System

Abstract

An object of a system according to an embodiment is to encourage eco-friendly behavior and promote a sustainable lifestyle.SOLUTION: A system includes an action recording part, a point management part, and an exchange part. The action recording unit records eco-friendly actions. The point management unit manages points based on the eco-friendly behavior recorded by the behavior recording unit. The exchange unit exchanges the points managed by the point management unit for a product, a service, or a donation.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] Existing technologies do not adequately provide effective incentive systems to encourage eco-friendly behavior, and there is room for improvement.

[0005] The system according to the embodiment aims to encourage eco-friendly behaviour and promote sustainable lifestyles. [Means for solving the problem]

[0006] The system according to the embodiment includes a behavior recording unit, a points management unit, and an exchange unit. The behavior recording unit records eco-friendly behavior. The points management unit manages points based on the eco-friendly behavior recorded by the behavior recording unit. The exchange unit exchanges the points managed by the points management unit for goods, services, or donations. [Effects of the Invention]

[0007] Systems according to embodiments can encourage eco-friendly behavior and promote sustainable lifestyles. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A reward application according to an embodiment of the present invention is a system that rewards users who adopt a sustainable lifestyle. The system allows users to earn points by practicing eco-friendly behavior and exchange the points for goods, services, or donations. In this way, the reward application can motivate users to practice sustainable lifestyles and promote eco-friendly behavior.

[0029] The reward providing application according to the embodiment includes an action recording unit, a point management unit, and an exchange unit. The action recording unit records eco-friendly actions taken by a user. For example, the action recording unit records actions such as recycling and using public transportation. The action recording unit also records actions such as when the user saves energy or uses reusable products. The point management unit manages points based on the eco-friendly actions recorded by the action recording unit. For example, points may be awarded for recycling. Points may also be awarded for using public transportation. Points may also be awarded for saving energy or using reusable products. The exchange unit exchanges the points managed by the point management unit for goods, services, or donations. For example, when a user accumulates a certain number of points, the user can use the points to purchase eco-friendly products. The user can also use the points to receive specific services (e.g., eco-tours or eco-workshops). The user can also donate the points to environmental protection organizations, etc. In this way, the reward providing application according to the embodiment can motivate users to practice sustainable lifestyles and promote eco-friendly behavior.

[0030] The behavior recording unit can record the user's recycling behavior and award points based on the recycling behavior. The behavior recording unit records the user's recycling behavior, for example. For example, points are awarded by taking a photo of the recycling process and uploading it to the app. The behavior recording unit can also measure the amount of recycling and award points according to the amount. Furthermore, the behavior recording unit can also record the frequency of recycling and award points according to the frequency. In this way, by recording the user's recycling behavior and awarding points, recycling can be promoted.

[0031] The behavior recording unit can record the user's public transportation usage history and award points based on the usage history. For example, the behavior recording unit records the usage history when the user uses public transportation. For example, points are awarded by linking the usage history of a transportation card to an app. The behavior recording unit can also automatically track public transportation usage using GPS data and award points based on that data. Furthermore, the behavior recording unit can record the frequency of public transportation usage and award points according to the frequency. In this way, by recording the user's public transportation usage history and awarding points, it is possible to encourage the use of public transportation.

[0032] The point management unit can allow a user to purchase eco-friendly products when they have accumulated a certain number of points. For example, when a user has accumulated a certain number of points, the point management unit can use those points to purchase eco-friendly products. For example, products that use renewable energy or products made from recycled materials are eligible. The point management unit can also provide a catalog of eco-friendly products and allow the user to select products using their points. Furthermore, the point management unit can manage the purchase history of eco-friendly products and suggest recommended products to the user. This allows users to purchase eco-friendly products when they have accumulated a certain number of points, thereby promoting the spread of eco-friendly products.

[0033] The exchange unit allows users to use their points to receive specific services. For example, the exchange unit allows users to use their points to receive specific services such as eco-tours and eco-workshops. For example, an eco-tour allows users to enjoy learning about the natural environment. An eco-workshop allows users to learn about recycling and energy conservation methods. Furthermore, the exchange unit allows users to use their points to participate in environmental education programs. This allows users to receive specific services using their points, thereby promoting the use of eco-friendly services.

[0034] The exchange unit allows users to donate points to environmental protection organizations. For example, the exchange unit allows users to donate to environmental protection organizations using points. For example, environmental protection organizations such as specific NPOs and NGOs are targeted. The exchange unit can also provide a list of organizations to which donations can be made, allowing users to select a donation destination using their points. Furthermore, the exchange unit can manage donation history and report the effects of donations to users. This allows users to support environmental protection activities by donating points to environmental protection organizations.

[0035] The behavior recording unit can record the user's eco-friendly behavior with photos and award points based on the photos. For example, when the user recycles, the behavior recording unit can award points by recording the activity with photos and uploading the photos to the app. For example, a photo taken of the recycling activity is considered a valid record. The behavior recording unit can also save photos as evidence of the eco-friendly behavior and award points based on the photos. Furthermore, the behavior recording unit can analyze the content of the photos and award points according to the type of eco-friendly behavior. In this way, by recording the user's eco-friendly behavior with photos and awarding points, the user can earn points while leaving evidence of their behavior.

[0036] The behavior recording unit can automatically track the user's public transportation usage history. For example, the behavior recording unit automatically tracks the usage history when the user uses public transportation. For example, the usage history of a transportation card can be automatically tracked by linking it to the app. The behavior recording unit can also automatically track the use of public transportation using GPS data and reflect that data in the app. Furthermore, the behavior recording unit can automatically track the frequency of public transportation use and award points based on that data. In this way, by automatically tracking the user's public transportation usage history, points can be earned without any hassle.

[0037] The behavior recording unit can track the user's eco-friendly behavior and analyze the tracked data to suggest the next action to be taken. For example, the behavior recording unit can track the user's recycling behavior and analyze the data to suggest the next action to be taken. For example, the behavior recording unit can analyze the frequency and amount of recycling and suggest the next recycling action to be taken. The behavior recording unit can also track the user's public transportation usage history and analyze the data to suggest the next public transportation usage to be taken. Furthermore, the behavior recording unit can track energy-saving behavior and analyze the data to suggest the next energy-saving action to be taken. In this way, by tracking the user's eco-friendly behavior and analyzing the data to suggest the next action to be taken, it is possible to support the practice of a sustainable lifestyle.

[0038] The behavior recording unit tracks the user's eco-friendly behavior, visualizes the tracked data in real time, and can provide instant feedback to the user. For example, the behavior recording unit tracks the user's recycling behavior and visualizes the data in real time. For example, the amount and frequency of recycling can be instantly displayed and feedback can be provided to the user. The behavior recording unit can also track the user's public transportation usage history and visualize the data in real time to display the amount of CO2 reduction. Furthermore, the behavior recording unit can track energy-saving behavior and visualize the data in real time to display the amount of savings. In this way, the user's eco-friendly behavior can be visualized in real time and instant feedback can be provided, making it easier for the user to realize the effects of their behavior.

[0039] The behavior recording unit can be linked with IoT devices in the home to automatically track eco-friendly behavior and introduce a system that allows users to earn points. The behavior recording unit, for example, uses a smart meter to monitor energy consumption and automatically track energy-saving behavior. For example, points are awarded when energy consumption falls below a certain standard. The behavior recording unit can also measure the amount of recycling using a smart trash can and automatically award points. For example, points are awarded when the amount of recycling exceeds a certain standard. The behavior recording unit can also monitor energy savings using a smart thermostat and automatically award points. For example, points are awarded when the set temperature is within an eco-friendly range. In this way, by linking with IoT devices in the home, automatically tracking eco-friendly behavior, and introducing a system that allows users to earn points, eco-friendly behavior can be promoted while reducing the user's effort.

[0040] The behavior recording unit can add a game element that allows users to compete with other users when practicing eco-friendly behavior, thereby increasing motivation. The behavior recording unit can, for example, introduce a ranking system that competes based on the amount of recycling or the number of times public transportation is used. For example, a special badge can be awarded to users who recycle the most. The behavior recording unit can also implement a challenge to compete for the amount of energy consumption reduction. For example, bonus points can be awarded to users who reduce energy consumption the most. Furthermore, the behavior recording unit can also hold an event to compete over the number of times a reusable product is used. For example, a special reward can be provided to users who use a reusable product the most. In this way, adding a game element that allows users to compete with other users can increase motivation for practicing eco-friendly behavior.

[0041] The point management unit can use the generation AI to analyze the user's point usage history and suggest the optimal exchange destination. For example, the point management unit can use the generation AI to analyze the user's past point usage history and suggest the optimal exchange destination. For example, it can suggest products and services that the user prefers based on the past exchange history. The point management unit can also use the generation AI to preferentially suggest products and services in a specific category. For example, it can suggest the most suitable eco-friendly products for the user. Furthermore, the point management unit can use the generation AI to make customized suggestions based on the user's preferences and behavioral patterns. For example, it can analyze the user's behavioral history and suggest the next eco-friendly product to purchase. In this way, it is possible to improve user convenience by using the generation AI to analyze the point usage history and suggest the optimal exchange destination.

[0042] The point management unit can dynamically set the expiration date of points and extend or shorten them depending on the user's behavior. For example, the point management unit extends the expiration date of points by continuing to engage in eco-friendly behavior. For example, it extends the expiration date of points for users who recycle frequently. The point management unit can also shorten the expiration date of points by engaging in specific behavior. For example, it shortens the expiration date of points for users who reduce their energy consumption by a small amount. Furthermore, the point management unit can extend the expiration date of points by engaging in eco-friendly behavior during a specific period. For example, it extends the expiration date of points for users who recycle during a campaign period. In this way, by dynamically setting the expiration date of points and extending or shortening it depending on the user's behavior, it is possible to encourage users to engage in eco-friendly behavior.

[0043] The point management unit provides a marketplace where points can be exchanged with other users, thereby increasing the liquidity of points between users. The point management unit, for example, provides a marketplace where points can be exchanged with other users. For example, it provides a platform for exchanging points for goods and services. The point management unit can also provide a function for directly exchanging points between users. For example, it can introduce a system for exchanging points in an auction format. Furthermore, in order to increase the liquidity of points, the point management unit can manage the point exchange history and suggest recommended exchange destinations to users. In this way, by providing a marketplace where points can be exchanged with other users, the liquidity of points between users can be increased.

[0044] The point management unit allows points to be used as a local currency, thereby revitalizing the local economy. The point management unit, for example, allows points to be used as a local currency. For example, points can be used at local stores and services. The point management unit can also allow points to be used at local events and festivals. Furthermore, the point management unit can also allow points to be used at local public services and facilities. For example, points can be used at local libraries and sports facilities. In this way, by allowing points to be used as a local currency, the local economy can be revitalized.

[0045] The behavior recording unit can use the generation AI to analyze the user's behavior data and improve the accuracy of tracking. The behavior recording unit can, for example, use the generation AI to analyze the user's behavior data and improve the accuracy of tracking. For example, the frequency of recycling and the usage of public transportation can be tracked with high accuracy. The behavior recording unit can also use the generation AI to analyze energy consumption patterns and accurately track energy-saving behavior. Furthermore, the behavior recording unit can also use the generation AI to track the usage history of reusable products with high accuracy. In this way, by using the generation AI to analyze the behavior data and improve the accuracy of tracking, the recording of eco-friendly behavior becomes more accurate.

[0046] The behavior recording unit can visualize tracking data in real time and provide instant feedback to the user. The behavior recording unit can, for example, instantly display the amount of recycling or the amount of energy saved and provide feedback to the user. For example, a feedback message can be displayed when the amount of recycling exceeds a certain standard. The behavior recording unit can also display the amount of CO2 reduction achieved by using public transportation in real time. Furthermore, the behavior recording unit can also display the effect of reducing environmental impact by using reusable products. In this way, by visualizing tracking data in real time and providing instant feedback, the user can more easily realize the effect of their actions.

[0047] The behavior recording unit can link the tracking data with other health management apps to improve a user's overall lifestyle. For example, the behavior recording unit can integrate eco-friendly behavior with health data to provide comprehensive feedback. For example, the behavior recording unit can integrate eco-friendly behavior with fitness data to provide customized advice to the user. The behavior recording unit can also integrate eco-friendly behavior with nutritional data to provide comprehensive health advice to the user. Furthermore, the behavior recording unit can link with other health management apps to share data on eco-friendly behavior. This allows the tracking data to be linked with other health management apps to improve a user's overall lifestyle.

[0048] The behavior recording unit can use the tracking data to evaluate the user's eco-friendly behavior and award badges or titles. The behavior recording unit can award badges, for example, based on the amount of recycling or the number of times public transportation is used. For example, a Recycle Master badge is awarded when the amount of recycling exceeds a certain standard. The behavior recording unit can also award titles based on the amount of reduction in energy consumption. For example, a user who has reduced energy consumption a large amount can be awarded the title of Eco Champion. Furthermore, the behavior recording unit can also award badges based on the number of times reusable products are used. For example, a special badge is awarded to a user who uses reusable products a large number of times. In this way, by using the tracking data to evaluate eco-friendly behavior and awarding badges or titles, it is possible to increase the motivation of users.

[0049] The behavior recording unit can use the generation AI to analyze the user's behavior history and suggest the eco-friendly behavior that is best suited to each individual user. For example, the behavior recording unit can use the generation AI to analyze the user's past behavior history and suggest the eco-friendly behavior that is best suited to each individual user. For example, the behavior recording unit can customize and suggest the next action to be taken based on the frequency of recycling and the usage of public transportation. The behavior recording unit can also analyze energy consumption patterns and suggest specific actions to save energy. Furthermore, the behavior recording unit can suggest the next eco-friendly product to purchase based on the usage history of reusable products. In this way, by using the generation AI to analyze the behavior history and suggest the eco-friendly behavior that is best suited to each individual user, it is possible to support the practice of a sustainable lifestyle.

[0050] The behavior recording unit can predict and notify the next eco-friendly behavior to be performed based on the user's behavior history. The behavior recording unit, for example, predicts and notifies the next eco-friendly behavior to be performed based on the user's behavior history. For example, the behavior recording unit can notify the next action to be performed based on the frequency of recycling or the usage of public transportation. The behavior recording unit can also analyze energy consumption patterns and notify the next energy-saving behavior to be performed. Furthermore, the behavior recording unit can notify the next eco-friendly product to be purchased based on the usage history of reusable products. In this way, the behavior of the user can be supported by predicting and notifying the next eco-friendly behavior to be performed based on the behavior history.

[0051] The behavior recording unit can introduce a mechanism that links recommended eco-friendly behaviors with IoT devices in the home and enables them to be automatically implemented. The behavior recording unit, for example, uses a smart meter to monitor energy consumption and automatically implements energy-saving behaviors. For example, it automatically implements energy-saving behaviors when energy consumption falls below a certain standard. The behavior recording unit can also measure the amount of recycling using a smart trash can and automatically implement recycling. For example, it automatically implements recycling when the amount of recycling exceeds a certain standard. Furthermore, the behavior recording unit can automatically implement energy conservation using a smart thermostat. For example, it automatically implements energy-saving behaviors when the set temperature is within an eco-friendly range. In this way, by linking recommended eco-friendly behaviors with IoT devices in the home and introducing a mechanism that enables them to be automatically implemented, it is possible to promote eco-friendly behaviors while reducing the user's effort.

[0052] The behavior recording unit can add a game element that allows users to compete with other users when practicing eco-friendly behavior, thereby increasing motivation. The behavior recording unit can, for example, introduce a ranking system that competes based on the amount of recycling or the number of times public transportation is used. For example, a special badge can be awarded to users who recycle the most. The behavior recording unit can also implement a challenge to compete for the amount of energy consumption reduction. For example, bonus points can be awarded to users who reduce energy consumption the most. Furthermore, the behavior recording unit can also hold an event to compete over the number of times a reusable product is used. For example, a special reward can be provided to users who use a reusable product the most. In this way, adding a game element that allows users to compete with other users can increase motivation for practicing eco-friendly behavior.

[0053] The behavior recording unit can use the generation AI to analyze the content of posts within a community and highlight the posts that evoke the most empathy. The behavior recording unit, for example, can use the generation AI to analyze the content of posts within a community and highlight the posts that evoke the most empathy. For example, posts with high empathy can be automatically displayed at the top. The behavior recording unit can also use the generation AI to preferentially display posts with high emotional scores. Furthermore, the behavior recording unit can use the generation AI to attach special marks to posts with high empathy. In this way, by using the generation AI to analyze the content of posts within a community and highlighting the posts that evoke the most empathy, it is possible to increase user engagement.

[0054] The behavior recording unit visualizes feedback within the community in real time, thereby promoting interaction between users. The behavior recording unit, for example, displays the number and content of feedback within the community in real time. For example, it displays special effects depending on the content of the feedback. The behavior recording unit can also display the content of the feedback in graphs and charts. Furthermore, the behavior recording unit can display the content of the feedback on a dashboard so that users can check it in real time. This makes it possible to visualize feedback within the community in real time and promote interaction between users, thereby supporting the practice of eco-friendly behavior.

[0055] The behavior recording unit can link the community function with other SNSs to widely share eco-friendly behaviors. The behavior recording unit, for example, links the community function with other SNSs to widely share eco-friendly behaviors. For example, the content of posts can be automatically shared on other SNSs. The behavior recording unit can also spread the content of posts using specific hashtags. Furthermore, the behavior recording unit can also notify followers of the eco-friendly behaviors on the SNSs. In this way, by linking the community function with other SNSs and widely sharing eco-friendly behaviors, it is possible to promote the spread of eco-friendly behaviors.

[0056] The behavior recording unit can enhance the ranking function within the community and award top users of the month or year. The behavior recording unit can display rankings based on the number of points earned, for example. For example, the top users of the month or year can be awarded special badges. The behavior recording unit can also provide special rewards to those who rank highly. Furthermore, the behavior recording unit can enhance the ranking function and hold events to award top users. This can enhance the ranking function within the community and award top users of the month or year, thereby increasing user motivation.

[0057] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0058] The behavior recording unit can record the user's eco-friendly behavior using audio and award points based on the audio data. For example, when a user recycles, they can record the activity using audio and upload it to the app, which can award points. The behavior recording unit can also save audio data as evidence of the eco-friendly behavior and award points based on the audio data. Furthermore, the behavior recording unit can analyze the content of the audio data and award points according to the type of eco-friendly behavior. In this way, by recording the user's eco-friendly behavior using audio and awarding points, the user can earn points while leaving evidence of their behavior.

[0059] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0060] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0061] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0062] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0063] The processing flow of the first embodiment will be briefly explained below.

[0064] Step 1: The behavior recorder allows users to record eco-friendly behaviors, such as recycling, using public transportation, saving energy, and using reusable products. Step 2: The points management unit manages points based on the eco-friendly actions recorded by the behavior recording unit, such as giving points for recycling, using public transportation, saving energy, and using reusable products. Step 3: The exchange unit exchanges the points managed by the point management unit for goods, services, or donations. For example, if a user accumulates a certain number of points, they can use those points to purchase eco-friendly goods, receive services such as eco-tours and eco-workshops, or donate to environmental protection organizations.

[0065] (Example 2) A reward application according to an embodiment of the present invention is a system that rewards users who adopt a sustainable lifestyle. The system allows users to earn points by practicing eco-friendly behavior and exchange the points for goods, services, or donations. In this way, the reward application can motivate users to practice sustainable lifestyles and promote eco-friendly behavior.

[0066] The reward providing application according to the embodiment includes an action recording unit, a point management unit, and an exchange unit. The action recording unit records eco-friendly actions taken by a user. For example, the action recording unit records actions such as recycling and using public transportation. The action recording unit also records actions such as when the user saves energy or uses reusable products. The point management unit manages points based on the eco-friendly actions recorded by the action recording unit. For example, points may be awarded for recycling. Points may also be awarded for using public transportation. Points may also be awarded for saving energy or using reusable products. The exchange unit exchanges the points managed by the point management unit for goods, services, or donations. For example, when a user accumulates a certain number of points, the user can use the points to purchase eco-friendly products. The user can also use the points to receive specific services (e.g., eco-tours or eco-workshops). The user can also donate the points to environmental protection organizations, etc. In this way, the reward providing application according to the embodiment can motivate users to practice sustainable lifestyles and promote eco-friendly behavior.

[0067] The behavior recording unit can record the user's recycling behavior and award points based on the recycling behavior. The behavior recording unit records the user's recycling behavior, for example. For example, points are awarded by taking a photo of the recycling process and uploading it to the app. The behavior recording unit can also measure the amount of recycling and award points according to the amount. Furthermore, the behavior recording unit can also record the frequency of recycling and award points according to the frequency. In this way, by recording the user's recycling behavior and awarding points, recycling can be promoted.

[0068] The behavior recording unit can record the user's public transportation usage history and award points based on the usage history. For example, the behavior recording unit records the usage history when the user uses public transportation. For example, points are awarded by linking the usage history of a transportation card to an app. The behavior recording unit can also automatically track public transportation usage using GPS data and award points based on that data. Furthermore, the behavior recording unit can record the frequency of public transportation usage and award points according to the frequency. In this way, by recording the user's public transportation usage history and awarding points, it is possible to encourage the use of public transportation.

[0069] The point management unit can allow a user to purchase eco-friendly products when they have accumulated a certain number of points. For example, when a user has accumulated a certain number of points, the point management unit can use those points to purchase eco-friendly products. For example, products that use renewable energy or products made from recycled materials are eligible. The point management unit can also provide a catalog of eco-friendly products and allow the user to select products using their points. Furthermore, the point management unit can manage the purchase history of eco-friendly products and suggest recommended products to the user. This allows users to purchase eco-friendly products when they have accumulated a certain number of points, thereby promoting the spread of eco-friendly products.

[0070] The exchange unit allows users to use their points to receive specific services. For example, the exchange unit allows users to use their points to receive specific services such as eco-tours and eco-workshops. For example, an eco-tour allows users to enjoy learning about the natural environment. An eco-workshop allows users to learn about recycling and energy conservation methods. Furthermore, the exchange unit allows users to use their points to participate in environmental education programs. This allows users to receive specific services using their points, thereby promoting the use of eco-friendly services.

[0071] The exchange unit allows users to donate points to environmental protection organizations. For example, the exchange unit allows users to donate to environmental protection organizations using points. For example, environmental protection organizations such as specific NPOs and NGOs are targeted. The exchange unit can also provide a list of organizations to which donations can be made, allowing users to select a donation destination using their points. Furthermore, the exchange unit can manage donation history and report the effects of donations to users. This allows users to support environmental protection activities by donating points to environmental protection organizations.

[0072] The behavior recording unit can record the user's eco-friendly behavior with photos and award points based on the photos. For example, when the user recycles, the behavior recording unit can award points by recording the activity with photos and uploading the photos to the app. For example, a photo taken of the recycling activity is considered a valid record. The behavior recording unit can also save photos as evidence of the eco-friendly behavior and award points based on the photos. Furthermore, the behavior recording unit can analyze the content of the photos and award points according to the type of eco-friendly behavior. In this way, by recording the user's eco-friendly behavior with photos and awarding points, the user can earn points while leaving evidence of their behavior.

[0073] The behavior recording unit can automatically track the user's public transportation usage history. For example, the behavior recording unit automatically tracks the usage history when the user uses public transportation. For example, the usage history of a transportation card can be automatically tracked by linking it to the app. The behavior recording unit can also automatically track the use of public transportation using GPS data and reflect that data in the app. Furthermore, the behavior recording unit can automatically track the frequency of public transportation use and award points based on that data. In this way, by automatically tracking the user's public transportation usage history, points can be earned without any hassle.

[0074] The behavior recording unit can track the user's eco-friendly behavior and analyze the tracked data to suggest the next action to be taken. For example, the behavior recording unit can track the user's recycling behavior and analyze the data to suggest the next action to be taken. For example, the behavior recording unit can analyze the frequency and amount of recycling and suggest the next recycling action to be taken. The behavior recording unit can also track the user's public transportation usage history and analyze the data to suggest the next public transportation usage to be taken. Furthermore, the behavior recording unit can track energy-saving behavior and analyze the data to suggest the next energy-saving action to be taken. In this way, by tracking the user's eco-friendly behavior and analyzing the data to suggest the next action to be taken, it is possible to support the practice of a sustainable lifestyle.

[0075] The behavior recording unit tracks the user's eco-friendly behavior, visualizes the tracked data in real time, and can provide instant feedback to the user. For example, the behavior recording unit tracks the user's recycling behavior and visualizes the data in real time. For example, the amount and frequency of recycling can be instantly displayed and feedback can be provided to the user. The behavior recording unit can also track the user's public transportation usage history and visualize the data in real time to display the amount of CO2 reduction. Furthermore, the behavior recording unit can track energy-saving behavior and visualize the data in real time to display the amount of savings. In this way, the user's eco-friendly behavior can be visualized in real time and instant feedback can be provided, making it easier for the user to realize the effects of their behavior.

[0076] The behavior recording unit can use the emotion estimation function to analyze the emotions of the user when practicing eco-friendly behavior and provide incentives to elicit positive emotions. The behavior recording unit can, for example, use the emotion estimation function to analyze the emotions of the user when recycling and provide incentives to elicit positive emotions. For example, a positive feedback message can be displayed after recycling. The behavior recording unit can also analyze the emotions of the user when using public transportation in real time and provide incentives to elicit positive emotions. Furthermore, the behavior recording unit can analyze the emotions of the user when practicing energy-saving behavior and provide incentives to elicit positive emotions. In this way, by analyzing the user's emotions and providing incentives to elicit positive emotions, it is possible to encourage the user to continue practicing eco-friendly behavior.

[0077] The behavior recording unit can be linked with IoT devices in the home to automatically track eco-friendly behavior and introduce a system that allows users to earn points. The behavior recording unit, for example, uses a smart meter to monitor energy consumption and automatically track energy-saving behavior. For example, points are awarded when energy consumption falls below a certain standard. The behavior recording unit can also measure the amount of recycling using a smart trash can and automatically award points. For example, points are awarded when the amount of recycling exceeds a certain standard. The behavior recording unit can also monitor energy savings using a smart thermostat and automatically award points. For example, points are awarded when the set temperature is within an eco-friendly range. In this way, by linking with IoT devices in the home, automatically tracking eco-friendly behavior, and introducing a system that allows users to earn points, eco-friendly behavior can be promoted while reducing the user's effort.

[0078] The behavior recording unit can add a game element that allows users to compete with other users when practicing eco-friendly behavior, thereby increasing motivation. The behavior recording unit can, for example, introduce a ranking system that competes based on the amount of recycling or the number of times public transportation is used. For example, a special badge can be awarded to users who recycle the most. The behavior recording unit can also implement a challenge to compete for the amount of energy consumption reduction. For example, bonus points can be awarded to users who reduce energy consumption the most. Furthermore, the behavior recording unit can also hold an event to compete over the number of times a reusable product is used. For example, a special reward can be provided to users who use a reusable product the most. In this way, adding a game element that allows users to compete with other users can increase motivation for practicing eco-friendly behavior.

[0079] The behavior recording unit can use the emotion estimation function to share the emotions felt by users when practicing eco-friendly behavior and promote empathy within the community. The behavior recording unit can, for example, use the emotion estimation function to analyze the emotions felt by users when recycling and share the emotions within the community. For example, the emotion score can be displayed within the community and supportive messages from other users can be received. The behavior recording unit can also analyze emotions felt when using public transportation in real time and share the emotions. For example, posts with high empathy can be highlighted based on the emotion score. Furthermore, the behavior recording unit can analyze emotions felt when practicing energy-saving behavior and share the emotions. For example, a special badge can be assigned according to the emotion score. This can support the practice of eco-friendly behavior by sharing emotions using the emotion estimation function and promoting empathy within the community.

[0080] The point management unit can use the generation AI to analyze the user's point usage history and suggest the optimal exchange destination. For example, the point management unit can use the generation AI to analyze the user's past point usage history and suggest the optimal exchange destination. For example, it can suggest products and services that the user prefers based on the past exchange history. The point management unit can also use the generation AI to preferentially suggest products and services in a specific category. For example, it can suggest the most suitable eco-friendly products for the user. Furthermore, the point management unit can use the generation AI to make customized suggestions based on the user's preferences and behavioral patterns. For example, it can analyze the user's behavioral history and suggest the next eco-friendly product to purchase. In this way, it is possible to improve user convenience by using the generation AI to analyze the point usage history and suggest the optimal exchange destination.

[0081] The point management unit can dynamically set the expiration date of points and extend or shorten them depending on the user's behavior. For example, the point management unit extends the expiration date of points by continuing to engage in eco-friendly behavior. For example, it extends the expiration date of points for users who recycle frequently. The point management unit can also shorten the expiration date of points by engaging in specific behavior. For example, it shortens the expiration date of points for users who reduce their energy consumption by a small amount. Furthermore, the point management unit can extend the expiration date of points by engaging in eco-friendly behavior during a specific period. For example, it extends the expiration date of points for users who recycle during a campaign period. In this way, by dynamically setting the expiration date of points and extending or shortening it depending on the user's behavior, it is possible to encourage users to engage in eco-friendly behavior.

[0082] The point management unit can use the emotion estimation function to analyze the emotion of the user when exchanging points and suggest the exchange destination that will provide the highest satisfaction. The point management unit, for example, uses the emotion estimation function to analyze the emotion of the user when exchanging points and suggest the exchange destination that will provide the highest satisfaction. For example, the point management unit makes suggestions based on the emotion scores from past exchanges. The point management unit can also analyze the user's emotion in real time and preferentially suggest exchange destinations with high emotion scores. Furthermore, the point management unit can suggest special exchange destinations based on the emotion score. For example, a special reward can be provided if the emotion score is high. In this way, by using the emotion estimation function to analyze the user's emotion and suggesting the exchange destination that will provide the highest satisfaction, user satisfaction can be improved.

[0083] The point management unit provides a marketplace where points can be exchanged with other users, thereby increasing the liquidity of points between users. The point management unit, for example, provides a marketplace where points can be exchanged with other users. For example, it provides a platform for exchanging points for goods and services. The point management unit can also provide a function for directly exchanging points between users. For example, it can introduce a system for exchanging points in an auction format. Furthermore, in order to increase the liquidity of points, the point management unit can manage the point exchange history and suggest recommended exchange destinations to users. In this way, by providing a marketplace where points can be exchanged with other users, the liquidity of points between users can be increased.

[0084] The point management unit allows points to be used as a local currency, thereby revitalizing the local economy. The point management unit, for example, allows points to be used as a local currency. For example, points can be used at local stores and services. The point management unit can also allow points to be used at local events and festivals. Furthermore, the point management unit can also allow points to be used at local public services and facilities. For example, points can be used at local libraries and sports facilities. In this way, by allowing points to be used as a local currency, the local economy can be revitalized.

[0085] The point management unit uses the emotion estimation function to share the emotions felt by users when exchanging points, allowing other users to use the emotion estimation function as a reference. The point management unit, for example, uses the emotion estimation function to share the emotions felt by users when exchanging points, allowing other users to use the emotion estimation function as a reference. For example, the point management unit displays an emotion score so that other users can use the emotion score as a reference. The point management unit can also analyze the user's emotions in real time and display an evaluation of the exchange destination based on the emotion score. Furthermore, the point management unit can display a ranking of the exchange destination according to the emotion score. For example, exchange destinations with high emotion scores are displayed preferentially. In this way, the emotion estimation function can be used to share the user's emotions, allowing other users to use the emotion estimation function as a reference, thereby improving satisfaction with point exchanges.

[0086] The behavior recording unit can use the generation AI to analyze the user's behavior data and improve the accuracy of tracking. The behavior recording unit can, for example, use the generation AI to analyze the user's behavior data and improve the accuracy of tracking. For example, the frequency of recycling and the usage of public transportation can be tracked with high accuracy. The behavior recording unit can also use the generation AI to analyze energy consumption patterns and accurately track energy-saving behavior. Furthermore, the behavior recording unit can also use the generation AI to track the usage history of reusable products with high accuracy. In this way, by using the generation AI to analyze the behavior data and improve the accuracy of tracking, the recording of eco-friendly behavior becomes more accurate.

[0087] The behavior recording unit can visualize tracking data in real time and provide instant feedback to the user. The behavior recording unit can, for example, instantly display the amount of recycling or the amount of energy saved and provide feedback to the user. For example, a feedback message can be displayed when the amount of recycling exceeds a certain standard. The behavior recording unit can also display the amount of CO2 reduction achieved by using public transportation in real time. Furthermore, the behavior recording unit can also display the effect of reducing environmental impact by using reusable products. In this way, by visualizing tracking data in real time and providing instant feedback, the user can more easily realize the effect of their actions.

[0088] The behavior recording unit can use the emotion estimation function to analyze the emotions of the user when checking the tracking data and design an interface that elicits positive emotions. The behavior recording unit, for example, uses the emotion estimation function to analyze the emotions of the user when checking the tracking data and design an interface that elicits positive emotions. For example, the behavior recording unit displays a feedback message according to the emotion score. The behavior recording unit can also analyze the user's emotions in real time and display a special animation when the emotion score is high. Furthermore, the behavior recording unit can provide customized feedback according to the emotion score. As a result, by analyzing emotions using the emotion estimation function and designing an interface that elicits positive emotions, user satisfaction can be improved.

[0089] The behavior recording unit can link the tracking data with other health management apps to improve a user's overall lifestyle. For example, the behavior recording unit can integrate eco-friendly behavior with health data to provide comprehensive feedback. For example, the behavior recording unit can integrate eco-friendly behavior with fitness data to provide customized advice to the user. The behavior recording unit can also integrate eco-friendly behavior with nutritional data to provide comprehensive health advice to the user. Furthermore, the behavior recording unit can link with other health management apps to share data on eco-friendly behavior. This allows the tracking data to be linked with other health management apps to improve a user's overall lifestyle.

[0090] The behavior recording unit can use the tracking data to evaluate the user's eco-friendly behavior and award badges or titles. The behavior recording unit can award badges, for example, based on the amount of recycling or the number of times public transportation is used. For example, a Recycle Master badge is awarded when the amount of recycling exceeds a certain standard. The behavior recording unit can also award titles based on the amount of reduction in energy consumption. For example, a user who has reduced energy consumption a large amount can be awarded the title of Eco Champion. Furthermore, the behavior recording unit can also award badges based on the number of times reusable products are used. For example, a special badge is awarded to a user who uses reusable products a large number of times. In this way, by using the tracking data to evaluate eco-friendly behavior and awarding badges or titles, it is possible to increase the motivation of users.

[0091] The behavior recording unit can use the emotion estimation function to analyze the emotions users feel when sharing tracking data and promote empathy within the community. The behavior recording unit, for example, uses the emotion estimation function to analyze the emotions users feel when sharing tracking data and share the emotions within the community. For example, the behavior recording unit can display an emotion score and receive supportive messages from other users. The behavior recording unit can also analyze users' emotions in real time and highlight posts that have a high degree of empathy based on the emotion score. Furthermore, the behavior recording unit can also assign special badges according to the emotion score. This makes it possible to support the practice of eco-friendly behavior by analyzing emotions using the emotion estimation function and promoting empathy within the community.

[0092] The behavior recording unit can use the generation AI to analyze the user's behavior history and suggest the eco-friendly behavior that is best suited to each individual user. For example, the behavior recording unit can use the generation AI to analyze the user's past behavior history and suggest the eco-friendly behavior that is best suited to each individual user. For example, the behavior recording unit can customize and suggest the next action to be taken based on the frequency of recycling and the usage of public transportation. The behavior recording unit can also analyze energy consumption patterns and suggest specific actions to save energy. Furthermore, the behavior recording unit can suggest the next eco-friendly product to purchase based on the usage history of reusable products. In this way, by using the generation AI to analyze the behavior history and suggest the eco-friendly behavior that is best suited to each individual user, it is possible to support the practice of a sustainable lifestyle.

[0093] The behavior recording unit can predict and notify the next eco-friendly behavior to be performed based on the user's behavior history. The behavior recording unit, for example, predicts and notifies the next eco-friendly behavior to be performed based on the user's behavior history. For example, the behavior recording unit can notify the next action to be performed based on the frequency of recycling or the usage of public transportation. The behavior recording unit can also analyze energy consumption patterns and notify the next energy-saving behavior to be performed. Furthermore, the behavior recording unit can notify the next eco-friendly product to be purchased based on the usage history of reusable products. In this way, the behavior of the user can be supported by predicting and notifying the next eco-friendly behavior to be performed based on the behavior history.

[0094] The behavior recording unit can use the emotion estimation function to analyze the emotions of the user when performing the recommended behavior and provide an incentive to elicit positive emotions. The behavior recording unit, for example, uses the emotion estimation function to analyze the emotions of the user when performing the recommended behavior and provide an incentive to elicit positive emotions. For example, the behavior recording unit displays a positive feedback message after the behavior. The behavior recording unit can also analyze the user's emotions in real time and award bonus points if the emotion score is high. Furthermore, the behavior recording unit can provide a special reward according to the emotion score. In this way, by analyzing emotions using the emotion estimation function and providing an incentive to elicit positive emotions, it is possible to encourage user behavior.

[0095] The behavior recording unit can introduce a mechanism that links recommended eco-friendly behaviors with IoT devices in the home and enables them to be automatically implemented. The behavior recording unit, for example, uses a smart meter to monitor energy consumption and automatically implements energy-saving behaviors. For example, it automatically implements energy-saving behaviors when energy consumption falls below a certain standard. The behavior recording unit can also measure the amount of recycling using a smart trash can and automatically implement recycling. For example, it automatically implements recycling when the amount of recycling exceeds a certain standard. Furthermore, the behavior recording unit can automatically implement energy conservation using a smart thermostat. For example, it automatically implements energy-saving behaviors when the set temperature is within an eco-friendly range. In this way, by linking recommended eco-friendly behaviors with IoT devices in the home and introducing a mechanism that enables them to be automatically implemented, it is possible to promote eco-friendly behaviors while reducing the user's effort.

[0096] The behavior recording unit can add a game element that allows users to compete with other users when practicing eco-friendly behavior, thereby increasing motivation. The behavior recording unit can, for example, introduce a ranking system that competes based on the amount of recycling or the number of times public transportation is used. For example, a special badge can be awarded to users who recycle the most. The behavior recording unit can also implement a challenge to compete for the amount of energy consumption reduction. For example, bonus points can be awarded to users who reduce energy consumption the most. Furthermore, the behavior recording unit can also hold an event to compete over the number of times a reusable product is used. For example, a special reward can be provided to users who use a reusable product the most. In this way, adding a game element that allows users to compete with other users can increase motivation for practicing eco-friendly behavior.

[0097] The behavior recording unit can use the emotion estimation function to share the emotions felt by users when they practice recommended behaviors, thereby promoting empathy within the community. The behavior recording unit, for example, uses the emotion estimation function to analyze the emotions felt by users when they practice recommended behaviors and share the emotions within the community. For example, the behavior recording unit can display an emotion score within the community and receive supportive messages from other users. The behavior recording unit can also analyze users' emotions in real time and highlight posts that have a high degree of empathy based on the emotion score. Furthermore, the behavior recording unit can also assign special badges according to the emotion score. This can support the practice of eco-friendly behaviors by sharing emotions using the emotion estimation function and promoting empathy within the community.

[0098] The behavior recording unit can use the generation AI to analyze the content of posts within a community and highlight the posts that evoke the most empathy. The behavior recording unit, for example, can use the generation AI to analyze the content of posts within a community and highlight the posts that evoke the most empathy. For example, posts with high empathy can be automatically displayed at the top. The behavior recording unit can also use the generation AI to preferentially display posts with high emotional scores. Furthermore, the behavior recording unit can use the generation AI to attach special marks to posts with high empathy. In this way, by using the generation AI to analyze the content of posts within a community and highlighting the posts that evoke the most empathy, it is possible to increase user engagement.

[0099] The behavior recording unit visualizes feedback within the community in real time, thereby promoting interaction between users. The behavior recording unit, for example, displays the number and content of feedback within the community in real time. For example, it displays special effects depending on the content of the feedback. The behavior recording unit can also display the content of the feedback in graphs and charts. Furthermore, the behavior recording unit can display the content of the feedback on a dashboard so that users can check it in real time. This makes it possible to visualize feedback within the community in real time and promote interaction between users, thereby supporting the practice of eco-friendly behavior.

[0100] The behavior recording unit can use the emotion estimation function to analyze the emotions expressed by users when interacting within a community and design an interface that elicits positive emotions. The behavior recording unit, for example, uses the emotion estimation function to analyze the emotions expressed by users when interacting within a community and design an interface that elicits positive emotions. For example, the behavior recording unit displays a feedback message according to the emotion score. The behavior recording unit can also analyze the user's emotions in real time and display a special animation when the emotion score is high. Furthermore, the behavior recording unit can provide customized feedback according to the emotion score. As a result, by analyzing emotions using the emotion estimation function and designing an interface that elicits positive emotions, user satisfaction can be improved.

[0101] The behavior recording unit can link the community function with other SNSs to widely share eco-friendly behaviors. The behavior recording unit, for example, links the community function with other SNSs to widely share eco-friendly behaviors. For example, the content of posts can be automatically shared on other SNSs. The behavior recording unit can also spread the content of posts using specific hashtags. Furthermore, the behavior recording unit can also notify followers of the eco-friendly behaviors on the SNSs. In this way, by linking the community function with other SNSs and widely sharing eco-friendly behaviors, it is possible to promote the spread of eco-friendly behaviors.

[0102] The behavior recording unit can enhance the ranking function within the community and award top users of the month or year. The behavior recording unit can display rankings based on the number of points earned, for example. For example, the top users of the month or year can be awarded special badges. The behavior recording unit can also provide special rewards to those who rank highly. Furthermore, the behavior recording unit can enhance the ranking function and hold events to award top users. This can enhance the ranking function within the community and award top users of the month or year, thereby increasing user motivation.

[0103] The behavior recording unit uses the emotion estimation function to allow users to share emotions expressed when interacting within a community, thereby providing reference for other users. The behavior recording unit, for example, uses the emotion estimation function to allow users to share emotions expressed when interacting within a community, thereby providing reference for other users. For example, the behavior recording unit displays an emotion score so that other users can use it as a reference. The behavior recording unit can also analyze users' emotions in real time and display an evaluation of interactions based on the emotion score. Furthermore, the behavior recording unit can display a ranking of interactions according to the emotion score. This allows users to share emotions using the emotion estimation function, thereby providing reference for other users, thereby promoting interactions within the community.

[0104] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0105] The behavior recording unit can record the user's eco-friendly behavior using audio and award points based on the audio data. For example, when a user recycles, they can record the activity using audio and upload it to the app, which can award points. The behavior recording unit can also save audio data as evidence of the eco-friendly behavior and award points based on the audio data. Furthermore, the behavior recording unit can analyze the content of the audio data and award points according to the type of eco-friendly behavior. In this way, by recording the user's eco-friendly behavior using audio and awarding points, the user can earn points while leaving evidence of their behavior.

[0106] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0107] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0108] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0109] The behavior recording unit tracks the user's eco-friendly behavior and can visualize the history of eco-friendly behavior based on the tracked data. For example, it can display the amount and frequency of recycling in a graph and provide feedback to the user. The behavior recording unit can also track the history of public transportation use and display the amount of CO2 reduction based on that data. Furthermore, the behavior recording unit can track energy-saving behavior and display the amount of savings based on that data. This makes it possible to visualize the user's history of eco-friendly behavior and make it easier to realize the effects of their actions, thereby supporting the practice of a sustainable lifestyle.

[0110] The behavior recording unit can use the emotion estimation function to analyze the emotions of a user when practicing eco-friendly behavior and provide incentives to elicit positive emotions. For example, the emotion estimation function can be used to analyze the emotions of a user when recycling and provide incentives to elicit positive emotions. For example, a positive feedback message can be displayed after recycling. The behavior recording unit can also analyze emotions in real time when using public transportation and provide incentives to elicit positive emotions. Furthermore, the behavior recording unit can analyze emotions when practicing energy-saving behavior and provide incentives to elicit positive emotions. In this way, by analyzing the user's emotions and providing incentives to elicit positive emotions, it is possible to encourage the user to continue practicing eco-friendly behavior.

[0111] The behavior recording unit can use the emotion estimation function to analyze the emotions of a user when practicing eco-friendly behavior and provide incentives to elicit positive emotions. For example, the emotion estimation function can be used to analyze the emotions of a user when recycling and provide incentives to elicit positive emotions. For example, a positive feedback message can be displayed after recycling. The behavior recording unit can also analyze emotions in real time when using public transportation and provide incentives to elicit positive emotions. Furthermore, the behavior recording unit can analyze emotions when practicing energy-saving behavior and provide incentives to elicit positive emotions. In this way, by analyzing the user's emotions and providing incentives to elicit positive emotions, it is possible to encourage the user to continue practicing eco-friendly behavior.

[0112] The behavior recording unit can use the emotion estimation function to analyze the emotions of a user when practicing eco-friendly behavior and provide incentives to elicit positive emotions. For example, the emotion estimation function can be used to analyze the emotions of a user when recycling and provide incentives to elicit positive emotions. For example, a positive feedback message can be displayed after recycling. The behavior recording unit can also analyze emotions in real time when using public transportation and provide incentives to elicit positive emotions. Furthermore, the behavior recording unit can analyze emotions when practicing energy-saving behavior and provide incentives to elicit positive emotions. In this way, by analyzing the user's emotions and providing incentives to elicit positive emotions, it is possible to encourage the user to continue practicing eco-friendly behavior.

[0113] The behavior recording unit can use the emotion estimation function to analyze the emotions of a user when practicing eco-friendly behavior and provide incentives to elicit positive emotions. For example, the emotion estimation function can be used to analyze the emotions of a user when recycling and provide incentives to elicit positive emotions. For example, a positive feedback message can be displayed after recycling. The behavior recording unit can also analyze emotions in real time when using public transportation and provide incentives to elicit positive emotions. Furthermore, the behavior recording unit can analyze emotions when practicing energy-saving behavior and provide incentives to elicit positive emotions. In this way, by analyzing the user's emotions and providing incentives to elicit positive emotions, it is possible to encourage the user to continue practicing eco-friendly behavior.

[0114] The behavior recording unit can use the emotion estimation function to analyze the emotions of a user when practicing eco-friendly behavior and provide incentives to elicit positive emotions. For example, the emotion estimation function can be used to analyze the emotions of a user when recycling and provide incentives to elicit positive emotions. For example, a positive feedback message can be displayed after recycling. The behavior recording unit can also analyze emotions in real time when using public transportation and provide incentives to elicit positive emotions. Furthermore, the behavior recording unit can analyze emotions when practicing energy-saving behavior and provide incentives to elicit positive emotions. In this way, by analyzing the user's emotions and providing incentives to elicit positive emotions, it is possible to encourage the user to continue practicing eco-friendly behavior.

[0115] The processing flow of the second embodiment will be briefly explained below.

[0116] Step 1: The behavior recorder allows users to record eco-friendly behaviors, such as recycling, using public transportation, saving energy, and using reusable products. Step 2: The points management unit manages points based on the eco-friendly actions recorded by the behavior recording unit, such as giving points for recycling, using public transportation, saving energy, and using reusable products. Step 3: The exchange unit exchanges the points managed by the point management unit for goods, services, or donations. For example, if a user accumulates a certain number of points, they can use those points to purchase eco-friendly goods, receive services such as eco-tours and eco-workshops, or donate to environmental protection organizations.

[0117] 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.

[0118] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0119] 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.

[0120] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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).

[0126] 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.

[0127] 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.

[0128] 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.

[0129] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0130] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0131] 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.

[0132] 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.

[0133] 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 AI 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.

[0134] 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.

[0135] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0136] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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).

[0141] 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.

[0142] 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.

[0143] 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.

[0144] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0145] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0146] 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.

[0147] 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.

[0148] 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 AI 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.

[0149] 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.

[0150] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0151] 7, a 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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).

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0161] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0162] 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.

[0163] 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.

[0164] 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 AI 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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).

[0170] 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 "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0171] 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."

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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]

[0184] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. An action recorder that records eco-friendly actions; a point management unit that manages points based on the eco-friendly behavior recorded by the behavior recording unit; an exchange unit that exchanges the points managed by the point management unit for goods, services, or donations. A system characterized by:

2. The behavior recording unit Recording the user's recycling behavior and awarding the points based on the recycling behavior.

2. The system of claim 1.

3. The behavior recording unit Recording the user's public transport usage history and awarding the points based on the usage history 2. The system of claim 1.

4. The point management unit When a user accumulates a certain number of points, the user can purchase the eco-friendly product.

2. The system of claim 1.

5. The exchange unit is Users can use the points to receive specific services.

2. The system of claim 1.

6. The exchange unit is Users can donate the points to environmental protection organizations.

2. The system of claim 1.

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