system

Abstract

An object of the system according to the embodiment is to make a proposal related to an activity on site, selection of a restaurant, and purchase from a travel plan in an integrated manner.SOLUTION: A system according to an embodiment includes a QR code generation unit, a movement proposal unit, an activity proposal unit, a food and drink proposal unit, and a purchase proposal unit. The QR code generation unit generates a QR code. The movement proposal unit makes a proposal regarding movement by using the QR code generated by the QR code generation unit. The activity proposal unit proposes an on-site activity based on the movement proposed by the movement proposal unit. The food / drink proposing unit proposes a restaurant on the basis of the activity proposed by the activity proposing unit. The purchase suggestion unit makes a suggestion regarding purchase on the basis of the restaurant suggested by the food / drink suggestion unit.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 does not provide a unified approach to trip planning, local activities, restaurant selection, and purchasing suggestions, leaving room for improvement.

[0005] The system according to the embodiment aims to provide a unified service that covers everything from travel planning to local activities, restaurant selection, and purchasing suggestions. [Means for solving the problem]

[0006] The system according to the embodiment includes a QR code generation unit, a travel suggestion unit, an activity suggestion unit, a dining suggestion unit, and a purchase suggestion unit. The QR code generation unit generates a QR code. The travel suggestion unit makes travel suggestions using the QR code generated by the QR code generation unit. The activity suggestion unit suggests local activities based on travel suggested by the travel suggestion unit. The dining suggestion unit suggests restaurants based on activities suggested by the activity suggestion unit. The purchase suggestion unit makes purchase suggestions based on restaurants suggested by the dining suggestion unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide a unified service that includes travel planning, local activities, restaurant selection, and purchasing suggestions. [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 nonvolatile storage devices that store various programs, various parameters, etc. Examples of nonvolatile 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[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 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[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) The Custom Xplorer system according to an embodiment of the present invention is a comprehensive service that allows users to experience customized travel recommendations. This service covers transportation, experiences, and payments using QR codes. As a result, the Custom Xplorer system allows users to cover transportation, experiences, dining, and purchases all with a single QR code, greatly improving the convenience of travel.

[0029] The Custom Explorer system according to the embodiment includes a QR code generation unit, a travel suggestion unit, an activity suggestion unit, a dining suggestion unit, and a purchase suggestion unit. The QR code generation unit generates a QR code. For example, the QR code generation unit suggests an optimal route based on a user's travel plan and generates a QR code. The travel suggestion unit makes travel suggestions using the QR code generated by the QR code generation unit. For example, the travel suggestion unit provides a train ticket from the departure point to the destination of the trip as a QR code, which can be scanned with a smartphone to pass through the ticket gate. The activity suggestion unit suggests local activities based on the travel suggested by the travel suggestion unit. For example, the activity suggestion unit issues tickets for tourist attractions and experiential activities to be visited by the user as QR codes, enabling smooth entry and participation at the local locations. The dining suggestion unit suggests restaurants based on the activities suggested by the activity suggestion unit. For example, the dining suggestion unit suggests optimal restaurants based on data on the user's favorite dishes and restaurants visited in the past, and allows reservations and payments to be made using QR codes. The purchase suggestion unit makes purchasing suggestions based on the restaurants suggested by the food and drink suggestion unit. For example, the purchase suggestion unit suggests local specialties and popular souvenirs from the area the user is visiting, and allows the user to smoothly purchase them using a QR code. As a result, the Custom Explorer system according to the embodiment allows users to cover all aspects of travel, experiences, dining, and purchases with a single QR code, greatly improving the convenience of travel.

[0030] The travel suggestion unit can analyze the user's real-time travel status and reflect optimal transfer guidance and delay information in the QR code. For example, the travel suggestion unit uses a generation AI to analyze the user's current location and destination in real time and provide optimal transfer guidance. For example, it can propose the smoothest route taking into account train delay information and congestion status. This allows the user to obtain the optimal travel route in real time.

[0031] The travel suggestion unit can suggest the optimal seat position and vehicle based on the user's past travel history and include that information in the QR code. For example, the travel suggestion unit uses a generation AI to analyze the user's past travel history and suggest the optimal seat position. For example, the QR code includes information on the user's preferred seat position and vehicle. This allows the user to travel comfortably based on their past travel history.

[0032] The transportation suggestion unit can use QR codes to enable the integrated use of transportation modes other than trains. The transportation suggestion unit uses, for example, QR codes to build a system that enables the integrated use of transportation modes other than trains. For example, bus and taxi tickets are also provided using QR codes. This allows the user to integrate the use of transportation modes other than trains.

[0033] The travel suggestion unit can incorporate information about tourist spots and rest areas into the travel route proposed by the generation AI, increasing the enjoyment of the journey. For example, the travel suggestion unit can incorporate information about tourist spots into the travel route proposed by the generation AI. For example, it can suggest tourist spots and famous places that can be visited during the journey and include that information in a QR code. This allows the user to obtain information about tourist spots and rest areas while traveling.

[0034] The activity suggestion unit allows the generation AI to analyze the user's past activity history and suggest a more personalized experience. For example, the activity suggestion unit allows the generation AI to analyze the user's past activity history and suggest a personalized experience. For example, the generation AI suggests activities that match the user's preferences based on places visited or events attended in the past. This allows the user to have a personalized experience based on their past activity history.

[0035] The activity suggestion unit reflects local weather and event information in real time and can include the optimal activity in the QR code. For example, the activity suggestion unit uses a generation AI to analyze local weather information in real time and suggest the optimal activity. For example, on rainy days, indoor activities are suggested and that information is included in the QR code. This allows the user to select the optimal activity based on local weather and event information.

[0036] The activity suggestion unit can use the QR code to enable smooth participation in local guided tours, workshops, and the like. The activity suggestion unit can use, for example, the QR code to enable smooth participation in local guided tours. For example, the QR code can be used to make reservations for and complete participation procedures for guided tours. This allows the user to smoothly participate in local guided tours and workshops.

[0037] The activity suggestion unit can incorporate information about local culture and history into the activities suggested by the generation AI to add learning elements. For example, the activity suggestion unit incorporates information about local culture and history into the activities suggested by the generation AI. For example, the QR code can include the history and cultural background of a tourist destination. This allows the user to obtain information about local culture and history.

[0038] The food and drink suggestion unit uses the generation AI to analyze the user's eating history and allergy information and suggest the most suitable restaurant. For example, the generation AI can analyze the user's eating history and suggest the most suitable restaurant. For example, it can suggest restaurants that suit the user based on restaurants they have visited in the past and their favorite dishes. This allows the user to select the most suitable restaurant based on their eating history and allergy information.

[0039] The food and drink suggestion unit can reflect local ingredients and seasonal menu items in real time and include them in the QR code. For example, the generative AI analyzes local ingredient information in real time and suggests the most suitable restaurant. For example, it suggests restaurants that serve dishes using seasonal ingredients. This allows users to select the most suitable restaurant based on local ingredients and seasonal menu items.

[0040] The food and drink suggestion unit can use QR codes to enable the user to check restaurant menus and reviews in advance. The food and drink suggestion unit, for example, uses QR codes to build a system that allows the user to check restaurant menus in advance. For example, by scanning a QR code, menu details and prices are displayed. This allows the user to check the restaurant menu and reviews in advance.

[0041] The food and drink suggestion unit can incorporate information about local food culture and history into the restaurants suggested by the generation AI, increasing the enjoyment of the meal. For example, the food and drink suggestion unit can incorporate information about local food culture and history into the restaurants suggested by the generation AI. For example, the QR code can include background information about traditional dishes and ingredients. This allows users to obtain information about local food culture and history.

[0042] The purchase suggestion unit uses the generation AI to analyze the user's purchasing history and preferences, and then suggests the most suitable souvenirs and keepsakes. For example, the purchase suggestion unit uses the generation AI to analyze the user's purchasing history and then suggests the most suitable souvenirs and keepsakes. For example, it suggests products that suit the user based on products purchased in the past and preferred styles. This allows the user to select the most suitable souvenirs and keepsakes based on their purchasing history and preferences.

[0043] The purchasing suggestion section can reflect local specialties and limited-edition products in real time and include them in the QR code. For example, the purchasing suggestion section uses generation AI to analyze local speciality information in real time and suggest the most suitable souvenirs and mementos. For example, seasonal specialties and limited-edition products can be included in the QR code. This allows users to make optimal purchases based on local specialties and limited-edition products.

[0044] The purchase suggestion unit can use QR codes to enable users to check information about local markets and shops in advance. The purchase suggestion unit, for example, uses QR codes to build a system that allows users to check information about local markets and shops in advance. For example, scanning a QR code displays the location and business hours of the market. This allows users to check information about local markets and shops in advance.

[0045] The purchase suggestion unit can incorporate information about local culture and history into the purchases suggested by the generation AI, making the purchase more enjoyable. For example, the purchase suggestion unit can incorporate information about local culture and history into the purchases suggested by the generation AI. For example, the background and manufacturing process of a local specialty product can be included in a QR code. This allows users to obtain information about local culture and history.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] The Custom Xplorer system can also include a health management unit that monitors the user's health condition. For example, the health management unit can monitor the user's heart rate and number of steps in real time and suggest appropriate rest and exercise. This makes it easier for users to maintain their health while traveling. The health management unit can also suggest appropriate meals and activities based on the user's health data. For example, if the user is tired, it can suggest a relaxing spa or light meal. Furthermore, the health management unit can provide information on medical institutions in case of an emergency, depending on the user's health condition. This allows users to enjoy their trip with peace of mind.

[0048] The Custom Xplorer system may further include an eco-suggestion unit that reduces the user's environmental impact during travel. For example, the eco-suggestion unit may suggest eco-friendly options based on the user's travel route and activities. This allows the user to be more environmentally conscious during travel. The eco-suggestion unit may also suggest local eco-friendly restaurants and accommodations. For example, it may suggest restaurants that use organic ingredients or hotels that have eco-certifications. Furthermore, the eco-suggestion unit may suggest eco-friendly activities based on the user's behavior. For example, it may suggest sightseeing by walking or cycling. This allows the user to make choices that reduce the environmental impact during travel.

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

[0050] Step 1: The QR code generator generates a QR code. For example, the QR code generator proposes an optimal route based on the user's travel plan and generates a QR code. Step 2: The travel suggestion unit makes travel suggestions using the QR code generated by the QR code generation unit. For example, the travel suggestion unit may provide a QR code representing a train ticket from the departure point to the destination of the trip, allowing the user to pass through the ticket gate by scanning it with a smartphone. Step 3: The activity suggestion unit suggests local activities based on the travel suggested by the travel suggestion unit. For example, the activity suggestion unit issues tickets for tourist attractions and experiential activities to the user as QR codes, enabling smooth entry and participation at the local sites. Step 4: The dining suggestion unit suggests restaurants based on the activity suggested by the activity suggestion unit. For example, the dining suggestion unit suggests the most suitable restaurant based on the user's favorite dishes and data on restaurants visited in the past, and allows reservations and payments to be made using QR codes. Step 5: The purchase suggestion unit makes purchasing suggestions based on the restaurants suggested by the food and beverage suggestion unit. For example, the purchase suggestion unit suggests local specialties and popular souvenirs from the area the user is visiting, and allows the user to smoothly purchase them using the QR code.

[0051] (Example 2) The Custom Xplorer system according to an embodiment of the present invention is a comprehensive service that allows users to experience customized travel recommendations. This service covers transportation, experiences, and payments using QR codes. As a result, the Custom Xplorer system allows users to cover transportation, experiences, dining, and purchases all with a single QR code, greatly improving the convenience of travel.

[0052] The Custom Explorer system according to the embodiment includes a QR code generation unit, a travel suggestion unit, an activity suggestion unit, a dining suggestion unit, and a purchase suggestion unit. The QR code generation unit generates a QR code. For example, the QR code generation unit suggests an optimal route based on a user's travel plan and generates a QR code. The travel suggestion unit makes travel suggestions using the QR code generated by the QR code generation unit. For example, the travel suggestion unit provides a train ticket from the departure point to the destination of the trip as a QR code, which can be scanned with a smartphone to pass through the ticket gate. The activity suggestion unit suggests local activities based on the travel suggested by the travel suggestion unit. For example, the activity suggestion unit issues tickets for tourist attractions and experiential activities to be visited by the user as QR codes, enabling smooth entry and participation at the local locations. The dining suggestion unit suggests restaurants based on the activities suggested by the activity suggestion unit. For example, the dining suggestion unit suggests optimal restaurants based on data on the user's favorite dishes and restaurants visited in the past, and allows reservations and payments to be made using QR codes. The purchase suggestion unit makes purchasing suggestions based on the restaurants suggested by the food and drink suggestion unit. For example, the purchase suggestion unit suggests local specialties and popular souvenirs from the area the user is visiting, and allows the user to smoothly purchase them using a QR code. As a result, the Custom Explorer system according to the embodiment allows users to cover all aspects of travel, experiences, dining, and purchases with a single QR code, greatly improving the convenience of travel.

[0053] The travel suggestion unit can analyze the user's real-time travel status and reflect optimal transfer guidance and delay information in the QR code. For example, the travel suggestion unit uses a generation AI to analyze the user's current location and destination in real time and provide optimal transfer guidance. For example, it can propose the smoothest route taking into account train delay information and congestion status. This allows the user to obtain the optimal travel route in real time.

[0054] The travel suggestion unit can suggest the optimal seat position and vehicle based on the user's past travel history and include that information in the QR code. For example, the travel suggestion unit uses a generation AI to analyze the user's past travel history and suggest the optimal seat position. For example, the QR code includes information on the user's preferred seat position and vehicle. This allows the user to travel comfortably based on their past travel history.

[0055] The travel suggestion unit can use the emotion estimation function to analyze the user's stress level during travel and suggest a route or vehicle that will help them relax. The travel suggestion unit, for example, uses the emotion estimation function to analyze the user's stress level during travel in real time and suggest a route that will help them relax. For example, it can select a route that avoids crowds or a route with beautiful scenery. This allows the user to select a route or vehicle that will help them relax during travel.

[0056] The transportation suggestion unit can use QR codes to enable the integrated use of transportation modes other than trains. The transportation suggestion unit uses, for example, QR codes to build a system that enables the integrated use of transportation modes other than trains. For example, bus and taxi tickets are also provided using QR codes. This allows the user to integrate the use of transportation modes other than trains.

[0057] The travel suggestion unit can incorporate information about tourist spots and rest areas into the travel route proposed by the generation AI, increasing the enjoyment of the journey. For example, the travel suggestion unit can incorporate information about tourist spots into the travel route proposed by the generation AI. For example, it can suggest tourist spots and famous places that can be visited during the journey and include that information in a QR code. This allows the user to obtain information about tourist spots and rest areas while traveling.

[0058] The travel suggestion unit can use the emotion estimation function to suggest spots and activities where the user can refresh themselves based on the emotions they feel while traveling. For example, the travel suggestion unit uses the emotion estimation function to analyze the emotions the user feels while traveling and suggests spots where the user can refresh themselves. For example, it suggests a cafe where the user can relax if they are feeling stressed. This allows the user to select spots and activities where the user can refresh themselves while traveling.

[0059] The activity suggestion unit allows the generation AI to analyze the user's past activity history and suggest a more personalized experience. For example, the activity suggestion unit allows the generation AI to analyze the user's past activity history and suggest a personalized experience. For example, the generation AI suggests activities that match the user's preferences based on places visited or events attended in the past. This allows the user to have a personalized experience based on their past activity history.

[0060] The activity suggestion unit reflects local weather and event information in real time and can include the optimal activity in the QR code. For example, the activity suggestion unit uses a generation AI to analyze local weather information in real time and suggest the optimal activity. For example, on rainy days, indoor activities are suggested and that information is included in the QR code. This allows the user to select the optimal activity based on local weather and event information.

[0061] The activity suggestion unit can use the emotion estimation function to suggest an activity that matches the user's current mood and reflect it in the QR code. For example, the activity suggestion unit can use the emotion estimation function to analyze the user's current mood and suggest an activity that matches it. For example, if the user feels like relaxing, the activity suggestion unit can suggest a spa or massage. This allows the user to select an activity that matches their current mood.

[0062] The activity suggestion unit can use the QR code to enable smooth participation in local guided tours, workshops, and the like. The activity suggestion unit can use, for example, the QR code to enable smooth participation in local guided tours. For example, the QR code can be used to make reservations for and complete participation procedures for guided tours. This allows the user to smoothly participate in local guided tours and workshops.

[0063] The activity suggestion unit can incorporate information about local culture and history into the activities suggested by the generation AI to add learning elements. For example, the activity suggestion unit incorporates information about local culture and history into the activities suggested by the generation AI. For example, the QR code can include the history and cultural background of a tourist destination. This allows the user to obtain information about local culture and history.

[0064] The activity suggestion unit can use the emotion estimation function to suggest relaxing spots and activities based on the emotions the user feels at the location. For example, the activity suggestion unit uses the emotion estimation function to analyze the emotions the user feels at the location and suggest relaxing spots. For example, it suggests cafes and parks where the user can relax when they are feeling stressed. This allows the user to select relaxing spots and activities at the location.

[0065] The food and drink suggestion unit uses the generation AI to analyze the user's eating history and allergy information and suggest the most suitable restaurant. For example, the generation AI can analyze the user's eating history and suggest the most suitable restaurant. For example, it can suggest restaurants that suit the user based on restaurants they have visited in the past and their favorite dishes. This allows the user to select the most suitable restaurant based on their eating history and allergy information.

[0066] The food and drink suggestion unit can reflect local ingredients and seasonal menu items in real time and include them in the QR code. For example, the generative AI analyzes local ingredient information in real time and suggests the most suitable restaurant. For example, it suggests restaurants that serve dishes using seasonal ingredients. This allows users to select the most suitable restaurant based on local ingredients and seasonal menu items.

[0067] The food and drink suggestion unit can use the emotion estimation function to suggest dishes and restaurants that match the user's current mood. For example, the food and drink suggestion unit uses the emotion estimation function to analyze the user's current mood and suggest dishes and restaurants that match it. For example, when the user feels like relaxing, the unit suggests cafes and light meals. This allows the user to select dishes and restaurants that match their current mood.

[0068] The food and drink suggestion unit can use QR codes to enable the user to check restaurant menus and reviews in advance. The food and drink suggestion unit, for example, uses QR codes to build a system that allows the user to check restaurant menus in advance. For example, by scanning a QR code, menu details and prices are displayed. This allows the user to check the restaurant menu and reviews in advance.

[0069] The food and drink suggestion unit can incorporate information about local food culture and history into the restaurants suggested by the generation AI, increasing the enjoyment of the meal. For example, the food and drink suggestion unit can incorporate information about local food culture and history into the restaurants suggested by the generation AI. For example, the QR code can include background information about traditional dishes and ingredients. This allows users to obtain information about local food culture and history.

[0070] The food and drink suggestion unit can use the emotion estimation function to suggest restaurants and menus where the user can relax based on the emotions felt while eating. For example, the food and drink suggestion unit uses the emotion estimation function to analyze the emotions felt by the user while eating and suggest restaurants where the user can relax. For example, it can suggest restaurants with a quiet atmosphere. This allows the user to select restaurants and menus where the user can relax while eating.

[0071] The purchase suggestion unit uses the generation AI to analyze the user's purchasing history and preferences, and then suggests the most suitable souvenirs and keepsakes. For example, the purchase suggestion unit uses the generation AI to analyze the user's purchasing history and then suggests the most suitable souvenirs and keepsakes. For example, it suggests products that suit the user based on products purchased in the past and preferred styles. This allows the user to select the most suitable souvenirs and keepsakes based on their purchasing history and preferences.

[0072] The purchasing suggestion section can reflect local specialties and limited-edition products in real time and include them in the QR code. For example, the purchasing suggestion section uses generation AI to analyze local speciality information in real time and suggest the most suitable souvenirs and mementos. For example, seasonal specialties and limited-edition products can be included in the QR code. This allows users to make optimal purchases based on local specialties and limited-edition products.

[0073] The purchase suggestion unit can use the emotion estimation function to make purchase suggestions that match the user's current mood. For example, the purchase suggestion unit uses the emotion estimation function to analyze the user's current mood and make purchase suggestions that match the mood. For example, when the user feels like relaxing, the purchase suggestion unit suggests soothing products. This allows the user to receive purchase suggestions that match the user's current mood.

[0074] The purchase suggestion unit can use QR codes to enable users to check information about local markets and shops in advance. The purchase suggestion unit, for example, uses QR codes to build a system that allows users to check information about local markets and shops in advance. For example, scanning a QR code displays the location and business hours of the market. This allows users to check information about local markets and shops in advance.

[0075] The purchase suggestion unit can incorporate information about local culture and history into the purchases suggested by the generation AI, making the purchase more enjoyable. For example, the purchase suggestion unit can incorporate information about local culture and history into the purchases suggested by the generation AI. For example, the background and manufacturing process of a local specialty product can be included in a QR code. This allows users to obtain information about local culture and history.

[0076] The purchase suggestion unit can use the emotion estimation function to suggest a relaxing purchasing experience based on the emotion the user feels while making a purchase. For example, the purchase suggestion unit uses the emotion estimation function to analyze the emotion the user feels while making a purchase and suggest a relaxing purchasing experience. For example, if the user is feeling stressed, the purchase suggestion unit suggests a shop where the user can relax. This allows the user to select a relaxing experience while making a purchase.

[0077] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0078] The Custom Xplorer system can also include a health management unit that monitors the user's health condition. For example, the health management unit can monitor the user's heart rate and number of steps in real time and suggest appropriate rest and exercise. This makes it easier for users to maintain their health while traveling. The health management unit can also suggest appropriate meals and activities based on the user's health data. For example, if the user is tired, it can suggest a relaxing spa or light meal. Furthermore, the health management unit can provide information on medical institutions in case of an emergency, depending on the user's health condition. This allows users to enjoy their trip with peace of mind.

[0079] The Custom Xplorer system may further include a music suggestion unit that provides a customized music playlist based on the user's preferences. For example, the music suggestion unit may suggest the most suitable music based on the user's past music history and current mood. This allows the user to enjoy music while traveling or during activities. The music suggestion unit may also provide a playlist related to local music and culture. For example, it may suggest traditional music or songs by popular artists in the area the user is visiting. Furthermore, the music suggestion unit may estimate the user's emotions and suggest calming music when the user wants to relax or upbeat music when the user is feeling energized. This allows the user to enjoy the optimal music experience during their trip.

[0080] The Custom Xplorer system can also be equipped with a safety management module to ensure the user's safety during their trip. For example, the safety management module can analyze the user's current location and surrounding safety information in real time and suggest routes that avoid dangerous areas. This allows the user to enjoy their trip with peace of mind. The safety management module can also provide information on the nearest police station or hospital in an emergency. Furthermore, the safety management module can estimate the user's emotions and suggest safe spots and activities if the user is feeling anxious. For example, if the user is feeling anxious, the module can suggest quiet cafes or parks. This allows the user to feel safe during their trip.

[0081] The Custom Xplorer system can also include a translation support unit to assist users in communicating while traveling. For example, the translation support unit can translate the language of the region the user is visiting in real time, facilitating communication. This allows users to enjoy their trip without feeling any language barriers. The translation support unit can also estimate the user's emotions and suggest simple phrases or gestures if the user is nervous. For example, if the user is nervous, it can suggest simple greetings or words of thanks. The translation support unit can also provide information about local culture and manners. This allows users to communicate smoothly with local people.

[0082] The Custom Xplorer system may further include an entertainment suggestion unit that provides entertainment for the user during their trip. For example, the entertainment suggestion unit may suggest content such as movies, TV dramas, and games based on the user's preferences. This allows the user to enjoy themselves while traveling or waiting. The entertainment suggestion unit may also provide information about local events and shows. For example, it may suggest tickets for concerts or plays in the area the user is visiting. Furthermore, the entertainment suggestion unit may estimate the user's emotions and suggest comedy movies when the user wants to relax or action movies when the user is in an energetic mood. This allows the user to have the optimal entertainment experience during their trip.

[0083] The Custom Xplorer system may further include an eco-suggestion unit that reduces the user's environmental impact during travel. For example, the eco-suggestion unit may suggest eco-friendly options based on the user's travel route and activities. This allows the user to be more environmentally conscious during travel. The eco-suggestion unit may also suggest local eco-friendly restaurants and accommodations. For example, it may suggest restaurants that use organic ingredients or hotels that have eco-certifications. Furthermore, the eco-suggestion unit may suggest eco-friendly activities based on the user's behavior. For example, it may suggest sightseeing by walking or cycling. This allows the user to make choices that reduce the environmental impact during travel.

[0084] The Custom Xplorer system can further include an education suggestion unit that deepens the user's learning during their trip. For example, the education suggestion unit may provide information about local history and culture based on the user's interests. This allows the user to incorporate learning elements into their trip. The education suggestion unit can also provide information about local museums and art galleries. For example, it may suggest historical landmarks and cultural facilities in the area to be visited. Furthermore, the education suggestion unit can estimate the user's emotions and suggest activities related to the user's areas of interest. For example, if the user is interested in art, it may suggest museums and art galleries. This allows the user to deepen their learning during their trip.

[0085] The Custom Xplorer system can also include a schedule management unit that assists users in managing their travel schedules. For example, the schedule management unit can suggest an optimal schedule based on the user's travel plans. This allows the user to enjoy their trip efficiently. The schedule management unit can also estimate the user's emotions and flexibly adjust the schedule, such as increasing rest time if the user is tired. For example, if the user is tired, it can suggest taking a break at a relaxing cafe. Furthermore, the schedule management unit can reflect information on local events and activities in real time and incorporate it into the schedule. This allows the user to maintain an optimal schedule during their trip.

[0086] The Custom Xplorer system may further include a luggage management unit that assists users in managing their luggage during their trip. For example, the luggage management unit may track the location of the user's luggage in real time to prevent loss or theft. This allows the user to enjoy their trip with peace of mind. The luggage management unit may also estimate the user's emotions and provide luggage location information if the user feels anxious. For example, if the user feels anxious, the luggage management unit may notify the user of the current location of the luggage. Furthermore, the luggage management unit may suggest luggage delivery services based on the user's travel plans. For example, the luggage management unit may suggest a service to send luggage to the user's next accommodation in advance. This allows the user to efficiently manage their luggage during their trip.

[0087] The Custom Xplorer system may further include a photo suggestion unit that assists users in taking photos during their trip. For example, the photo suggestion unit may suggest optimal photo spots based on the user's travel route. This allows the user to take beautiful photos during their trip. The photo suggestion unit may also suggest optimal photo timing based on the local weather and time of day. For example, it may suggest taking photos on the beach during sunset. Furthermore, the photo suggestion unit may estimate the user's emotions and suggest taking photos in a bright location when the user is in a happy mood, or in a quiet location when the user wants to relax. This allows the user to have an optimal photo experience during their trip.

[0088] The processing flow of the second embodiment will be briefly explained below.

[0089] Step 1: The QR code generator generates a QR code. For example, the QR code generator proposes an optimal route based on the user's travel plan and generates a QR code. Step 2: The travel suggestion unit makes travel suggestions using the QR code generated by the QR code generation unit. For example, the travel suggestion unit may provide a QR code representing a train ticket from the departure point to the destination of the trip, allowing the user to pass through the ticket gate by scanning it with a smartphone. Step 3: The activity suggestion unit suggests local activities based on the travel suggested by the travel suggestion unit. For example, the activity suggestion unit issues tickets for tourist attractions and experiential activities to the user as QR codes, enabling smooth entry and participation at the local sites. Step 4: The dining suggestion unit suggests restaurants based on the activity suggested by the activity suggestion unit. For example, the dining suggestion unit suggests the most suitable restaurant based on the user's favorite dishes and data on restaurants visited in the past, and allows reservations and payments to be made using QR codes. Step 5: The purchase suggestion unit makes purchasing suggestions based on the restaurants suggested by the food and beverage suggestion unit. For example, the purchase suggestion unit suggests local specialties and popular souvenirs from the area the user is visiting, and allows the user to smoothly purchase them using the QR code.

[0090] 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.

[0091] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<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.

[0092] 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.

[0093] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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).

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0103] 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. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0116] 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.

[0117] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0118] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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).

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0134] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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).

[0143] 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.

[0144] 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."

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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]

[0157] 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. a QR code generation unit that generates a QR code; a travel suggestion unit that makes travel suggestions using the QR code generated by the QR code generation unit; an activity suggestion unit that suggests local activities based on the movement suggested by the movement suggestion unit; a dining suggestion unit that suggests restaurants based on the activity suggested by the activity suggestion unit; a purchase suggestion unit that makes purchase suggestions based on the restaurants suggested by the eating and drinking suggestion unit; A system characterized by:

2. The movement suggestion unit Analyze the user's real-time movement status and reflect optimal transfer guidance and delay information in the QR code.

2. The system of claim 1.

3. The movement suggestion unit The route proposed by the generative AI incorporates information about tourist spots and rest areas to increase enjoyment during travel.

2. The system of claim 1.

4. The activity suggestion unit Generative AI analyzes users' past activity history to suggest more personalized experiences 2. The system of claim 1.

5. The food and drink suggestion unit Generative AI analyzes the user's eating history and allergy information to suggest the most suitable restaurant 2. The system of claim 1.

6. The purchase proposal unit Generative AI analyzes users' purchasing history and preferences to suggest the best souvenirs and mementos.

2. The system of claim 1.

7. The movement suggestion unit Using emotion estimation, the system analyzes the user's stress level during travel and suggests routes and vehicles that will help them relax.

2. The system of claim 1.

8. The activity suggestion unit Using emotion estimation function, activities that match the user's current mood are suggested and reflected in the QR code.

2. The system of claim 1.

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