System

Abstract

An object of a system according to an embodiment is to automatically provide surrounding information during movement and to make a movement experience more enjoyable.SOLUTION: A system includes a word-of-mouth information providing part, an area information providing part, a coupon information providing part, a mile management part, and a health management part. The word-of-mouth information providing portion automatically provides word-of-mouth information around the current location when the user is strolling or driving. The area information providing unit provides history, local news, event information, trivia, and the like of an area where the user is currently present. The coupon information providing unit allows the user to receive coupon information around the current location. The mile manager may earn points according to the distance walked by the user. The health management unit supports diet and health management of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology does not adequately provide systems that automatically provide information about the surrounding area while moving, and there is room for improvement.

[0005] The system according to the embodiment aims to automatically provide surrounding information while traveling, making the travel experience more enjoyable. [Means for solving the problem]

[0006] The system according to the embodiment includes a word-of-mouth information providing unit, an area information providing unit, a coupon information providing unit, a mile management unit, and a health management unit. The word-of-mouth information providing unit automatically provides word-of-mouth information about the area around the user's current location while the user is walking or driving. The area information providing unit provides the history, local news, event information, trivia, etc. of the area where the user is currently located. The coupon information providing unit allows the user to receive coupon information about the area around the user's current location. The mile management unit allows the user to earn points according to the distance walked. The health management unit supports the user in dieting and health management. [Effects of the Invention]

[0007] The system according to the embodiment automatically provides surrounding information while traveling, making the travel experience more enjoyable. [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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

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

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

[0028] (Example 1) The city walking app according to the embodiment of the present invention is a system that automatically provides word-of-mouth information about the area around the user's current location and introduces area information and coupon information while the user is walking or driving. This makes the city walking app more enjoyable for the user and also supports health management.

[0029] A city walking app according to an embodiment includes a word-of-mouth information providing unit, an area information providing unit, a coupon information providing unit, a mile management unit, and a health management unit. The word-of-mouth information providing unit automatically provides word-of-mouth information about the area around the user's current location while the user is walking or driving. For example, when the user passes by a cafe, word-of-mouth information about the cafe is automatically displayed. The word-of-mouth information providing unit can also automatically display word-of-mouth information about a restaurant when the user passes by the restaurant. The word-of-mouth information providing unit can also automatically display word-of-mouth information about a tourist spot when the user visits the tourist spot. The area information providing unit provides the history, local news, event information, trivia, etc. of the area where the user is currently located. For example, when the user visits a tourist spot, the history of the tourist spot and related anecdotes are displayed. The area information providing unit can also provide local news and event information about the area when the user visits the area. The area information providing unit can also provide trivia information about the location when the user visits the location. The coupon information providing unit allows the user to receive coupon information about the area around the user's current location. For example, when a user passes near a certain restaurant, a discount coupon for that restaurant is displayed. The coupon information providing unit can also provide coupon information for a certain shop when the user passes near that shop. The coupon information providing unit can also provide coupon information for a certain facility when the user passes near that facility. The mile management unit is equipped with a mile function that allows the user to earn points based on the distance walked. For example, the user can earn a certain number of points for every kilometer walked, and these points can be exchanged for various benefits. The mile management unit can also provide bonus points when the user walks a specific distance. The mile management unit can also provide special rewards when the user achieves a goal set by the user. The health management unit is equipped with a function to support the user's diet and health management. For example, the health management unit records the user's number of steps and calories burned and provides advice on achieving goals.The health management unit can also record the user's diet and suggest balanced meals. The health management unit can also record the user's exercise history and provide an effective exercise plan. As a result, the city walking app according to the embodiment can make the user's travel experience more enjoyable and support health management. For example, the user can discover a new cafe while walking or learn about and participate in an event, making travel a more enjoyable experience. Furthermore, by utilizing the mile function and health management function, the user can live a healthy life.

[0030] The word-of-mouth information providing unit can use the generation AI to preferentially display the most interesting word-of-mouth information based on the user's past behavioral history and preferences. The word-of-mouth information providing unit, for example, analyzes the user's past visit history and search history, and the generation AI preferentially displays the most interesting word-of-mouth information based on that data. For example, word-of-mouth information about cafes and restaurants that the user has visited in the past is preferentially displayed. The word-of-mouth information providing unit can also display interesting word-of-mouth information based on the user's preferences. For example, word-of-mouth information about the user's favorite dishes and drinks is preferentially displayed. The word-of-mouth information providing unit can also display interesting word-of-mouth information based on the user's behavioral history. For example, word-of-mouth information about areas that the user frequently visits is preferentially displayed. This makes it possible to provide word-of-mouth information based on the user's interests.

[0031] The word-of-mouth information providing unit can collect real-time user ratings for word-of-mouth information and preferentially display word-of-mouth information with high ratings. The word-of-mouth information providing unit, for example, builds a system that collects user ratings for word-of-mouth information in real time and preferentially displays information with high ratings. For example, the word-of-mouth information providing unit ranks the word-of-mouth information based on star ratings or the number of comments. The word-of-mouth information providing unit can also display word-of-mouth information based on user ratings. For example, word-of-mouth information for highly rated restaurants and cafes is preferentially displayed. The word-of-mouth information providing unit can also update the word-of-mouth information based on the ratings collected in real time. For example, when a new rating is added, the display order of the word-of-mouth information is changed. This allows word-of-mouth information with high ratings to be preferentially displayed.

[0032] The word-of-mouth information providing unit can automatically display advertisements for related products that may interest the user, in addition to word-of-mouth information. The word-of-mouth information providing unit, for example, builds a system that automatically displays advertisements for products related to word-of-mouth information. For example, an advertisement for a specific dish served at a restaurant is displayed together with word-of-mouth information about the restaurant. The word-of-mouth information providing unit can also display advertisements for products that may interest the user. For example, an advertisement for a drink served at a cafe is displayed together with word-of-mouth information about the cafe. The word-of-mouth information providing unit can also display advertisements for products related to word-of-mouth information. For example, an advertisement for souvenirs sold at a tourist destination is displayed together with word-of-mouth information about the tourist destination. This makes it possible to provide advertisements for related products that may interest the user.

[0033] The word-of-mouth information providing unit can provide word-of-mouth information by voice, allowing a user to obtain information without relying on vision while driving or walking. The word-of-mouth information providing unit, for example, builds a system that provides word-of-mouth information by voice, allowing a user to obtain information without relying on vision while driving or walking. For example, word-of-mouth information is provided by voice in conjunction with a navigation system. The word-of-mouth information providing unit can also provide word-of-mouth information by voice so that a user can obtain information without relying on vision. For example, word-of-mouth information is read aloud using a voice assistant on a smartphone. The word-of-mouth information providing unit can also provide word-of-mouth information by voice. For example, word-of-mouth information is provided by voice in conjunction with an in-vehicle system. This allows a user to obtain information without relying on vision while driving or walking.

[0034] The area information providing unit can use the generation AI to provide area information customized based on the user's interests and concerns. For example, the area information providing unit uses the generation AI to analyze the user's past behavioral history and search history and provide area information customized based on the user's interests and concerns. For example, if the user is interested in history, historical information about that area is displayed preferentially. The area information providing unit can also provide area information customized based on the user's interests and concerns. For example, if the user is interested in art, art gallery information in that area is displayed preferentially. The area information providing unit can also use the generation AI to provide area information based on the user's interests and concerns. For example, if the user is interested in gourmet food, restaurant information in that area is displayed preferentially. This makes it possible to provide area information based on the user's interests and concerns.

[0035] The area information providing unit can collect user feedback on the area information and improve the accuracy of the information based on the feedback. The area information providing unit, for example, collects user feedback on the area information and builds a system that improves the accuracy of the information based on the feedback. For example, users rate and comment on the provided information. The area information providing unit can also update the area information based on the user feedback. For example, when new feedback is added, the content of the area information is revised. The area information providing unit can also improve the accuracy of the area information based on the feedback. For example, information that has been highly rated by users is preferentially displayed. This improves the accuracy of the area information based on the user feedback.

[0036] The area information providing unit visually displays area information using AR technology, allowing the user to experience the experience of actually visiting the location. The area information providing unit, for example, builds a system that visually displays area information using AR technology, allowing the user to experience the experience of actually visiting the location. For example, the area information is displayed by overlaying it using a smartphone camera. The area information providing unit can also display information using AR technology so that the user can visually experience the area information. For example, the area information is displayed using AR glasses. The area information providing unit can also use AR technology to allow the user to experience the experience of actually visiting the location. For example, the area information is displayed using projection mapping. This allows the user to experience the experience of actually visiting the location.

[0037] The area information providing unit can add a function that allows area information to be shared with other users, thereby promoting community-based information exchange. The area information providing unit, for example, adds a function that allows area information to be shared with other users, and builds a system that promotes community-based information exchange. For example, information about places that a user has visited is shared on a social networking service. The area information providing unit can also promote the formation of a community by allowing users to share area information with other users. For example, area information is shared using a forum or chat function. The area information providing unit can also promote information exchange between users by sharing area information. For example, word-of-mouth information about places that a user has visited is shared. This can promote community-based information exchange.

[0038] The coupon information providing unit can use the generation AI to provide optimal coupon information based on the user's purchasing history and preferences. The coupon information providing unit, for example, uses the generation AI to analyze the user's past purchasing history and preferences and build a system that provides optimal coupon information. For example, coupons related to products that the user frequently purchases are preferentially displayed. The coupon information providing unit can also provide optimal coupon information based on the user's purchasing history. For example, coupons related to products that the user has purchased in the past are displayed. The coupon information providing unit can also use the generation AI to provide coupon information based on the user's preferences. For example, coupons related to products of the user's favorite brand are displayed. This makes it possible to provide optimal coupon information based on the user's purchasing history and preferences.

[0039] The coupon information providing unit can track coupon usage status in real time and prioritize displaying frequently used coupons. The coupon information providing unit, for example, builds a system that tracks coupon usage status in real time and prioritizes displaying frequently used coupons. For example, coupons that are frequently used by users are prioritized. The coupon information providing unit can also display coupon information based on coupon usage status. For example, coupons that are frequently used are prioritized. The coupon information providing unit can also update coupon information based on usage status tracked in real time. For example, when new usage status is added, the display order of coupon information is changed. This allows frequently used coupons to be prioritized.

[0040] The coupon information providing unit can add a function that allows coupon information to be linked with an SNS and shared with friends and family. The coupon information providing unit, for example, builds a system that adds a function that allows coupon information to be linked with an SNS and shared with friends and family. For example, a coupon acquired by a user is shared on an SNS. The coupon information providing unit can also promote coupon use by allowing users to share coupon information with friends and family. For example, coupon information is shared through an SNS. The coupon information providing unit can also promote information exchange between users by sharing coupon information. For example, the usage status of coupons acquired by a user is shared. This allows coupon information to be shared with friends and family.

[0041] The coupon information providing unit can provide coupon information by voice, allowing the user to obtain information without relying on vision while driving or walking. The coupon information providing unit, for example, builds a system that provides coupon information by voice, allowing the user to obtain information without relying on vision while driving or walking. For example, the coupon information is provided by voice in conjunction with a navigation system. The coupon information providing unit can also provide coupon information by voice so that the user can obtain information without relying on vision. For example, the coupon information is read out using a voice assistant on a smartphone. The coupon information providing unit can also provide coupon information by voice. For example, the coupon information is provided by voice in conjunction with an in-vehicle system. This allows the user to obtain coupon information without relying on vision while driving or walking.

[0042] The mile management unit can use the generation AI to propose an optimal exercise plan based on the user's past exercise data, thereby promoting mile acquisition. The mile management unit, for example, uses the generation AI to analyze the user's past exercise data and build a system that proposes an optimal exercise plan. For example, it provides an exercise plan customized based on the user's exercise history. The mile management unit can also propose an optimal exercise plan based on the user's exercise data. For example, it provides an exercise plan tailored to the user's exercise habits. The mile management unit can also use the generation AI to propose an exercise plan based on the user's exercise data. For example, it provides an exercise plan tailored to the user's goals. This makes it possible to propose an optimal exercise plan based on the user's exercise data, promoting mile acquisition.

[0043] The mile management unit can display the mile acquisition status in real time and provide feedback to maintain the user's motivation. The mile management unit, for example, builds a system that displays the mile acquisition status in real time and provides feedback to maintain the user's motivation. For example, it displays the number of miles acquired and the goals achieved. The mile management unit can also provide feedback based on the user's mile acquisition status. For example, it displays the progress toward the goals set by the user. The mile management unit can also provide feedback based on the mile acquisition status displayed in real time. For example, it displays an encouraging message when the user achieves a goal. In this way, it is possible to display the mile acquisition status in real time and provide feedback to maintain the user's motivation.

[0044] The mile management unit can support comprehensive health management by linking the mile function with other fitness apps and sharing data. The mile management unit, for example, links the mile function with other fitness apps to build a system for sharing data. For example, a user's exercise data is integrated across multiple apps and displayed. The mile management unit can also support comprehensive health management by linking with other fitness apps. For example, the user's exercise data and diet data are shared. The mile management unit can also link with fitness apps to centrally manage the user's health data. For example, data collected by multiple apps is integrated and displayed. This allows for linking with other fitness apps to support comprehensive health management.

[0045] The mile management unit can provide events and challenges in which users can participate according to the miles earned, thereby promoting the formation of a community. The mile management unit, for example, builds a system that provides events and challenges in which users can participate according to the miles earned. For example, a walking event can be held in which users who have earned a certain number of miles can participate. The mile management unit can also promote the formation of a community by providing events and challenges in which users can participate. For example, it can provide challenges in which users compete against each other. The mile management unit can also promote interaction between users through events and challenges. For example, it can promote interaction at events in which users participate. In this way, events and challenges can be provided according to the miles earned, promoting the formation of a community.

[0046] The health management unit can use the generation AI to provide personalized health advice based on the user's health data. The health management unit, for example, uses the generation AI to analyze the user's health data and build a system that provides personalized health advice. For example, it provides advice customized based on the user's exercise history and dietary data. The health management unit can also provide personalized health advice based on the user's health data. For example, it provides advice tailored to the user's health condition. The health management unit can also use the generation AI to provide health advice based on the user's health data. For example, it provides advice tailored to the user's goals. This makes it possible to provide personalized health advice based on the user's health data.

[0047] The health management unit can be added with a function to analyze health management data in real time and issue an alert if an abnormality is detected. The health management unit, for example, builds a system that analyzes health management data in real time and issues an alert if an abnormality is detected. For example, an alert is issued when an abnormality in heart rate or blood pressure is detected. The health management unit can also analyze a user's health management data in real time and issue an alert if an abnormality is detected. For example, an alert is issued when an abnormal body temperature or blood sugar level is detected. The health management unit can also issue an alert if an abnormality is detected based on the health management data analyzed in real time. For example, an alert is issued when an abnormal heart rate or blood pressure is detected. In this way, health management data is analyzed in real time and an alert is issued if an abnormality is detected.

[0048] The health management unit can link the health management function with other medical apps to centrally manage comprehensive health data. The health management unit, for example, links the health management function with other medical apps to build a system that centrally manages comprehensive health data. For example, a user's exercise data and dietary data are integrated across multiple apps and displayed. The health management unit can also centrally manage comprehensive health data by linking with other medical apps. For example, centrally managing a user's health data supports comprehensive health management. The health management unit can also centrally manage a user's health data by linking with medical apps. For example, data collected by multiple apps is integrated and displayed. This allows for linking with other medical apps to centrally manage comprehensive health data.

[0049] The health management unit can visually display the health management data to enable the user to intuitively understand it. The health management unit, for example, builds a system that visually displays the health management data to enable the user to intuitively understand it. For example, the health management unit displays the health data using graphs and charts. The health management unit can also visually display the health management data to enable the user to intuitively understand it. For example, the health data is displayed using a dashboard. The health management unit can also visually display the health data to enable the user to intuitively understand it. For example, the health data is displayed using infographics. In this way, the health management data is visually displayed to enable the user to intuitively understand it.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The city walking app may further include a route suggestion unit that analyzes the user's movement patterns and suggests an optimal route. For example, when the user visits tourist spots, the route suggestion unit may suggest a route that efficiently goes around multiple tourist spots. The route suggestion unit may also suggest a route that includes interesting spots based on the user's preferences. For example, if the user likes to visit cafes, the route suggestion unit may suggest a route that includes many cafes. The route suggestion unit may also suggest an optimal route taking into account the user's travel time. For example, the route suggestion unit may suggest a route that allows the user to enjoy sightseeing within a limited time. This may further improve the user's travel experience.

[0052] The city walking app may also include a recommendation unit that analyzes the user's movement history and recommends places visited in the past. For example, it may suggest that the user revisit a cafe or restaurant that the user has visited in the past. The recommendation unit may also suggest new spots related to places visited in the past based on the user's preferences. For example, it may suggest a new restaurant that serves a dish that the user likes. The recommendation unit may also provide event information for places visited in the past based on the user's movement history. For example, it may suggest events held at tourist spots that the user has visited in the past. This may further enhance the user's movement experience.

[0053] The city walking app may further include a rest spot suggestion unit that analyzes the user's movement data and suggests optimal rest spots. For example, after the user has walked for a long time, a nearby cafe or park may be suggested. The rest spot suggestion unit may also suggest interesting rest spots based on the user's preferences. For example, if the user likes nature, a park rich in nature may be suggested. The rest spot suggestion unit may also suggest optimal times to take a break based on the user's movement data. For example, it may suggest taking a break after the user has walked a certain distance. This may make the user's travel experience even more comfortable.

[0054] The city walking app may further include a shopping spot suggestion unit that analyzes the user's movement data and suggests optimal shopping spots. For example, when the user visits a shopping area, the unit suggests popular shops nearby. The shopping spot suggestion unit may also suggest interesting shopping spots based on the user's preferences. For example, if the user is interested in fashion, the unit may suggest fashion-related shops. The shopping spot suggestion unit may also suggest optimal shopping times based on the user's movement data. For example, the unit may suggest shopping after the user has walked a certain distance. This may further enhance the user's movement experience.

[0055] The city walking app may further include a tourist route suggestion unit that analyzes the user's movement data and suggests an optimal tourist route. For example, when the user visits tourist spots, the system may suggest a route that efficiently visits multiple tourist spots. The tourist route suggestion unit may also suggest a route that includes interesting tourist spots based on the user's preferences. For example, if the user is interested in history, the system may suggest a route that includes many historical tourist spots. The tourist route suggestion unit may also suggest an optimal tourist route taking into account the user's travel time. For example, the system may suggest a route that allows the user to enjoy sightseeing within a limited time. This may further improve the user's sightseeing experience.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The review information provider automatically provides reviews of the area around the user's current location while the user is walking or driving. For example, when the user passes by a cafe, restaurant, or tourist spot, the reviews are automatically displayed. Step 2: The area information provider provides the user with the history, local news, event information, trivia, etc. of the area they are currently in. For example, when a user visits a tourist spot or region, the user will be shown the history of that location, related episodes, local news, event information, and trivia. Step 3: The coupon information providing unit allows the user to receive coupon information for the area around the user's current location. For example, when the user passes by a restaurant, shop, or facility, discount coupons and coupon information for that location are displayed. Step 4: The mileage management unit can earn points according to the distance the user walks. For example, the user can earn a certain number of points for every kilometer they walk, and the points can be exchanged for rewards. It can also provide bonus points or special rewards when a certain distance is walked. Step 5: The health management section supports the user's diet and health management. For example, it records the user's steps and calories burned and provides advice on how to achieve goals. It can also record dietary information and suggest balanced meals, and record exercise history to provide effective exercise plans.

[0058] (Example 2) The city walking app according to the embodiment of the present invention is a system that automatically provides word-of-mouth information about the area around the user's current location and introduces area information and coupon information while the user is walking or driving. This makes the city walking app more enjoyable for the user and also supports health management.

[0059] A city walking app according to an embodiment includes a word-of-mouth information providing unit, an area information providing unit, a coupon information providing unit, a mile management unit, and a health management unit. The word-of-mouth information providing unit automatically provides word-of-mouth information about the area around the user's current location while the user is walking or driving. For example, when the user passes by a cafe, word-of-mouth information about the cafe is automatically displayed. The word-of-mouth information providing unit can also automatically display word-of-mouth information about a restaurant when the user passes by the restaurant. The word-of-mouth information providing unit can also automatically display word-of-mouth information about a tourist spot when the user visits the tourist spot. The area information providing unit provides the history, local news, event information, trivia, etc. of the area where the user is currently located. For example, when the user visits a tourist spot, the history of the tourist spot and related anecdotes are displayed. The area information providing unit can also provide local news and event information about the area when the user visits the area. The area information providing unit can also provide trivia information about the location when the user visits the location. The coupon information providing unit allows the user to receive coupon information about the area around the user's current location. For example, when a user passes near a certain restaurant, a discount coupon for that restaurant is displayed. The coupon information providing unit can also provide coupon information for a certain shop when the user passes near that shop. The coupon information providing unit can also provide coupon information for a certain facility when the user passes near that facility. The mile management unit is equipped with a mile function that allows the user to earn points based on the distance walked. For example, the user can earn a certain number of points for every kilometer walked, and these points can be exchanged for various benefits. The mile management unit can also provide bonus points when the user walks a specific distance. The mile management unit can also provide special rewards when the user achieves a goal set by the user. The health management unit is equipped with a function to support the user's diet and health management. For example, the health management unit records the user's number of steps and calories burned and provides advice on achieving goals.The health management unit can also record the user's diet and suggest balanced meals. The health management unit can also record the user's exercise history and provide an effective exercise plan. As a result, the city walking app according to the embodiment can make the user's travel experience more enjoyable and support health management. For example, the user can discover a new cafe while walking or learn about and participate in an event, making travel a more enjoyable experience. Furthermore, by utilizing the mile function and health management function, the user can live a healthy life.

[0060] The word-of-mouth information providing unit can use the generation AI to preferentially display the most interesting word-of-mouth information based on the user's past behavioral history and preferences. The word-of-mouth information providing unit, for example, analyzes the user's past visit history and search history, and the generation AI preferentially displays the most interesting word-of-mouth information based on that data. For example, word-of-mouth information about cafes and restaurants that the user has visited in the past is preferentially displayed. The word-of-mouth information providing unit can also display interesting word-of-mouth information based on the user's preferences. For example, word-of-mouth information about the user's favorite dishes and drinks is preferentially displayed. The word-of-mouth information providing unit can also display interesting word-of-mouth information based on the user's behavioral history. For example, word-of-mouth information about areas that the user frequently visits is preferentially displayed. This makes it possible to provide word-of-mouth information based on the user's interests.

[0061] The word-of-mouth information providing unit can collect real-time user ratings for word-of-mouth information and preferentially display word-of-mouth information with high ratings. The word-of-mouth information providing unit, for example, builds a system that collects user ratings for word-of-mouth information in real time and preferentially displays information with high ratings. For example, the word-of-mouth information providing unit ranks the word-of-mouth information based on star ratings or the number of comments. The word-of-mouth information providing unit can also display word-of-mouth information based on user ratings. For example, word-of-mouth information for highly rated restaurants and cafes is preferentially displayed. The word-of-mouth information providing unit can also update the word-of-mouth information based on the ratings collected in real time. For example, when a new rating is added, the display order of the word-of-mouth information is changed. This allows word-of-mouth information with high ratings to be preferentially displayed.

[0062] The word-of-mouth information providing unit can use the emotion estimation function to provide word-of-mouth information tailored to the user's current emotional state. The word-of-mouth information providing unit, for example, uses the emotion estimation function to analyze the user's current emotional state and build a system that provides word-of-mouth information tailored to that emotion. For example, when the user is relaxed, word-of-mouth information about cafes is displayed. The word-of-mouth information providing unit can also display word-of-mouth information based on the user's emotional state. For example, when the user is excited, word-of-mouth information about activities is displayed. The word-of-mouth information providing unit can also use the emotion estimation function to provide word-of-mouth information according to the user's emotional state. For example, when the user is tired, word-of-mouth information about relaxation facilities is displayed. This makes it possible to provide word-of-mouth information tailored to the user's emotional state.

[0063] The word-of-mouth information providing unit can automatically display advertisements for related products that may interest the user, in addition to word-of-mouth information. The word-of-mouth information providing unit, for example, builds a system that automatically displays advertisements for products related to word-of-mouth information. For example, an advertisement for a specific dish served at a restaurant is displayed together with word-of-mouth information about the restaurant. The word-of-mouth information providing unit can also display advertisements for products that may interest the user. For example, an advertisement for a drink served at a cafe is displayed together with word-of-mouth information about the cafe. The word-of-mouth information providing unit can also display advertisements for products related to word-of-mouth information. For example, an advertisement for souvenirs sold at a tourist destination is displayed together with word-of-mouth information about the tourist destination. This makes it possible to provide advertisements for related products that may interest the user.

[0064] The word-of-mouth information providing unit can provide word-of-mouth information by voice, allowing a user to obtain information without relying on vision while driving or walking. The word-of-mouth information providing unit, for example, builds a system that provides word-of-mouth information by voice, allowing a user to obtain information without relying on vision while driving or walking. For example, word-of-mouth information is provided by voice in conjunction with a navigation system. The word-of-mouth information providing unit can also provide word-of-mouth information by voice so that a user can obtain information without relying on vision. For example, word-of-mouth information is read aloud using a voice assistant on a smartphone. The word-of-mouth information providing unit can also provide word-of-mouth information by voice. For example, word-of-mouth information is provided by voice in conjunction with an in-vehicle system. This allows a user to obtain information without relying on vision while driving or walking.

[0065] The word-of-mouth information providing unit can use the emotion estimation function to provide information on events and activities that the user is interested in in real time. The word-of-mouth information providing unit, for example, uses the emotion estimation function to analyze the emotional state of the user and build a system that provides information on events and activities that match that state in real time. For example, if the user is having fun, entertainment information is provided. The word-of-mouth information providing unit can also provide information on events and activities based on the emotional state of the user. For example, if the user is relaxed, relaxation-related information is provided. The word-of-mouth information providing unit can also use the emotion estimation function to provide information on events and activities that the user is likely to be interested in. For example, if the user is excited, activity information is provided. This makes it possible to provide information on events and activities that the user is likely to be interested in.

[0066] The area information providing unit can use the generation AI to provide area information customized based on the user's interests and concerns. For example, the area information providing unit uses the generation AI to analyze the user's past behavioral history and search history and provide area information customized based on the user's interests and concerns. For example, if the user is interested in history, historical information about that area is displayed preferentially. The area information providing unit can also provide area information customized based on the user's interests and concerns. For example, if the user is interested in art, art gallery information in that area is displayed preferentially. The area information providing unit can also use the generation AI to provide area information based on the user's interests and concerns. For example, if the user is interested in gourmet food, restaurant information in that area is displayed preferentially. This makes it possible to provide area information based on the user's interests and concerns.

[0067] The area information providing unit can collect user feedback on the area information and improve the accuracy of the information based on the feedback. The area information providing unit, for example, collects user feedback on the area information and builds a system that improves the accuracy of the information based on the feedback. For example, users rate and comment on the provided information. The area information providing unit can also update the area information based on the user feedback. For example, when new feedback is added, the content of the area information is revised. The area information providing unit can also improve the accuracy of the area information based on the feedback. For example, information that has been highly rated by users is preferentially displayed. This improves the accuracy of the area information based on the user feedback.

[0068] The area information providing unit can use the emotion estimation function to provide area information tailored to the user's current emotional state. The area information providing unit, for example, uses the emotion estimation function to analyze the user's current emotional state and builds a system that provides area information tailored to that emotion. For example, when the user is relaxed, information about quiet places is displayed. The area information providing unit can also provide area information based on the user's emotional state. For example, when the user is excited, activity information is displayed. The area information providing unit can also use the emotion estimation function to provide area information according to the user's emotional state. For example, when the user is tired, information about relaxation facilities is displayed. This makes it possible to provide area information tailored to the user's emotional state.

[0069] The area information providing unit visually displays area information using AR technology, allowing the user to experience the experience of actually visiting the location. The area information providing unit, for example, builds a system that visually displays area information using AR technology, allowing the user to experience the experience of actually visiting the location. For example, the area information is displayed by overlaying it using a smartphone camera. The area information providing unit can also display information using AR technology so that the user can visually experience the area information. For example, the area information is displayed using AR glasses. The area information providing unit can also use AR technology to allow the user to experience the experience of actually visiting the location. For example, the area information is displayed using projection mapping. This allows the user to experience the experience of actually visiting the location.

[0070] The area information providing unit can add a function that allows area information to be shared with other users, thereby promoting community-based information exchange. The area information providing unit, for example, adds a function that allows area information to be shared with other users, and builds a system that promotes community-based information exchange. For example, information about places that a user has visited is shared on a social networking service. The area information providing unit can also promote the formation of a community by allowing users to share area information with other users. For example, area information is shared using a forum or chat function. The area information providing unit can also promote information exchange between users by sharing area information. For example, word-of-mouth information about places that a user has visited is shared. This can promote community-based information exchange.

[0071] The area information providing unit can use the emotion estimation function to provide information about the history and culture of an area that is likely to interest the user. The area information providing unit, for example, uses the emotion estimation function to analyze the user's emotional state and build a system that provides information about the history and culture of an area that is tailored to that state. For example, historical episodes that are likely to interest the user are displayed. The area information providing unit can also provide information about the history and culture of an area based on the user's emotional state. For example, if the user is relaxed, relaxation-related history and cultural information is provided. The area information providing unit can also use the emotion estimation function to provide information about the history and culture of an area that is likely to interest the user. For example, activity-related history and cultural information is provided if the user is excited. This makes it possible to provide information about the history and culture of an area that is likely to interest the user.

[0072] The coupon information providing unit can use the generation AI to provide optimal coupon information based on the user's purchasing history and preferences. The coupon information providing unit, for example, uses the generation AI to analyze the user's past purchasing history and preferences and build a system that provides optimal coupon information. For example, coupons related to products that the user frequently purchases are preferentially displayed. The coupon information providing unit can also provide optimal coupon information based on the user's purchasing history. For example, coupons related to products that the user has purchased in the past are displayed. The coupon information providing unit can also use the generation AI to provide coupon information based on the user's preferences. For example, coupons related to products of the user's favorite brand are displayed. This makes it possible to provide optimal coupon information based on the user's purchasing history and preferences.

[0073] The coupon information providing unit can track coupon usage status in real time and prioritize displaying frequently used coupons. The coupon information providing unit, for example, builds a system that tracks coupon usage status in real time and prioritizes displaying frequently used coupons. For example, coupons that are frequently used by users are prioritized. The coupon information providing unit can also display coupon information based on coupon usage status. For example, coupons that are frequently used are prioritized. The coupon information providing unit can also update coupon information based on usage status tracked in real time. For example, when new usage status is added, the display order of coupon information is changed. This allows frequently used coupons to be prioritized.

[0074] The coupon information providing unit can use the emotion estimation function to provide coupon information tailored to the user's current emotional state. The coupon information providing unit, for example, uses the emotion estimation function to analyze the user's current emotional state and build a system that provides coupon information tailored to that emotion. For example, if the user is relaxed, relaxation-related coupons are displayed. The coupon information providing unit can also provide coupon information based on the user's emotional state. For example, if the user is excited, activity-related coupons are displayed. The coupon information providing unit can also use the emotion estimation function to provide coupon information according to the user's emotional state. For example, if the user is tired, coupons for relaxation facilities are displayed. This makes it possible to provide coupon information tailored to the user's emotional state.

[0075] The coupon information providing unit can add a function that allows coupon information to be linked with an SNS and shared with friends and family. The coupon information providing unit, for example, builds a system that adds a function that allows coupon information to be linked with an SNS and shared with friends and family. For example, a coupon acquired by a user is shared on an SNS. The coupon information providing unit can also promote coupon use by allowing users to share coupon information with friends and family. For example, coupon information is shared through an SNS. The coupon information providing unit can also promote information exchange between users by sharing coupon information. For example, the usage status of coupons acquired by a user is shared. This allows coupon information to be shared with friends and family.

[0076] The coupon information providing unit can provide coupon information by voice, allowing the user to obtain information without relying on vision while driving or walking. The coupon information providing unit, for example, builds a system that provides coupon information by voice, allowing the user to obtain information without relying on vision while driving or walking. For example, the coupon information is provided by voice in conjunction with a navigation system. The coupon information providing unit can also provide coupon information by voice so that the user can obtain information without relying on vision. For example, the coupon information is read out using a voice assistant on a smartphone. The coupon information providing unit can also provide coupon information by voice. For example, the coupon information is provided by voice in conjunction with an in-vehicle system. This allows the user to obtain coupon information without relying on vision while driving or walking.

[0077] The coupon information providing unit can use the emotion estimation function to provide information on limited sales and special events that the user may be interested in. The coupon information providing unit, for example, uses the emotion estimation function to analyze the emotional state of the user and build a system that provides information on limited sales and special events that match that state. For example, if the user is having fun, entertainment information is provided. The coupon information providing unit can also provide information on limited sales and special events based on the emotional state of the user. For example, if the user is relaxed, relaxation-related information is provided. The coupon information providing unit can also use the emotion estimation function to provide information on limited sales and special events that the user may be interested in. For example, if the user is excited, activity-related information is provided. This makes it possible to provide information on limited sales and special events that the user may be interested in.

[0078] The mile management unit can use the generation AI to propose an optimal exercise plan based on the user's past exercise data, thereby promoting mile acquisition. The mile management unit, for example, uses the generation AI to analyze the user's past exercise data and build a system that proposes an optimal exercise plan. For example, it provides an exercise plan customized based on the user's exercise history. The mile management unit can also propose an optimal exercise plan based on the user's exercise data. For example, it provides an exercise plan tailored to the user's exercise habits. The mile management unit can also use the generation AI to propose an exercise plan based on the user's exercise data. For example, it provides an exercise plan tailored to the user's goals. This makes it possible to propose an optimal exercise plan based on the user's exercise data, promoting mile acquisition.

[0079] The mile management unit can display the mile acquisition status in real time and provide feedback to maintain the user's motivation. The mile management unit, for example, builds a system that displays the mile acquisition status in real time and provides feedback to maintain the user's motivation. For example, it displays the number of miles acquired and the goals achieved. The mile management unit can also provide feedback based on the user's mile acquisition status. For example, it displays the progress toward the goals set by the user. The mile management unit can also provide feedback based on the mile acquisition status displayed in real time. For example, it displays an encouraging message when the user achieves a goal. In this way, it is possible to display the mile acquisition status in real time and provide feedback to maintain the user's motivation.

[0080] The mile management unit can use the emotion estimation function to provide incentives for earning miles that match the user's current emotional state. The mile management unit, for example, uses the emotion estimation function to analyze the user's current emotional state and build a system that provides incentives for earning miles that match the emotion. For example, if the user is relaxed, it provides a relaxation-related incentive. The mile management unit can also provide incentives based on the user's emotional state. For example, if the user is excited, it provides an activity-related incentive. The mile management unit can also use the emotion estimation function to provide incentives that match the user's emotional state. For example, if the user is tired, it provides an incentive for a relaxation facility. In this way, it is possible to provide incentives for earning miles that match the user's emotional state.

[0081] The mile management unit can support comprehensive health management by linking the mile function with other fitness apps and sharing data. The mile management unit, for example, links the mile function with other fitness apps to build a system for sharing data. For example, a user's exercise data is integrated across multiple apps and displayed. The mile management unit can also support comprehensive health management by linking with other fitness apps. For example, the user's exercise data and diet data are shared. The mile management unit can also link with fitness apps to centrally manage the user's health data. For example, data collected by multiple apps is integrated and displayed. This allows for linking with other fitness apps to support comprehensive health management.

[0082] The mile management unit can provide events and challenges in which users can participate according to the miles earned, thereby promoting the formation of a community. The mile management unit, for example, builds a system that provides events and challenges in which users can participate according to the miles earned. For example, a walking event can be held in which users who have earned a certain number of miles can participate. The mile management unit can also promote the formation of a community by providing events and challenges in which users can participate. For example, it can provide challenges in which users compete against each other. The mile management unit can also promote interaction between users through events and challenges. For example, it can promote interaction at events in which users participate. In this way, events and challenges can be provided according to the miles earned, promoting the formation of a community.

[0083] The mile management unit can use the emotion estimation function to provide benefits and rewards that the user is likely to be interested in. For example, the mile management unit uses the emotion estimation function to analyze the user's emotional state and build a system that provides benefits and rewards that match that state. For example, if the user is having fun, entertainment-related benefits are provided. The mile management unit can also provide benefits and rewards based on the user's emotional state. For example, if the user is relaxed, relaxation-related benefits are provided. The mile management unit can also use the emotion estimation function to provide benefits and rewards that the user is likely to be interested in. For example, if the user is excited, activity-related benefits are provided. In this way, it is possible to provide benefits and rewards that the user is likely to be interested in.

[0084] The health management unit can use the generation AI to provide personalized health advice based on the user's health data. The health management unit, for example, uses the generation AI to analyze the user's health data and build a system that provides personalized health advice. For example, it provides advice customized based on the user's exercise history and dietary data. The health management unit can also provide personalized health advice based on the user's health data. For example, it provides advice tailored to the user's health condition. The health management unit can also use the generation AI to provide health advice based on the user's health data. For example, it provides advice tailored to the user's goals. This makes it possible to provide personalized health advice based on the user's health data.

[0085] The health management unit can be added with a function to analyze health management data in real time and issue an alert if an abnormality is detected. The health management unit, for example, builds a system that analyzes health management data in real time and issues an alert if an abnormality is detected. For example, an alert is issued when an abnormality in heart rate or blood pressure is detected. The health management unit can also analyze a user's health management data in real time and issue an alert if an abnormality is detected. For example, an alert is issued when an abnormal body temperature or blood sugar level is detected. The health management unit can also issue an alert if an abnormality is detected based on the health management data analyzed in real time. For example, an alert is issued when an abnormal heart rate or blood pressure is detected. In this way, health management data is analyzed in real time and an alert is issued if an abnormality is detected.

[0086] The health management unit can use the emotion estimation function to provide health management advice tailored to the user's current emotional state. For example, the health management unit uses the emotion estimation function to analyze the user's current emotional state and build a system that provides health management advice tailored to that emotion. For example, if the user is relaxed, relaxation-related advice is provided. The health management unit can also provide health management advice based on the user's emotional state. For example, if the user is excited, activity-related advice is provided. The health management unit can also use the emotion estimation function to provide health management advice according to the user's emotional state. For example, if the user is tired, advice on relaxation facilities is provided. This makes it possible to provide health management advice tailored to the user's emotional state.

[0087] The health management unit can link the health management function with other medical apps to centrally manage comprehensive health data. The health management unit, for example, links the health management function with other medical apps to build a system that centrally manages comprehensive health data. For example, a user's exercise data and dietary data are integrated across multiple apps and displayed. The health management unit can also centrally manage comprehensive health data by linking with other medical apps. For example, centrally managing a user's health data supports comprehensive health management. The health management unit can also centrally manage a user's health data by linking with medical apps. For example, data collected by multiple apps is integrated and displayed. This allows for linking with other medical apps to centrally manage comprehensive health data.

[0088] The health management unit can visually display the health management data to enable the user to intuitively understand it. The health management unit, for example, builds a system that visually displays the health management data to enable the user to intuitively understand it. For example, the health management unit displays the health data using graphs and charts. The health management unit can also visually display the health management data to enable the user to intuitively understand it. For example, the health data is displayed using a dashboard. The health management unit can also visually display the health data to enable the user to intuitively understand it. For example, the health data is displayed using infographics. In this way, the health management data is visually displayed to enable the user to intuitively understand it.

[0089] The health management unit can use the emotion estimation function to provide health-related news and information that the user is likely to be interested in. For example, the health management unit uses the emotion estimation function to analyze the user's emotional state and build a system that provides health-related news and information tailored to that state. For example, if the user is relaxed, relaxation-related news is provided. The health management unit can also provide health-related news and information based on the user's emotional state. For example, if the user is excited, activity-related news is provided. The health management unit can also use the emotion estimation function to provide health-related news and information that the user is likely to be interested in. For example, if the user is tired, relaxation-related information is provided. This makes it possible to provide health-related news and information that the user is likely to be interested in.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The city walking app may further include a route suggestion unit that analyzes the user's movement patterns and suggests an optimal route. For example, when the user visits tourist spots, the route suggestion unit may suggest a route that efficiently goes around multiple tourist spots. The route suggestion unit may also suggest a route that includes interesting spots based on the user's preferences. For example, if the user likes to visit cafes, the route suggestion unit may suggest a route that includes many cafes. The route suggestion unit may also suggest an optimal route taking into account the user's travel time. For example, the route suggestion unit may suggest a route that allows the user to enjoy sightseeing within a limited time. This may further improve the user's travel experience.

[0092] The city walking app may further include a music providing unit that estimates the user's emotions and provides music that the user may be interested in based on the estimated emotions. For example, if the user is relaxed, relaxing music is provided. The music providing unit may also provide music based on the user's emotional state. For example, if the user is excited, energetic music is provided. The music providing unit may also use the emotion estimation function to provide music according to the user's emotional state. For example, if the user is tired, relaxation music is provided. In this way, music that matches the user's emotional state can be provided.

[0093] The city walking app may also include a recommendation unit that analyzes the user's movement history and recommends places visited in the past. For example, it may suggest that the user revisit a cafe or restaurant that the user has visited in the past. The recommendation unit may also suggest new spots related to places visited in the past based on the user's preferences. For example, it may suggest a new restaurant that serves a dish that the user likes. The recommendation unit may also provide event information for places visited in the past based on the user's movement history. For example, it may suggest events held at tourist spots that the user has visited in the past. This may further enhance the user's movement experience.

[0094] The city walking app may further include an entertainment information providing unit that estimates the user's emotions and provides information on movies and dramas that the user may be interested in based on the estimated emotions. For example, if the user is relaxed, information on relaxing movies is provided. The entertainment information providing unit may also provide information on movies and dramas based on the user's emotional state. For example, if the user is excited, information on action movies is provided. The entertainment information providing unit may also use the emotion estimation function to provide information on movies and dramas that match the user's emotional state. For example, if the user is tired, information on relaxation movies is provided. This makes it possible to provide entertainment information that matches the user's emotional state.

[0095] The city walking app may further include a rest spot suggestion unit that analyzes the user's movement data and suggests optimal rest spots. For example, after the user has walked for a long time, a nearby cafe or park may be suggested. The rest spot suggestion unit may also suggest interesting rest spots based on the user's preferences. For example, if the user likes nature, a park rich in nature may be suggested. The rest spot suggestion unit may also suggest optimal times to take a break based on the user's movement data. For example, it may suggest taking a break after the user has walked a certain distance. This may make the user's travel experience even more comfortable.

[0096] The city walking app may further include a sports information providing unit that estimates the user's emotions and provides information on sports events that the user may be interested in based on the estimated emotions. For example, if the user is excited, information on energetic sports events is provided. The sports information providing unit may also provide information on sports events based on the user's emotional state. For example, if the user is relaxed, information on relaxation sports is provided. The sports information providing unit may also use the emotion estimation function to provide information on sports events according to the user's emotional state. For example, if the user is tired, information on relaxation sports is provided. In this way, it is possible to provide information on sports events that match the user's emotional state.

[0097] The city walking app may further include a shopping spot suggestion unit that analyzes the user's movement data and suggests optimal shopping spots. For example, when the user visits a shopping area, the unit suggests popular shops nearby. The shopping spot suggestion unit may also suggest interesting shopping spots based on the user's preferences. For example, if the user is interested in fashion, the unit may suggest fashion-related shops. The shopping spot suggestion unit may also suggest optimal shopping times based on the user's movement data. For example, the unit may suggest shopping after the user has walked a certain distance. This may further enhance the user's movement experience.

[0098] The city walking app may further include a recipe providing unit that estimates the user's emotions and provides cooking recipes that the user may be interested in based on the estimated emotions. For example, if the user is relaxed, it provides recipes for relaxing dishes. The recipe providing unit may also provide cooking recipes based on the user's emotional state. For example, if the user is excited, it provides recipes for energetic dishes. The recipe providing unit may also use the emotion estimation function to provide cooking recipes according to the user's emotional state. For example, if the user is tired, it provides recipes for relaxation dishes. In this way, it is possible to provide cooking recipes that match the user's emotional state.

[0099] The city walking app may further include a tourist route suggestion unit that analyzes the user's movement data and suggests an optimal tourist route. For example, when the user visits tourist spots, the system may suggest a route that efficiently visits multiple tourist spots. The tourist route suggestion unit may also suggest a route that includes interesting tourist spots based on the user's preferences. For example, if the user is interested in history, the system may suggest a route that includes many historical tourist spots. The tourist route suggestion unit may also suggest an optimal tourist route taking into account the user's travel time. For example, the system may suggest a route that allows the user to enjoy sightseeing within a limited time. This may further improve the user's sightseeing experience.

[0100] The city walking app may further include a reading list providing unit that estimates the user's emotions and provides a reading list that the user may be interested in based on the estimated emotions. For example, if the user is relaxed, a list of relaxing books is provided. The reading list providing unit may also provide a reading list based on the user's emotional state. For example, if the user is excited, a list of action novels is provided. The reading list providing unit may also use the emotion estimation function to provide a reading list according to the user's emotional state. For example, if the user is tired, a list of relaxation books is provided. In this way, a reading list that matches the user's emotional state can be provided.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The review information provider automatically provides reviews of the area around the user's current location while the user is walking or driving. For example, when the user passes by a cafe, restaurant, or tourist spot, the reviews are automatically displayed. Step 2: The area information provider provides the user with the history, local news, event information, trivia, etc. of the area they are currently in. For example, when a user visits a tourist spot or region, the user will be shown the history of that location, related episodes, local news, event information, and trivia. Step 3: The coupon information providing unit allows the user to receive coupon information for the area around the user's current location. For example, when the user passes by a restaurant, shop, or facility, discount coupons and coupon information for that location are displayed. Step 4: The mileage management unit can earn points according to the distance the user walks. For example, the user can earn a certain number of points for every kilometer they walk, and the points can be exchanged for rewards. It can also provide bonus points or special rewards when a certain distance is walked. Step 5: The health management section supports the user's diet and health management. For example, it records the user's steps and calories burned and provides advice on how to achieve goals. It can also record dietary information and suggest balanced meals, and record exercise history to provide effective exercise plans.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0116] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0131] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0147] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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).

[0156] 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.

[0157] 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."

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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]

[0170] 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 word-of-mouth information providing unit that automatically provides word-of-mouth information around the user's current location when the user is walking or driving; The area information section provides the user with information such as the history of the area they are currently in, local news, event information, and trivia. a coupon information providing unit that allows a user to receive coupon information for the area around the user's current location; A mileage management section that allows users to earn points according to the distance they walk; A health management unit that supports the user's diet and health management. A system characterized by:

2. The area information providing unit Using generative AI, provide area information customized based on the user's interests.

2. The system of claim 1.

3. The coupon information providing unit Using a generation AI, the optimal coupon information is provided based on the user's purchase history and preferences.

2. The system of claim 1.

4. The mileage management unit Using generative AI, the system proposes optimal exercise plans based on the user's past exercise data, encouraging them to earn miles.

2. The system of claim 1.

5. The health management department Using generative AI to provide personalized health advice based on the user's health data 2. The system of claim 1.

6. The word-of-mouth information providing unit Providing the word-of-mouth information tailored to the user's current emotional state 2. The system of claim 1.

7. The area information providing unit Providing area information tailored to the user's current emotional state 2. The system of claim 1.

8. The coupon information providing unit Providing the coupon information tailored to the user's current emotional state 2. The system of claim 1.

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