System

Abstract

An object of a system according to an embodiment is to make it possible to create an optimum itinerary even in a place with which a traveler is unfamiliar and to promptly cope with an accident.SOLUTION: A system according to an embodiment includes an itinerary arrangement unit, a schedule change proposal unit, and an information collection unit. An itinerary preparing part prepares an optimum itinerary based on the desire of a traveler. The schedule change proposal unit proposes an alternative plan at the time of an accident. The information collection unit collects the latest information of the site.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has made it difficult for travelers to create itineraries in unfamiliar locations and to respond in the event of an accident, and it has been difficult to obtain the latest local information in a timely manner.

[0005] The system according to the embodiment aims to enable travelers to create optimal itineraries even in unfamiliar places and to respond quickly in the event of an accident. [Means for solving the problem]

[0006] The system according to the embodiment includes an itinerary creation unit, a plan change suggestion unit, and an information collection unit. The itinerary creation unit creates an optimal itinerary based on the traveler's wishes. The plan change suggestion unit proposes alternative plans in the event of an accident. The information collection unit collects the latest local information. [Effects of the Invention]

[0007] The system according to the embodiment can create an optimal itinerary even in places that are unfamiliar to travelers, and can respond quickly in the event of an accident. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A travel support system according to an embodiment of the present invention is a system that uses AI technology to provide travel support for travelers and travel agencies. This system provides support for first-time travelers in unfamiliar places and activities, and provides travel agencies with immediate support for travel destinations around the world. As a result, the travel support system allows travelers to enjoy their trips with peace of mind, even when traveling to a destination for the first time, and allows travel agencies to respond quickly and accurately to customer needs.

[0029] A travel support system according to an embodiment includes an itinerary creation unit, a plan change suggestion unit, and an information collection unit. The itinerary creation unit creates an optimal itinerary based on a traveler's preferences. For example, if a traveler inputs a request such as "I want to enjoy visiting art museums and cafes on my first trip to Paris," the itinerary creation unit will propose an itinerary that includes the Louvre, the Musee d'Orsay, and popular local cafes based on the request. The plan change suggestion unit proposes alternative plans in the event of an emergency. For example, if a planned tourist attraction is suddenly closed, the plan change suggestion unit will suggest other nearby tourist attractions or activities. The information collection unit collects the latest local information. For example, it obtains local event information, traffic conditions, weather forecasts, etc. in real time and notifies the traveler. This allows the travel support system according to an embodiment to create an optimal itinerary based on a traveler's preferences and quickly respond to emergencies.

[0030] The itinerary creation unit can analyze a traveler's past travel history or social media posts to generate a customized itinerary based on individual preferences. For example, the itinerary creation unit analyzes a traveler's past travel history to collect data on places visited and activities participated in. For example, the itinerary creation unit identifies the traveler's preferences based on information about cities visited in the past and tours participated in, and proposes a new itinerary based on the traveler's preferences. The itinerary creation unit also analyzes social media posts to identify places and activities in which the traveler is interested. For example, it analyzes photos and comments posted by the traveler on Instagram to generate an itinerary that includes the traveler's favorite tourist spots and restaurants. The itinerary creation unit also analyzes the traveler's online reviews and ratings to create a customized itinerary based on places and activities that the traveler has previously rated highly. For example, it incorporates restaurants and hotels that the traveler has previously rated highly into the new itinerary. This makes it possible to provide a customized itinerary based on the traveler's preferences.

[0031] The itinerary creation unit can propose a reasonable itinerary based on the traveler's health condition or physical fitness level. For example, the itinerary creation unit allows the traveler to input their health condition in advance and proposes a reasonable itinerary based on that information. For example, for a traveler with heart disease, the itinerary creation unit proposes tourist spots that avoid excessive exercise. The itinerary creation unit also considers the traveler's physical fitness level and creates an itinerary that optimizes walking distance and travel time. For example, for elderly people or travelers with children, the itinerary creation unit proposes tourist spots that can be enjoyed within a short travel distance. The itinerary creation unit also builds a system that monitors the traveler's health data in real time and adjusts the itinerary according to their physical fitness. For example, if their physical fitness worsens during the trip, the itinerary creation unit makes adjustments such as increasing rest time. This makes it possible to provide a reasonable itinerary that suits the traveler's health condition and physical fitness level.

[0032] The plan change suggestion unit can analyze the traveler's current location or surrounding conditions in real time and propose optimal alternatives. For example, the plan change suggestion unit identifies the traveler's current location using GPS and analyzes nearby tourist attractions and activities in real time. For example, if a planned tourist spot is closed, it proposes another nearby tourist spot. The plan change suggestion unit also obtains surrounding traffic and weather information in real time and proposes optimal alternatives. For example, if traffic congestion or bad weather is expected, it proposes an alternative route or indoor activities. The plan change suggestion unit also analyzes the traveler's current location and information on nearby restaurants and cafes to propose optimal dining spots in the event of a sudden change in plans. For example, if the planned restaurant is fully booked, it proposes another nearby restaurant. This makes it possible to provide optimal alternatives based on the traveler's current location and surrounding conditions.

[0033] The plan change suggestion unit can automatically refer to the traveler's insurance information or emergency contact information and quickly provide the necessary support. For example, the plan change suggestion unit registers the traveler's insurance information in advance and builds a system that automatically references it when an accident occurs. For example, if a traveler is injured, the system suggests the nearest hospital based on the insurance information. The plan change suggestion unit also develops a system that registers emergency contact information in advance and automatically notifies the emergency contact when an accident occurs. For example, if a traveler gets lost, the system sends location information to the emergency contact. The plan change suggestion unit also builds a system that quickly provides the necessary support based on the traveler's insurance information. For example, if a traveler is robbed, the system automatically contacts the insurance company and processes the procedure for receiving support. This allows support to be provided quickly based on the traveler's insurance information and emergency contact information.

[0034] The information collection unit can analyze local social media or blogs to collect the latest word-of-mouth information. For example, the information collection unit analyzes local social media posts in real time to collect the latest word-of-mouth information. For example, it collects the latest ratings and comments about local restaurants and tourist attractions. The information collection unit also analyzes local blog posts to extract information useful to travelers. For example, it collects the latest blog posts about local event information and recommended spots. The information collection unit also builds a system that provides travelers with the latest word-of-mouth information based on data from local social media and blogs. For example, it notifies travelers of the latest word-of-mouth information about places they plan to visit. This allows the latest local word-of-mouth information to be collected and provided to travelers.

[0035] The information collection unit can collect real-time feedback from local residents or travelers and update the information. For example, the information collection unit builds a system that collects real-time feedback from local residents and travelers. For example, it collects the latest ratings and comments on local tourist attractions and restaurants. The information collection unit also provides a platform that allows travelers to share information they have obtained locally in real time. For example, it develops an app that allows travelers to post the latest information on places they have visited. The information collection unit also builds a system that updates information in real time based on feedback from local residents and travelers. For example, it updates local event information and traffic conditions based on the latest feedback. This makes it possible to collect real-time feedback from local residents and travelers and update the information.

[0036] The information collection unit can analyze a customer's past travel history or feedback and provide information that best suits individual needs. For example, the information collection unit analyzes a customer's past travel history and collects data on places visited and activities participated in. For example, information that best suits the customer's needs is provided based on information on cities visited in the past and tours participated in. The information collection unit also analyzes customer feedback and provides information based on places and activities that have been highly rated in the past. For example, it provides the latest information on restaurants and hotels that have been highly rated by customers. The information collection unit also builds a system that provides information that best suits individual needs based on the customer's travel history and feedback. For example, it provides information on restaurants and tourist spots that match the customer's preferences. This makes it possible to provide the best information based on the customer's past travel history and feedback.

[0037] The information collection unit can suggest appropriate restaurants and activities based on the customer's health condition or dietary restrictions. For example, the information collection unit has the customer input their health condition in advance and suggests appropriate restaurants and activities based on that information. For example, for a customer with allergies, it suggests restaurants that do not contain allergens. The information collection unit also builds a system that suggests appropriate restaurants taking into account the customer's dietary restrictions. For example, it suggests restaurants that offer vegetarian or gluten-free menus. The information collection unit also develops a system that suggests reasonable activities based on the customer's health data. For example, for a customer with heart disease, it suggests tourist spots that avoid excessive exercise. This makes it possible to suggest appropriate restaurants and activities based on the customer's health condition and dietary restrictions.

[0038] The information collection unit can analyze past customer feedback and customize the content of the guided tour. For example, the information collection unit analyzes past customer feedback and customizes the content of the guided tour based on the content of guided tours that have received particularly high ratings. For example, the information collection unit creates a guided tour focusing on tourist spots and activities that customers have previously given high ratings. The information collection unit also builds a system that improves the content of the guided tour based on customer feedback. For example, it corrects problems pointed out in past feedback and provides a more understandable guided tour. The information collection unit also analyzes past customer feedback in real time and dynamically customizes the content of the guided tour. For example, it adjusts the content of the guided tour according to the customer's interests and concerns. This makes it possible to customize the content of the guided tour based on past customer feedback.

[0039] The information collection unit can provide detailed guidebooks and video tours based on the customer's interests. For example, the information collection unit allows the customer to input their interests in advance and provides a detailed guidebook based on that information. For example, a customer who is interested in history can be provided with a guidebook that introduces historical tourist spots in detail. The information collection unit also builds a system that creates and provides video tours based on the customer's interests. For example, a customer who loves nature can be provided with a video tour that introduces beautiful scenery. The information collection unit also analyzes the customer's interests in real time and dynamically customizes the content of the guidebook or video tour. For example, if a customer shows interest in a particular tourist spot, detailed information about that spot can be provided. This makes it possible to provide detailed guidebooks and video tours based on the customer's interests.

[0040] The information gathering unit can provide a detailed guide on the local language or culture to help the customer communicate smoothly. The information gathering unit, for example, builds a system that provides a detailed guide on the local language and culture. For example, it provides a guide introducing basic greetings, phrases, and cultural manners. The information gathering unit also provides a language guide in real time to help customers communicate smoothly locally. For example, it uses a chatbot to support conversations in the local language. The information gathering unit also provides information on local culture and customs to help customers communicate smoothly locally. For example, it provides a guide introducing local dining etiquette and how to greet people. This helps customers communicate smoothly through a detailed guide on the local language and culture.

[0041] The information gathering unit can analyze a customer's past communication history and suggest the optimal communication method. For example, the information gathering unit builds a system that analyzes a customer's past communication history and suggests the optimal communication method. For example, it suggests a communication method suitable for the customer based on data on phrases and languages ​​used in the past. The information gathering unit also develops a system that supports conversations on site based on the customer's communication history. For example, it provides a chatbot that automatically suggests phrases used in the past. The information gathering unit also provides advice to make communication on site smoother based on the customer's past communication data. For example, it suggests appropriate phrases and ways to deal with situations that have been difficult in the past. This makes it possible to suggest the optimal communication method based on the customer's past communication history.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The travel support system can further include a translation unit. The translation unit provides real-time translation when a traveler communicates in the local language. For example, when a traveler orders at a local restaurant, the translation unit can translate the menu contents to accurately convey the traveler's desired dish. The translation unit can also suggest phrases to help travelers have smooth conversations with local people. For example, when a traveler asks for directions, the translation unit can provide appropriate phrases to facilitate communication with local people. Furthermore, the translation unit can also support travelers in understanding information about local culture and customs. For example, when a traveler participates in a local festival or event, the translation unit can explain the background and meaning of the event, allowing the traveler to enjoy the local culture more deeply. This allows travelers to communicate with local people without feeling a language barrier.

[0044] The travel support system can further include a safety confirmation unit. The safety confirmation unit provides real-time safety information for places that travelers plan to visit. For example, if demonstrations or riots are occurring in a city that a traveler plans to visit, the unit will immediately notify the traveler of this information and suggest alternative tourist destinations to the traveler. The safety confirmation unit can also evaluate the safety of hotels and accommodations where travelers will be staying and suggest safe places to stay. For example, if there are many crimes occurring around the hotel that a traveler has booked, the unit can suggest a hotel in a safer area. Furthermore, if a traveler encounters an emergency, the safety confirmation unit can provide information on the nearest police station or hospital to help them respond quickly. This allows travelers to enjoy their trip with peace of mind.

[0045] The travel support system can further include an entertainment suggestion unit. The entertainment suggestion unit provides local entertainment information based on the traveler's interests and preferences. For example, if the traveler is a music lover, the entertainment suggestion unit can suggest information about local live music venues and concerts. Also, if the traveler is a movie lover, the entertainment suggestion unit can provide information about local movie theaters and movies currently showing. Furthermore, the entertainment suggestion unit can also provide information about local events and festivals that the traveler can participate in. For example, the entertainment suggestion unit can notify the traveler of information about music festivals and art exhibitions being held in cities the traveler is visiting and encourage them to participate. This allows the traveler to enjoy local entertainment to the fullest.

[0046] The travel support system can further include an ecotourism suggestion unit. The ecotourism suggestion unit suggests environmentally friendly sightseeing plans to travelers. For example, it suggests environmentally friendly means of transportation and accommodation when travelers visit nature reserves or eco-parks. The ecotourism suggestion unit can also provide information on environmental conservation activities and volunteer activities in which travelers can participate. For example, it can provide opportunities for travelers to participate in beach cleanups or tree planting activities. Furthermore, the ecotourism suggestion unit can also provide information on restaurants where travelers can enjoy environmentally friendly meals. For example, it can suggest restaurants that use organic ingredients or restaurants that serve local ingredients. This allows travelers to enjoy environmentally friendly travel.

[0047] The travel support system may further include a cultural experience suggestion unit. The cultural experience suggestion unit suggests plans that allow travelers to experience local culture and traditions. For example, the cultural experience suggestion unit may offer travelers opportunities to participate in cooking classes where they can learn traditional local cuisine or workshops where they can make local crafts. The cultural experience suggestion unit may also provide travelers with information on local festivals and events. For example, the cultural experience suggestion unit may notify travelers of information about traditional festivals and music events held in cities they are visiting and encourage them to participate. The cultural experience suggestion unit may also suggest guided tours that allow travelers to learn about local history and culture. For example, the cultural experience suggestion unit may offer tours led by professional guides when travelers visit historical buildings and museums. This allows travelers to gain a deeper understanding of and experience local culture and traditions.

[0048] The travel support system can further include a health management unit. The health management unit monitors the traveler's health condition and provides appropriate advice. For example, if a traveler becomes tired after a long flight or travel, it can suggest stretching or light exercise. The health management unit can also provide advice on diet and hydration to help travelers maintain their health while they are traveling. For example, it can suggest ways for travelers to eat and hydrate that are appropriate for the local climate. Furthermore, if a traveler becomes ill, the health management unit can provide information on the nearest medical institution and support them in responding quickly. This allows travelers to maintain their health and enjoy their trip with peace of mind.

[0049] The processing flow of the first embodiment will be briefly explained below.

[0050] Step 1: The itinerary creation unit creates an optimal itinerary based on the traveler's preferences. For example, if a traveler inputs a preference such as "I would like to enjoy visiting museums and cafes on my first trip to Paris," the itinerary creation unit will suggest an itinerary that includes the Louvre, the Musee d'Orsay, and popular local cafes. Step 2: The schedule change suggestion unit proposes alternative plans in the event of an accident. For example, if a planned tourist spot is suddenly closed, the schedule change suggestion unit will suggest other nearby tourist spots or activities. Step 3: The information gathering unit collects the latest local information, such as local event information, traffic conditions, and weather forecasts, in real time and notifies the traveler.

[0051] (Example 2) A travel support system according to an embodiment of the present invention is a system that uses AI technology to provide travel support for travelers and travel agencies. This system provides support for first-time travelers in unfamiliar places and activities, and provides travel agencies with immediate support for travel destinations around the world. As a result, the travel support system allows travelers to enjoy their trips with peace of mind, even when traveling to a destination for the first time, and allows travel agencies to respond quickly and accurately to customer needs.

[0052] A travel support system according to an embodiment includes an itinerary creation unit, a plan change suggestion unit, and an information collection unit. The itinerary creation unit creates an optimal itinerary based on a traveler's preferences. For example, if a traveler inputs a request such as "I want to enjoy visiting art museums and cafes on my first trip to Paris," the itinerary creation unit will propose an itinerary that includes the Louvre, the Musee d'Orsay, and popular local cafes based on the request. The plan change suggestion unit proposes alternative plans in the event of an emergency. For example, if a planned tourist attraction is suddenly closed, the plan change suggestion unit will suggest other nearby tourist attractions or activities. The information collection unit collects the latest local information. For example, it obtains local event information, traffic conditions, weather forecasts, etc. in real time and notifies the traveler. This allows the travel support system according to an embodiment to create an optimal itinerary based on a traveler's preferences and quickly respond to emergencies.

[0053] The itinerary creation unit can analyze a traveler's past travel history or social media posts to generate a customized itinerary based on individual preferences. For example, the itinerary creation unit analyzes a traveler's past travel history to collect data on places visited and activities participated in. For example, the itinerary creation unit identifies the traveler's preferences based on information about cities visited in the past and tours participated in, and proposes a new itinerary based on the traveler's preferences. The itinerary creation unit also analyzes social media posts to identify places and activities in which the traveler is interested. For example, it analyzes photos and comments posted by the traveler on Instagram to generate an itinerary that includes the traveler's favorite tourist spots and restaurants. The itinerary creation unit also analyzes the traveler's online reviews and ratings to create a customized itinerary based on places and activities that the traveler has previously rated highly. For example, it incorporates restaurants and hotels that the traveler has previously rated highly into the new itinerary. This makes it possible to provide a customized itinerary based on the traveler's preferences.

[0054] The itinerary creation unit can propose a reasonable itinerary based on the traveler's health condition or physical fitness level. For example, the itinerary creation unit allows the traveler to input their health condition in advance and proposes a reasonable itinerary based on that information. For example, for a traveler with heart disease, the itinerary creation unit proposes tourist spots that avoid excessive exercise. The itinerary creation unit also considers the traveler's physical fitness level and creates an itinerary that optimizes walking distance and travel time. For example, for elderly people or travelers with children, the itinerary creation unit proposes tourist spots that can be enjoyed within a short travel distance. The itinerary creation unit also builds a system that monitors the traveler's health data in real time and adjusts the itinerary according to their physical fitness. For example, if their physical fitness worsens during the trip, the itinerary creation unit makes adjustments such as increasing rest time. This makes it possible to provide a reasonable itinerary that suits the traveler's health condition and physical fitness level.

[0055] The itinerary creation unit can use the emotion estimation function to analyze the traveler's current emotional state and suggest an itinerary that includes relaxing spots or activities. The itinerary creation unit, for example, analyzes the traveler's emotional state in real time and suggests relaxing spots. For example, if the traveler is feeling stressed, it suggests an itinerary that includes quiet parks and spas. The itinerary creation unit also uses the emotion estimation function to suggest activities that the traveler can enjoy. For example, if the traveler is excited, it suggests an itinerary that includes adventure sports and entertainment facilities. The itinerary creation unit also suggests relaxing restaurants and cafes based on the traveler's emotional data. For example, if the traveler is tired, it suggests an itinerary that includes a cafe with a quiet and calm atmosphere. This makes it possible to provide a relaxing itinerary that suits the traveler's emotional state.

[0056] The plan change suggestion unit can analyze the traveler's current location or surrounding conditions in real time and propose optimal alternatives. For example, the plan change suggestion unit identifies the traveler's current location using GPS and analyzes nearby tourist attractions and activities in real time. For example, if a planned tourist spot is closed, it proposes another nearby tourist spot. The plan change suggestion unit also obtains surrounding traffic and weather information in real time and proposes optimal alternatives. For example, if traffic congestion or bad weather is expected, it proposes an alternative route or indoor activities. The plan change suggestion unit also analyzes the traveler's current location and information on nearby restaurants and cafes to propose optimal dining spots in the event of a sudden change in plans. For example, if the planned restaurant is fully booked, it proposes another nearby restaurant. This makes it possible to provide optimal alternatives based on the traveler's current location and surrounding conditions.

[0057] The plan change suggestion unit can automatically refer to the traveler's insurance information or emergency contact information and quickly provide the necessary support. For example, the plan change suggestion unit registers the traveler's insurance information in advance and builds a system that automatically references it when an accident occurs. For example, if a traveler is injured, the system suggests the nearest hospital based on the insurance information. The plan change suggestion unit also develops a system that registers emergency contact information in advance and automatically notifies the emergency contact when an accident occurs. For example, if a traveler gets lost, the system sends location information to the emergency contact. The plan change suggestion unit also builds a system that quickly provides the necessary support based on the traveler's insurance information. For example, if a traveler is robbed, the system automatically contacts the insurance company and processes the procedure for receiving support. This allows support to be provided quickly based on the traveler's insurance information and emergency contact information.

[0058] The plan change suggestion unit can use the emotion estimation function to analyze the stress level of the traveler and suggest alternative plans that will help them relax. The plan change suggestion unit, for example, uses the emotion estimation function to analyze the stress level of the traveler in real time. For example, if the traveler is feeling stressed, it suggests a cafe or park where they can relax. The plan change suggestion unit also suggests activities that can reduce stress based on the traveler's emotion data. For example, if the traveler is nervous, it suggests a relaxing massage or spa. The plan change suggestion unit also uses the emotion estimation function to suggest alternative plans in real time based on the traveler's stress level. For example, if the traveler is tired, it makes adjustments such as increasing break times. This makes it possible to provide alternative plans that will help them relax based on the traveler's stress level.

[0059] The information collection unit can analyze local social media or blogs to collect the latest word-of-mouth information. For example, the information collection unit analyzes local social media posts in real time to collect the latest word-of-mouth information. For example, it collects the latest ratings and comments about local restaurants and tourist attractions. The information collection unit also analyzes local blog posts to extract information useful to travelers. For example, it collects the latest blog posts about local event information and recommended spots. The information collection unit also builds a system that provides travelers with the latest word-of-mouth information based on data from local social media and blogs. For example, it notifies travelers of the latest word-of-mouth information about places they plan to visit. This allows the latest local word-of-mouth information to be collected and provided to travelers.

[0060] The information collection unit can collect real-time feedback from local residents or travelers and update the information. For example, the information collection unit builds a system that collects real-time feedback from local residents and travelers. For example, it collects the latest ratings and comments on local tourist attractions and restaurants. The information collection unit also provides a platform that allows travelers to share information they have obtained locally in real time. For example, it develops an app that allows travelers to post the latest information on places they have visited. The information collection unit also builds a system that updates information in real time based on feedback from local residents and travelers. For example, it updates local event information and traffic conditions based on the latest feedback. This makes it possible to collect real-time feedback from local residents and travelers and update the information.

[0061] The information collection unit can use the emotion estimation function to analyze the popularity of local events or activities and notify travelers. The information collection unit, for example, uses the emotion estimation function to analyze the popularity of local events and activities. For example, popular events and activities are identified based on the emotion scores of social media posts and blog articles. The information collection unit also builds a system that collects emotion data related to local events and activities and notifies travelers. For example, events and activities with high emotion scores are notified in real time. The information collection unit also uses the emotion estimation function to analyze the popularity of local events and activities and propose an optimal plan to travelers. For example, an itinerary including events with high emotion scores is proposed. This allows the popularity of local events and activities to be analyzed and notified to travelers.

[0062] The information collection unit can analyze a customer's past travel history or feedback and provide information that best suits individual needs. For example, the information collection unit analyzes a customer's past travel history and collects data on places visited and activities participated in. For example, information that best suits the customer's needs is provided based on information on cities visited in the past and tours participated in. The information collection unit also analyzes customer feedback and provides information based on places and activities that have been highly rated in the past. For example, it provides the latest information on restaurants and hotels that have been highly rated by customers. The information collection unit also builds a system that provides information that best suits individual needs based on the customer's travel history and feedback. For example, it provides information on restaurants and tourist spots that match the customer's preferences. This makes it possible to provide the best information based on the customer's past travel history and feedback.

[0063] The information collection unit can suggest appropriate restaurants and activities based on the customer's health condition or dietary restrictions. For example, the information collection unit has the customer input their health condition in advance and suggests appropriate restaurants and activities based on that information. For example, for a customer with allergies, it suggests restaurants that do not contain allergens. The information collection unit also builds a system that suggests appropriate restaurants taking into account the customer's dietary restrictions. For example, it suggests restaurants that offer vegetarian or gluten-free menus. The information collection unit also develops a system that suggests reasonable activities based on the customer's health data. For example, for a customer with heart disease, it suggests tourist spots that avoid excessive exercise. This makes it possible to suggest appropriate restaurants and activities based on the customer's health condition and dietary restrictions.

[0064] The information collection unit can use the emotion estimation function to analyze the customer's current emotional state and suggest relaxing spots or activities. The information collection unit, for example, uses the emotion estimation function to analyze the customer's emotional state in real time and suggest relaxing spots. For example, if the customer is feeling stressed, it can suggest a quiet park or spa. The information collection unit also suggests relaxing restaurants or cafes based on the customer's emotional data. For example, if the customer is tired, it can suggest a cafe with a quiet and calm atmosphere. The information collection unit also uses the emotion estimation function to suggest activities that the customer can enjoy. For example, if the customer is excited, it can suggest adventure sports or entertainment facilities. This makes it possible to suggest relaxing spots and activities according to the customer's emotional state.

[0065] The information collection unit can analyze past customer feedback and customize the content of the guided tour. For example, the information collection unit analyzes past customer feedback and customizes the content of the guided tour based on the content of guided tours that have received particularly high ratings. For example, the information collection unit creates a guided tour focusing on tourist spots and activities that customers have previously given high ratings. The information collection unit also builds a system that improves the content of the guided tour based on customer feedback. For example, it corrects problems pointed out in past feedback and provides a more understandable guided tour. The information collection unit also analyzes past customer feedback in real time and dynamically customizes the content of the guided tour. For example, it adjusts the content of the guided tour according to the customer's interests and concerns. This makes it possible to customize the content of the guided tour based on past customer feedback.

[0066] The information collection unit can provide detailed guidebooks and video tours based on the customer's interests. For example, the information collection unit allows the customer to input their interests in advance and provides a detailed guidebook based on that information. For example, a customer who is interested in history can be provided with a guidebook that introduces historical tourist spots in detail. The information collection unit also builds a system that creates and provides video tours based on the customer's interests. For example, a customer who loves nature can be provided with a video tour that introduces beautiful scenery. The information collection unit also analyzes the customer's interests in real time and dynamically customizes the content of the guidebook or video tour. For example, if a customer shows interest in a particular tourist spot, detailed information about that spot can be provided. This makes it possible to provide detailed guidebooks and video tours based on the customer's interests.

[0067] The information collection unit can use the emotion estimation function to analyze the customer's current emotional state and suggest relaxing spots or activities. The information collection unit, for example, uses the emotion estimation function to analyze the customer's emotional state in real time and suggest relaxing spots. For example, if the customer is feeling stressed, it can suggest a quiet park or spa. The information collection unit also suggests relaxing restaurants or cafes based on the customer's emotional data. For example, if the customer is tired, it can suggest a cafe with a quiet and calm atmosphere. The information collection unit also uses the emotion estimation function to suggest activities that the customer can enjoy. For example, if the customer is excited, it can suggest adventure sports or entertainment facilities. This makes it possible to suggest relaxing spots and activities according to the customer's emotional state.

[0068] The information gathering unit can provide a detailed guide on the local language or culture to help the customer communicate smoothly. The information gathering unit, for example, builds a system that provides a detailed guide on the local language and culture. For example, it provides a guide introducing basic greetings, phrases, and cultural manners. The information gathering unit also provides a language guide in real time to help customers communicate smoothly locally. For example, it uses a chatbot to support conversations in the local language. The information gathering unit also provides information on local culture and customs to help customers communicate smoothly locally. For example, it provides a guide introducing local dining etiquette and how to greet people. This helps customers communicate smoothly through a detailed guide on the local language and culture.

[0069] The information gathering unit can analyze a customer's past communication history and suggest the optimal communication method. For example, the information gathering unit builds a system that analyzes a customer's past communication history and suggests the optimal communication method. For example, it suggests a communication method suitable for the customer based on data on phrases and languages ​​used in the past. The information gathering unit also develops a system that supports conversations on site based on the customer's communication history. For example, it provides a chatbot that automatically suggests phrases used in the past. The information gathering unit also provides advice to make communication on site smoother based on the customer's past communication data. For example, it suggests appropriate phrases and ways to deal with situations that have been difficult in the past. This makes it possible to suggest the optimal communication method based on the customer's past communication history.

[0070] The information collection unit can use the emotion estimation function to analyze the customer's current emotional state and suggest a communication method that will help them relax. The information collection unit, for example, uses the emotion estimation function to analyze the customer's emotional state in real time and suggest a communication method that will help them relax. For example, if the customer is nervous, the information collection unit suggests phrases or topics that will help them relax. The information collection unit also provides advice to make communication on-site smoother based on the customer's emotional data. For example, if the customer is feeling stressed, the information collection unit suggests ways to conduct the conversation in a way that will help them relax. The information collection unit also uses the emotion estimation function to build a system that suggests communication methods that will help customers relax in real time. For example, the information collection unit suggests appropriate phrases and topics depending on the customer's emotional state. This makes it possible to suggest a communication method that will help them relax depending on the customer's emotional state.

[0071] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0072] The travel support system can further include a translation unit. The translation unit provides real-time translation when a traveler communicates in the local language. For example, when a traveler orders at a local restaurant, the translation unit can translate the menu contents to accurately convey the traveler's desired dish. The translation unit can also suggest phrases to help travelers have smooth conversations with local people. For example, when a traveler asks for directions, the translation unit can provide appropriate phrases to facilitate communication with local people. Furthermore, the translation unit can also support travelers in understanding information about local culture and customs. For example, when a traveler participates in a local festival or event, the translation unit can explain the background and meaning of the event, allowing the traveler to enjoy the local culture more deeply. This allows travelers to communicate with local people without feeling a language barrier.

[0073] The travel support system can further include a safety confirmation unit. The safety confirmation unit provides real-time safety information for places that travelers plan to visit. For example, if demonstrations or riots are occurring in a city that a traveler plans to visit, the unit will immediately notify the traveler of this information and suggest alternative tourist destinations to the traveler. The safety confirmation unit can also evaluate the safety of hotels and accommodations where travelers will be staying and suggest safe places to stay. For example, if there are many crimes occurring around the hotel that a traveler has booked, the unit can suggest a hotel in a safer area. Furthermore, if a traveler encounters an emergency, the safety confirmation unit can provide information on the nearest police station or hospital to help them respond quickly. This allows travelers to enjoy their trip with peace of mind.

[0074] The travel support system can further include an entertainment suggestion unit. The entertainment suggestion unit provides local entertainment information based on the traveler's interests and preferences. For example, if the traveler is a music lover, the entertainment suggestion unit can suggest information about local live music venues and concerts. Also, if the traveler is a movie lover, the entertainment suggestion unit can provide information about local movie theaters and movies currently showing. Furthermore, the entertainment suggestion unit can also provide information about local events and festivals that the traveler can participate in. For example, the entertainment suggestion unit can notify the traveler of information about music festivals and art exhibitions being held in cities the traveler is visiting and encourage them to participate. This allows the traveler to enjoy local entertainment to the fullest.

[0075] The travel support system can further use the emotion estimation function to suggest relaxing accommodations based on the traveler's emotional state. For example, if the traveler is feeling stressed, hotels and resorts with a quiet and calm atmosphere can be suggested. Also, if the traveler is tired, accommodations that offer spa or massage services can be suggested. Furthermore, the emotion estimation function can also be used to suggest room types and amenities that will help the traveler relax. For example, if the traveler wants to relax, spacious rooms or rooms with balconies can be suggested. This allows the traveler to choose the optimal accommodations according to their emotional state.

[0076] The travel support system can also use its emotion estimation function to suggest the optimal means of transportation based on the traveler's emotional state. For example, if a traveler is tired, it can suggest comfortable means of transportation such as a taxi or rental car. If a traveler wants to relax, it can also suggest train or bus routes with enjoyable scenery. Furthermore, if a traveler is feeling stressed, it can also use the emotion estimation function to suggest travel times and routes that will avoid crowds. For example, if a traveler wants to avoid crowds, it can suggest traveling early in the morning or late at night. This allows travelers to choose the optimal means of transportation according to their emotional state.

[0077] The travel support system can further use the emotion estimation function to suggest optimal meal plans based on the traveler's emotional state. For example, if a traveler is feeling stressed, restaurants or cafes with a relaxing atmosphere can be suggested. Also, if a traveler is excited, lively restaurants or bars can be suggested. Furthermore, if a traveler is tired, the emotion estimation function can also suggest restaurants that serve nutritionally balanced meals. For example, if a traveler wants to relax, restaurants that serve healthy menus can be suggested. This allows travelers to choose the optimal meal plan according to their emotional state.

[0078] The travel support system can also use the emotion estimation function to suggest optimal sightseeing routes based on the traveler's emotional state. For example, if a traveler wants to relax, it can suggest a route that takes them on a walk through a quiet park or nature. If the traveler is excited, it can also suggest a route that includes active activities and tourist spots. Furthermore, if a traveler is feeling stressed, it can also use the emotion estimation function to suggest sightseeing routes that avoid crowds. For example, if a traveler wants to avoid crowds, it can suggest sightseeing in the early morning or evening. This allows travelers to choose the optimal sightseeing route according to their emotional state.

[0079] The travel support system can further include an ecotourism suggestion unit. The ecotourism suggestion unit suggests environmentally friendly sightseeing plans to travelers. For example, it suggests environmentally friendly means of transportation and accommodation when travelers visit nature reserves or eco-parks. The ecotourism suggestion unit can also provide information on environmental conservation activities and volunteer activities in which travelers can participate. For example, it can provide opportunities for travelers to participate in beach cleanups or tree planting activities. Furthermore, the ecotourism suggestion unit can also provide information on restaurants where travelers can enjoy environmentally friendly meals. For example, it can suggest restaurants that use organic ingredients or restaurants that serve local ingredients. This allows travelers to enjoy environmentally friendly travel.

[0080] The travel support system may further include a cultural experience suggestion unit. The cultural experience suggestion unit suggests plans that allow travelers to experience local culture and traditions. For example, the cultural experience suggestion unit may offer travelers opportunities to participate in cooking classes where they can learn traditional local cuisine or workshops where they can make local crafts. The cultural experience suggestion unit may also provide travelers with information on local festivals and events. For example, the cultural experience suggestion unit may notify travelers of information about traditional festivals and music events held in cities they are visiting and encourage them to participate. The cultural experience suggestion unit may also suggest guided tours that allow travelers to learn about local history and culture. For example, the cultural experience suggestion unit may offer tours led by professional guides when travelers visit historical buildings and museums. This allows travelers to gain a deeper understanding of and experience local culture and traditions.

[0081] The travel support system can further include a health management unit. The health management unit monitors the traveler's health condition and provides appropriate advice. For example, if a traveler becomes tired after a long flight or travel, it can suggest stretching or light exercise. The health management unit can also provide advice on diet and hydration to help travelers maintain their health while they are traveling. For example, it can suggest ways for travelers to eat and hydrate that are appropriate for the local climate. Furthermore, if a traveler becomes ill, the health management unit can provide information on the nearest medical institution and support them in responding quickly. This allows travelers to maintain their health and enjoy their trip with peace of mind.

[0082] The processing flow of the second embodiment will be briefly explained below.

[0083] Step 1: The itinerary creation unit creates an optimal itinerary based on the traveler's preferences. For example, if a traveler inputs a preference such as "I would like to enjoy visiting museums and cafes on my first trip to Paris," the itinerary creation unit will suggest an itinerary that includes the Louvre, the Musee d'Orsay, and popular local cafes. Step 2: The schedule change suggestion unit proposes alternative plans in the event of an accident. For example, if a planned tourist spot is suddenly closed, the schedule change suggestion unit will suggest other nearby tourist spots or activities. Step 3: The information gathering unit collects the latest local information, such as local event information, traffic conditions, and weather forecasts, in real time and notifies the traveler.

[0084] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0085] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0086] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0087] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0088] 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.

[0089] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0090] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0091] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0092] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0093] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0094] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0095] 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.

[0096] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0097] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0098] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0099] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0100] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0101] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0102] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0103] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0104] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0105] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0106] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0107] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0108] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0109] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0110] 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.

[0111] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0112] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0113] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0114] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0115] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0116] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0117] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0118] 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.

[0119] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0120] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0121] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0122] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0123] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0124] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0125] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0126] 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.

[0127] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0128] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0129] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0130] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0131] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0132] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0133] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0134] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0135] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0136] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0137] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0138] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0139] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0140] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0141] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0142] 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.

[0143] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0144] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0145] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0146] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0147] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0148] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0149] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0150] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0151] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an itinerary creation unit that creates an optimal itinerary based on the traveler's wishes; A schedule change proposal department that proposes alternative plans in the event of an accident; An information gathering unit that collects the latest local information. A system characterized by:

2. The itinerary creation unit Analyzing the traveler's past travel history or social media posts to generate a customized itinerary based on individual preferences The system of claim 1 .

3. The itinerary creation unit Propose a reasonable itinerary based on the traveler's health condition or physical fitness level The system of claim 1 .

4. The itinerary creation unit Analyzing the traveler's current emotional state and suggesting an itinerary that includes relaxing spots or activities The system of claim 1 .

5. The schedule change proposal unit Analyzing the traveler's current location or surrounding conditions in real time and proposing optimal alternatives The system of claim 1 .

6. The schedule change proposal unit Automatically look up the traveler's insurance information or emergency contact information to provide the necessary assistance quickly The system of claim 1 .

7. The schedule change proposal unit Analyze the traveler's stress level and suggest relaxing alternatives The system of claim 1 .

8. The information collecting unit Analyze local social media or blogs to gather the latest reviews The system of claim 1 .

Images