System

Abstract

An object of a system according to an embodiment is to propose an optimal route and a tourist spot only by inputting a destination and a moving method by a user.SOLUTION: A system according to an embodiment includes a destination input unit, a travel method input unit, a route calculation unit, and a tourist resort suggestion unit. The destination input unit inputs a destination of the user. The movement method input unit inputs a movement method. The route calculation unit calculates an optimum route based on the information input by the destination input unit and the moving method input unit. The sightseeing spot proposal unit proposes a sightseeing spot on the route calculated by the route calculation 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] With conventional technology, even if a user inputs their destination and mode of transportation, the optimal route or tourist spots are not automatically suggested, making it difficult to create a travel plan.

[0005] The system according to the embodiment aims to suggest optimal routes and tourist spots simply by having the user input the destination and mode of transportation. [Means for solving the problem]

[0006] The system according to the embodiment includes a destination input unit, a transportation method input unit, a route calculation unit, and a tourist spot suggestion unit. The destination input unit inputs a user's destination. The transportation method input unit inputs a transportation method. The route calculation unit calculates an optimal route based on the information input by the destination input unit and the transportation method input unit. The tourist spot suggestion unit suggests tourist spots along the route calculated by the route calculation unit. [Effects of the Invention]

[0007] The system according to the embodiment can suggest optimal routes and tourist spots simply by the user inputting the destination and mode of transportation. [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) The travel plan suggestion system according to an embodiment of the present invention is a system that suggests optimal routes and tourist spots when a user inputs a destination and a mode of transportation. This allows the user to enjoy themselves while traveling, improving the quality of their trip.

[0029] A travel plan proposal system according to an embodiment includes a destination input unit, a transportation input unit, a route calculation unit, and a tourist spot proposal unit. The destination input unit inputs a user's destination. For example, the user inputs information such as "travel from Tokyo to Kyoto by car." The transportation input unit inputs the user's transportation method. For example, the user inputs a transportation method such as car, train, or bus. The route calculation unit calculates an optimal route based on the information input by the destination input unit and the transportation input unit. For example, the generation AI calculates an optimal route based on the input information and takes into account tourist spots and detour spots along the route. The tourist spot proposal unit proposes tourist spots along the route calculated by the route calculation unit. For example, the generation AI proposes tourist spots and detour spots based on a prompt such as "Please suggest tourist spots along the route from Tokyo to Kyoto." As a result, the travel plan proposal system according to an embodiment can propose an optimal route and tourist spots when the user inputs a destination and transportation method.

[0030] The route calculation unit takes into account past traffic data and weather information and can update the optimal route in real time. For example, when the generation AI calculates a route, the route calculation unit takes into account past traffic data and weather information and updates the optimal route in real time. For example, the route is adjusted based on congestion information and weather forecasts. The route calculation unit also calculates the optimal route based on past traffic data and weather information and updates it in real time. For example, it suggests routes that should be avoided in rainy weather. The route calculation unit also takes into account traffic data and weather information when the generation AI calculates a route and updates the optimal route in real time. For example, it reflects information on traffic accidents and construction work. This allows the optimal route to be updated in real time, taking into account past traffic data and weather information.

[0031] The tourist destination suggestion unit can suggest tourist destinations customized based on the user's preferences and past visit history. For example, the tourist destination suggestion unit makes customized suggestions based on the user's preferences and past visit history for tourist destinations suggested by the generation AI. For example, it prioritizes suggestions of theme parks and museums that the user likes. The tourist destination suggestion unit also suggests tourist destinations customized by the generation AI based on the user's preferences and past visit history. For example, it suggests places similar to tourist destinations that the user has visited in the past. The tourist destination suggestion unit also suggests customized tourist destinations by having the generation AI analyze the user's preferences and past visit history. For example, it proposes plans that include natural landscapes and historical buildings that the user likes. This makes it possible to suggest tourist destinations customized based on the user's preferences and past visit history.

[0032] The tourist destination suggestion unit can display reviews and ratings from other users in real time based on the destination and method of travel input by the user, for reference. The tourist destination suggestion unit, for example, displays reviews and ratings from other users in real time based on the destination and method of travel input by the user. For example, it displays ratings for a specific tourist destination or route. The tourist destination suggestion unit also displays reviews and ratings from other users in real time for reference by the user. For example, it displays comments and photos from past travelers. The tourist destination suggestion unit also displays reviews and ratings from other users in real time based on the information input by the user, for reference. For example, it displays ratings for a specific restaurant or accommodation. This allows reviews and ratings from other users to be displayed in real time for reference.

[0033] The tourist destination suggestion unit can simultaneously provide information on events and festivals that the user may be interested in based on the destination and mode of travel input by the user. The tourist destination suggestion unit provides information on events and festivals that the user may be interested in, for example, based on the destination and mode of travel input by the user. For example, it displays events held in a particular season. Furthermore, the tourist destination suggestion unit simultaneously provides information on events and festivals that the user may be interested in when the user inputs the destination and mode of travel. For example, it displays information on local festivals and cultural events. Furthermore, the tourist destination suggestion unit provides information on events and festivals that the user may be interested in based on the information input by the user. For example, it displays information on music festivals and art exhibitions. In this way, it is possible to simultaneously provide information on events and festivals that the user may be interested in.

[0034] The tourist destination suggestion unit can learn the user's past travel history and preferences and propose individually customized travel plans. The tourist destination suggestion unit, for example, analyzes the user's past travel history and proposes travel plans that match the preferences. For example, suggestions are made based on data on tourist destinations and accommodations visited in the past. The tourist destination suggestion unit also learns the user's preferences and proposes individually customized travel plans. For example, it prioritizes suggestions of activities and dining spots that the user prefers. The tourist destination suggestion unit also proposes customized travel plans based on the user's past travel history and preferences. For example, it proposes plans that include theme parks and natural scenery that the user prefers. In this way, the tourist destination suggestion unit can learn the user's past travel history and preferences and propose individually customized travel plans.

[0035] The tourist destination suggestion unit can refer to past travel data and suggest the most popular routes and tourist destinations based on the destination and method of travel input by the user. The tourist destination suggestion unit, for example, refers to past travel data and suggests the most popular routes and tourist destinations based on the destination and method of travel input by the user. For example, tourist destinations and routes that have been visited by many travelers in the past are preferentially displayed. The tourist destination suggestion unit also analyzes past travel data based on the information input by the user and suggests popular tourist destinations and routes. For example, it suggests tourist destinations that are good to visit in a particular season. The tourist destination suggestion unit also suggests routes and tourist destinations that are optimal for the destination and method of travel input by the user based on the past travel data. For example, it refers to reviews and ratings from past travelers. In this way, it is possible to refer to past travel data and suggest the most popular routes and tourist destinations.

[0036] The tourist destination suggestion unit can display other users' reviews and ratings in real time for tourist destinations suggested by the generation AI for reference. The tourist destination suggestion unit, for example, displays other users' reviews and ratings in real time for tourist destinations suggested by the generation AI. For example, it displays ratings for specific tourist destinations or routes. The tourist destination suggestion unit also displays other users' reviews and ratings in real time for reference. For example, it displays comments and photos from past travelers. The tourist destination suggestion unit also displays other users' reviews and ratings in real time for reference. For example, it displays ratings for specific restaurants or accommodations. This allows other users' reviews and ratings to be displayed in real time for reference.

[0037] The tourist destination suggestion unit can make customized suggestions based on the user's preferences and past visit history for tourist destinations suggested by the generation AI. For example, the tourist destination suggestion unit makes customized suggestions based on the user's preferences and past visit history for tourist destinations suggested by the generation AI. For example, it prioritizes suggestions of theme parks and museums that the user likes. The tourist destination suggestion unit also makes customized suggestions of tourist destinations based on the user's preferences and past visit history. For example, it suggests places similar to tourist destinations that the user has visited in the past. The tourist destination suggestion unit also analyzes the user's preferences and past visit history and makes customized suggestions of tourist destinations. For example, it proposes plans that include natural landscapes and historical buildings that the user likes. This makes it possible to propose customized tourist destinations based on the user's preferences and past visit history.

[0038] The tourist destination suggestion unit can simultaneously suggest activities and events that the user may be interested in when the generation AI calculates a route. For example, the tourist destination suggestion unit simultaneously suggests activities and events that the user may be interested in when the generation AI calculates a route. For example, it displays events and activities that are held in a particular season. The tourist destination suggestion unit also simultaneously suggests activities and events that the user may be interested in. For example, it displays information about local festivals and cultural events. The tourist destination suggestion unit also simultaneously suggests activities and events that the user may be interested in when the generation AI calculates a route. For example, it displays information about music festivals and art exhibitions. This makes it possible to simultaneously suggest activities and events that the user may be interested in.

[0039] The tourist destination suggestion unit can include reviews and ratings from past visitors in the detailed information about tourist destinations provided by the generation AI so that users can refer to it. For example, the tourist destination suggestion unit includes reviews and ratings from past visitors in the detailed information about tourist destinations provided by the generation AI. For example, it displays the tourist destination's rating score and comments. The tourist destination suggestion unit also provides detailed information about tourist destinations based on the reviews and ratings from past visitors. For example, it displays photos and videos of visitors. The tourist destination suggestion unit also includes reviews and ratings from past visitors in the detailed information about tourist destinations provided by the generation AI so that users can refer to it. For example, it displays visitor experiences and recommended points. This allows users to refer to the information, including the reviews and ratings from past visitors.

[0040] The tourist destination suggestion unit can include local guide and tour information in the detailed information of tourist destinations provided by the generation AI, allowing users to enjoy the experience even more. For example, the tourist destination suggestion unit includes local guide and tour information in the detailed information of tourist destinations provided by the generation AI. For example, it displays reservation information and prices for guided tours. The tourist destination suggestion unit also provides detailed information of tourist destinations by the generation AI based on the local guide and tour information. For example, it displays recommended routes and highlights by the guide. The tourist destination suggestion unit also includes local guide and tour information in the detailed information of tourist destinations provided by the generation AI, allowing users to enjoy the experience even more. For example, it displays information about special experience tours and events. This allows users to enjoy the experience even more, including local guide and tour information.

[0041] The tourist destination suggestion unit can include information about local culture and history in the detailed information about tourist destinations provided by the generation AI, allowing the user to gain a deeper understanding. For example, the tourist destination suggestion unit includes information about local culture and history in the detailed information about tourist destinations provided by the generation AI. For example, it explains the historical background and cultural significance of the tourist destination. The tourist destination suggestion unit also provides detailed information about tourist destinations based on information about local culture and history. For example, it displays information about traditional festivals and cultural events. The tourist destination suggestion unit also includes information about local culture and history in the detailed information about tourist destinations provided by the generation AI, allowing the user to gain a deeper understanding. For example, it displays details about historical buildings and cultural heritage sites. This allows the user to gain a deeper understanding by including information about local culture and history.

[0042] The tourist destination suggestion unit can include information about local specialties and souvenirs in the detailed information about tourist destinations provided by the generation AI, allowing users to enjoy their trips even more. For example, the tourist destination suggestion unit includes information about local specialties and souvenirs in the detailed information about tourist destinations provided by the generation AI. For example, it introduces local specialties and recommended souvenirs. The tourist destination suggestion unit also provides detailed information about tourist destinations based on the local specialties and souvenir information. For example, it displays where to purchase local specialties and prices. The tourist destination suggestion unit also includes information about local specialties and souvenirs in the detailed information about tourist destinations provided by the generation AI, allowing users to enjoy their trips even more. For example, it displays information about events where you can sample local specialties or try them out. This allows users to enjoy their trips even more, including information about local specialties and souvenirs.

[0043] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0044] The travel plan proposal system can further include a health management unit that monitors the user's health condition. For example, the system can obtain the user's heart rate and step count in real time and suggest rest spots and snacks based on the user's health condition. The health management unit can also suggest reasonable travel plans based on the user's health data. For example, it can suggest routes that avoid long travel times and tourist spots where moderate exercise is possible. This makes it possible to provide travel plans that take the user's health condition into consideration.

[0045] The travel plan proposal system can further include a meal proposal unit that takes into account the user's food preferences. For example, restaurants and cafes along the route can be proposed based on the user's input of their preferred cuisine types and allergy information. The meal proposal unit can also propose local specialties and recommended dining spots based on the user's food preferences. For example, if the user is vegetarian, vegetarian restaurants can be preferentially proposed. This makes it possible to provide a travel plan that takes into account the user's food preferences.

[0046] The travel plan suggestion system can further include a budget management unit that takes into account the user's budget. For example, if the user inputs the budget they can spend on their trip, the system can suggest tourist spots and accommodations that can be enjoyed within that budget. The budget management unit can also suggest cost-effective plans based on the user's budget. For example, it can suggest discount information and great value package tours. This makes it possible to provide travel plans that take the user's budget into consideration.

[0047] The travel plan proposal system may further include an activity proposal unit that proposes activities that interest the user. For example, the activity proposal unit proposes activity spots along the route based on the user's input of an activity that interests the user. The activity proposal unit may also propose special experiences or events based on the user's interests. For example, if the user is interested in adventure sports, the activity proposal unit may propose spots for rafting or paragliding. This makes it possible to provide a travel plan that includes activities that interest the user.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The destination input unit inputs the user's destination. For example, the user inputs information such as "travel from Tokyo to Kyoto by car." Step 2: The transportation method input unit inputs the user's transportation method, such as car, train, or bus. Step 3: The route calculation unit calculates the optimal route based on the information entered by the destination input unit and the transportation method input unit. For example, the generation AI calculates the optimal route based on the entered information, taking into account tourist attractions and detour spots along the route. Step 4: The tourist spot suggestion unit suggests tourist spots along the route calculated by the route calculation unit. For example, the generation AI might suggest tourist spots and detour spots based on a prompt such as, "Please suggest tourist spots along the route from Tokyo to Kyoto."

[0050] (Example 2) The travel plan suggestion system according to an embodiment of the present invention is a system that suggests optimal routes and tourist spots when a user inputs a destination and a mode of transportation. This allows the user to enjoy themselves while traveling, improving the quality of their trip.

[0051] A travel plan proposal system according to an embodiment includes a destination input unit, a transportation input unit, a route calculation unit, and a tourist spot proposal unit. The destination input unit inputs a user's destination. For example, the user inputs information such as "travel from Tokyo to Kyoto by car." The transportation input unit inputs the user's transportation method. For example, the user inputs a transportation method such as car, train, or bus. The route calculation unit calculates an optimal route based on the information input by the destination input unit and the transportation input unit. For example, the generation AI calculates an optimal route based on the input information and takes into account tourist spots and detour spots along the route. The tourist spot proposal unit proposes tourist spots along the route calculated by the route calculation unit. For example, the generation AI proposes tourist spots and detour spots based on a prompt such as "Please suggest tourist spots along the route from Tokyo to Kyoto." As a result, the travel plan proposal system according to an embodiment can propose an optimal route and tourist spots when the user inputs a destination and transportation method.

[0052] The route calculation unit takes into account past traffic data and weather information and can update the optimal route in real time. For example, when the generation AI calculates a route, the route calculation unit takes into account past traffic data and weather information and updates the optimal route in real time. For example, the route is adjusted based on congestion information and weather forecasts. The route calculation unit also calculates the optimal route based on past traffic data and weather information and updates it in real time. For example, it suggests routes that should be avoided in rainy weather. The route calculation unit also takes into account traffic data and weather information when the generation AI calculates a route and updates the optimal route in real time. For example, it reflects information on traffic accidents and construction work. This allows the optimal route to be updated in real time, taking into account past traffic data and weather information.

[0053] The tourist destination suggestion unit can suggest tourist destinations customized based on the user's preferences and past visit history. For example, the tourist destination suggestion unit makes customized suggestions based on the user's preferences and past visit history for tourist destinations suggested by the generation AI. For example, it prioritizes suggestions of theme parks and museums that the user likes. The tourist destination suggestion unit also suggests tourist destinations customized by the generation AI based on the user's preferences and past visit history. For example, it suggests places similar to tourist destinations that the user has visited in the past. The tourist destination suggestion unit also suggests customized tourist destinations by having the generation AI analyze the user's preferences and past visit history. For example, it proposes plans that include natural landscapes and historical buildings that the user likes. This makes it possible to suggest tourist destinations customized based on the user's preferences and past visit history.

[0054] The tourist destination suggestion unit can use the emotion estimation function to analyze the emotions the user is feeling when calculating a route and suggest tourist destinations that will elicit positive emotions. For example, the tourist destination suggestion unit can use the emotion estimation function to analyze the emotions the user is feeling when calculating a route and suggest tourist destinations that will elicit positive emotions. For example, it can suggest relaxing natural scenery and fun activities. The tourist destination suggestion unit can also analyze the user's emotions in real time and suggest tourist destinations that will elicit positive emotions. For example, it can suggest plans that include events and festivals that the user can enjoy. The tourist destination suggestion unit can also use the emotion estimation function to analyze the emotions the user is feeling when calculating a route and suggest tourist destinations that will elicit positive emotions. For example, it can suggest plans that include activities that are useful for relieving stress. In this way, it is possible to analyze the user's emotions and suggest tourist destinations that will elicit positive emotions.

[0055] The tourist destination suggestion unit can display reviews and ratings from other users in real time based on the destination and method of travel input by the user, for reference. The tourist destination suggestion unit, for example, displays reviews and ratings from other users in real time based on the destination and method of travel input by the user. For example, it displays ratings for a specific tourist destination or route. The tourist destination suggestion unit also displays reviews and ratings from other users in real time for reference by the user. For example, it displays comments and photos from past travelers. The tourist destination suggestion unit also displays reviews and ratings from other users in real time based on the information input by the user, for reference. For example, it displays ratings for a specific restaurant or accommodation. This allows reviews and ratings from other users to be displayed in real time for reference.

[0056] The tourist destination suggestion unit can simultaneously provide information on events and festivals that the user may be interested in based on the destination and mode of travel input by the user. The tourist destination suggestion unit provides information on events and festivals that the user may be interested in, for example, based on the destination and mode of travel input by the user. For example, it displays events held in a particular season. Furthermore, the tourist destination suggestion unit simultaneously provides information on events and festivals that the user may be interested in when the user inputs the destination and mode of travel. For example, it displays information on local festivals and cultural events. Furthermore, the tourist destination suggestion unit provides information on events and festivals that the user may be interested in based on the information input by the user. For example, it displays information on music festivals and art exhibitions. In this way, it is possible to simultaneously provide information on events and festivals that the user may be interested in.

[0057] The tourist destination suggestion unit can use the emotion estimation function to suggest relaxing spots and activities based on the emotion the user is feeling at the time of input. The tourist destination suggestion unit, for example, uses the emotion estimation function to suggest relaxing spots and activities based on the emotion the user is feeling at the time of input. For example, it suggests hot spring resorts and relaxation facilities. The tourist destination suggestion unit also analyzes the user's emotion in real time to suggest relaxing spots and activities. For example, it suggests plans that include nature walks and yoga classes. The tourist destination suggestion unit also uses the emotion estimation function to suggest relaxing spots and activities based on the emotion the user is feeling at the time of input. For example, it suggests quiet beaches and parks. In this way, it is possible to suggest relaxing spots and activities based on the user's emotion.

[0058] The tourist destination suggestion unit can learn the user's past travel history and preferences and propose individually customized travel plans. The tourist destination suggestion unit, for example, analyzes the user's past travel history and proposes travel plans that match the preferences. For example, suggestions are made based on data on tourist destinations and accommodations visited in the past. The tourist destination suggestion unit also learns the user's preferences and proposes individually customized travel plans. For example, it prioritizes suggestions of activities and dining spots that the user prefers. The tourist destination suggestion unit also proposes customized travel plans based on the user's past travel history and preferences. For example, it proposes plans that include theme parks and natural scenery that the user prefers. In this way, the tourist destination suggestion unit can learn the user's past travel history and preferences and propose individually customized travel plans.

[0059] The tourist destination suggestion unit can refer to past travel data and suggest the most popular routes and tourist destinations based on the destination and method of travel input by the user. The tourist destination suggestion unit, for example, refers to past travel data and suggests the most popular routes and tourist destinations based on the destination and method of travel input by the user. For example, tourist destinations and routes that have been visited by many travelers in the past are preferentially displayed. The tourist destination suggestion unit also analyzes past travel data based on the information input by the user and suggests popular tourist destinations and routes. For example, it suggests tourist destinations that are good to visit in a particular season. The tourist destination suggestion unit also suggests routes and tourist destinations that are optimal for the destination and method of travel input by the user based on the past travel data. For example, it refers to reviews and ratings from past travelers. In this way, it is possible to refer to past travel data and suggest the most popular routes and tourist destinations.

[0060] The tourist destination suggestion unit can use the emotion estimation function to analyze the emotion the user is feeling when entering information and suggest destinations and transportation methods that will elicit positive emotions. For example, the tourist destination suggestion unit can analyze the emotion the user is feeling when entering information and suggest destinations and transportation methods that will elicit positive emotions. For example, it can suggest relaxing hot spring resorts and places rich in nature. The tourist destination suggestion unit can also use the emotion estimation function to analyze the emotion the user is feeling when entering information and suggest destinations and transportation methods that will elicit positive emotions. For example, it can suggest a plan that includes activities that are useful for relieving stress. The tourist destination suggestion unit can also analyze the user's emotions in real time and suggest destinations and transportation methods that will elicit positive emotions. For example, it can suggest a plan that includes events and festivals that the user can enjoy. In this way, it is possible to analyze the user's emotions and suggest destinations and transportation methods that will elicit positive emotions.

[0061] The tourist destination suggestion unit can display other users' reviews and ratings in real time for tourist destinations suggested by the generation AI for reference. The tourist destination suggestion unit, for example, displays other users' reviews and ratings in real time for tourist destinations suggested by the generation AI. For example, it displays ratings for specific tourist destinations or routes. The tourist destination suggestion unit also displays other users' reviews and ratings in real time for reference. For example, it displays comments and photos from past travelers. The tourist destination suggestion unit also displays other users' reviews and ratings in real time for reference. For example, it displays ratings for specific restaurants or accommodations. This allows other users' reviews and ratings to be displayed in real time for reference.

[0062] The tourist destination suggestion unit can make customized suggestions based on the user's preferences and past visit history for tourist destinations suggested by the generation AI. For example, the tourist destination suggestion unit makes customized suggestions based on the user's preferences and past visit history for tourist destinations suggested by the generation AI. For example, it prioritizes suggestions of theme parks and museums that the user likes. The tourist destination suggestion unit also makes customized suggestions of tourist destinations based on the user's preferences and past visit history. For example, it suggests places similar to tourist destinations that the user has visited in the past. The tourist destination suggestion unit also analyzes the user's preferences and past visit history and makes customized suggestions of tourist destinations. For example, it proposes plans that include natural landscapes and historical buildings that the user likes. This makes it possible to propose customized tourist destinations based on the user's preferences and past visit history.

[0063] The tourist destination suggestion unit can simultaneously suggest activities and events that the user may be interested in when the generation AI calculates a route. For example, the tourist destination suggestion unit simultaneously suggests activities and events that the user may be interested in when the generation AI calculates a route. For example, it displays events and activities that are held in a particular season. The tourist destination suggestion unit also simultaneously suggests activities and events that the user may be interested in. For example, it displays information about local festivals and cultural events. The tourist destination suggestion unit also simultaneously suggests activities and events that the user may be interested in when the generation AI calculates a route. For example, it displays information about music festivals and art exhibitions. This makes it possible to simultaneously suggest activities and events that the user may be interested in.

[0064] The tourist destination suggestion unit can include reviews and ratings from past visitors in the detailed information about tourist destinations provided by the generation AI so that users can refer to it. For example, the tourist destination suggestion unit includes reviews and ratings from past visitors in the detailed information about tourist destinations provided by the generation AI. For example, it displays the tourist destination's rating score and comments. The tourist destination suggestion unit also provides detailed information about tourist destinations based on the reviews and ratings from past visitors. For example, it displays photos and videos of visitors. The tourist destination suggestion unit also includes reviews and ratings from past visitors in the detailed information about tourist destinations provided by the generation AI so that users can refer to it. For example, it displays visitor experiences and recommended points. This allows users to refer to the information, including the reviews and ratings from past visitors.

[0065] The tourist destination suggestion unit can include local guide and tour information in the detailed information of tourist destinations provided by the generation AI, allowing users to enjoy the experience even more. For example, the tourist destination suggestion unit includes local guide and tour information in the detailed information of tourist destinations provided by the generation AI. For example, it displays reservation information and prices for guided tours. The tourist destination suggestion unit also provides detailed information of tourist destinations by the generation AI based on the local guide and tour information. For example, it displays recommended routes and highlights by the guide. The tourist destination suggestion unit also includes local guide and tour information in the detailed information of tourist destinations provided by the generation AI, allowing users to enjoy the experience even more. For example, it displays information about special experience tours and events. This allows users to enjoy the experience even more, including local guide and tour information.

[0066] The tourist destination suggestion unit can include information about local culture and history in the detailed information about tourist destinations provided by the generation AI, allowing the user to gain a deeper understanding. For example, the tourist destination suggestion unit includes information about local culture and history in the detailed information about tourist destinations provided by the generation AI. For example, it explains the historical background and cultural significance of the tourist destination. The tourist destination suggestion unit also provides detailed information about tourist destinations based on information about local culture and history. For example, it displays information about traditional festivals and cultural events. The tourist destination suggestion unit also includes information about local culture and history in the detailed information about tourist destinations provided by the generation AI, allowing the user to gain a deeper understanding. For example, it displays details about historical buildings and cultural heritage sites. This allows the user to gain a deeper understanding by including information about local culture and history.

[0067] The tourist destination suggestion unit can include information about local specialties and souvenirs in the detailed information about tourist destinations provided by the generation AI, allowing users to enjoy their trips even more. For example, the tourist destination suggestion unit includes information about local specialties and souvenirs in the detailed information about tourist destinations provided by the generation AI. For example, it introduces local specialties and recommended souvenirs. The tourist destination suggestion unit also provides detailed information about tourist destinations based on the local specialties and souvenir information. For example, it displays where to purchase local specialties and prices. The tourist destination suggestion unit also includes information about local specialties and souvenirs in the detailed information about tourist destinations provided by the generation AI, allowing users to enjoy their trips even more. For example, it displays information about events where you can sample local specialties or try them out. This allows users to enjoy their trips even more, including information about local specialties and souvenirs.

[0068] The tourist destination suggestion unit can use the emotion estimation function to suggest relaxing spots and activities based on the emotions the user feels when viewing detailed information about the tourist destination. For example, the tourist destination suggestion unit can use the emotion estimation function to suggest relaxing spots and activities based on the emotions the user feels when viewing detailed information about the tourist destination. For example, it can suggest hot spring resorts and relaxation facilities. The tourist destination suggestion unit can also analyze the user's emotions in real time to suggest relaxing spots and activities. For example, it can suggest plans that include nature walks and yoga classes. The tourist destination suggestion unit can also use the emotion estimation function to suggest relaxing spots and activities based on the emotions the user feels when viewing detailed information about the tourist destination. For example, it can suggest quiet beaches and parks. In this way, it can suggest relaxing spots and activities based on the user's emotions.

[0069] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0070] The travel plan proposal system can further include a health management unit that monitors the user's health condition. For example, the system can obtain the user's heart rate and step count in real time and suggest rest spots and snacks based on the user's health condition. The health management unit can also suggest reasonable travel plans based on the user's health data. For example, it can suggest routes that avoid long travel times and tourist spots where moderate exercise is possible. This makes it possible to provide travel plans that take the user's health condition into consideration.

[0071] The travel plan proposal system can further include a meal proposal unit that takes into account the user's food preferences. For example, restaurants and cafes along the route can be proposed based on the user's input of their preferred cuisine types and allergy information. The meal proposal unit can also propose local specialties and recommended dining spots based on the user's food preferences. For example, if the user is vegetarian, vegetarian restaurants can be preferentially proposed. This makes it possible to provide a travel plan that takes into account the user's food preferences.

[0072] The travel plan suggestion system can further include a budget management unit that takes into account the user's budget. For example, if the user inputs the budget they can spend on their trip, the system can suggest tourist spots and accommodations that can be enjoyed within that budget. The budget management unit can also suggest cost-effective plans based on the user's budget. For example, it can suggest discount information and great value package tours. This makes it possible to provide travel plans that take the user's budget into consideration.

[0073] The travel plan proposal system may further include an activity proposal unit that proposes activities that interest the user. For example, the activity proposal unit proposes activity spots along the route based on the user's input of an activity that interests the user. The activity proposal unit may also propose special experiences or events based on the user's interests. For example, if the user is interested in adventure sports, the activity proposal unit may propose spots for rafting or paragliding. This makes it possible to provide a travel plan that includes activities that interest the user.

[0074] The travel plan suggestion system can also estimate the user's emotions and suggest relaxing spots based on the estimated emotions. For example, if the user is feeling stressed, hot springs or relaxation facilities can be suggested. The emotion suggestion function can also be used to suggest active activities or events if the user is enjoying themselves. For example, if the user is excited, adventure sports or live events can be suggested. This makes it possible to provide travel plans based on the user's emotions.

[0075] The travel plan suggestion system can further estimate the user's emotions and suggest meals based on the estimated emotions. For example, if the user is tired, it can suggest relaxing cafes and snacks. Also, using the emotion estimation function, it can suggest special dinners or local specialties if the user is having fun. For example, if the user is excited, it can suggest lively restaurants and bars. This makes it possible to suggest meals based on the user's emotions.

[0076] The travel plan suggestion system can also estimate the user's emotions and suggest accommodations based on the estimated emotions. For example, if the user wants to relax, a quiet resort hotel or hot spring inn can be suggested. Also, using the emotion suggestion function, if the user is feeling active, a hotel or hostel with plenty of activities can be suggested. For example, if the user is excited, a hotel in an urban area with a good nightlife can be suggested. This makes it possible to suggest accommodations based on the user's emotions.

[0077] The travel plan suggestion system can further estimate the user's emotions and suggest transportation methods based on the estimated emotions. For example, if the user is tired, it can suggest comfortable transportation methods and routes that include rest stops. Also, using the emotion suggestion function, if the user is enjoying themselves, it can suggest transportation methods and routes that allow for scenic views. For example, if the user is excited, it can suggest sightseeing trains and cruises. In this way, it is possible to suggest transportation methods based on the user's emotions.

[0078] The travel plan suggestion system can also estimate the user's emotions and suggest tourist spots based on the estimated emotions. For example, if the user wants to relax, quiet natural landscapes or parks can be suggested. Also, using the emotion suggestion function, if the user is feeling active, tourist spots or theme parks with plenty of activities can be suggested. For example, if the user is excited, adventure sports or live events can be suggested. This makes it possible to suggest tourist spots based on the user's emotions.

[0079] The travel plan suggestion system can further estimate the user's emotions and adjust the entire travel plan based on the estimated emotions. For example, if the user is feeling stressed, the system can suggest a plan that includes many relaxing spots and activities. Also, using the emotion estimation function, if the user is having fun, the system can suggest a plan that includes many active activities and events. For example, if the user is excited, the system can suggest a plan that includes many adventure sports and live events. This makes it possible to provide an entire travel plan based on the user's emotions.

[0080] The processing flow of the second embodiment will be briefly explained below.

[0081] Step 1: The destination input unit inputs the user's destination. For example, the user inputs information such as "travel from Tokyo to Kyoto by car." Step 2: The transportation method input unit inputs the user's transportation method, such as car, train, or bus. Step 3: The route calculation unit calculates the optimal route based on the information entered by the destination input unit and the transportation method input unit. For example, the generation AI calculates the optimal route based on the entered information, taking into account tourist attractions and detour spots along the route. Step 4: The tourist spot suggestion unit suggests tourist spots along the route calculated by the route calculation unit. For example, the generation AI might suggest tourist spots and detour spots based on a prompt such as, "Please suggest tourist spots along the route from Tokyo to Kyoto."

[0082] 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.

[0083] 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.

[0084] 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.

[0085] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0086] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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).

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0101] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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).

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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).

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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).

[0135] 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.

[0136] 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."

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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]

[0149] 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 destination input unit for inputting a user's destination; a movement method input unit for inputting a movement method; a route calculation unit that calculates an optimal route based on the information input by the destination input unit and the travel method input unit; a tourist spot suggestion unit that suggests tourist spots on the route calculated by the route calculation unit. A system characterized by:

2. The route calculation unit Taking into account past traffic data and weather information, the optimal route is updated in real time.

2. The system of claim 1.

3. The tourist destination suggestion unit Proposing customized tourist spots based on the user's preferences and past visit history 2. The system of claim 1.

4. The tourist destination suggestion unit Analyze the emotions felt by the user when calculating the route and suggest tourist spots that elicit positive emotions 2. The system of claim 1.

5. The tourist destination suggestion unit Based on the destination and travel method entered by the user, reviews and ratings from other users are displayed in real time for reference.

2. The system of claim 1.

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