system

Abstract

The system according to this embodiment aims to provide mental care for pet owners suffering from pet loss. [Solution] The system according to the embodiment comprises a generation unit, a display unit, and a care unit. The generation unit generates a video of the pet using a generation AI based on photos and videos of the pet. The display unit displays the video generated by the generation unit in a virtual space. The care unit provides mental care to the pet owner by allowing them to view the video displayed by the display unit.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, the mental care of the owner due to pet loss has not been sufficiently carried out, and there is room for improvement.

[0005] The system according to the embodiment aims to perform mental care for the owner due to pet loss.

Means for Solving the Problems

[0006] The system according to the embodiment includes a generation unit, a display unit, and a care unit. The generation unit generates an AI-generated video of a pet based on photos and videos of the pet. The display unit displays the video generated by the generation unit in a virtual space. The care unit performs mental care by allowing the owner to view the video displayed by the display unit.

Effects of the Invention

[0007] The system according to this embodiment can provide mental care to pet owners suffering from pet loss. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0014] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the 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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The pet loss care system according to an embodiment of the present invention is a system that uses a generation AI to generate videos of real pets, allowing users to view their pets in a virtual space. The pet loss care system takes photos and videos of pets as input to the generation AI, which then generates videos of the pets that appear almost alive. The generated videos are placed in a virtual space, and pet owners can access them anytime, anywhere, from devices such as smartphones or personal computers. This system aims to provide mental care for pet owners suffering from pet loss, stimulate the need for perpetual memorial services for pets, and create a new market for post-pet loss care. For example, photos and videos of pets are input to the generation AI. The owner uploads photos and videos of their pet. This information is input to the generation AI. The generation AI analyzes the input information and generates videos of the pets that appear almost alive. The generation AI reproduces the pet's movements and expressions to create realistic videos. For example, it can reproduce scenes of pets running around in a field or playing with other pets. The generated videos are placed in a virtual space. Pet owners can access a virtual space from devices such as smartphones and personal computers to view their pets. For example, when an owner accesses the virtual space using their smartphone, they can see their pet running around in a field. This system aims to provide mental care for pet owners suffering from pet loss. Because owners can see their pets anytime, anywhere, it can fill the void in their hearts. It also aims to stimulate the need for perpetual memorial services for pets and create a new market for post-pet loss care. For example, by creating a perpetual memorial service for a pet's video in the virtual space, owners can preserve memories of their pet forever. In this way, a system that generates videos of real pets using generative AI and allows users to view their pets in a virtual space can provide mental care for pet owners suffering from pet loss and stimulate the need for perpetual memorial services for pets, thereby creating a new market. Thus, a pet loss care system can provide mental care for pet owners and stimulate the need for perpetual memorial services for pets.

[0029] The pet loss care system according to this embodiment comprises a generation unit, a display unit, and a care unit. The generation unit generates videos of pets using a generation AI based on photos and videos of the pets. For example, the generation unit takes photos and videos of the pets as input to the generation AI, which then generates videos of the pets that look as if they were alive. The generation unit uses the generation AI to reproduce the pets' movements and expressions, generating realistic videos. For example, the generation AI can reproduce scenes of pets running around in a field or playing with other pets. Some or all of the above-described processes in the generation unit are performed using the generation AI. The display unit displays the videos generated by the generation unit in a virtual space. For example, the display unit places the generated videos in a virtual space, allowing pet owners to view their pets anytime, anywhere by accessing it from a device such as a smartphone or personal computer. The display unit displays videos of pets in a virtual space. For example, when a pet owner accesses the virtual space using their smartphone, they can see their pets running around in a field. Some or all of the above-described processes in the display unit may be performed using AI or without AI. The care unit provides mental care by allowing the owner to view videos displayed by the display unit. For example, the care unit can help fill the void in the owner's heart by allowing them to watch videos of their pet. Because the care unit allows the owner to see their pet anytime, anywhere, it can provide mental care for pet loss. Some or all of the above-described processing in the care unit may be performed using AI or not. As a result, the pet loss care system according to this embodiment can provide mental care for the owner.

[0030] The generation unit uses AI to create videos of pets based on photos and videos of the pets. For example, the generation unit takes photos and videos of the pet as input and the AI ​​generates videos of the pet that look as if they were alive. Specifically, the generation AI uses deep learning technology to learn the characteristics of the pet and reproduce its movements and expressions. The generation AI analyzes the pet's image data and simulates the movement of its skeleton and muscles to generate natural movements. For example, in a scene where a pet is running around in a field, the AI ​​realistically reproduces the movement of its legs and body balance, and meticulously depicts the movement of its fur in the wind and the changes in its shadows. The generation AI also focuses on expressing the pet's emotions, realistically reproducing expressions such as joy, surprise, and excitement. As a result, the generated videos have a sense of realism as if the pet were actually there. Furthermore, the generation unit can combine multiple photos and videos provided by the user to generate a wider variety of scenes and movements. For example, it can be customized to meet user requests, such as scenes of the pet playing at home or spending time with its owner. Some or all of the processing described above in the generation unit is performed using a generation AI. The generation AI may operate on the cloud, and users can access the generation AI via the internet to generate videos. This allows the generation unit to provide users with high-quality, realistic videos of their pets, contributing to pet loss care.

[0031] The display unit displays videos generated by the generation unit within a virtual space. For example, the display unit places the generated videos within the virtual space, allowing pet owners to access them from devices such as smartphones or personal computers, enabling them to view their pets anytime, anywhere. Specifically, the display unit utilizes virtual reality (VR) and augmented reality (AR) technologies to provide an immersive environment for users to enjoy videos of their pets. For instance, by wearing a VR headset, users can experience videos of their pets in a 360-degree field of view, giving them the feeling of being with their pets. Furthermore, AR technology allows for the overlaying of pet videos onto the user's real-world environment. This allows users to experience the feeling of spending time with their pets in real-world spaces such as their living room or garden. The display unit also features a well-designed user interface (UI), enabling intuitive playback, pause, and scene switching. For example, users can use a smartphone's touchscreen to swipe to switch between pet videos and pinch to zoom in and out. Additionally, the display unit can continuously improve video quality and display methods based on user feedback. For example, a user can request a specific scene or movement, which can then be coordinated with the generation unit to generate and display a new video. This allows the display unit to provide users with a consistently fresh and moving experience, which can be helpful in caring for someone grieving the loss of a pet.

[0032] The Care Unit provides mental care by allowing pet owners to view videos displayed by the Display Unit. For example, the Care Unit can help pet owners fill emotional voids by allowing them to watch videos of their pets. Specifically, the Care Unit employs a psychological approach, monitoring the user's emotional state and providing pet videos at appropriate times. For instance, playing pet videos when a user is feeling stressed or sad can provide emotional comfort. The Care Unit can also customize video content and display methods based on user feedback. For example, users can request their favorite pet movements or scenes, and the Care Unit can collaborate with the Generation Unit to generate and display new videos. Furthermore, the Care Unit provides additional features to support the user's mental care. For example, it can combine relaxation music and meditation guides to help users enter a deeper state of relaxation. The Care Unit also provides a platform for users to share memories of their pets. For example, users can share generated videos with family and friends to gain empathy and support. In this way, the Care Unit comprehensively supports the user's mental care and can alleviate the pain of pet loss. Some or all of the above-described processes in the care section may be performed using AI or not. This allows the pet loss care system according to the embodiment to provide mental care to pet owners.

[0033] The generation unit can reproduce the movements and expressions of pets using a generation AI. For example, the generation unit uses the generation AI to reproduce the movements and expressions of pets and generate realistic videos. The generation unit can use motion capture and facial recognition technology to have the generation AI reproduce the movements and expressions of pets. For example, the generation AI captures the movements of pets using motion capture technology and reproduces those movements. The generation AI also analyzes the expressions of pets using facial recognition technology and reproduces those expressions. In this way, by having the generation AI reproduce the movements and expressions of pets, it is possible to generate more realistic videos of pets. Some or all of the above processing in the generation unit is performed using the generation AI.

[0034] The display unit can display videos of pets in a virtual space. For example, the display unit can place generated videos in a virtual space, allowing pet owners to view their pets anytime, anywhere by accessing them from devices such as smartphones or personal computers. The display unit can use 3D rendering and interactive display technologies to display videos of pets in a virtual space. For example, the display unit can display videos of pets using 3D rendering technology, allowing pet owners to interact with their pets in the virtual space. The display unit can also use interactive display technology to allow pet owners to manipulate the videos of their pets. This allows pet owners to view their pets anytime, anywhere by displaying videos of them in a virtual space. Some or all of the above-described processes in the display unit may be performed using AI or not.

[0035] The care department can provide mental care by allowing pet owners to watch videos of their pets. For example, the care department can help pet owners fill emotional voids by watching videos of their pets. The care department can provide mental care for pet loss because pet owners can see their pets anytime, anywhere. The care department can use psychotherapy and relaxation techniques to clarify specific methods and standards for mental care. For example, the care department can help pet owners experience relaxation effects by watching videos of their pets. The care department can also help pet owners gain psychological stability by watching videos of their pets. Thus, pet owners can provide mental care by watching videos of their pets. Some or all of the above processes in the care department may be performed using AI or not.

[0036] The memorial service unit can provide perpetual memorial services for videos of pets in a virtual space. For example, by providing perpetual memorial services for generated videos of pets in a virtual space, the memorial service unit can allow pet owners to preserve their memories of their pets forever. The memorial service unit can use digital archives and online memorial services to clarify the specific methods and criteria for perpetual memorial services. For example, the memorial service unit can save videos of pets as a digital archive and provide perpetual memorial services in a virtual space. Alternatively, the memorial service unit can use online memorial services to provide perpetual memorial services for videos of pets in a virtual space. This allows pet owners to preserve their memories of their pets forever by providing perpetual memorial services for videos of their pets in a virtual space. Some or all of the above-described processes in the memorial service unit may be performed using AI or not.

[0037] The generation unit can estimate the owner's emotions and adjust the pet's movements and expressions based on the estimated emotions. For example, if the owner is sad, the generation AI can reproduce the pet's gentle expressions and slow movements. If the owner is happy, the generation AI can reproduce the pet's lively movements and cheerful expressions. If the owner is relaxed, the generation AI can reproduce the pet's calm movements and calm expressions. This allows for more appropriate mental care by adjusting the pet's movements and expressions based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the generation unit is performed using the generation AI.

[0038] The generation unit can analyze the pet's past behavioral patterns and reproduce more realistic movements. For example, the generation unit's generating AI analyzes past videos to reproduce movements the pet frequently performed. The generation unit's generating AI can learn data to reproduce specific behavioral patterns of the pet (e.g., playing with toys, sleeping). The generation unit's generating AI can perform detailed motion analysis to reproduce the speed and rhythm of the pet's movements. In this way, by analyzing the pet's past behavioral patterns, it is possible to reproduce more realistic movements. Some or all of the above processing in the generation unit is performed using the generating AI.

[0039] The generation unit can add a function that allows pet owners to request specific scenes and generate those scenes. For example, the generation unit can request a specific place where the pet spent time with their pet (e.g., a park, inside the house), and the generation AI can recreate that scene. The generation unit can also request a specific action of the pet by the pet (e.g., playing with a toy, eating), and the generation AI can generate that scene. The generation unit can also request a specific time of day for the pet (e.g., morning, evening), and the generation AI can recreate that scene. This allows for the generation of more personalized videos by enabling pet owners to request specific scenes. Some or all of the above processing in the generation unit is performed using the generation AI.

[0040] The generation unit can estimate the owner's emotions and select video scenes to generate based on the estimated emotions. For example, if the owner is sad, the generation AI can select calm scenes of the pet. If the owner is happy, the generation AI can select lively scenes of the pet. If the owner is relaxed, the generation AI can select calm scenes of the pet. This allows for more appropriate mental care by selecting video scenes based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the generation unit is performed using the generation AI.

[0041] The generation unit can add interactions with other pets and their owners when generating videos of pets. For example, the generation unit can generate scenes where the generation AI plays with other pets. The generation unit can generate scenes where the generation AI spends time with the pet and its owner. The generation unit can generate scenes where the pet and its entire family are together. By adding interactions with other pets and their owners, more realistic videos can be generated. Some or all of the above processing in the generation unit is performed using the generation AI.

[0042] The generation unit can reflect seasonal and weather changes when generating videos of pets. For example, the generation unit's AI can generate a scene of a pet playing in the snow. The generation unit's AI can generate a scene of a pet playing in a spring flower field. The generation unit's AI can generate a scene of a pet playing on a summer beach. By reflecting seasonal and weather changes, it is possible to generate more realistic videos. Some or all of the above processing in the generation unit is performed using the generation AI.

[0043] The display unit can estimate the owner's emotions and adjust the order in which videos are displayed based on the estimated emotions. For example, if the owner is sad, the generating AI can display calm scenes of the pet first. If the owner is having fun, the generating AI can display active scenes of the pet first. If the owner is relaxed, the generating AI can display calm scenes of the pet first. This allows for more appropriate mental care by adjusting the order of videos based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the display unit may be performed using AI or not.

[0044] The display unit can be enhanced with features that allow users to customize how pets are displayed in the virtual space. For example, the display unit can provide a function that allows owners to customize the size and color of their pets. The display unit can also provide a function that allows owners to customize the movements and expressions of their pets. The display unit can also provide a function that allows owners to customize the background and environment of their pets. This allows for customization of how pets are displayed in the virtual space, enabling displays tailored to the owner's preferences. Some or all of the above-described processes in the display unit may be performed using AI or not.

[0045] The display unit can be enhanced with features that allow pet owners to interact with their pets in a virtual space. For example, the display unit can provide a function that allows pet owners to throw virtual toys to their pets. The display unit can provide a function that allows pet owners to feed their pets virtual food. The display unit can provide a function that allows pet owners to take their pets for walks in a virtual space. This enables a more realistic experience by allowing pet owners to interact with their pets in a virtual space. Some or all of the above processing in the display unit may be performed using AI or not.

[0046] The display unit can estimate the owner's emotions and adjust the brightness and color tone of the displayed video based on the estimated emotions. For example, if the owner is sad, the generating AI can lower the brightness of the video and adjust the color tone to a calmer one. If the owner is enjoying themselves, the generating AI can increase the brightness of the video and adjust the color tone to a brighter one. If the owner is relaxed, the generating AI can set the brightness of the video to a moderate level and adjust the color tone to a gentle one. This allows for more appropriate mental care by adjusting the brightness and color tone of the video based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the display unit may be performed using AI or not.

[0047] The display unit can add background music and sound effects when displaying videos of pets in a virtual space. For example, the display unit can use a generating AI to select and play background music that matches the pet's movements. The display unit can use a generating AI to add sound effects (e.g., running sounds, barking) that correspond to the pet's actions. The display unit can use a generating AI to select and play music that matches the owner's emotions. By adding background music and sound effects, a more realistic video can be displayed. Some or all of the above processing in the display unit may be performed using AI, or it may be performed without using AI.

[0048] The display unit can add a function that allows users to share videos of their pets with other users when displaying videos of pets in a virtual space. For example, the display unit can provide a function that allows pet owners to share videos of their pets with family and friends. The display unit can provide a function that allows pet owners to share videos of their pets on social media. The display unit can provide a function that allows pet owners to share videos of their pets with other pet owners. This allows users to share memories of their pets with other users. Some or all of the above processing in the display unit may be performed using AI or not.

[0049] The care unit can estimate the owner's emotions and adjust the content of mental care based on the estimated emotions. For example, if the owner is sad, the care unit can use a generating AI to display calm scenes of the pet and provide mental care. If the owner is happy, the care unit can use a generating AI to display active scenes of the pet and provide mental care. If the owner is relaxed, the care unit can use a generating AI to display calm scenes of the pet and provide mental care. In this way, more appropriate care can be provided by adjusting the content of mental care based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the care unit may be performed using AI or not using AI.

[0050] The care department can analyze the owner's past mental care history and provide the most suitable care method. For example, the care department can provide the same mental care method that was previously effective for the owner. The care department can propose new care methods based on the owner's past mental care history. The care department can analyze the owner's mental care history and provide care at the optimal time. In this way, by analyzing past mental care history, the care department can provide the most suitable care method. Some or all of the above processes in the care department may be performed using AI or not.

[0051] The care department can monitor the emotional changes of pet owners after they watch videos of their pets and incorporate this into future care. For example, the care department can monitor the emotions of pet owners after they watch videos of their pets and adjust the content of the next care. The care department can record the emotional changes of pet owners after they watch videos of their pets and incorporate this into future care. The care department can analyze the emotions of pet owners after they watch videos of their pets and suggest methods for future care. In this way, by monitoring the emotional changes of pet owners, this can be incorporated into future care. Some or all of the above processes in the care department may be performed using AI or not.

[0052] The care unit can estimate the owner's emotions and adjust the frequency of care based on the estimated emotions. For example, if the owner is sad, the care unit can provide mental care more frequently. If the owner is happy, the care unit can provide mental care at a moderate frequency. If the owner is relaxed, the care unit can provide mental care less frequently. This allows for more appropriate care by adjusting the frequency of care based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the care unit may be performed using AI or not.

[0053] The care unit can provide relaxing music or guided meditation after the owner has watched a video of their pet. For example, the care unit can play relaxing music after the owner has watched a video of their pet. The care unit can provide guided meditation after the owner has watched a video of their pet. The care unit can play relaxing ambient sounds after the owner has watched a video of their pet. This allows for more effective mental care by providing relaxing music or guided meditation after the owner has watched a video of their pet. Some or all of the above processing in the care unit may be performed using AI or not.

[0054] The care department can add a function that allows pet owners to keep an emotional journal after watching videos of their pets. For example, the care department can provide a function that allows pet owners to keep an emotional journal after watching videos of their pets. The care department can provide questions for pet owners to record their emotions after watching videos of their pets. The care department can provide templates for pet owners to keep an emotional journal after watching videos of their pets. This allows pet owners to record changes in their emotions by keeping an emotional journal after watching videos of their pets, which can be used to improve future care. Some or all of the above processes in the care department may be performed using AI or not.

[0055] The memorial service unit can estimate the owner's emotions and adjust the memorial service method based on the estimated emotions. For example, if the owner is sad, the generating AI can display a memorial service scene accompanied by calming music. If the owner is relaxed, the generating AI can display a memorial service scene in a quiet environment. If the owner is grateful, the generating AI can display a memorial service scene that includes a message of gratitude. This allows for a more appropriate memorial service by adjusting the memorial service method based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the memorial service unit may be performed using AI or not.

[0056] The memorial service section can add features that allow users to customize the memorial service scene in the virtual space. For example, the memorial service section can provide a function that allows the owner to select the background for the memorial service scene. The memorial service section can provide a function that allows the owner to select the music to be used in the memorial service scene. The memorial service section can provide a function that allows the owner to customize the message displayed in the memorial service scene. This allows for a memorial service tailored to the owner's preferences by enabling the customization of the memorial service scene. Some or all of the above processes in the memorial service section may be performed using AI or not.

[0057] The memorial service section can be enhanced with a feature that allows pet owners to leave messages for their pets during the memorial service. For example, the memorial service section can provide a function that allows pet owners to input messages of gratitude for their pets and display them in the memorial service scene. The memorial service section can provide a function that allows pet owners to input memories of their pets and display them in the memorial service scene. The memorial service section can provide a function that allows pet owners to input messages of prayer for their pets and display them in the memorial service scene. This allows for a more emotional memorial service by enabling pet owners to leave messages for their pets during the memorial service. Some or all of the above processes in the memorial service section may be performed using AI or not.

[0058] The memorial service unit can estimate the owner's emotions and adjust the timing of memorial services based on those estimated emotions. For example, if the owner is sad, the memorial service unit will suggest memorial services more frequently. If the owner is relaxed, the memorial service unit can suggest memorial services at a moderate frequency. If the owner feels grateful, the memorial service unit can suggest memorial services on specific anniversaries. By adjusting the timing of memorial services based on the owner's emotions, more appropriate memorial services can be performed. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the memorial service unit may be performed using AI or not.

[0059] The memorial service section can add a function that allows users to perform memorial services together with other pet owners in the virtual space. For example, the memorial service section can provide a function that allows pet owners to share memorial service scenes with other pet owners. The memorial service section can provide a function that allows pet owners to exchange memorial service messages with other pet owners. The memorial service section can provide a function that allows pet owners to customize memorial service scenes together with other pet owners. This makes it possible to have a shared memorial service experience by performing memorial services together with other pet owners. Some or all of the above processes in the memorial service section may be performed using AI or not.

[0060] The memorial service section can add a function to display photos and videos of pets as mementos during memorial services in the virtual space. For example, the memorial service section can provide a function that allows pet owners to display photos of their pets as mementos during the memorial service. The memorial service section can provide a function that allows pet owners to display videos of their pets as mementos during the memorial service. The memorial service section can provide a function that allows pet owners to display photo albums of their pets as mementos during the memorial service. This makes it possible to have a more emotionally charged memorial service by displaying photos and videos of pets as mementos. Some or all of the above processing in the memorial service section may be performed using AI or not.

[0061] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0062] The pet loss care system can also be equipped with a voice recognition unit. The voice recognition unit can recognize the owner's voice and change the pet's actions and scenes in the video based on that voice. For example, if the owner says "sit," the generating AI can generate a scene of the pet sitting. Also, if the owner says "let's play," the generating AI can generate a scene of the pet playing. Furthermore, if the owner calls the pet's name, the generating AI can generate a scene of the pet turning towards the owner. This allows for a more interactive experience by changing the pet's actions and scenes in response to the owner's voice.

[0063] The pet loss care system can also include a reminder function. This reminder function provides owners with the opportunity to regularly watch videos of their pets. For example, the reminder function can send notifications to ensure owners don't forget to watch videos of their pets amidst their busy daily lives. Reminders can also be set for specific days (e.g., the pet's birthday, the anniversary of their death). This allows owners to provide continuous emotional support by regularly watching videos of their pets.

[0064] The pet loss care system can also be equipped with a pet growth simulation unit. This unit provides a function that allows owners to simulate their pet's growth process. For example, a generating AI can recreate the growth process from puppyhood to adulthood. It can also simulate changes in behavior and habits that occur as the pet grows. This allows owners to relive their pet's growth process, fostering a deeper emotional connection.

[0065] The pet loss care system can also be equipped with a pet health management unit. This unit simulates the pet's health condition and provides health management advice to the owner. For example, a generating AI can simulate the pet's diet and exercise, and suggest appropriate health management methods. It can also advise the owner on appropriate care methods based on the pet's health condition. This allows owners to provide more appropriate care by simulating their pet's health management.

[0066] The pet loss care system can also be equipped with a pet future prediction unit. This unit provides a function to predict the future appearance and behavior of the pet and present it to the owner. For example, a generative AI can simulate the pet's future appearance and present it to the owner. It can also predict the pet's future behavior and habits and provide advice to the owner. This allows owners to consider their relationship with their pet from a longer-term perspective by predicting the pet's future.

[0067] The pet loss care system can also include a pet memory sharing section. This section provides a function for pet owners to share memories of their pets with other pet owners. For example, pet owners can share videos and photos of their pets with other pet owners to receive empathy and advice. They can also share episodes related to their pets' memories and interact with other pet owners. This allows pet owners to share memories of their pets with other pet owners, providing a richer community experience.

[0068] The following briefly describes the processing flow for example form 1.

[0069] Step 1: The generation unit uses a generation AI to create videos of pets based on photos and videos of the pets. The generation unit inputs photos and videos of the pets into the generation AI, which then generates videos of the pets that look as if they were alive. The generation AI reproduces the pets' movements and expressions to create realistic videos. For example, the generation AI can reproduce scenes of pets running around in a field or playing with other pets. Step 2: The display unit displays the video generated by the generation unit in a virtual space. The display unit places the generated video in a virtual space, allowing pet owners to view their pets anytime, anywhere by accessing it from devices such as smartphones or personal computers. For example, when a pet owner accesses the virtual space using their smartphone, they can see their pet running around in a field. Step 3: The care unit provides mental care by allowing pet owners to watch videos displayed on the display unit. By watching videos of their pets, pet owners can fill the void in their hearts. Because pet owners can see their pets anytime, anywhere, mental care for pet loss can be provided.

[0070] (Example of form 2) The pet loss care system according to an embodiment of the present invention is a system that uses a generation AI to generate videos of real pets, allowing users to view their pets in a virtual space. The pet loss care system takes photos and videos of pets as input to the generation AI, which then generates videos of the pets that appear almost alive. The generated videos are placed in a virtual space, and pet owners can access them anytime, anywhere, from devices such as smartphones or personal computers. This system aims to provide mental care for pet owners suffering from pet loss, stimulate the need for perpetual memorial services for pets, and create a new market for post-pet loss care. For example, photos and videos of pets are input to the generation AI. The owner uploads photos and videos of their pet. This information is input to the generation AI. The generation AI analyzes the input information and generates videos of the pets that appear almost alive. The generation AI reproduces the pet's movements and expressions to create realistic videos. For example, it can reproduce scenes of pets running around in a field or playing with other pets. The generated videos are placed in a virtual space. Pet owners can access a virtual space from devices such as smartphones and personal computers to view their pets. For example, when an owner accesses the virtual space using their smartphone, they can see their pet running around in a field. This system aims to provide mental care for pet owners suffering from pet loss. Because owners can see their pets anytime, anywhere, it can fill the void in their hearts. It also aims to stimulate the need for perpetual memorial services for pets and create a new market for post-pet loss care. For example, by creating a perpetual memorial service for a pet's video in the virtual space, owners can preserve memories of their pet forever. In this way, a system that generates videos of real pets using generative AI and allows users to view their pets in a virtual space can provide mental care for pet owners suffering from pet loss and stimulate the need for perpetual memorial services for pets, thereby creating a new market. Thus, a pet loss care system can provide mental care for pet owners and stimulate the need for perpetual memorial services for pets.

[0071] The pet loss care system according to this embodiment comprises a generation unit, a display unit, and a care unit. The generation unit generates videos of pets using a generation AI based on photos and videos of the pets. For example, the generation unit takes photos and videos of the pets as input to the generation AI, which then generates videos of the pets that look as if they were alive. The generation unit uses the generation AI to reproduce the pets' movements and expressions, generating realistic videos. For example, the generation AI can reproduce scenes of pets running around in a field or playing with other pets. Some or all of the above-described processes in the generation unit are performed using the generation AI. The display unit displays the videos generated by the generation unit in a virtual space. For example, the display unit places the generated videos in a virtual space, allowing pet owners to view their pets anytime, anywhere by accessing it from a device such as a smartphone or personal computer. The display unit displays videos of pets in a virtual space. For example, when a pet owner accesses the virtual space using their smartphone, they can see their pets running around in a field. Some or all of the above-described processes in the display unit may be performed using AI or without AI. The care unit provides mental care by allowing the owner to view videos displayed by the display unit. For example, the care unit can help fill the void in the owner's heart by allowing them to watch videos of their pet. Because the care unit allows the owner to see their pet anytime, anywhere, it can provide mental care for pet loss. Some or all of the above-described processing in the care unit may be performed using AI or not. As a result, the pet loss care system according to this embodiment can provide mental care for the owner.

[0072] The generation unit uses AI to create videos of pets based on photos and videos of the pets. For example, the generation unit takes photos and videos of the pet as input and the AI ​​generates videos of the pet that look as if they were alive. Specifically, the generation AI uses deep learning technology to learn the characteristics of the pet and reproduce its movements and expressions. The generation AI analyzes the pet's image data and simulates the movement of its skeleton and muscles to generate natural movements. For example, in a scene where a pet is running around in a field, the AI ​​realistically reproduces the movement of its legs and body balance, and meticulously depicts the movement of its fur in the wind and the changes in its shadows. The generation AI also focuses on expressing the pet's emotions, realistically reproducing expressions such as joy, surprise, and excitement. As a result, the generated videos have a sense of realism as if the pet were actually there. Furthermore, the generation unit can combine multiple photos and videos provided by the user to generate a wider variety of scenes and movements. For example, it can be customized to meet user requests, such as scenes of the pet playing at home or spending time with its owner. Some or all of the processing described above in the generation unit is performed using a generation AI. The generation AI may operate on the cloud, and users can access the generation AI via the internet to generate videos. This allows the generation unit to provide users with high-quality, realistic videos of their pets, contributing to pet loss care.

[0073] The display unit displays videos generated by the generation unit within a virtual space. For example, the display unit places the generated videos within the virtual space, allowing pet owners to access them from devices such as smartphones or personal computers, enabling them to view their pets anytime, anywhere. Specifically, the display unit utilizes virtual reality (VR) and augmented reality (AR) technologies to provide an immersive environment for users to enjoy videos of their pets. For instance, by wearing a VR headset, users can experience videos of their pets in a 360-degree field of view, giving them the feeling of being with their pets. Furthermore, AR technology allows for the overlaying of pet videos onto the user's real-world environment. This allows users to experience the feeling of spending time with their pets in real-world spaces such as their living room or garden. The display unit also features a well-designed user interface (UI), enabling intuitive playback, pause, and scene switching. For example, users can use a smartphone's touchscreen to swipe to switch between pet videos and pinch to zoom in and out. Additionally, the display unit can continuously improve video quality and display methods based on user feedback. For example, a user can request a specific scene or movement, which can then be coordinated with the generation unit to generate and display a new video. This allows the display unit to provide users with a consistently fresh and moving experience, which can be helpful in caring for someone grieving the loss of a pet.

[0074] The Care Unit provides mental care by allowing pet owners to view videos displayed by the Display Unit. For example, the Care Unit can help pet owners fill emotional voids by allowing them to watch videos of their pets. Specifically, the Care Unit employs a psychological approach, monitoring the user's emotional state and providing pet videos at appropriate times. For instance, playing pet videos when a user is feeling stressed or sad can provide emotional comfort. The Care Unit can also customize video content and display methods based on user feedback. For example, users can request their favorite pet movements or scenes, and the Care Unit can collaborate with the Generation Unit to generate and display new videos. Furthermore, the Care Unit provides additional features to support the user's mental care. For example, it can combine relaxation music and meditation guides to help users enter a deeper state of relaxation. The Care Unit also provides a platform for users to share memories of their pets. For example, users can share generated videos with family and friends to gain empathy and support. In this way, the Care Unit comprehensively supports the user's mental care and can alleviate the pain of pet loss. Some or all of the above-described processes in the care section may be performed using AI or not. This allows the pet loss care system according to the embodiment to provide mental care to pet owners.

[0075] The generation unit can reproduce the movements and expressions of pets using a generation AI. For example, the generation unit uses the generation AI to reproduce the movements and expressions of pets and generate realistic videos. The generation unit can use motion capture and facial recognition technology to have the generation AI reproduce the movements and expressions of pets. For example, the generation AI captures the movements of pets using motion capture technology and reproduces those movements. The generation AI also analyzes the expressions of pets using facial recognition technology and reproduces those expressions. In this way, by having the generation AI reproduce the movements and expressions of pets, it is possible to generate more realistic videos of pets. Some or all of the above processing in the generation unit is performed using the generation AI.

[0076] The display unit can display videos of pets in a virtual space. For example, the display unit can place generated videos in a virtual space, allowing pet owners to view their pets anytime, anywhere by accessing them from devices such as smartphones or personal computers. The display unit can use 3D rendering and interactive display technologies to display videos of pets in a virtual space. For example, the display unit can display videos of pets using 3D rendering technology, allowing pet owners to interact with their pets in the virtual space. The display unit can also use interactive display technology to allow pet owners to manipulate the videos of their pets. This allows pet owners to view their pets anytime, anywhere by displaying videos of them in a virtual space. Some or all of the above-described processes in the display unit may be performed using AI or not.

[0077] The care department can provide mental care by allowing pet owners to watch videos of their pets. For example, the care department can help pet owners fill emotional voids by watching videos of their pets. The care department can provide mental care for pet loss because pet owners can see their pets anytime, anywhere. The care department can use psychotherapy and relaxation techniques to clarify specific methods and standards for mental care. For example, the care department can help pet owners experience relaxation effects by watching videos of their pets. The care department can also help pet owners gain psychological stability by watching videos of their pets. Thus, pet owners can provide mental care by watching videos of their pets. Some or all of the above processes in the care department may be performed using AI or not.

[0078] The memorial service unit can provide perpetual memorial services for videos of pets in a virtual space. For example, by providing perpetual memorial services for generated videos of pets in a virtual space, the memorial service unit can allow pet owners to preserve their memories of their pets forever. The memorial service unit can use digital archives and online memorial services to clarify the specific methods and criteria for perpetual memorial services. For example, the memorial service unit can save videos of pets as a digital archive and provide perpetual memorial services in a virtual space. Alternatively, the memorial service unit can use online memorial services to provide perpetual memorial services for videos of pets in a virtual space. This allows pet owners to preserve their memories of their pets forever by providing perpetual memorial services for videos of their pets in a virtual space. Some or all of the above-described processes in the memorial service unit may be performed using AI or not.

[0079] The generation unit can estimate the owner's emotions and adjust the pet's movements and expressions based on the estimated emotions. For example, if the owner is sad, the generation AI can reproduce the pet's gentle expressions and slow movements. If the owner is happy, the generation AI can reproduce the pet's lively movements and cheerful expressions. If the owner is relaxed, the generation AI can reproduce the pet's calm movements and calm expressions. This allows for more appropriate mental care by adjusting the pet's movements and expressions based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the generation unit is performed using the generation AI.

[0080] The generation unit can analyze the pet's past behavioral patterns and reproduce more realistic movements. For example, the generation unit's generating AI analyzes past videos to reproduce movements the pet frequently performed. The generation unit's generating AI can learn data to reproduce specific behavioral patterns of the pet (e.g., playing with toys, sleeping). The generation unit's generating AI can perform detailed motion analysis to reproduce the speed and rhythm of the pet's movements. In this way, by analyzing the pet's past behavioral patterns, it is possible to reproduce more realistic movements. Some or all of the above processing in the generation unit is performed using the generating AI.

[0081] The generation unit can add a function that allows pet owners to request specific scenes and generate those scenes. For example, the generation unit can request a specific place where the pet spent time with their pet (e.g., a park, inside the house), and the generation AI can recreate that scene. The generation unit can also request a specific action of the pet by the pet (e.g., playing with a toy, eating), and the generation AI can generate that scene. The generation unit can also request a specific time of day for the pet (e.g., morning, evening), and the generation AI can recreate that scene. This allows for the generation of more personalized videos by enabling pet owners to request specific scenes. Some or all of the above processing in the generation unit is performed using the generation AI.

[0082] The generation unit can estimate the owner's emotions and select video scenes to generate based on the estimated emotions. For example, if the owner is sad, the generation AI can select calm scenes of the pet. If the owner is happy, the generation AI can select lively scenes of the pet. If the owner is relaxed, the generation AI can select calm scenes of the pet. This allows for more appropriate mental care by selecting video scenes based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the generation unit is performed using the generation AI.

[0083] The generation unit can add interactions with other pets and their owners when generating videos of pets. For example, the generation unit can generate scenes where the generation AI plays with other pets. The generation unit can generate scenes where the generation AI spends time with the pet and its owner. The generation unit can generate scenes where the pet and its entire family are together. By adding interactions with other pets and their owners, more realistic videos can be generated. Some or all of the above processing in the generation unit is performed using the generation AI.

[0084] The generation unit can reflect seasonal and weather changes when generating videos of pets. For example, the generation unit's AI can generate a scene of a pet playing in the snow. The generation unit's AI can generate a scene of a pet playing in a spring flower field. The generation unit's AI can generate a scene of a pet playing on a summer beach. By reflecting seasonal and weather changes, it is possible to generate more realistic videos. Some or all of the above processing in the generation unit is performed using the generation AI.

[0085] The display unit can estimate the owner's emotions and adjust the order in which videos are displayed based on the estimated emotions. For example, if the owner is sad, the generating AI can display calm scenes of the pet first. If the owner is having fun, the generating AI can display active scenes of the pet first. If the owner is relaxed, the generating AI can display calm scenes of the pet first. This allows for more appropriate mental care by adjusting the order of videos based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the display unit may be performed using AI or not.

[0086] The display unit can be enhanced with features that allow users to customize how pets are displayed in the virtual space. For example, the display unit can provide a function that allows owners to customize the size and color of their pets. The display unit can also provide a function that allows owners to customize the movements and expressions of their pets. The display unit can also provide a function that allows owners to customize the background and environment of their pets. This allows for customization of how pets are displayed in the virtual space, enabling displays tailored to the owner's preferences. Some or all of the above-described processes in the display unit may be performed using AI or not.

[0087] The display unit can be enhanced with features that allow pet owners to interact with their pets in a virtual space. For example, the display unit can provide a function that allows pet owners to throw virtual toys to their pets. The display unit can provide a function that allows pet owners to feed their pets virtual food. The display unit can provide a function that allows pet owners to take their pets for walks in a virtual space. This enables a more realistic experience by allowing pet owners to interact with their pets in a virtual space. Some or all of the above processing in the display unit may be performed using AI or not.

[0088] The display unit can estimate the owner's emotions and adjust the brightness and color tone of the displayed video based on the estimated emotions. For example, if the owner is sad, the generating AI can lower the brightness of the video and adjust the color tone to a calmer one. If the owner is enjoying themselves, the generating AI can increase the brightness of the video and adjust the color tone to a brighter one. If the owner is relaxed, the generating AI can set the brightness of the video to a moderate level and adjust the color tone to a gentle one. This allows for more appropriate mental care by adjusting the brightness and color tone of the video based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the display unit may be performed using AI or not.

[0089] The display unit can add background music and sound effects when displaying videos of pets in a virtual space. For example, the display unit can use a generating AI to select and play background music that matches the pet's movements. The display unit can use a generating AI to add sound effects (e.g., running sounds, barking) that correspond to the pet's actions. The display unit can use a generating AI to select and play music that matches the owner's emotions. By adding background music and sound effects, a more realistic video can be displayed. Some or all of the above processing in the display unit may be performed using AI, or it may be performed without using AI.

[0090] The display unit can add a function that allows users to share videos of their pets with other users when displaying videos of pets in a virtual space. For example, the display unit can provide a function that allows pet owners to share videos of their pets with family and friends. The display unit can provide a function that allows pet owners to share videos of their pets on social media. The display unit can provide a function that allows pet owners to share videos of their pets with other pet owners. This allows users to share memories of their pets with other users. Some or all of the above processing in the display unit may be performed using AI or not.

[0091] The care unit can estimate the owner's emotions and adjust the content of mental care based on the estimated emotions. For example, if the owner is sad, the care unit can use a generating AI to display calm scenes of the pet and provide mental care. If the owner is happy, the care unit can use a generating AI to display active scenes of the pet and provide mental care. If the owner is relaxed, the care unit can use a generating AI to display calm scenes of the pet and provide mental care. In this way, more appropriate care can be provided by adjusting the content of mental care based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the care unit may be performed using AI or not using AI.

[0092] The care department can analyze the owner's past mental care history and provide the most suitable care method. For example, the care department can provide the same mental care method that was previously effective for the owner. The care department can propose new care methods based on the owner's past mental care history. The care department can analyze the owner's mental care history and provide care at the optimal time. In this way, by analyzing past mental care history, the care department can provide the most suitable care method. Some or all of the above processes in the care department may be performed using AI or not.

[0093] The care department can monitor the emotional changes of pet owners after they watch videos of their pets and incorporate this into future care. For example, the care department can monitor the emotions of pet owners after they watch videos of their pets and adjust the content of the next care. The care department can record the emotional changes of pet owners after they watch videos of their pets and incorporate this into future care. The care department can analyze the emotions of pet owners after they watch videos of their pets and suggest methods for future care. In this way, by monitoring the emotional changes of pet owners, this can be incorporated into future care. Some or all of the above processes in the care department may be performed using AI or not.

[0094] The care unit can estimate the owner's emotions and adjust the frequency of care based on the estimated emotions. For example, if the owner is sad, the care unit can provide mental care more frequently. If the owner is happy, the care unit can provide mental care at a moderate frequency. If the owner is relaxed, the care unit can provide mental care less frequently. This allows for more appropriate care by adjusting the frequency of care based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the care unit may be performed using AI or not.

[0095] The care unit can provide relaxing music or guided meditation after the owner has watched a video of their pet. For example, the care unit can play relaxing music after the owner has watched a video of their pet. The care unit can provide guided meditation after the owner has watched a video of their pet. The care unit can play relaxing ambient sounds after the owner has watched a video of their pet. This allows for more effective mental care by providing relaxing music or guided meditation after the owner has watched a video of their pet. Some or all of the above processing in the care unit may be performed using AI or not.

[0096] The care department can add a function that allows pet owners to keep an emotional journal after watching videos of their pets. For example, the care department can provide a function that allows pet owners to keep an emotional journal after watching videos of their pets. The care department can provide questions for pet owners to record their emotions after watching videos of their pets. The care department can provide templates for pet owners to keep an emotional journal after watching videos of their pets. This allows pet owners to record changes in their emotions by keeping an emotional journal after watching videos of their pets, which can be used to improve future care. Some or all of the above processes in the care department may be performed using AI or not.

[0097] The memorial service unit can estimate the owner's emotions and adjust the memorial service method based on the estimated emotions. For example, if the owner is sad, the generating AI can display a memorial service scene accompanied by calming music. If the owner is relaxed, the generating AI can display a memorial service scene in a quiet environment. If the owner is grateful, the generating AI can display a memorial service scene that includes a message of gratitude. This allows for a more appropriate memorial service by adjusting the memorial service method based on the owner's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the memorial service unit may be performed using AI or not.

[0098] The memorial service section can add features that allow users to customize the memorial service scene in the virtual space. For example, the memorial service section can provide a function that allows the owner to select the background for the memorial service scene. The memorial service section can provide a function that allows the owner to select the music to be used in the memorial service scene. The memorial service section can provide a function that allows the owner to customize the message displayed in the memorial service scene. This allows for a memorial service tailored to the owner's preferences by enabling the customization of the memorial service scene. Some or all of the above processes in the memorial service section may be performed using AI or not.

[0099] The memorial service section can be enhanced with a feature that allows pet owners to leave messages for their pets during the memorial service. For example, the memorial service section can provide a function that allows pet owners to input messages of gratitude for their pets and display them in the memorial service scene. The memorial service section can provide a function that allows pet owners to input memories of their pets and display them in the memorial service scene. The memorial service section can provide a function that allows pet owners to input messages of prayer for their pets and display them in the memorial service scene. This allows for a more emotional memorial service by enabling pet owners to leave messages for their pets during the memorial service. Some or all of the above processes in the memorial service section may be performed using AI or not.

[0100] The memorial service unit can estimate the owner's emotions and adjust the timing of memorial services based on those estimated emotions. For example, if the owner is sad, the memorial service unit will suggest memorial services more frequently. If the owner is relaxed, the memorial service unit can suggest memorial services at a moderate frequency. If the owner feels grateful, the memorial service unit can suggest memorial services on specific anniversaries. By adjusting the timing of memorial services based on the owner's emotions, more appropriate memorial services can be performed. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the memorial service unit may be performed using AI or not.

[0101] The memorial service section can add a function that allows users to perform memorial services together with other pet owners in the virtual space. For example, the memorial service section can provide a function that allows pet owners to share memorial service scenes with other pet owners. The memorial service section can provide a function that allows pet owners to exchange memorial service messages with other pet owners. The memorial service section can provide a function that allows pet owners to customize memorial service scenes together with other pet owners. This makes it possible to have a shared memorial service experience by performing memorial services together with other pet owners. Some or all of the above processes in the memorial service section may be performed using AI or not.

[0102] The memorial service section can add a function to display photos and videos of pets as mementos during memorial services in the virtual space. For example, the memorial service section can provide a function that allows pet owners to display photos of their pets as mementos during the memorial service. The memorial service section can provide a function that allows pet owners to display videos of their pets as mementos during the memorial service. The memorial service section can provide a function that allows pet owners to display photo albums of their pets as mementos during the memorial service. This makes it possible to have a more emotionally charged memorial service by displaying photos and videos of pets as mementos. Some or all of the above processing in the memorial service section may be performed using AI or not.

[0103] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0104] The pet loss care system can also be equipped with a voice recognition unit. The voice recognition unit can recognize the owner's voice and change the pet's actions and scenes in the video based on that voice. For example, if the owner says "sit," the generating AI can generate a scene of the pet sitting. Also, if the owner says "let's play," the generating AI can generate a scene of the pet playing. Furthermore, if the owner calls the pet's name, the generating AI can generate a scene of the pet turning towards the owner. This allows for a more interactive experience by changing the pet's actions and scenes in response to the owner's voice.

[0105] The pet loss care system can also be equipped with an emotional feedback unit. This unit provides feedback on the owner's emotions after watching videos of their pet. For example, the owner can input emotions such as "happy" or "sad" after watching the video. The emotional feedback unit can collect this emotional data and use it to generate future videos. This allows for the creation of more appropriate videos based on the owner's emotions.

[0106] The pet loss care system can also be equipped with a biofeedback unit. This unit monitors the owner's biometric information (e.g., heart rate, skin electrical activity) and adjusts the content of the pet's videos based on that information. For example, if the owner's heart rate is high, the AI ​​can generate calm scenes of the pet. Conversely, if the owner's skin electrical activity is low, the AI ​​can generate active scenes of the pet. This allows for more effective mental care by adjusting the video content based on the owner's biometric information.

[0107] The pet loss care system can also be equipped with a storytelling section. This section allows pet owners to share memories of their pets, and a generating AI can create narrative videos based on these stories. For example, if an owner says, "I went to the beach with my pet," the generating AI can recreate that scene. Similarly, if an owner says, "The day my pet first came home," the generating AI can create that scene. This allows for a more emotionally engaging experience by generating narrative videos based on the owner's memories.

[0108] The pet loss care system can also include a reminder function. This reminder function provides owners with the opportunity to regularly watch videos of their pets. For example, the reminder function can send notifications to ensure owners don't forget to watch videos of their pets amidst their busy daily lives. Reminders can also be set for specific days (e.g., the pet's birthday, the anniversary of their death). This allows owners to provide continuous emotional support by regularly watching videos of their pets.

[0109] The pet loss care system can also be equipped with a pet growth simulation unit. This unit provides a function that allows owners to simulate their pet's growth process. For example, a generating AI can recreate the growth process from puppyhood to adulthood. It can also simulate changes in behavior and habits that occur as the pet grows. This allows owners to relive their pet's growth process, fostering a deeper emotional connection.

[0110] The pet loss care system can also be equipped with a pet health management unit. This unit simulates the pet's health condition and provides health management advice to the owner. For example, a generating AI can simulate the pet's diet and exercise, and suggest appropriate health management methods. It can also advise the owner on appropriate care methods based on the pet's health condition. This allows owners to provide more appropriate care by simulating their pet's health management.

[0111] The pet loss care system can also be equipped with a pet future prediction unit. This unit provides a function to predict the future appearance and behavior of the pet and present it to the owner. For example, a generative AI can simulate the pet's future appearance and present it to the owner. It can also predict the pet's future behavior and habits and provide advice to the owner. This allows owners to consider their relationship with their pet from a longer-term perspective by predicting the pet's future.

[0112] The pet loss care system can also include a pet memory sharing section. This section provides a function for pet owners to share memories of their pets with other pet owners. For example, pet owners can share videos and photos of their pets with other pet owners to receive empathy and advice. They can also share episodes related to their pets' memories and interact with other pet owners. This allows pet owners to share memories of their pets with other pet owners, providing a richer community experience.

[0113] The pet loss care system can also be equipped with a pet emotion simulation unit. This unit simulates the pet's emotions and adjusts the video content based on those emotions. For example, a generating AI can simulate the pet's feelings of joy and sadness and generate video scenes based on those emotions. It can also suggest appropriate care methods to the owner based on the pet's emotions. This allows for the creation of more realistic videos and the provision of appropriate care to the owner by simulating the pet's emotions.

[0114] The following briefly describes the processing flow for example form 2.

[0115] Step 1: The generation unit uses a generation AI to create videos of pets based on photos and videos of the pets. The generation unit inputs photos and videos of the pets into the generation AI, which then generates videos of the pets that look as if they were alive. The generation AI reproduces the pets' movements and expressions to create realistic videos. For example, the generation AI can reproduce scenes of pets running around in a field or playing with other pets. Step 2: The display unit displays the video generated by the generation unit in a virtual space. The display unit places the generated video in a virtual space, allowing pet owners to view their pets anytime, anywhere by accessing it from devices such as smartphones or personal computers. For example, when a pet owner accesses the virtual space using their smartphone, they can see their pet running around in a field. Step 3: The care unit provides mental care by allowing pet owners to watch videos displayed on the display unit. By watching videos of their pets, pet owners can fill the void in their hearts. Because pet owners can see their pets anytime, anywhere, mental care for pet loss can be provided.

[0116] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0117] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0118] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0119] Each of the multiple elements described above, including the generation unit, display unit, care unit, and memorial unit, is implemented by at least one of the smart device 14 and the data processing device 12. For example, the generation unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. The display unit is implemented by the display 40A of the smart device 14 or the specific processing unit 290 of the data processing device 12. The care unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. The memorial unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

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

[0121] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0122] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0123] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0124] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the 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 image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0126] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0127] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0128] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

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

[0131] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 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 a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0135] Each of the multiple elements described above, including the generation unit, display unit, care unit, and memorial unit, is implemented, for example, in at least one of the smart glasses 214 and the data processing device 12. For example, the generation unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. The display unit is implemented by the display of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. The care unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. The memorial unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0136] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0137] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0138] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0139] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0140] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0141] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0142] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0143] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0144] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0145] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0146] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0147] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0148] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0149] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0150] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0151] Each of the multiple elements described above, including the generation unit, display unit, care unit, and memorial unit, is implemented by at least one of the headset terminal 314 and the data processing unit 12. For example, the generation unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The display unit is implemented by the display 343 of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The care unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The memorial unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0152] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0153] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0154] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0155] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0156] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0157] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0158] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0159] The controlled 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 robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0160] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0161] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0162] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0163] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0164] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0165] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0166] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0167] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0168] Each of the multiple elements described above, including the generation unit, display unit, care unit, and memorial unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the generation unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing unit 12. The display unit is implemented by the display of the robot 414 or the specific processing unit 290 of the data processing unit 12. The care unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing unit 12. The memorial unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing unit 12. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0169] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0170] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0171] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0172] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0173] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0174] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0175] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0176] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0177] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0178] 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.

[0179] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0180] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0181] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0182] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0183] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0184] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0185] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0186] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0187] (Note 1) A generation unit that generates videos of pets using AI based on pet photos and videos, A display unit that displays the video generated by the generation unit in a virtual space, The device includes a care unit that provides mental care to the owner by allowing them to watch videos displayed on the aforementioned display unit. A system characterized by the following features. (Note 2) The generating unit is The AI ​​generates images to recreate the movements and expressions of pets. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned display unit is Displaying videos of pets in a virtual space The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned care unit is Pet owners can use videos of their pets for mental health care. The system described in Appendix 1, characterized by the features described herein. (Note 5) It features a memorial service section that provides perpetual memorial services for videos of pets in a virtual space. The system described in Appendix 1, characterized by the features described herein. (Note 6) The generating unit is It estimates the owner's emotions and adjusts the pet's movements and facial expressions based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 7) The generating unit is By analyzing the pet's past behavioral patterns, we can recreate more realistic movements. The system described in Appendix 1, characterized by the features described herein. (Note 8) The generating unit is We've added a feature that allows pet owners to request specific scenes and generate those scenes. The system described in Appendix 1, characterized by the features described herein. (Note 9) The generating unit is The system estimates the owner's emotions and selects video scenes to generate based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The generating unit is When generating pet videos, add interactions with other pets and their owners. The system described in Appendix 1, characterized by the features described herein. (Note 11) The generating unit is When generating pet videos, reflect changes in season and weather. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned display unit is It estimates the owner's emotions and adjusts the order in which videos are displayed based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned display unit is We will add a feature that allows you to customize how pets are displayed in the virtual space. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned display unit is Add a feature that allows pet owners to interact with their pets in a virtual space. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned display unit is It estimates the owner's emotions and adjusts the brightness and color tone of the displayed video based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned display unit is When displaying pet videos in a virtual space, add background music and sound effects. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned display unit is Add a feature that allows users to share videos of their pets with other users when displaying them in a virtual space. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned care unit is The system estimates the owner's emotions and adjusts the content of mental care based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned care unit is We analyze the owner's past mental health care history and provide the most suitable care method. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned care unit is Monitor the emotional changes of pet owners after they watch videos of their pets and use that information to inform future care. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned care unit is The system estimates the owner's emotions and adjusts the frequency of care based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned care unit is After pet owners watch videos of their pets, the service provides relaxing music and guided meditations. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned care unit is Add a feature that allows pet owners to keep an emotional journal after watching videos of their pets. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned memorial service section is, We estimate the owner's emotions and adjust the method of memorial service based on those estimated emotions. The system described in Appendix 4, characterized by the features described herein. (Note 25) The aforementioned memorial service section is, Add a feature that allows you to customize the memorial service scene in the virtual space. The system described in Appendix 4, characterized by the features described herein. (Note 26) The aforementioned memorial service section is, Add a feature that allows pet owners to leave a message for their pet when commemorating them. The system described in Appendix 4, characterized by the features described herein. (Note 27) The aforementioned memorial service section is, The system estimates the owner's emotions and adjusts the timing of the memorial service based on those estimated emotions. The system described in Appendix 4, characterized by the features described herein. (Note 28) The aforementioned memorial service section is, Add a feature that allows users to perform memorial services in a virtual space together with other pet owners. The system described in Appendix 4, characterized by the features described herein. (Note 29) The aforementioned memorial service section is, We will add a feature that displays photos and videos of pets as mementos during memorial services in the virtual space. The system described in Appendix 4, characterized by the features described herein. [Explanation of symbols]

[0188] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A generation unit that generates videos of pets using AI based on photos and videos of pets, A display unit that displays the video generated by the generation unit in a virtual space, The device includes a care unit that provides mental care by allowing the owner to watch videos displayed on the aforementioned display unit. A system characterized by the following features.

2. The generating unit is The AI ​​generates images to recreate the movements and expressions of pets. The system according to feature 1.

3. The aforementioned display unit is Displaying videos of pets in a virtual space The system according to feature 1.

4. The aforementioned care unit is Pet owners can use videos of their pets for mental health care. The system according to feature 1.

5. It features a memorial service section that provides perpetual memorial services for videos of pets in a virtual space. The system according to feature 1.

6. The generating unit is It estimates the owner's emotions and adjusts the pet's movements and facial expressions based on those estimated emotions. The system according to feature 1.

Images