allowing the user to confirm it.

[0332] Step 8:

[0333] During the trip, the server utilizes an emotion engine to continuously monitor the user's emotional state. Based on changes in emotions, the plan is readjusted as needed.

[0334] Step 9:

[0335] The server promotes local tourism resources and contributes to economic revitalization through a local currency system. It provides users with emotionally-driven information on local specialties and events.

[0336] (Example 2)

[0337] 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".

[0338] In planning user trips, conventional systems failed to adequately consider users' emotions and individual preferences, resulting in a low degree of personalization. Furthermore, it was difficult to readjust the plan to reflect changes in users' emotions during the trip, leading to insufficient utilization of local tourism resources and inadequate contributions to the local community.

[0339] 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.

[0340] In this invention, the server includes natural language processing means for analyzing user input information, emotion analysis means for inferring the user's emotional state, and travel plan generation means based on the analysis results and emotional state. This enables the provision of detailed travel plans that take into account the user's individual emotions, the optimization of the real-time experience based on the user's emotional state during the trip, and further contributes to the local economy.

[0341] "User input information" refers to data that encapsulates the user's wishes and interests regarding travel, and is information in text format expressed in natural language.

[0342] "Natural language processing technology" refers to techniques that enable computers to understand and analyze human language, employing methods that include morphological analysis and semantic analysis.

[0343] "Emotional analysis methods" refer to technologies that infer emotional states from user input based on tone and word choices, and utilize emotion recognition algorithms.

[0344] "External databases and APIs" refer to repositories and application interfaces that provide data such as tourism information and weather information that can be accessed via the internet.

[0345] "Travel plan generation method" refers to the process of creating an optimal travel plan that reflects the user's needs and emotions, and is performed by the system based on data acquired from external sources.

[0346] "Real-time optimization" refers to operations that instantly readjust travel plans and itineraries in response to changes in the user's current location and emotional state, providing an experience tailored to the user.

[0347] "Travel monitoring" is a process of constantly observing the user's behavior and emotional state as they progress through their trip, and restructuring the plan as needed.

[0348] "Contributing to the local economy" refers to activities that aim to revitalize the region through tourism by promoting local culture and specialty products, thereby contributing to the development of the local economy.

[0349] A "local monetary system" refers to the local currency and payment methods used by travelers, and is a mechanism that has a direct impact on the local economy.

[0350] The system of this invention aims to optimize the user's travel experience and has a configuration that combines natural language processing technology and sentiment analysis means. Its embodiments are described in detail below.

[0351] First, the user enters their travel preferences and interests into their device. The entered data is analyzed via a natural language processing engine, and based on this analysis, the user's basic needs are understood. Furthermore, the device has a built-in emotion engine that analyzes the tone and selected words from the user's input to infer the user's emotional state. This allows the system to identify emotional needs, such as the user's desire for relaxation.

[0352] The analyzed information is sent to a server via the internet. The server accesses external databases and APIs to collect travel information and then generates a travel plan that best fits the user's needs and preferences. This plan suggests tourist destinations and activities tailored to the user's tastes. For example, a user seeking relaxation might be recommended less crowded hot spring resorts or quiet natural areas.

[0353] Furthermore, during the trip, the server monitors the user's emotional state in real time. It utilizes the user's smartphone app to collect feedback and recognize changes in their emotional state. Based on these changes, the server adjusts the selection of tourist destinations and suggests events in real time. This ensures that users continuously receive a travel experience tailored to their individual emotions and needs.

[0354] To contribute to the revitalization of the local economy, the server promotes local tourist resources and provides information on specialty products and events based on user sentiment. In this way, travelers are delivered attractive local experiences, and a sense of connection with the region is fostered.

[0355] For example, if a user inputs "I want to relax in a quiet place away from the hustle and bustle of the city," the system analyzes this need and suggests places like nature-rich retreats or quiet beaches. Furthermore, if the user provides feedback during their trip indicating a desire to "learn more about the local culture," the system will provide additional information such as traditional festivals or local craft experiences.

[0356] Examples of prompts include: "Please recommend a relaxing travel destination. Conditions: Stress relief, quiet environment" or "Please suggest tourist spots where I can experience the local culture. Interests: Hands-on experiences, traditional festivals."

[0357] This system allows users to enjoy flexible and personalized travel experiences tailored to their emotions and desires. Furthermore, it contributes to local communities through initiatives that utilize local resources.

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

[0359] Step 1:

[0360] The user inputs their travel preferences and interests into the device. This input includes specific information such as the travel destination, purpose, duration, budget, and emotional state the user wants to express. The device analyzes this information using natural language processing technology to understand the user's basic needs and emotional state. For example, it might receive input such as, "I want to go to a quiet place with abundant nature." The output obtained here is a list of standardized needs and an estimated emotional state.

[0361] Step 2:

[0362] The terminal sends the analyzed information to the server. The input includes estimated data on the user's needs and emotions. The server retrieves tourist information from external databases and APIs. Specifically, the server aggregates relevant information such as the characteristics of tourist destinations, seasonal information, and recommended activities. The output here is foundational data for travel plans that may suit the user's needs.

[0363] Step 3:

[0364] The server matches collected tourist information with user needs and sentiment data to generate the optimal travel plan. This process utilizes an AI model to generate and output multiple travel plans optimized for the user's conditions. For example, for a user seeking relaxation, it might suggest uncrowded hot spring resorts or quiet nature parks. The output here is a list of specific itineraries and potential destinations.

[0365] Step 4:

[0366] During the trip, the user's emotional state is monitored in real time by the device. The device receives user feedback as input and uses an emotion engine to detect changes in emotion. For example, if the user provides feedback such as "I want to do more active activities," this becomes the input. As output, suggestions for tourist destinations and activities that have been re-selected based on the emotional state are generated.

[0367] Step 5:

[0368] The server leverages local tourism resources to provide personalized information on local products and events based on the user's emotions. This stage includes the integration of local product promotions and a local currency system. Inputs are user emotion data and local promotional information, while output is a suggestion of engaging local experiences for the user.

[0369] In this way, this system uses natural language processing and sentiment analysis, starting with user input, to optimize the travel experience in real time. It can also strengthen relationships with local communities.

[0370] (Application Example 2)

[0371] 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."

[0372] For travelers, creating an optimal travel plan tailored to their individual needs and emotions is a challenging task. Furthermore, systems capable of flexibly responding to unexpected situations during travel are limited. Additionally, mechanisms for receiving real-time suggestions that respond to changing emotions are insufficient. Addressing these challenges is necessary to further personalize the user's travel experience and promote integration between local communities and travelers.

[0373] 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.

[0374] In this invention, the server includes means for receiving user input information and analyzing it using natural language processing technology, means for inferring the user's emotional state using an emotion engine and reflecting that information in the travel plan, and means for monitoring the user's location information and surrounding environment during the trip and dynamically redesigning the route in response to changes in the emotional state. This enables the optimization of the travel plan according to the user's needs and real-time sightseeing suggestions that are appropriate to their emotions.

[0375] "User input information" refers to text data such as travel preferences and interests that travelers enter into their devices.

[0376] "Natural language processing technology" is a technology that allows computers to analyze and understand human language, extracting meaning and intent from user input information.

[0377] An "emotion engine" is a technology that infers an emotional state from the words a user inputs or the conditions they select, and uses that information to process the system.

[0378] A "travel plan" is a plan of itineraries and destinations suggested based on the user's needs and interests.

[0379] "External databases and APIs" refer to external sources of information and interfaces that the system uses to retrieve tourist information and surrounding data.

[0380] "Real-time optimization" means instantly readjusting the travel plan in response to changes in the user's situation and emotions during their trip.

[0381] "Location information" refers to geographical data about the user's current location.

[0382] "Surrounding environment" refers to facilities, natural environments, or conditions that exist in the vicinity of the place the user is visiting.

[0383] "Emotion-responsive tourist information" refers to information about tourist spots and events that are appropriate for the user's emotional state.

[0384] This invention is a system that utilizes an emotion engine to enhance the user's travel experience. This system acquires user input information using devices such as smartphones and smart glasses. When the user inputs their travel wishes and interests, this information is analyzed using natural language processing technology. For the analysis, Python's natural language processing libraries NLTK and spaCy are used. The emotion engine utilizes an API for Sentiment Analysis to infer the user's emotional state from the tone and selection of the input words.

[0385] Based on these analysis results, the server retrieves tourist information from external databases using the Google Places API and other tools. It then optimizes the generated travel plan to match the user's emotions and dynamically redesigns the route in real time based on location information. During this process, cloud database services such as Firebase are used to keep the information instantly up-to-date.

[0386] For example, if a user enters a desire to "relax in a peaceful natural setting," the emotion engine will determine that the user is seeking relaxation and suggest information about quiet nature parks or hot spring resorts. During the trip, if the system detects an emotion such as "I want to avoid crowds today," it will redesign the route to avoid crowds and guide the user to peaceful spots.

[0387] An example of a prompt to input into a generative AI model is: "Design an application that suggests the optimal travel and sightseeing plan based on the user's emotions and interests, and provides a real-time, emotionally resonant experience."

[0388] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0389] Step 1:

[0390] The terminal receives text input from the user regarding their travel preferences and interests. This input information is then analyzed using natural language processing techniques. Specifically, the meaning of words and phrases is extracted using Python libraries such as NLTK and spaCy to identify the user's basic needs. The input for this step is the user's free-form text, and the output is the analyzed keywords and sentences.

[0391] Step 2:

[0392] The device uses an emotion engine to infer the user's emotional state based on the analyzed information, including the tone of voice and selected conditions. Using an API for Sentiment Analysis, it can determine, for example, that the user prioritizes relaxation from an input such as "I want to relax." The input for this step is the analysis results obtained in step 1, and the output is an evaluation of the user's emotional state.

[0393] Step 3:

[0394] The server retrieves tourist information from sources such as the Google Places API based on the user's needs and emotional state. It accesses external databases to collect tourist destinations and events that are suitable for the user. The input for this step is the emotional state and needs output from step 2, and the output is a list of recommended tourist information.

[0395] Step 4:

[0396] The server generates a series of travel plans based on the acquired tourist information. This includes optimizing the order of visits, estimating transportation methods and travel times. A generation AI model is used to create the plan that best matches the individual conditions. The input for this step is the list of tourist information from step 3, and the output is the optimized travel plan.

[0397] Step 5:

[0398] The device monitors the user's location during travel, checking changes in the surrounding environment and the user's emotional state in real time. It dynamically redesigns the route and suggests a new plan based on the emotional changes. A database service such as Firebase is used to enable real-time updates. The input for this step is the current location and the user's emotional state, and the output is the redesigned route or suggestion.

[0399] 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.

[0400] 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.

[0401] 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.

[0402] [Third Embodiment]

[0403] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0404] 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.

[0405] 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).

[0406] 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.

[0407] 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.

[0408] 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).

[0409] 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.

[0410] 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.

[0411] 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.

[0412] 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.

[0413] 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.

[0414] 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".

[0415] This invention is a system that allows users to customize and optimize their travel plans using their own device. First, the user inputs basic travel information, such as their budget, cities they want to visit, and tourist destinations of interest, into the device. This device uses natural language processing technology to analyze the user's input and clarify their needs.

[0416] The analysis results are sent to a server, which uses external databases and APIs to generate travel plans in real time. This includes information such as the crowd situation at the destination, the weather, and recommended tourist attractions. For example, if a user specifies that they want a relaxing hot spring trip with a budget of 100,000 yen, the server will create a list of hot spring resorts that fit within that budget and suggest the most suitable destination from that list.

[0417] During your trip, the server interacts with your device to monitor your progress in real time. This allows the server to consider traffic conditions and facility congestion, and, if necessary, suggest new routes or alternative tourist destinations. For example, if your planned tourist destination is crowded, the server will recommend nearby tourist destinations to your device.

[0418] Furthermore, it has the functionality to promote local tourism resources and contribute to the local economy by utilizing a local currency system. The server introduces local specialties and events of the visited area to users, enhancing the appeal of travel and contributing to regional revitalization.

[0419] In this way, by providing travel plans that match users' preferences and conditions, and by responding to diverse situations at the destination, it is possible to create a system that provides a fulfilling travel experience while giving back to the local community.

[0420] The following describes the processing flow.

[0421] Step 1:

[0422] The terminal displays an interface for the user to input information about their travel purpose, budget, and desired destinations. The user enters this information through this interface.

[0423] Step 2:

[0424] The device analyzes information entered by the user using a natural language processing engine. The analysis results identify the user's travel needs and preferences.

[0425] Step 3:

[0426] The device sends the analysis results as data to the server. This prepares the server for creating the travel plan in the next step.

[0427] Step 4:

[0428] The server extracts user criteria based on data received from the terminal. It retrieves necessary tourist information, congestion status, and weather data from available external databases and APIs.

[0429] Step 5:

[0430] The server applies an AI model and generates multiple travel plans using the acquired information. Each plan is specialized based on the user's conditions.

[0431] Step 6:

[0432] The server selects the most suitable travel plan for the user from the generated options and optimizes the itinerary to be efficient and appealing.

[0433] Step 7:

[0434] The server sends an optimized travel plan to the device. The device displays this plan and presents it to the user.

[0435] Step 8:

[0436] The server monitors the user's location and surrounding environment in real time during their trip. If necessary, it redesigns the travel route, taking into account traffic and congestion conditions.

[0437] Step 9:

[0438] The server conducts promotional activities using local tourism resources and the local currency system, and notifies users' devices of local specialties and event information. This promotes contributions to the local economy.

[0439] (Example 1)

[0440] 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."

[0441] In planning travel itineraries, it is difficult for users to gather a large amount of information on their own and create the optimal plan, and it is also difficult to maintain an optimal plan in real time as the situation changes during the trip. In addition, there is the problem that they cannot effectively contribute to the local economy of the travel destination.

[0442] 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.

[0443] In this invention, the server includes means for acquiring user input information and analyzing it using lexical analysis technology, means for acquiring information for creating an itinerary based on the analysis results from external information sources and data acquisition means, and means for selecting the plan best suited to the user's requirements from a plurality of generated itineraries and optimizing the travel itinerary in real time. This enables users to efficiently and effectively plan their trips, and to make an economic contribution to the destination region while continuing to optimize the plan in real time during the trip.

[0444] "User input information" refers to data such as budget, destinations, and activities of interest that users provide in order to plan their trip.

[0445] "Vocabulary analysis technology" is a technique that uses natural language processing technology to analyze the intent and requests of users from the information they input.

[0446] A "travel itinerary" refers to a detailed travel schedule that includes destinations, activities, and time allocations.

[0447] "External information sources" refer to external databases or APIs that the server connects to in order to generate travel itineraries, and are sources from which real-time information is obtained.

[0448] "Data acquisition methods" refer to the processes and technologies used to obtain necessary information from external sources.

[0449] "Real-time optimization" means adjusting the itinerary in real time according to changes in the user's environment and circumstances during their trip, always maintaining the optimal state.

[0450] "Environmental information" refers to factors that affect a user's trip, such as weather, traffic, and congestion at tourist spots.

[0451] "Contributing to the local economy" refers to actions and impacts that promote local economic activity, such as users purchasing local products or participating in local events during their travels.

[0452] "Artificial intelligence technology" refers to technologies that utilize machine learning and data analysis capabilities to generate itinerary plans tailored to user needs.

[0453] The embodiment for carrying out this invention is configured as follows: First, the user inputs information necessary for travel planning using their own terminal. Specifically, they input their budget, cities and countries to visit, activities and tourist destinations of interest, etc. The terminal collects this information and uses vocabulary analysis technology to analyze the user's requests in detail.

[0454] The analyzed information is sent to the server via the network. Based on this received information, the server accesses external information sources such as databases and APIs to obtain data such as congestion levels at the destination, weather information, and the latest events and exhibitions at tourist spots.

[0455] The server integrates the acquired information and uses artificial intelligence technology to generate an optimal travel itinerary that matches the user's requests. This itinerary generation uses an AI model that analyzes and optimizes data in real time. For example, it may adjust the order of destinations based on factors such as congestion levels.

[0456] The generated travel itinerary is sent to the device, where the user can review it on the screen and make changes or adjustments as needed. During the trip, the user's location and environmental information is sent to the server via the device, and the server dynamically redesigns the route based on this information. For example, if a planned tourist destination is crowded, the server will suggest a different nearby tourist destination.

[0457] Furthermore, the server suggests to users purchasing local products or participating in local events to promote contributions to the local economy of their travel destination. This creates benefits not only for the traveler but also for the region they visit.

[0458] An example of a prompt message is, "Please plan a budget-friendly museum tour in Tokyo. Please take into account crowd information and weather forecasts." In this way, the present invention aims to comprehensively support the user's travel experience and contribute to the local community.

[0459] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0460] Step 1:

[0461] The user uses a terminal to input information necessary for travel planning. This input information includes budget, cities to visit, and tourist attractions and activities of interest. The terminal receives this information and prepares it for analysis using lexical analysis technology. The input text data is analyzed using natural language processing technology to clarify the user's intent. As a result of the analysis, the user's desired travel conditions are clarified. A specific example of this process is when the user inputs "I want to enjoy a relaxing hot spring trip" into the terminal, and the terminal analyzes that information.

[0462] Step 2:

[0463] The terminal sends the analysis results to the server. During this process, data processing takes place, involving the transmission of the generated analysis results data over the network. Based on the received analysis data, the server prepares to access external databases and APIs that serve as information sources. It receives the analysis results as input and proceeds with preparations for acquiring external data. A concrete example of this operation is when the terminal sends the analysis result "hot spring trip" to the server.

[0464] Step 3:

[0465] The server retrieves travel-related data from external databases and APIs. It obtains the latest information necessary for travel planning, such as congestion levels, weather, and special event information for planned destinations. This process involves data collection from external sources and data processing to obtain context related to user requests. As output, various travel-related data is aggregated on the server. Specifically, the server collects the latest weather information related to "hot springs in Tokyo."

[0466] Step 4:

[0467] The server uses artificial intelligence technology to generate a travel plan based on the acquired data. This generating AI model is used to design an optimal travel schedule that takes into account congestion information and weather. Using data acquired from external sources as input, the AI ​​model performs data calculations to generate the travel plan. The output is a travel itinerary customized for the user. Specifically, the server uses AI to suggest a relaxing hot spring schedule that avoids congestion at the destination.

[0468] Step 5:

[0469] The server sends the generated travel itinerary to the user's device. The device receives this data and prepares to visually present the information to the user. The generated itinerary data is received from the server as input and processed to be displayed in a format that the user can confirm. Specifically, the server can then display the completed hot spring trip schedule on the device screen.

[0470] Step 6:

[0471] During travel, the server continuously receives location and environmental information through the user's device. Based on this information, the server optimizes the itinerary in real time and dynamically redesigns the route as needed. It takes real-time location information as input and performs data calculations to recalculate the optimal itinerary. The output is an updated itinerary plan. A concrete example of this operation is when the server proposes a new route that avoids traffic congestion while the user is traveling.

[0472] Step 7:

[0473] The server suggests actions to users that encourage economic contribution by utilizing local resources at their travel destination. It prepares to provide information on local specialties and events that can be accessed on the device. The data output presents information on local specialties and local events that users can participate in, encouraging actions that contribute to the economy. Specifically, the server sends users information about participating in a local festival held in a hot spring resort.

[0474] (Application Example 1)

[0475] 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."

[0476] In recent years, meal delivery services have faced the problem of insufficient support for users to select appropriate suppliers based on their preferences and budget, resulting in a lack of improved user experience. Furthermore, there is a lack of optimal supply planning that takes into account real-time congestion and delivery times, highlighting the need to improve supply efficiency. Additionally, effectively promoting local food resources and contributing to the local economy is crucial.

[0477] 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.

[0478] In this invention, the server includes means for receiving user input information and analyzing it using natural language processing technology, means for obtaining information from an external database and API for generating a meal supply plan based on the analysis results, means for selecting the plan best suited to the user's conditions from among the generated meal supply plans and optimizing the delivery route in real time, and means for selecting the optimal supplier considering delivery time and congestion status obtained from an external API. This enables the optimization of meal supply plans based on user preferences, realizes efficient supply considering congestion status and delivery time, and promotes the revitalization of the local economy by utilizing local food resources.

[0479] "A means of receiving user input information and analyzing it using natural language processing technology" refers to a process of receiving information such as the user's specified food preferences and budget from a terminal, analyzing that information using natural language processing technology, and clarifying the user's needs.

[0480] "Means for obtaining information from external databases and APIs to generate a meal supply plan based on analysis results" refers to a method that utilizes analyzed user information to obtain real-time menu and supplier information from external databases and APIs, and generates appropriate meal supply options.

[0481] "A means of selecting the optimal meal supply plan from multiple generated plans that best suits the user's conditions and optimizing the delivery route in real time" refers to a function that selects the optimal plan that matches the user's desired conditions from among pre-generated supply plans and dynamically adjusts the delivery route and time based on that selection.

[0482] "A method for selecting the optimal supplier by considering delivery time and congestion status obtained from external APIs" refers to a method of evaluating delivery time and the degree of congestion at suppliers obtained using external APIs, and determining the optimal supplier for rapid and efficient delivery.

[0483] The system implementing this invention is comprised of communication between a user's terminal and a server. When the user inputs their preferred food genre and budget into the terminal, this information is analyzed using natural language processing technology. For the analysis, a natural language processing model using the Hugging Face Transformers library is utilized to reveal detailed needs regarding the user's preferences.

[0484] The server retrieves real-time data from external APIs (such as restaurant database APIs and map service APIs) based on the analyzed information and generates an optimal meal delivery plan. At this stage, Python frameworks like Flask or Django can be used. The retrieved data is dynamically optimized, taking into account delivery times and congestion levels, and presented to the user on a smartphone application developed with Flutter.

[0485] For example, if a user enters "I want to eat spicy food for 3000 yen" into the terminal, the system will search for restaurants serving spicy food in the vicinity, taking into account the user's location, and recommend restaurants based on factors such as waiting times and discount information. In this process, it is possible to suggest the restaurant and menu that best suits the user's criteria.

[0486] By using a generative AI model, prompts like the following can be used to instruct the system to derive the optimal plan from user input: "Based on the text entered by the user, generate a plan that suggests the best restaurant and menu in real time. Take into account the user's location, budget, and culinary preferences, and retrieve and process the necessary information from an external API."

[0487] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0488] Step 1:

[0489] The user enters their preferred food genre and budget into the device. This user input is collected in text format on the device. This serves as the initial input for the program.

[0490] Step 2:

[0491] The device analyzes the collected text information using natural language processing technology. Using the Hugging Face Transformers library, it analyzes the user's input text and extracts the user's specific wishes and conditions. This result is output as analyzed data.

[0492] Step 3:

[0493] The server retrieves real-time data from external APIs based on the analysis results. Based on the analyzed needs, it accesses restaurant database APIs and map service APIs to obtain supplier and delivery information. The input is the analyzed needs, and the output is the retrieved data.

[0494] Step 4:

[0495] The server generates and optimizes a meal supply plan based on the acquired data. It creates a list of target restaurants and menus, evaluates delivery times and congestion levels, and dynamically adjusts the plan. The input is the acquired data, and the optimized supply plan is output.

[0496] Step 5:

[0497] The server sends an optimized meal delivery plan to the terminal. Through a smartphone app developed with Flutter, the user can review and select the proposed plan. The output is user-facing display data.

[0498] Step 6:

[0499] The user selects their preferred option from the presented choices and places an order. The selected plan is recorded within the application via taps or clicks and output as the final order data.

[0500] 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.

[0501] This invention is a system that combines an emotion engine to further enhance the user's travel experience. The user inputs their travel wishes and interests into the terminal. At this point, the terminal uses a natural language processing engine to analyze this input information and understand the user's basic needs.

[0502] Furthermore, the device incorporates an emotion engine that infers the user's emotional state from the tone of the words they type and the conditions they select. For example, if a user types, "I'm stressed and want to go somewhere relaxing," the emotion engine will determine that the user prioritizes relaxation.

[0503] The analyzed information is sent to a server, which then generates a travel plan optimized for the user's needs and emotions based on tourism information obtained from external databases and APIs. For example, if the user wants to relax, quiet hot spring resorts with little crowding or peaceful, nature-rich locations will be suggested.

[0504] During the trip, the server utilizes an emotion engine to monitor the user's emotional state in real time. If the user expresses, for example, excitement or dissatisfaction, the server will re-select sightseeing destinations or suggest events accordingly. This makes it possible to provide an experience that fits the user's emotions.

[0505] Furthermore, the server promotes local tourism resources and contributes to the revitalization of the local economy by utilizing a local currency system. Based on the user's emotions indicated by the emotion engine, it provides personalized information on local products and events, creating an attractive local experience for the user.

[0506] In this way, this system optimizes travel plans that take user emotions into consideration and adjusts the travel experience in real time, thereby realizing more personalized travel and simultaneously promoting integration with local communities.

[0507] The following describes the processing flow.

[0508] Step 1:

[0509] The user inputs information about their travel preferences, budget, and destination region through the device. The device provides an interface for collecting this information.

[0510] Step 2:

[0511] The device uses natural language processing technology to analyze user input and extract basic travel needs and conditions. The analyzed information is used as data to clarify the user's intentions.

[0512] Step 3:

[0513] The device operates an emotion engine based on user input to detect the user's emotional state. For example, it analyzes word choices and tone to infer emotions such as wanting to relax or seeking stimulation.

[0514] Step 4:

[0515] The terminal sends the analyzed data and detected emotion data to the server. The server receives this data and uses it for processing.

[0516] Step 5:

[0517] The server collects tourism information from external databases and APIs based on the received data, and generates travel plans that match the user's needs and preferences. The plans take into account factors such as the level of crowding at the destinations and the weather.

[0518] Step 6:

[0519] The server creates several travel plans and selects the one best suited to the user. The selection is based on the user's emotional state.

[0520] Step 7:

[0521] The server sends the selected travel plan to the terminal. The terminal then presents the plan to the user, allowing the user to confirm it.

[0522] Step 8:

[0523] During the trip, the server utilizes an emotion engine to continuously monitor the user's emotional state. Based on changes in emotions, the plan is readjusted as needed.

[0524] Step 9:

[0525] The server promotes local tourism resources and contributes to economic revitalization through a local currency system. It provides users with emotionally-driven information on local specialties and events.

[0526] (Example 2)

[0527] 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."

[0528] In planning user trips, conventional systems failed to adequately consider users' emotions and individual preferences, resulting in a low degree of personalization. Furthermore, it was difficult to readjust the plan to reflect changes in users' emotions during the trip, leading to insufficient utilization of local tourism resources and inadequate contributions to the local community.

[0529] 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.

[0530] In this invention, the server includes natural language processing means for analyzing user input information, emotion analysis means for inferring the user's emotional state, and travel plan generation means based on the analysis results and emotional state. This enables the provision of detailed travel plans that take into account the user's individual emotions, the optimization of the real-time experience based on the user's emotional state during the trip, and further contributes to the local economy.

[0531] "User input information" refers to data that encapsulates the user's wishes and interests regarding travel, and is information in text format expressed in natural language.

[0532] "Natural language processing technology" refers to techniques that enable computers to understand and analyze human language, employing methods that include morphological analysis and semantic analysis.

[0533] "Emotional analysis methods" refer to technologies that infer emotional states from user input based on tone and word choices, and utilize emotion recognition algorithms.

[0534] "External databases and APIs" refer to repositories and application interfaces that provide data such as tourism information and weather information that can be accessed via the internet.

[0535] "Travel plan generation method" refers to the process of creating an optimal travel plan that reflects the user's needs and emotions, and is performed by the system based on data acquired from external sources.

[0536] "Real-time optimization" refers to operations that instantly readjust travel plans and itineraries in response to changes in the user's current location and emotional state, providing an experience tailored to the user.

[0537] "Travel monitoring" is a process of constantly observing the user's behavior and emotional state as they progress through their trip, and restructuring the plan as needed.

[0538] "Contributing to the local economy" refers to activities that aim to revitalize the region through tourism by promoting local culture and specialty products, thereby contributing to the development of the local economy.

[0539] A "local monetary system" refers to the local currency and payment methods used by travelers, and is a mechanism that has a direct impact on the local economy.

[0540] The system of this invention aims to optimize the user's travel experience and has a configuration that combines natural language processing technology and sentiment analysis means. Its embodiments are described in detail below.

[0541] First, the user enters their travel preferences and interests into their device. The entered data is analyzed via a natural language processing engine, and based on this analysis, the user's basic needs are understood. Furthermore, the device has a built-in emotion engine that analyzes the tone and selected words from the user's input to infer the user's emotional state. This allows the system to identify emotional needs, such as the user's desire for relaxation.

[0542] The analyzed information is sent to a server via the internet. The server accesses external databases and APIs to collect travel information and then generates a travel plan that best fits the user's needs and preferences. This plan suggests tourist destinations and activities tailored to the user's tastes. For example, a user seeking relaxation might be recommended less crowded hot spring resorts or quiet natural areas.

[0543] Furthermore, during the trip, the server monitors the user's emotional state in real time. It utilizes the user's smartphone app to collect feedback and recognize changes in their emotional state. Based on these changes, the server adjusts the selection of tourist destinations and suggests events in real time. This ensures that users continuously receive a travel experience tailored to their individual emotions and needs.

[0544] To contribute to the revitalization of the local economy, the server promotes local tourist resources and provides information on specialty products and events based on user sentiment. In this way, travelers are delivered attractive local experiences, and a sense of connection with the region is fostered.

[0545] For example, if a user inputs "I want to relax in a quiet place away from the hustle and bustle of the city," the system analyzes this need and suggests places like nature-rich retreats or quiet beaches. Furthermore, if the user provides feedback during their trip indicating a desire to "learn more about the local culture," the system will provide additional information such as traditional festivals or local craft experiences.

[0546] Examples of prompts include: "Please recommend a relaxing travel destination. Conditions: Stress relief, quiet environment" or "Please suggest tourist spots where I can experience the local culture. Interests: Hands-on experiences, traditional festivals."

[0547] This system allows users to enjoy flexible and personalized travel experiences tailored to their emotions and desires. Furthermore, it contributes to local communities through initiatives that utilize local resources.

[0548] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0549] Step 1:

[0550] The user inputs their travel preferences and interests into the device. This input includes specific information such as the travel destination, purpose, duration, budget, and emotional state the user wants to express. The device analyzes this information using natural language processing technology to understand the user's basic needs and emotional state. For example, it might receive input such as, "I want to go to a quiet place with abundant nature." The output obtained here is a list of standardized needs and an estimated emotional state.

[0551] Step 2:

[0552] The terminal sends the analyzed information to the server. The input includes estimated data on the user's needs and emotions. The server retrieves tourist information from external databases and APIs. Specifically, the server aggregates relevant information such as the characteristics of tourist destinations, seasonal information, and recommended activities. The output here is foundational data for travel plans that may suit the user's needs.

[0553] Step 3:

[0554] The server matches collected tourist information with user needs and sentiment data to generate the optimal travel plan. This process utilizes an AI model to generate and output multiple travel plans optimized for the user's conditions. For example, for a user seeking relaxation, it might suggest uncrowded hot spring resorts or quiet nature parks. The output here is a list of specific itineraries and potential destinations.

[0555] Step 4:

[0556] During the trip, the user's emotional state is monitored in real time by the device. The device receives user feedback as input and uses an emotion engine to detect changes in emotion. For example, if the user provides feedback such as "I want to do more active activities," this becomes the input. As output, suggestions for tourist destinations and activities that have been re-selected based on the emotional state are generated.

[0557] Step 5:

[0558] The server leverages local tourism resources to provide personalized information on local products and events based on the user's emotions. This stage includes the integration of local product promotions and a local currency system. Inputs are user emotion data and local promotional information, while output is a suggestion of engaging local experiences for the user.

[0559] In this way, this system uses natural language processing and sentiment analysis, starting with user input, to optimize the travel experience in real time. It can also strengthen relationships with local communities.

[0560] (Application Example 2)

[0561] 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."

[0562] For travelers, creating an optimal travel plan tailored to their individual needs and emotions is a challenging task. Furthermore, systems capable of flexibly responding to unexpected situations during travel are limited. Additionally, mechanisms for receiving real-time suggestions that respond to changing emotions are insufficient. Addressing these challenges is necessary to further personalize the user's travel experience and promote integration between local communities and travelers.

[0563] 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.

[0564] In this invention, the server includes means for receiving user input information and analyzing it using natural language processing technology, means for inferring the user's emotional state using an emotion engine and reflecting that information in the travel plan, and means for monitoring the user's location information and surrounding environment during the trip and dynamically redesigning the route in response to changes in the emotional state. This enables the optimization of the travel plan according to the user's needs and real-time sightseeing suggestions that are appropriate to their emotions.

[0565] "User input information" refers to text data such as travel preferences and interests that travelers enter into their devices.

[0566] "Natural language processing technology" is a technology that allows computers to analyze and understand human language, extracting meaning and intent from user input information.

[0567] An "emotion engine" is a technology that infers an emotional state from the words a user inputs or the conditions they select, and uses that information to process the system.

[0568] A "travel plan" is a plan of itineraries and destinations suggested based on the user's needs and interests.

[0569] "External databases and APIs" refer to external sources of information and interfaces that the system uses to retrieve tourist information and surrounding data.

[0570] "Real-time optimization" means instantly readjusting the travel plan in response to changes in the user's situation and emotions during their trip.

[0571] "Location information" refers to geographical data about the user's current location.

[0572] "Surrounding environment" refers to facilities, natural environments, or conditions that exist in the vicinity of the place the user is visiting.

[0573] "Emotion-responsive tourist information" refers to information about tourist spots and events that are appropriate for the user's emotional state.

[0574] This invention is a system that utilizes an emotion engine to enhance the user's travel experience. This system acquires user input information using devices such as smartphones and smart glasses. When the user inputs their travel wishes and interests, this information is analyzed using natural language processing technology. For the analysis, Python's natural language processing libraries NLTK and spaCy are used. The emotion engine utilizes an API for Sentiment Analysis to infer the user's emotional state from the tone and selection of the input words.

[0575] Based on these analysis results, the server retrieves tourist information from external databases using the Google Places API and other tools. It then optimizes the generated travel plan to match the user's emotions and dynamically redesigns the route in real time based on location information. During this process, cloud database services such as Firebase are used to keep the information instantly up-to-date.

[0576] For example, if a user enters a desire to "relax in a peaceful natural setting," the emotion engine will determine that the user is seeking relaxation and suggest information about quiet nature parks or hot spring resorts. During the trip, if the system detects an emotion such as "I want to avoid crowds today," it will redesign the route to avoid crowds and guide the user to peaceful spots.

[0577] An example of a prompt to input into a generative AI model is: "Design an application that suggests the optimal travel and sightseeing plan based on the user's emotions and interests, and provides a real-time, emotionally resonant experience."

[0578] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0579] Step 1:

[0580] The terminal receives text input from the user regarding their travel preferences and interests. This input information is then analyzed using natural language processing techniques. Specifically, the meaning of words and phrases is extracted using Python libraries such as NLTK and spaCy to identify the user's basic needs. The input for this step is the user's free-form text, and the output is the analyzed keywords and sentences.

[0581] Step 2:

[0582] The device uses an emotion engine to infer the user's emotional state based on the analyzed information, including the tone of voice and selected conditions. Using an API for Sentiment Analysis, it can determine, for example, that the user prioritizes relaxation from an input such as "I want to relax." The input for this step is the analysis results obtained in step 1, and the output is an evaluation of the user's emotional state.

[0583] Step 3:

[0584] The server retrieves tourist information from sources such as the Google Places API based on the user's needs and emotional state. It accesses external databases to collect tourist destinations and events that are suitable for the user. The input for this step is the emotional state and needs output from step 2, and the output is a list of recommended tourist information.

[0585] Step 4:

[0586] The server generates a series of travel plans based on the acquired tourist information. This includes optimizing the order of visits, estimating transportation methods and travel times. A generation AI model is used to create the plan that best matches the individual conditions. The input for this step is the list of tourist information from step 3, and the output is the optimized travel plan.

[0587] Step 5:

[0588] The device monitors the user's location during travel, checking changes in the surrounding environment and the user's emotional state in real time. It dynamically redesigns the route and suggests a new plan based on the emotional changes. A database service such as Firebase is used to enable real-time updates. The input for this step is the current location and the user's emotional state, and the output is the redesigned route or suggestion.

[0589] 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.

[0590] 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.

[0591] 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.

[0592] [Fourth Embodiment]

[0593] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0594] 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.

[0595] 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).

[0596] 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.

[0597] 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.

[0598] 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).

[0599] 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.

[0600] 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.

[0601] 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.

[0602] 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.

[0603] 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.

[0604] 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.

[0605] 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".

[0606] This invention is a system that allows users to customize and optimize their travel plans using their own device. First, the user inputs basic travel information, such as their budget, cities they want to visit, and tourist destinations of interest, into the device. This device uses natural language processing technology to analyze the user's input and clarify their needs.

[0607] The analysis results are sent to a server, which uses external databases and APIs to generate travel plans in real time. This includes information such as the crowd situation at the destination, the weather, and recommended tourist attractions. For example, if a user specifies that they want a relaxing hot spring trip with a budget of 100,000 yen, the server will create a list of hot spring resorts that fit within that budget and suggest the most suitable destination from that list.

[0608] During your trip, the server interacts with your device to monitor your progress in real time. This allows the server to consider traffic conditions and facility congestion, and, if necessary, suggest new routes or alternative tourist destinations. For example, if your planned tourist destination is crowded, the server will recommend nearby tourist destinations to your device.

[0609] Furthermore, it has the functionality to promote local tourism resources and contribute to the local economy by utilizing a local currency system. The server introduces local specialties and events of the visited area to users, enhancing the appeal of travel and contributing to regional revitalization.

[0610] In this way, by providing travel plans that match users' preferences and conditions, and by responding to diverse situations at the destination, it is possible to create a system that provides a fulfilling travel experience while giving back to the local community.

[0611] The following describes the processing flow.

[0612] Step 1:

[0613] The terminal displays an interface for the user to input information about their travel purpose, budget, and desired destinations. The user enters this information through this interface.

[0614] Step 2:

[0615] The device analyzes information entered by the user using a natural language processing engine. The analysis results identify the user's travel needs and preferences.

[0616] Step 3:

[0617] The device sends the analysis results as data to the server. This prepares the server for creating the travel plan in the next step.

[0618] Step 4:

[0619] The server extracts user criteria based on data received from the terminal. It retrieves necessary tourist information, congestion status, and weather data from available external databases and APIs.

[0620] Step 5:

[0621] The server applies an AI model and generates multiple travel plans using the acquired information. Each plan is specialized based on the user's conditions.

[0622] Step 6:

[0623] The server selects the most suitable travel plan for the user from the generated options and optimizes the itinerary to be efficient and appealing.

[0624] Step 7:

[0625] The server sends an optimized travel plan to the device. The device displays this plan and presents it to the user.

[0626] Step 8:

[0627] The server monitors the user's location and surrounding environment in real time during their trip. If necessary, it redesigns the travel route, taking into account traffic and congestion conditions.

[0628] Step 9:

[0629] The server conducts promotional activities using local tourism resources and the local currency system, and notifies users' devices of local specialties and event information. This promotes contributions to the local economy.

[0630] (Example 1)

[0631] 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".

[0632] In planning travel itineraries, it is difficult for users to gather a large amount of information on their own and create the optimal plan, and it is also difficult to maintain an optimal plan in real time as the situation changes during the trip. In addition, there is the problem that they cannot effectively contribute to the local economy of the travel destination.

[0633] 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.

[0634] In this invention, the server includes means for acquiring user input information and analyzing it using lexical analysis technology, means for acquiring information for creating an itinerary based on the analysis results from external information sources and data acquisition means, and means for selecting the plan best suited to the user's requirements from a plurality of generated itineraries and optimizing the travel itinerary in real time. This enables users to efficiently and effectively plan their trips, and to make an economic contribution to the destination region while continuing to optimize the plan in real time during the trip.

[0635] "User input information" refers to data such as budget, destinations, and activities of interest that users provide in order to plan their trip.

[0636] "Vocabulary analysis technology" is a technique that uses natural language processing technology to analyze the intent and requests of users from the information they input.

[0637] A "travel itinerary" refers to a detailed travel schedule that includes destinations, activities, and time allocations.

[0638] "External information sources" refer to external databases or APIs that the server connects to in order to generate travel itineraries, and are sources from which real-time information is obtained.

[0639] "Data acquisition methods" refer to the processes and technologies used to obtain necessary information from external sources.

[0640] "Real-time optimization" means adjusting the itinerary in real time according to changes in the user's environment and circumstances during their trip, always maintaining the optimal state.

[0641] "Environmental information" refers to factors that affect a user's trip, such as weather, traffic, and congestion at tourist spots.

[0642] "Contributing to the local economy" refers to actions and impacts that promote local economic activity, such as users purchasing local products or participating in local events during their travels.

[0643] "Artificial intelligence technology" refers to technologies that utilize machine learning and data analysis capabilities to generate itinerary plans tailored to user needs.

[0644] The embodiment for carrying out this invention is configured as follows: First, the user inputs information necessary for travel planning using their own terminal. Specifically, they input their budget, cities and countries to visit, activities and tourist destinations of interest, etc. The terminal collects this information and uses vocabulary analysis technology to analyze the user's requests in detail.

[0645] The analyzed information is sent to the server via the network. Based on this received information, the server accesses external information sources such as databases and APIs to obtain data such as congestion levels at the destination, weather information, and the latest events and exhibitions at tourist spots.

[0646] The server integrates the acquired information and uses artificial intelligence technology to generate an optimal travel itinerary that matches the user's requests. This itinerary generation uses an AI model that analyzes and optimizes data in real time. For example, it may adjust the order of destinations based on factors such as congestion levels.

[0647] The generated travel itinerary is sent to the device, where the user can review it on the screen and make changes or adjustments as needed. During the trip, the user's location and environmental information is sent to the server via the device, and the server dynamically redesigns the route based on this information. For example, if a planned tourist destination is crowded, the server will suggest a different nearby tourist destination.

[0648] Furthermore, the server suggests to users purchasing local products or participating in local events to promote contributions to the local economy of their travel destination. This creates benefits not only for the traveler but also for the region they visit.

[0649] An example of a prompt message is, "Please plan a budget-friendly museum tour in Tokyo. Please take into account crowd information and weather forecasts." In this way, the present invention aims to comprehensively support the user's travel experience and contribute to the local community.

[0650] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0651] Step 1:

[0652] The user uses a terminal to input information necessary for travel planning. This input information includes budget, cities to visit, and tourist attractions and activities of interest. The terminal receives this information and prepares it for analysis using lexical analysis technology. The input text data is analyzed using natural language processing technology to clarify the user's intent. As a result of the analysis, the user's desired travel conditions are clarified. A specific example of this process is when the user inputs "I want to enjoy a relaxing hot spring trip" into the terminal, and the terminal analyzes that information.

[0653] Step 2:

[0654] The terminal sends the analysis results to the server. During this process, data processing takes place, involving the transmission of the generated analysis results data over the network. Based on the received analysis data, the server prepares to access external databases and APIs that serve as information sources. It receives the analysis results as input and proceeds with preparations for acquiring external data. A concrete example of this operation is when the terminal sends the analysis result "hot spring trip" to the server.

[0655] Step 3:

[0656] The server retrieves travel-related data from external databases and APIs. It obtains the latest information necessary for travel planning, such as congestion levels, weather, and special event information for planned destinations. This process involves data collection from external sources and data processing to obtain context related to user requests. As output, various travel-related data is aggregated on the server. Specifically, the server collects the latest weather information related to "hot springs in Tokyo."

[0657] Step 4:

[0658] The server uses artificial intelligence technology to generate a travel plan based on the acquired data. This generating AI model is used to design an optimal travel schedule that takes into account congestion information and weather. Using data acquired from external sources as input, the AI ​​model performs data calculations to generate the travel plan. The output is a travel itinerary customized for the user. Specifically, the server uses AI to suggest a relaxing hot spring schedule that avoids congestion at the destination.

[0659] Step 5:

[0660] The server sends the generated travel itinerary to the user's device. The device receives this data and prepares to visually present the information to the user. The generated itinerary data is received from the server as input and processed to be displayed in a format that the user can confirm. Specifically, the server can then display the completed hot spring trip schedule on the device screen.

[0661] Step 6:

[0662] During travel, the server continuously receives location and environmental information through the user's device. Based on this information, the server optimizes the itinerary in real time and dynamically redesigns the route as needed. It takes real-time location information as input and performs data calculations to recalculate the optimal itinerary. The output is an updated itinerary plan. A concrete example of this operation is when the server proposes a new route that avoids traffic congestion while the user is traveling.

[0663] Step 7:

[0664] The server suggests actions to users that encourage economic contribution by utilizing local resources at their travel destination. It prepares to provide information on local specialties and events that can be accessed on the device. The data output presents information on local specialties and local events that users can participate in, encouraging actions that contribute to the economy. Specifically, the server sends users information about participating in a local festival held in a hot spring resort.

[0665] (Application Example 1)

[0666] 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".

[0667] In recent years, meal delivery services have faced the problem of insufficient support for users to select appropriate suppliers based on their preferences and budget, resulting in a lack of improved user experience. Furthermore, there is a lack of optimal supply planning that takes into account real-time congestion and delivery times, highlighting the need to improve supply efficiency. Additionally, effectively promoting local food resources and contributing to the local economy is crucial.

[0668] 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.

[0669] In this invention, the server includes means for receiving user input information and analyzing it using natural language processing technology, means for obtaining information from an external database and API for generating a meal supply plan based on the analysis results, means for selecting the plan best suited to the user's conditions from among the generated meal supply plans and optimizing the delivery route in real time, and means for selecting the optimal supplier considering delivery time and congestion status obtained from an external API. This enables the optimization of meal supply plans based on user preferences, realizes efficient supply considering congestion status and delivery time, and promotes the revitalization of the local economy by utilizing local food resources.

[0670] "A means of receiving user input information and analyzing it using natural language processing technology" refers to a process of receiving information such as the user's specified food preferences and budget from a terminal, analyzing that information using natural language processing technology, and clarifying the user's needs.

[0671] "Means for obtaining information from external databases and APIs to generate a meal supply plan based on analysis results" refers to a method that utilizes analyzed user information to obtain real-time menu and supplier information from external databases and APIs, and generates appropriate meal supply options.

[0672] "A means of selecting the optimal meal supply plan from multiple generated plans that best suits the user's conditions and optimizing the delivery route in real time" refers to a function that selects the optimal plan that matches the user's desired conditions from among pre-generated supply plans and dynamically adjusts the delivery route and time based on that selection.

[0673] "A method for selecting the optimal supplier by considering delivery time and congestion status obtained from external APIs" refers to a method of evaluating delivery time and the degree of congestion at suppliers obtained using external APIs, and determining the optimal supplier for rapid and efficient delivery.

[0674] The system implementing this invention is comprised of communication between a user's terminal and a server. When the user inputs their preferred food genre and budget into the terminal, this information is analyzed using natural language processing technology. For the analysis, a natural language processing model using the Hugging Face Transformers library is utilized to reveal detailed needs regarding the user's preferences.

[0675] The server retrieves real-time data from external APIs (such as restaurant database APIs and map service APIs) based on the analyzed information and generates an optimal meal delivery plan. At this stage, Python frameworks like Flask or Django can be used. The retrieved data is dynamically optimized, taking into account delivery times and congestion levels, and presented to the user on a smartphone application developed with Flutter.

[0676] For example, if a user enters "I want to eat spicy food for 3000 yen" into the terminal, the system will search for restaurants serving spicy food in the vicinity, taking into account the user's location, and recommend restaurants based on factors such as waiting times and discount information. In this process, it is possible to suggest the restaurant and menu that best suits the user's criteria.

[0677] By using a generative AI model, prompts like the following can be used to instruct the system to derive the optimal plan from user input: "Based on the text entered by the user, generate a plan that suggests the best restaurant and menu in real time. Take into account the user's location, budget, and culinary preferences, and retrieve and process the necessary information from an external API."

[0678] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0679] Step 1:

[0680] The user enters their preferred food genre and budget into the device. This user input is collected in text format on the device. This serves as the initial input for the program.

[0681] Step 2:

[0682] The device analyzes the collected text information using natural language processing technology. Using the Hugging Face Transformers library, it analyzes the user's input text and extracts the user's specific wishes and conditions. This result is output as analyzed data.

[0683] Step 3:

[0684] The server retrieves real-time data from external APIs based on the analysis results. Based on the analyzed needs, it accesses restaurant database APIs and map service APIs to obtain supplier and delivery information. The input is the analyzed needs, and the output is the retrieved data.

[0685] Step 4:

[0686] The server generates and optimizes a meal supply plan based on the acquired data. It creates a list of target restaurants and menus, evaluates delivery times and congestion levels, and dynamically adjusts the plan. The input is the acquired data, and the optimized supply plan is output.

[0687] Step 5:

[0688] The server sends an optimized meal delivery plan to the terminal. Through a smartphone app developed with Flutter, the user can review and select the proposed plan. The output is user-facing display data.

[0689] Step 6:

[0690] The user selects their preferred option from the presented choices and places an order. The selected plan is recorded within the application via taps or clicks and output as the final order data.

[0691] 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.

[0692] This invention is a system that combines an emotion engine to further enhance the user's travel experience. The user inputs their travel wishes and interests into the terminal. At this point, the terminal uses a natural language processing engine to analyze this input information and understand the user's basic needs.

[0693] Furthermore, the device incorporates an emotion engine that infers the user's emotional state from the tone of the words they type and the conditions they select. For example, if a user types, "I'm stressed and want to go somewhere relaxing," the emotion engine will determine that the user prioritizes relaxation.

[0694] The analyzed information is sent to a server, which then generates a travel plan optimized for the user's needs and emotions based on tourism information obtained from external databases and APIs. For example, if the user wants to relax, quiet hot spring resorts with little crowding or peaceful, nature-rich locations will be suggested.

[0695] During the trip, the server utilizes an emotion engine to monitor the user's emotional state in real time. If the user expresses, for example, excitement or dissatisfaction, the server will re-select sightseeing destinations or suggest events accordingly. This makes it possible to provide an experience that fits the user's emotions.

[0696] Furthermore, the server promotes local tourism resources and contributes to the revitalization of the local economy by utilizing a local currency system. Based on the user's emotions indicated by the emotion engine, it provides personalized information on local products and events, creating an attractive local experience for the user.

[0697] In this way, this system optimizes travel plans that take user emotions into consideration and adjusts the travel experience in real time, thereby realizing more personalized travel and simultaneously promoting integration with local communities.

[0698] The following describes the processing flow.

[0699] Step 1:

[0700] The user inputs information about their travel preferences, budget, and destination region through the device. The device provides an interface for collecting this information.

[0701] Step 2:

[0702] The device uses natural language processing technology to analyze user input and extract basic travel needs and conditions. The analyzed information is used as data to clarify the user's intentions.

[0703] Step 3:

[0704] The device operates an emotion engine based on user input to detect the user's emotional state. For example, it analyzes word choices and tone to infer emotions such as wanting to relax or seeking stimulation.

[0705] Step 4:

[0706] The terminal sends the analyzed data and detected emotion data to the server. The server receives this data and uses it for processing.

[0707] Step 5:

[0708] The server collects tourism information from external databases and APIs based on the received data, and generates travel plans that match the user's needs and preferences. The plans take into account factors such as the level of crowding at the destinations and the weather.

[0709] Step 6:

[0710] The server creates several travel plans and selects the one best suited to the user. The selection is based on the user's emotional state.

[0711] Step 7:

[0712] The server sends the selected travel plan to the terminal. The terminal then presents the plan to the user, allowing the user to confirm it.

[0713] Step 8:

[0714] During the trip, the server utilizes an emotion engine to continuously monitor the user's emotional state. Based on changes in emotions, the plan is readjusted as needed.

[0715] Step 9:

[0716] The server promotes local tourism resources and contributes to economic revitalization through a local currency system. It provides users with emotionally-driven information on local specialties and events.

[0717] (Example 2)

[0718] 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".

[0719] In planning user trips, conventional systems failed to adequately consider users' emotions and individual preferences, resulting in a low degree of personalization. Furthermore, it was difficult to readjust the plan to reflect changes in users' emotions during the trip, leading to insufficient utilization of local tourism resources and inadequate contributions to the local community.

[0720] 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.

[0721] In this invention, the server includes natural language processing means for analyzing user input information, emotion analysis means for inferring the user's emotional state, and travel plan generation means based on the analysis results and emotional state. This enables the provision of detailed travel plans that take into account the user's individual emotions, the optimization of the real-time experience based on the user's emotional state during the trip, and further contributes to the local economy.

[0722] "User input information" refers to data that encapsulates the user's wishes and interests regarding travel, and is information in text format expressed in natural language.

[0723] "Natural language processing technology" refers to techniques that enable computers to understand and analyze human language, employing methods that include morphological analysis and semantic analysis.

[0724] "Emotional analysis methods" refer to technologies that infer emotional states from user input based on tone and word choices, and utilize emotion recognition algorithms.

[0725] "External databases and APIs" refer to repositories and application interfaces that provide data such as tourism information and weather information that can be accessed via the internet.

[0726] "Travel plan generation method" refers to the process of creating an optimal travel plan that reflects the user's needs and emotions, and is performed by the system based on data acquired from external sources.

[0727] "Real-time optimization" refers to operations that instantly readjust travel plans and itineraries in response to changes in the user's current location and emotional state, providing an experience tailored to the user.

[0728] "Travel monitoring" is a process of constantly observing the user's behavior and emotional state as they progress through their trip, and restructuring the plan as needed.

[0729] "Contributing to the local economy" refers to activities that aim to revitalize the region through tourism by promoting local culture and specialty products, thereby contributing to the development of the local economy.

[0730] A "local monetary system" refers to the local currency and payment methods used by travelers, and is a mechanism that has a direct impact on the local economy.

[0731] The system of this invention aims to optimize the user's travel experience and has a configuration that combines natural language processing technology and sentiment analysis means. Its embodiments are described in detail below.

[0732] First, the user enters their travel preferences and interests into their device. The entered data is analyzed via a natural language processing engine, and based on this analysis, the user's basic needs are understood. Furthermore, the device has a built-in emotion engine that analyzes the tone and selected words from the user's input to infer the user's emotional state. This allows the system to identify emotional needs, such as the user's desire for relaxation.

[0733] The analyzed information is sent to a server via the internet. The server accesses external databases and APIs to collect travel information and then generates a travel plan that best fits the user's needs and preferences. This plan suggests tourist destinations and activities tailored to the user's tastes. For example, a user seeking relaxation might be recommended less crowded hot spring resorts or quiet natural areas.

[0734] Furthermore, during the trip, the server monitors the user's emotional state in real time. It utilizes the user's smartphone app to collect feedback and recognize changes in their emotional state. Based on these changes, the server adjusts the selection of tourist destinations and suggests events in real time. This ensures that users continuously receive a travel experience tailored to their individual emotions and needs.

[0735] To contribute to the revitalization of the local economy, the server promotes local tourist resources and provides information on specialty products and events based on user sentiment. In this way, travelers are delivered attractive local experiences, and a sense of connection with the region is fostered.

[0736] For example, if a user inputs "I want to relax in a quiet place away from the hustle and bustle of the city," the system analyzes this need and suggests places like nature-rich retreats or quiet beaches. Furthermore, if the user provides feedback during their trip indicating a desire to "learn more about the local culture," the system will provide additional information such as traditional festivals or local craft experiences.

[0737] Examples of prompts include: "Please recommend a relaxing travel destination. Conditions: Stress relief, quiet environment" or "Please suggest tourist spots where I can experience the local culture. Interests: Hands-on experiences, traditional festivals."

[0738] This system allows users to enjoy flexible and personalized travel experiences tailored to their emotions and desires. Furthermore, it contributes to local communities through initiatives that utilize local resources.

[0739] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0740] Step 1:

[0741] The user inputs their travel preferences and interests into the device. This input includes specific information such as the travel destination, purpose, duration, budget, and emotional state the user wants to express. The device analyzes this information using natural language processing technology to understand the user's basic needs and emotional state. For example, it might receive input such as, "I want to go to a quiet place with abundant nature." The output obtained here is a list of standardized needs and an estimated emotional state.

[0742] Step 2:

[0743] The terminal sends the analyzed information to the server. The input includes estimated data on the user's needs and emotions. The server retrieves tourist information from external databases and APIs. Specifically, the server aggregates relevant information such as the characteristics of tourist destinations, seasonal information, and recommended activities. The output here is foundational data for travel plans that may suit the user's needs.

[0744] Step 3:

[0745] The server matches collected tourist information with user needs and sentiment data to generate the optimal travel plan. This process utilizes an AI model to generate and output multiple travel plans optimized for the user's conditions. For example, for a user seeking relaxation, it might suggest uncrowded hot spring resorts or quiet nature parks. The output here is a list of specific itineraries and potential destinations.

[0746] Step 4:

[0747] During the trip, the user's emotional state is monitored in real time by the device. The device receives user feedback as input and uses an emotion engine to detect changes in emotion. For example, if the user provides feedback such as "I want to do more active activities," this becomes the input. As output, suggestions for tourist destinations and activities that have been re-selected based on the emotional state are generated.

[0748] Step 5:

[0749] The server leverages local tourism resources to provide personalized information on local products and events based on the user's emotions. This stage includes the integration of local product promotions and a local currency system. Inputs are user emotion data and local promotional information, while output is a suggestion of engaging local experiences for the user.

[0750] In this way, this system uses natural language processing and sentiment analysis, starting with user input, to optimize the travel experience in real time. It can also strengthen relationships with local communities.

[0751] (Application Example 2)

[0752] 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".

[0753] For travelers, creating an optimal travel plan tailored to their individual needs and emotions is a challenging task. Furthermore, systems capable of flexibly responding to unexpected situations during travel are limited. Additionally, mechanisms for receiving real-time suggestions that respond to changing emotions are insufficient. Addressing these challenges is necessary to further personalize the user's travel experience and promote integration between local communities and travelers.

[0754] 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.

[0755] In this invention, the server includes means for receiving user input information and analyzing it using natural language processing technology, means for inferring the user's emotional state using an emotion engine and reflecting that information in the travel plan, and means for monitoring the user's location information and surrounding environment during the trip and dynamically redesigning the route in response to changes in the emotional state. This enables the optimization of the travel plan according to the user's needs and real-time sightseeing suggestions that are appropriate to their emotions.

[0756] "User input information" refers to text data such as travel preferences and interests that travelers enter into their devices.

[0757] "Natural language processing technology" is a technology that allows computers to analyze and understand human language, extracting meaning and intent from user input information.

[0758] An "emotion engine" is a technology that infers an emotional state from the words a user inputs or the conditions they select, and uses that information to process the system.

[0759] A "travel plan" is a plan of itineraries and destinations suggested based on the user's needs and interests.

[0760] "External databases and APIs" refer to external sources of information and interfaces that the system uses to retrieve tourist information and surrounding data.

[0761] "Real-time optimization" means instantly readjusting the travel plan in response to changes in the user's situation and emotions during their trip.

[0762] "Location information" refers to geographical data about the user's current location.

[0763] "Surrounding environment" refers to facilities, natural environments, or conditions that exist in the vicinity of the place the user is visiting.

[0764] "Emotion-responsive tourist information" refers to information about tourist spots and events that are appropriate for the user's emotional state.

[0765] This invention is a system that utilizes an emotion engine to enhance the user's travel experience. This system acquires user input information using devices such as smartphones and smart glasses. When the user inputs their travel wishes and interests, this information is analyzed using natural language processing technology. For the analysis, Python's natural language processing libraries NLTK and spaCy are used. The emotion engine utilizes an API for Sentiment Analysis to infer the user's emotional state from the tone and selection of the input words.

[0766] Based on these analysis results, the server retrieves tourist information from external databases using the Google Places API and other tools. It then optimizes the generated travel plan to match the user's emotions and dynamically redesigns the route in real time based on location information. During this process, cloud database services such as Firebase are used to keep the information instantly up-to-date.

[0767] For example, if a user enters a desire to "relax in a peaceful natural setting," the emotion engine will determine that the user is seeking relaxation and suggest information about quiet nature parks or hot spring resorts. During the trip, if the system detects an emotion such as "I want to avoid crowds today," it will redesign the route to avoid crowds and guide the user to peaceful spots.

[0768] An example of a prompt to input into a generative AI model is: "Design an application that suggests the optimal travel and sightseeing plan based on the user's emotions and interests, and provides a real-time, emotionally resonant experience."

[0769] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0770] Step 1:

[0771] The terminal receives text input from the user regarding their travel preferences and interests. This input information is then analyzed using natural language processing techniques. Specifically, the meaning of words and phrases is extracted using Python libraries such as NLTK and spaCy to identify the user's basic needs. The input for this step is the user's free-form text, and the output is the analyzed keywords and sentences.

[0772] Step 2:

[0773] The device uses an emotion engine to infer the user's emotional state based on the analyzed information, including the tone of voice and selected conditions. Using an API for Sentiment Analysis, it can determine, for example, that the user prioritizes relaxation from an input such as "I want to relax." The input for this step is the analysis results obtained in step 1, and the output is an evaluation of the user's emotional state.

[0774] Step 3:

[0775] The server retrieves tourist information from sources such as the Google Places API based on the user's needs and emotional state. It accesses external databases to collect tourist destinations and events that are suitable for the user. The input for this step is the emotional state and needs output from step 2, and the output is a list of recommended tourist information.

[0776] Step 4:

[0777] The server generates a series of travel plans based on the acquired tourist information. This includes optimizing the order of visits, estimating transportation methods and travel times. A generation AI model is used to create the plan that best matches the individual conditions. The input for this step is the list of tourist information from step 3, and the output is the optimized travel plan.

[0778] Step 5:

[0779] The device monitors the user's location during travel, checking changes in the surrounding environment and the user's emotional state in real time. It dynamically redesigns the route and suggests a new plan based on the emotional changes. A database service such as Firebase is used to enable real-time updates. The input for this step is the current location and the user's emotional state, and the output is the redesigned route or suggestion.

[0780] 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.

[0781] 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.

[0782] 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 robot 414.

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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."

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] The following is further disclosed regarding the embodiments described above.

[0802] (Claim 1)

[0803] A means of receiving user input information and analyzing it using natural language processing technology,

[0804] A means of obtaining information from external databases and APIs to generate travel plans based on analysis results,

[0805] A method for selecting the most suitable travel plan from multiple generated plans based on the user's conditions and optimizing the itinerary in real time,

[0806] A means of monitoring the user's location and surrounding environment during travel, and dynamically redesigning the route as needed,

[0807] A system that includes this.

[0808] (Claim 2)

[0809] The system according to claim 1, which includes means for promoting local tourism resources and contributing to the local economy by utilizing a local currency system.

[0810] (Claim 3)

[0811] The system according to claim 1, comprising means for generating a travel plan by applying an AI model based on user conditions, while taking into account the congestion and weather conditions of the destination.

[0812] "Example 1"

[0813] (Claim 1)

[0814] A means of obtaining user input information and analyzing it using lexical analysis technology,

[0815] A means for obtaining information from external information sources and data acquisition means for creating a travel plan based on the analysis results,

[0816] A means to select the optimal itinerary from multiple generated plans based on the user's requirements and optimize the travel itinerary in real time,

[0817] A means of monitoring the user's location and environmental information during travel and dynamically redesigning the route as needed,

[0818] Providing users with information on local specialties and events in travel destinations is a means of contributing to the local economy.

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, which includes means for generating an itinerary plan by applying artificial intelligence technology while taking into account the congestion and weather conditions of the destination.

[0822] (Claim 3)

[0823] The system according to claim 1, comprising means for presenting a generated itinerary to the user and adjusting the itinerary based on the user's selection.

[0824] "Application Example 1"

[0825] (Claim 1)

[0826] A means of receiving user input information and analyzing it using natural language processing technology,

[0827] A means of obtaining information from external databases and APIs to generate a meal supply plan based on the analysis results,

[0828] A means to select the plan best suited to the user's conditions from multiple generated meal supply plans and optimize the delivery route in real time,

[0829] A means of monitoring the user's location and surrounding environment during delivery, and dynamically redesigning the route as needed,

[0830] A method for selecting the optimal supplier by considering delivery time and congestion status obtained from an external API,

[0831] A system that includes this.

[0832] (Claim 2)

[0833] The system according to claim 1, which includes means for promoting local food resources and contributing to the local economy by utilizing a local currency system.

[0834] (Claim 3)

[0835] The system according to claim 1, comprising means for generating a meal supply plan by applying an AI model based on user conditions, while taking into account the congestion status of the supplier and delivery time.

[0836] "Example 2 of combining an emotion engine"

[0837] (Claim 1)

[0838] A means of receiving user input information and analyzing it using natural language processing technology,

[0839] A means of sentiment analysis that infers the user's emotional state from the analyzed information,

[0840] A means of obtaining information from external databases and APIs for generating travel plans based on analysis results and emotional states,

[0841] A method for selecting the most suitable travel plan from multiple generated plans based on the user's conditions and emotions, and optimizing the itinerary in real time,

[0842] A means to monitor the user's emotional state during travel and dynamically adjust the provision of tourist resources and events as needed,

[0843] A system that includes promotional tools to integrate local currency systems in order to contribute to the local economy.

[0844] (Claim 2)

[0845] The system according to claim 1, comprising means for providing personalized local products and event information based on the user's emotional state.

[0846] (Claim 3)

[0847] The system according to claim 1, comprising means for generating a travel plan using an AI model that takes into account the user's conditions and emotions, and reflects the congestion and weather conditions of the destination.

[0848] "Application example 2 when combining with an emotional engine"

[0849] (Claim 1)

[0850] A means of receiving user input information and analyzing it using natural language processing technology,

[0851] A means of obtaining information from external databases and APIs to generate travel plans based on analysis results,

[0852] A method for using an emotion engine to infer the user's emotional state and reflect that information in the travel plan,

[0853] A method for selecting the most suitable travel plan from multiple generated plans based on the user's conditions and optimizing the itinerary in real time,

[0854] A means of monitoring the user's location and surrounding environment during travel, and dynamically redesigning the route in response to changes in their emotional state,

[0855] A means of dynamically guiding tourists with information about tourist destinations that responds to their emotions,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, which includes means for promoting local tourism resources and contributing to the local economy by utilizing a local currency system.

[0859] (Claim 3)

[0860] The system according to claim 1, comprising means for generating a travel plan by applying an AI model based on user conditions, while taking into account the congestion and weather conditions of the destination. [Explanation of symbols]

[0861] 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 of receiving user input information and analyzing it using natural language processing technology, A means of obtaining information from external databases and APIs to generate travel plans based on analysis results, A method for selecting the most suitable travel plan from multiple generated plans based on the user's conditions and optimizing the itinerary in real time, A means of monitoring the user's location and surrounding environment during travel, and dynamically redesigning the route as needed, A system that includes this.

2. The system according to claim 1, which includes means for promoting local tourism resources and contributing to the local economy by utilizing a local currency system.

3. The system according to claim 1, comprising means for generating a travel plan by applying an AI model based on user conditions, while taking into account the congestion and weather conditions of the destination.

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