system

Abstract

The system according to this embodiment aims to enrich the content of the shoots by setting shooting themes that reflect the opinions of parents and children. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a storage unit, and a provision unit. The collection unit collects parental experiences and children's opinions. The analysis unit analyzes the information collected by the collection unit and sets a shooting theme. The storage unit stores photos and videos taken by the user. The provision unit provides shooting advice from professionals.

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 a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, the setting of shooting themes reflecting the opinions of parents and children has not been sufficiently carried out, and there is room for improvement.

[0005] The system according to the embodiment aims to set a shooting theme reflecting the opinions of parents and children and enrich the shooting content.

Means for Solving the Problems

[0006] The system according to the embodiment includes a collection unit, an analysis unit, a storage unit, and a provision unit. The collection unit collects the testimonials of parents and the opinions of children. The analysis unit analyzes the information collected by the collection unit to set a shooting theme. The storage unit stores the photos and videos taken by the user. The provision unit provides shooting advice from a professional. [Effects of the Invention]

[0007] The system according to this embodiment can set shooting themes that reflect the opinions of parents and children, and enrich the content of the shoots. [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) An AI agent system according to an embodiment of the present invention is a system that makes suggestions to enrich the content of children's photos and videos based on parents' experiences and children's opinions. This AI agent system collects and analyzes parents' experiences and children's opinions to set shooting themes, saves photos and videos taken by the user, and provides shooting advice from professionals. For example, the AI ​​agent system collects experiences from parents such as "I'm glad I took pictures" or "I regret not taking more pictures," as well as comments from children such as "I wish there were more pictures like this." This information is collected from online comments, survey results, and advice from professional photographers. Next, the AI ​​agent system analyzes the collected information and sets shooting themes. For example, specific themes such as "Take close-up photos showing the size of your child's hands and feet by placing your hand next to them" or "Take pictures of your baby in a diaper by lowering the camera to eye level with the baby" are set. Users take photos and videos according to the themes set each month using their smartphones or computers. The photos and videos taken are saved in an online album and can be developed or made into photo books. Users can also receive shooting advice from professionals for a fee. Furthermore, comments can be added to the photos and videos taken, creating a record of the child's growth. This allows parents to look back on their child's development and ensures that they take photos without regrets. This system allows parents to record their child's growth in a more comprehensive way, and children will have more memorable photos and videos. In addition, by taking photos according to themes suggested by the AI ​​agent, the variety of photos expands, and more diverse scenes can be recorded. This allows the AI ​​agent system to enrich the content of the photos based on parents' experiences and children's opinions.

[0029] The AI ​​agent system according to this embodiment comprises a collection unit, an analysis unit, a storage unit, and a provision unit. The collection unit collects parental experiences and children's opinions. Parental experiences include, for example, comments such as "I'm glad I took the photos" or "I regret not taking the photos," but are not limited to such examples. Children's opinions include, for example, comments such as "I wish there were more photos like this," but are not limited to such examples. The collection unit collects information from, for example, online comments, survey results, and advice from professional photographers. Some or all of the above processing in the collection unit may be performed using, for example, AI, or not using AI. For example, the collection unit can input online comments into the AI, and the AI ​​can analyze the comments to extract experiences and opinions. The analysis unit analyzes the information collected by the collection unit and sets a shooting theme. The analysis unit sets a specific theme, for example, "Take close-up photos showing the size by placing the parent's hand on the child's hand or foot" or "Take photos of the baby in a diaper by lowering the camera to the same eye level as the baby." Some or all of the above-described processes in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input collected information into the AI, which can analyze the information and generate shooting themes. The storage unit saves photos and videos taken by the user. The storage unit saves the photos and videos taken into an online album, for example. Some or all of the above-described processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the photos and videos taken into the AI, which can save them into an online album. The provision unit provides shooting advice from professionals. The provision unit provides shooting advice from professionals for a fee, for example. Some or all of the above-described processes in the provision unit may be performed using AI, for example, or without AI. For example, the provision unit can input shooting advice from professionals into the AI, which can then provide it to the user. As a result, the AI ​​agent system according to this embodiment can enrich the shooting content based on the experiences of parents and the opinions of children.

[0030] The collection team gathers parental experiences and children's opinions. Parental experiences include, for example, comments like "I'm glad I took the photos" or "I regret not taking more photos," but are not limited to these examples. Specifically, they collect detailed anecdotes about the joys and regrets parents felt during their children's growth and the value of the photos they took. This will provide information that can be helpful to other parents when they face similar situations. Children's opinions include, for example, comments like "I wish I had more photos like this," but are not limited to these examples. Specifically, they collect what children felt when they looked back on their lives after growing up, or what specific moments they wished they had captured in photos. This will help parents decide what kind of photos they should take during their children's growth. The collection team gathers information from sources such as online comments, survey results, and advice from professional photographers. Online comments are collected from social media, forums, and blogs, while survey results are collected from online surveys and paper questionnaires. Advice from professional photographers includes opinions and suggestions from professionals with specialized knowledge and skills in photography. Some or all of the processing described above in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input comments from the internet into an AI, which can then analyze the comments and extract personal experiences and opinions. The AI ​​can use natural language processing technology to analyze the comments, extract important keywords and phrases, classify them, and organize them as parental experiences and children's opinions. This allows the data collection unit to efficiently collect and analyze large amounts of information.

[0031] The analysis unit analyzes the information collected by the collection unit to set shooting themes. For example, the analysis unit sets specific themes such as, "Take close-up photos showing the size of your child's hands and feet by placing your hands next to them," or "Take photos of your baby in a diaper by lowering the camera to eye level with them." Specifically, it analyzes what moments and situations are important based on the collected experiences of parents and opinions of children, and sets shooting themes based on that. Some or all of the above processing in the analysis unit may be performed using AI, or not. For example, the analysis unit can input the collected information into the AI, which can analyze the information and generate shooting themes. The AI ​​uses machine learning algorithms to find common patterns and trends from the collected information and proposes the most suitable shooting themes based on them. For example, the AI ​​can extract the theme "recording growth" from parents' experiences and the theme "moments of play" from children's opinions. In this way, the analysis unit can set shooting themes that are valuable to parents and children based on the collected information. Furthermore, the analysis unit can provide detailed advice on specific shooting methods, angles, and lighting techniques based on the set shooting theme. This allows parents to take photos more effectively and beautifully document their children's growth.

[0032] The storage unit stores photos and videos taken by the user. For example, the storage unit can save the photos and videos taken to an online album. Specifically, it uploads the photos and videos taken by the user to a cloud storage service for secure storage. Some or all of the above processes in the storage unit may be performed using AI, or not. For example, the storage unit can input the photos and videos taken into the AI, which can then save them to an online album. The AI ​​can analyze the content of the photos and videos using image recognition technology and automatically tag them. This allows the user to easily search for specific photos and videos later. For example, the AI ​​can recognize people, places, events, etc., in a photo and tag them accordingly, such as "birthday," "travel," or "family photo." Furthermore, the storage unit can automatically organize the photos and videos taken by the user and create albums and slideshows. This allows the user to easily look back on memories. The storage unit can also regularly back up photos and videos to prevent data loss. This allows the storage unit to securely store the user's precious memories and make them accessible at any time.

[0033] The service provider offers photography advice from professionals. For example, the service provider offers professional photography advice for a fee. Specifically, it provides users with advice on photography techniques, tips, and equipment selection from professional photographers. Some or all of the above processes in the service provider may be performed using AI, or not. For example, the service provider can input professional photography advice into an AI, which then provides it to the user. The AI ​​can select and provide the most suitable advice based on the user's photography style and preferences. For example, the AI ​​can analyze photos taken by the user, point out areas for improvement such as composition, lighting, and color, and provide specific advice based on that. Furthermore, the service provider can also offer a service where users can receive feedback from professional photographers on their photos and videos. This allows users to improve their photography skills. The service provider can also regularly hold online workshops and seminars by professional photographers, providing users with opportunities to ask questions and seek advice directly. This allows the service provider to support users in taking better photos while receiving advice from professional photographers.

[0034] The storage unit can save captured photos and videos to an online album. For example, the storage unit can save captured photos and videos to cloud storage. For example, the storage unit can upload captured photos and videos to cloud storage. The storage unit can also save captured photos and videos to a dedicated online album. For example, the storage unit can upload captured photos and videos to a dedicated website for user access. Furthermore, the storage unit can save captured photos and videos to local storage. For example, the storage unit can save captured photos and videos to the user's computer or smartphone storage. This allows for easy access to captured photos and videos by saving them to an online album. Some or all of the above processes in the storage unit may be performed using AI, or not. For example, the storage unit can input captured photos and videos into an AI, which can then save them to an online album.

[0035] The service provider can offer professional photography advice for a fee. For example, the service provider can offer online courses by professional photographers. For example, the service provider can offer video tutorials in which professional photographers teach photography techniques and tips. The service provider can also offer individual advice from professional photographers. For example, the service provider can send photos and videos taken by users to professional photographers, who then provide feedback. Furthermore, the service provider can offer workshops led by professional photographers. For example, the service provider can host photography workshops instructed directly by professional photographers. This allows users to improve their photography skills by offering professional photography advice for a fee. Some or all of the above processes in the service provider may be performed using AI, for example, or not using AI. For example, the service provider can input advice from professional photographers into AI, which then provides it to the user.

[0036] The analysis unit can set shooting themes based on online comments, survey results, and advice from professional photographers. For example, the analysis unit can collect online comments and analyze them using text mining technology. For example, the analysis unit can collect comments from social media and blogs and extract shooting themes using text mining technology. The analysis unit can also collect survey results and analyze them using sentiment analysis technology. For example, the analysis unit can collect online and paper-based survey results and set shooting themes using sentiment analysis technology. Furthermore, the analysis unit can collect and analyze advice from professional photographers. For example, the analysis unit can collect and analyze the content of interviews and workshops with professional photographers to set shooting themes. This allows for the provision of more enriching shooting content by setting shooting themes based on online comments, survey results, and advice from professional photographers. Some or all of the above processing in the analysis unit may be performed using AI, for example, or not. For example, the analysis unit can input collected comments and survey results into AI, which can analyze them to generate shooting themes.

[0037] The storage unit can add comments to captured photos and videos to create a record of growth. For example, the storage unit can add text comments to captured photos and videos. For example, the storage unit can add comments to photos and videos taken by the user, such as the date and time they were taken, the location, and anecdotes from the time they were taken. The storage unit can also add audio comments to captured photos and videos. For example, the storage unit can add audio comments to photos and videos taken by the user. Furthermore, the storage unit can add video comments to captured photos and videos. For example, the storage unit can add video comments to photos and videos taken by the user. This allows users to look back on their child's growth by adding comments to captured photos and videos to create a record of growth. Some or all of the above processing in the storage unit may be performed using AI, for example, or not. For example, the storage unit can have AI perform the process of adding comments to captured photos and videos.

[0038] The service provider can offer functions for developing and creating photo books. For example, the service provider can develop photographs taken through an online development service. For example, the service provider can allow users to upload photographs they have taken to an online development service and receive the developed photographs by mail. The service provider can also offer a service to create photo books from photographs taken. For example, the service provider can allow users to upload photographs they have taken to an online photo book service and receive the printed photo book. Furthermore, the service provider can also provide a handmade photo book from the photographs taken. For example, the service provider can provide a kit for users to create a handmade photo book from their photographs. By providing functions for developing and creating photo books, the service provider can help users preserve their photographs and videos in a tangible form. Some or all of the above processes performed by the service provider may be carried out using AI, for example, or not. For example, the service provider can have AI perform the process of developing photographs taken.

[0039] The collection unit can analyze the parent's past experience story submission history and select the optimal collection method. For example, the collection unit can analyze the frequency of experiences the parent has submitted in the past and determine the optimal collection frequency. For example, the collection unit can analyze the content of experiences the parent has submitted in the past and customize the collection method. The collection unit can also analyze the method (online, offline, etc.) the parent has submitted experiences in the past and select the optimal collection method. For example, the collection unit can select the optimal collection method based on the parent's past experience story submission method. In this way, the optimal collection method can be selected by analyzing the parent's past experience story submission history. Some or all of the above processing in the collection unit may be performed using AI, for example, or not using AI. For example, the collection unit can input the parent's past experience story submission history into AI, and the AI ​​can select the optimal collection method.

[0040] The data collection unit can filter the collected personal stories based on the parents' current living situation and areas of interest. For example, the data collection unit collects personal stories based on the parents' current living situation (work, family, etc.). For example, the data collection unit collects personal stories based on the parents' areas of interest (hobbies, interests, etc.). The data collection unit can also filter the collected personal stories based on the parents' current living situation and areas of interest. For example, the data collection unit prioritizes collecting personal stories that are highly relevant based on the parents' current living situation and areas of interest. This allows for the collection of more relevant personal stories by filtering them based on the parents' current living situation and areas of interest. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input the parents' current living situation and areas of interest into an AI, which can then filter the personal stories.

[0041] The collection unit can prioritize the collection of highly relevant testimonials by considering the parents' geographical location information when collecting testimonials. For example, the collection unit can prioritize the collection of testimonials related to a specific region based on the parents' geographical location information. For example, the collection unit can prioritize the collection of testimonials related to local events based on the parents' geographical location information. The collection unit can also prioritize the collection of testimonials related to local culture and customs based on the parents' geographical location information. For example, the collection unit can prioritize the collection of testimonials related to local culture and customs based on the parents' geographical location information. This allows for the priority collection of region-related testimonials by considering the parents' geographical location information when collecting testimonials. Some or all of the above processing in the collection unit may be performed using AI, for example, or without AI. For example, the collection unit can input the parents' geographical location information into AI, which can then prioritize the collection of highly relevant testimonials.

[0042] The data collection unit can analyze parents' social media activity and collect relevant testimonials when collecting testimonials. For example, the data collection unit can analyze parents' social media activity and collect relevant testimonials. For example, the data collection unit can collect testimonials of high interest based on parents' social media activity. The data collection unit can also analyze parents' social media activity and select the optimal collection method. For example, the data collection unit can select the optimal collection method based on parents' social media activity. This allows for the collection of relevant testimonials by analyzing parents' social media activity. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input parents' social media activity into AI, and the AI ​​can collect relevant testimonials.

[0043] The analysis unit can adjust the level of detail of a shooting theme based on the importance of the testimonials when setting the shooting theme. For example, the analysis unit can set a detailed shooting theme based on a highly important testimonial. For example, the analysis unit can set a simple shooting theme based on a less important testimonial. The analysis unit can also adjust the level of detail of a theme based on the importance of the testimonial. For example, the analysis unit can adjust the level of detail of a theme based on the importance of the testimonial. This allows for setting more important themes in detail by adjusting the level of detail of the theme based on the importance of the testimonial. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the importance of the testimonials into the AI, and the AI ​​can adjust the level of detail of the theme.

[0044] The analysis unit can apply different analysis algorithms depending on the category of the testimonial when setting the shooting theme. For example, the analysis unit can apply different analysis algorithms depending on the category of the testimonial. For example, the analysis unit can select the optimal analysis algorithm depending on the category of the testimonial. The analysis unit can also customize the analysis algorithm depending on the category of the testimonial. For example, the analysis unit can customize the analysis algorithm depending on the category of the testimonial. This allows for the setting of more appropriate shooting themes by applying different analysis algorithms depending on the category of the testimonial. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the category of the testimonial into the AI, and the AI ​​can apply the optimal analysis algorithm.

[0045] The analysis unit can determine the priority of shooting themes based on the submission timing of testimonials. For example, the analysis unit can determine the priority of themes based on the submission timing of testimonials. For example, the analysis unit can select the optimal theme based on the submission timing of testimonials. The analysis unit can also adjust the priority of themes based on the submission timing of testimonials. For example, the analysis unit can adjust the priority of themes based on the submission timing of testimonials. This allows for the prioritization of more appropriate themes by determining the priority of themes based on the submission timing of testimonials. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the submission timing of testimonials into the AI, and the AI ​​can determine the priority of themes.

[0046] The analysis unit can adjust the order of themes based on the relevance of the testimonials when setting themes for shooting. For example, the analysis unit adjusts the order of themes based on the relevance of the testimonials. For example, the analysis unit determines the optimal order of themes based on the relevance of the testimonials. The analysis unit can also customize the order of themes based on the relevance of the testimonials. For example, the analysis unit customizes the order of themes based on the relevance of the testimonials. This allows themes to be provided in a more appropriate order by adjusting the order of themes based on the relevance of the testimonials. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the relevance of the testimonials into the AI, and the AI ​​can adjust the order of themes.

[0047] The storage unit can select the optimal storage method when saving photos or videos by referring to the parent's past saving history. For example, the storage unit selects the optimal storage method based on the parent's past saving history. For example, the storage unit customizes the storage method based on the parent's past saving history. The storage unit can also suggest a storage method based on the parent's past saving history. For example, the storage unit suggests a storage method based on the parent's past saving history. This allows the optimal storage method to be selected by referring to the parent's past saving history. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's past saving history into AI, and the AI ​​can select the optimal storage method.

[0048] The storage unit can customize the storage method based on the parent's current living situation when saving photos and videos. For example, the storage unit can suggest the optimal storage method based on the parent's current living situation. For example, the storage unit can customize the storage method based on the parent's current living situation. The storage unit can also select a storage method based on the parent's current living situation. For example, the storage unit can select a storage method based on the parent's current living situation. This allows for the provision of a more appropriate storage method by customizing the storage method based on the parent's current living situation. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's current living situation into AI, and the AI ​​can customize the storage method.

[0049] The storage unit can select the optimal storage method when saving photos and videos, taking into account the parent's geographical location information. For example, the storage unit selects the optimal storage method based on the parent's geographical location information. For example, the storage unit customizes the storage method based on the parent's geographical location information. The storage unit can also suggest a storage method based on the parent's geographical location information. For example, the storage unit suggests a storage method based on the parent's geographical location information. By selecting a storage method that takes the parent's geographical location information into account, the storage unit can provide the most appropriate storage method for the region. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's geographical location information into AI, which can then select the optimal storage method.

[0050] The storage unit can analyze the parent's social media activity and suggest a storage method when saving photos and videos. For example, the storage unit can suggest the optimal storage method based on the parent's social media activity. For example, the storage unit can customize the storage method based on the parent's social media activity. The storage unit can also select a storage method based on the parent's social media activity. For example, the storage unit selects a storage method based on the parent's social media activity. This allows the storage unit to suggest the optimal storage method by analyzing the parent's social media activity. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's social media activity into AI, and the AI ​​can suggest the optimal storage method.

[0051] The service provider can provide optimal advice by referring to the parent's past advice history when providing shooting advice. For example, the service provider can provide optimal shooting advice based on the parent's past advice history. For example, the service provider can customize the advice content based on the parent's past advice history. The service provider can also select an advice method based on the parent's past advice history. For example, the service provider can select an advice method based on the parent's past advice history. This allows the service provider to provide optimal shooting advice by referring to the parent's past advice history. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI. For example, the service provider can input the parent's past advice history into AI, and the AI ​​can provide optimal advice.

[0052] The service provider can customize the advice given when providing photography advice based on the parents' current living situation. For example, the service provider can suggest the most suitable advice based on the parents' current living situation. For example, the service provider can customize the advice based on the parents' current living situation. The service provider can also select an advice based on the parents' current living situation. For example, the service provider can select an advice based on the parents' current living situation. By customizing the advice based on the parents' current living situation, more appropriate advice can be provided. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can input the parents' current living situation into the AI, and the AI ​​can customize the advice.

[0053] The service provider can provide optimal advice by considering the parent's geographical location information when providing shooting advice. For example, the service provider can provide optimal shooting advice based on the parent's geographical location information. For example, the service provider can customize the advice content based on the parent's geographical location information. The service provider can also select an advice method based on the parent's geographical location information. For example, the service provider can select an advice method based on the parent's geographical location information. By providing advice while considering the parent's geographical location information, the service provider can provide optimal advice relevant to the region. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI. For example, the service provider can input the parent's geographical location information into AI, and the AI ​​can provide optimal advice.

[0054] The service provider can analyze the parents' social media activity and propose advice methods when providing photography advice. For example, the service provider can propose the most suitable advice method based on the parents' social media activity. For example, the service provider can customize the advice method based on the parents' social media activity. The service provider can also select an advice method based on the parents' social media activity. For example, the service provider can select an advice method based on the parents' social media activity. This allows the service provider to propose the most suitable advice method by analyzing the parents' social media activity. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can input the parents' social media activity into AI, and the AI ​​can propose the most suitable advice method.

[0055] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0056] The analysis unit can analyze the parent's past shooting theme history and suggest the most suitable shooting theme. For example, it can analyze the frequency and content of themes the parent has photographed in the past and prioritize suggesting themes the parent prefers. The analysis unit collects the parent's past shooting theme history and analyzes it using AI. For example, it suggests the most suitable theme based on the frequency of themes the parent has photographed in the past. It can also analyze the content of themes the parent has photographed in the past and prioritize suggesting themes the parent prefers. Furthermore, it can adjust the order of shooting themes based on the parent's past shooting theme history. For example, it suggests themes in the optimal order based on the order of themes the parent has photographed in the past. In this way, by analyzing the parent's past shooting theme history, it can suggest more appropriate shooting themes.

[0057] The service provider can analyze a parent's past history of photography advice and suggest the most appropriate advice. For example, it can analyze the content and frequency of advice parents have received in the past and prioritize suggesting advice that parents prefer. The service provider collects a parent's past history of photography advice and analyzes it using AI. For example, it suggests the most appropriate advice based on the content of advice parents have received in the past. It can also analyze the frequency of advice parents have received in the past and prioritize suggesting advice that parents prefer. Furthermore, it can adjust the order of advice based on a parent's past history of photography advice. For example, it can suggest advice in the optimal order based on the order in which parents have received advice in the past. In this way, by analyzing a parent's past history of photography advice, more appropriate advice can be suggested.

[0058] The storage unit can analyze the parent's past saving history and suggest the optimal saving method. For example, it can analyze the format and frequency of photos and videos the parent has saved in the past and prioritize suggesting the saving method the parent prefers. The storage unit collects the parent's past saving history and analyzes it using AI. For example, it suggests the optimal saving method based on the format of photos and videos the parent has saved in the past. It can also analyze the frequency of photos and videos the parent has saved in the past and prioritize suggesting the saving method the parent prefers. Furthermore, it can adjust the order of saving methods based on the parent's past saving history. For example, it suggests saving methods in the optimal order based on the order of photos and videos the parent has saved in the past. In this way, by analyzing the parent's past saving history, it can suggest a more appropriate saving method.

[0059] The analysis unit can analyze the parents' current living situation and suggest the most suitable shooting themes. For example, if the parents are busy, the analysis unit can suggest simple and quick shooting themes, and if the parents have more time, it can suggest more detailed and time-consuming shooting themes. The analysis unit collects information on the parents' current living situation and analyzes it using AI. For example, it suggests the most suitable shooting themes based on the parents' work and family circumstances. It can also analyze the parents' current living situation and adjust the frequency of shooting themes. For example, if the parents are busy, it reduces the frequency of shooting themes, and if the parents have more time, it increases the frequency. In this way, by analyzing the parents' current living situation, it can suggest more appropriate shooting themes.

[0060] The service provider can analyze the parents' current living situation and propose optimal photography advice. For example, if the parents are busy, the service provider can propose simple, short-duration photography advice, and if the parents have more time, it can propose more detailed, time-consuming photography advice. The service provider collects information on the parents' current living situation and analyzes it using AI. For example, it proposes optimal photography advice based on the parents' work and family circumstances. It can also analyze the parents' current living situation and adjust the frequency of advice. For example, if the parents are busy, the frequency of advice is reduced, and if the parents have more time, the frequency is increased. In this way, by analyzing the parents' current living situation, it can propose more appropriate photography advice.

[0061] The following briefly describes the processing flow for example form 1.

[0062] Step 1: The data collection team gathers parental experiences and children's opinions. Parental experiences include comments like "I'm glad I took the photos" and "I regret not taking more photos," while children's opinions include comments like "I wish I had more photos like this." The data collection team gathers information from online comments, survey results, and advice from professional photographers. These processes can also be performed using AI. Step 2: The analysis unit analyzes the information collected by the collection unit and sets a shooting theme. For example, it sets a specific theme such as "Take close-up photos showing the size of the child's hands and feet by placing a parent's hand next to them" or "Take photos of the baby in a diaper by lowering the camera to the same eye level as the baby." These processes can also be performed using AI. Step 3: The storage unit saves photos and videos taken by the user. For example, it saves photos and videos to an online album. These processes can also be performed using AI. Step 4: The service provider offers photography advice from professionals. For example, they might offer professional photography advice for a fee. These processes can also be performed using AI.

[0063] (Example of form 2) An AI agent system according to an embodiment of the present invention is a system that makes suggestions to enrich the content of children's photos and videos based on parents' experiences and children's opinions. This AI agent system collects and analyzes parents' experiences and children's opinions to set shooting themes, saves photos and videos taken by the user, and provides shooting advice from professionals. For example, the AI ​​agent system collects experiences from parents such as "I'm glad I took pictures" or "I regret not taking more pictures," as well as comments from children such as "I wish there were more pictures like this." This information is collected from online comments, survey results, and advice from professional photographers. Next, the AI ​​agent system analyzes the collected information and sets shooting themes. For example, specific themes such as "Take close-up photos showing the size of your child's hands and feet by placing your hand next to them" or "Take pictures of your baby in a diaper by lowering the camera to eye level with the baby" are set. Users take photos and videos according to the themes set each month using their smartphones or computers. The photos and videos taken are saved in an online album and can be developed or made into photo books. Users can also receive shooting advice from professionals for a fee. Furthermore, comments can be added to the photos and videos taken, creating a record of the child's growth. This allows parents to look back on their child's development and ensures that they take photos without regrets. This system allows parents to record their child's growth in a more comprehensive way, and children will have more memorable photos and videos. In addition, by taking photos according to themes suggested by the AI ​​agent, the variety of photos expands, and more diverse scenes can be recorded. This allows the AI ​​agent system to enrich the content of the photos based on parents' experiences and children's opinions.

[0064] The AI ​​agent system according to this embodiment comprises a collection unit, an analysis unit, a storage unit, and a provision unit. The collection unit collects parental experiences and children's opinions. Parental experiences include, for example, comments such as "I'm glad I took the photos" or "I regret not taking the photos," but are not limited to such examples. Children's opinions include, for example, comments such as "I wish there were more photos like this," but are not limited to such examples. The collection unit collects information from, for example, online comments, survey results, and advice from professional photographers. Some or all of the above processing in the collection unit may be performed using, for example, AI, or not using AI. For example, the collection unit can input online comments into the AI, and the AI ​​can analyze the comments to extract experiences and opinions. The analysis unit analyzes the information collected by the collection unit and sets a shooting theme. The analysis unit sets a specific theme, for example, "Take close-up photos showing the size by placing the parent's hand on the child's hand or foot" or "Take photos of the baby in a diaper by lowering the camera to the same eye level as the baby." Some or all of the above-described processes in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input collected information into the AI, which can analyze the information and generate shooting themes. The storage unit saves photos and videos taken by the user. The storage unit saves the photos and videos taken into an online album, for example. Some or all of the above-described processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the photos and videos taken into the AI, which can save them into an online album. The provision unit provides shooting advice from professionals. The provision unit provides shooting advice from professionals for a fee, for example. Some or all of the above-described processes in the provision unit may be performed using AI, for example, or without AI. For example, the provision unit can input shooting advice from professionals into the AI, which can then provide it to the user. As a result, the AI ​​agent system according to this embodiment can enrich the shooting content based on the experiences of parents and the opinions of children.

[0065] The collection team gathers parental experiences and children's opinions. Parental experiences include, for example, comments like "I'm glad I took the photos" or "I regret not taking more photos," but are not limited to these examples. Specifically, they collect detailed anecdotes about the joys and regrets parents felt during their children's growth and the value of the photos they took. This will provide information that can be helpful to other parents when they face similar situations. Children's opinions include, for example, comments like "I wish I had more photos like this," but are not limited to these examples. Specifically, they collect what children felt when they looked back on their lives after growing up, or what specific moments they wished they had captured in photos. This will help parents decide what kind of photos they should take during their children's growth. The collection team gathers information from sources such as online comments, survey results, and advice from professional photographers. Online comments are collected from social media, forums, and blogs, while survey results are collected from online surveys and paper questionnaires. Advice from professional photographers includes opinions and suggestions from professionals with specialized knowledge and skills in photography. Some or all of the processing described above in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input comments from the internet into an AI, which can then analyze the comments and extract personal experiences and opinions. The AI ​​can use natural language processing technology to analyze the comments, extract important keywords and phrases, classify them, and organize them as parental experiences and children's opinions. This allows the data collection unit to efficiently collect and analyze large amounts of information.

[0066] The analysis unit analyzes the information collected by the collection unit to set shooting themes. For example, the analysis unit sets specific themes such as, "Take close-up photos showing the size of your child's hands and feet by placing your hands next to them," or "Take photos of your baby in a diaper by lowering the camera to eye level with them." Specifically, it analyzes what moments and situations are important based on the collected experiences of parents and opinions of children, and sets shooting themes based on that. Some or all of the above processing in the analysis unit may be performed using AI, or not. For example, the analysis unit can input the collected information into the AI, which can analyze the information and generate shooting themes. The AI ​​uses machine learning algorithms to find common patterns and trends from the collected information and proposes the most suitable shooting themes based on them. For example, the AI ​​can extract the theme "recording growth" from parents' experiences and the theme "moments of play" from children's opinions. In this way, the analysis unit can set shooting themes that are valuable to parents and children based on the collected information. Furthermore, the analysis unit can provide detailed advice on specific shooting methods, angles, and lighting techniques based on the set shooting theme. This allows parents to take photos more effectively and beautifully document their children's growth.

[0067] The storage unit stores photos and videos taken by the user. For example, the storage unit can save the photos and videos taken to an online album. Specifically, it uploads the photos and videos taken by the user to a cloud storage service for secure storage. Some or all of the above processes in the storage unit may be performed using AI, or not. For example, the storage unit can input the photos and videos taken into the AI, which can then save them to an online album. The AI ​​can analyze the content of the photos and videos using image recognition technology and automatically tag them. This allows the user to easily search for specific photos and videos later. For example, the AI ​​can recognize people, places, events, etc., in a photo and tag them accordingly, such as "birthday," "travel," or "family photo." Furthermore, the storage unit can automatically organize the photos and videos taken by the user and create albums and slideshows. This allows the user to easily look back on memories. The storage unit can also regularly back up photos and videos to prevent data loss. This allows the storage unit to securely store the user's precious memories and make them accessible at any time.

[0068] The service provider offers photography advice from professionals. For example, the service provider offers professional photography advice for a fee. Specifically, it provides users with advice on photography techniques, tips, and equipment selection from professional photographers. Some or all of the above processes in the service provider may be performed using AI, or not. For example, the service provider can input professional photography advice into an AI, which then provides it to the user. The AI ​​can select and provide the most suitable advice based on the user's photography style and preferences. For example, the AI ​​can analyze photos taken by the user, point out areas for improvement such as composition, lighting, and color, and provide specific advice based on that. Furthermore, the service provider can also offer a service where users can receive feedback from professional photographers on their photos and videos. This allows users to improve their photography skills. The service provider can also regularly hold online workshops and seminars by professional photographers, providing users with opportunities to ask questions and seek advice directly. This allows the service provider to support users in taking better photos while receiving advice from professional photographers.

[0069] The storage unit can save captured photos and videos to an online album. For example, the storage unit can save captured photos and videos to cloud storage. For example, the storage unit can upload captured photos and videos to cloud storage. The storage unit can also save captured photos and videos to a dedicated online album. For example, the storage unit can upload captured photos and videos to a dedicated website for user access. Furthermore, the storage unit can save captured photos and videos to local storage. For example, the storage unit can save captured photos and videos to the user's computer or smartphone storage. This allows for easy access to captured photos and videos by saving them to an online album. Some or all of the above processes in the storage unit may be performed using AI, or not. For example, the storage unit can input captured photos and videos into an AI, which can then save them to an online album.

[0070] The service provider can offer professional photography advice for a fee. For example, the service provider can offer online courses by professional photographers. For example, the service provider can offer video tutorials in which professional photographers teach photography techniques and tips. The service provider can also offer individual advice from professional photographers. For example, the service provider can send photos and videos taken by users to professional photographers, who then provide feedback. Furthermore, the service provider can offer workshops led by professional photographers. For example, the service provider can host photography workshops instructed directly by professional photographers. This allows users to improve their photography skills by offering professional photography advice for a fee. Some or all of the above processes in the service provider may be performed using AI, for example, or not using AI. For example, the service provider can input advice from professional photographers into AI, which then provides it to the user.

[0071] The analysis unit can set shooting themes based on online comments, survey results, and advice from professional photographers. For example, the analysis unit can collect online comments and analyze them using text mining technology. For example, the analysis unit can collect comments from social media and blogs and extract shooting themes using text mining technology. The analysis unit can also collect survey results and analyze them using sentiment analysis technology. For example, the analysis unit can collect online and paper-based survey results and set shooting themes using sentiment analysis technology. Furthermore, the analysis unit can collect and analyze advice from professional photographers. For example, the analysis unit can collect and analyze the content of interviews and workshops with professional photographers to set shooting themes. This allows for the provision of more enriching shooting content by setting shooting themes based on online comments, survey results, and advice from professional photographers. Some or all of the above processing in the analysis unit may be performed using AI, for example, or not. For example, the analysis unit can input collected comments and survey results into AI, which can analyze them to generate shooting themes.

[0072] The storage unit can add comments to captured photos and videos to create a record of growth. For example, the storage unit can add text comments to captured photos and videos. For example, the storage unit can add comments to photos and videos taken by the user, such as the date and time they were taken, the location, and anecdotes from the time they were taken. The storage unit can also add audio comments to captured photos and videos. For example, the storage unit can add audio comments to photos and videos taken by the user. Furthermore, the storage unit can add video comments to captured photos and videos. For example, the storage unit can add video comments to photos and videos taken by the user. This allows users to look back on their child's growth by adding comments to captured photos and videos to create a record of growth. Some or all of the above processing in the storage unit may be performed using AI, for example, or not. For example, the storage unit can have AI perform the process of adding comments to captured photos and videos.

[0073] The service provider can offer functions for developing and creating photo books. For example, the service provider can develop photographs taken through an online development service. For example, the service provider can allow users to upload photographs they have taken to an online development service and receive the developed photographs by mail. The service provider can also offer a service to create photo books from photographs taken. For example, the service provider can allow users to upload photographs they have taken to an online photo book service and receive the printed photo book. Furthermore, the service provider can also provide a handmade photo book from the photographs taken. For example, the service provider can provide a kit for users to create a handmade photo book from their photographs. By providing functions for developing and creating photo books, the service provider can help users preserve their photographs and videos in a tangible form. Some or all of the above processes performed by the service provider may be carried out using AI, for example, or not. For example, the service provider can have AI perform the process of developing photographs taken.

[0074] The data collection unit can estimate the parent's emotions and adjust the timing of collecting testimonials based on the estimated emotions. For example, the data collection unit can capture the parent's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For example, the data collection unit can calculate an emotion score based on changes in facial expressions and adjust the timing of collecting testimonials. The data collection unit can also record the parent's voice and estimate their emotions using voice analysis technology. For example, the data collection unit can analyze the tone and speed of the voice, calculate an emotion score, and adjust the timing of collecting testimonials. Furthermore, the data collection unit can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, the data collection unit can calculate an emotion score based on fluctuations in heart rate and adjust the timing of collecting testimonials. By adjusting the timing of collecting testimonials based on the parent's emotions, testimonials can be collected at a more appropriate time. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. The generating AI may be, but is not limited to, text generating AI (e.g., LLM) or multimodal generating AI. Some or all of the processing described above in the collection unit may be performed using AI, or not using AI. For example, the collection unit may input parental emotion data into the AI, which can then adjust the timing of collecting the experiences.

[0075] The collection unit can analyze the parent's past experience story submission history and select the optimal collection method. For example, the collection unit can analyze the frequency of experiences the parent has submitted in the past and determine the optimal collection frequency. For example, the collection unit can analyze the content of experiences the parent has submitted in the past and customize the collection method. The collection unit can also analyze the method (online, offline, etc.) the parent has submitted experiences in the past and select the optimal collection method. For example, the collection unit can select the optimal collection method based on the parent's past experience story submission method. In this way, the optimal collection method can be selected by analyzing the parent's past experience story submission history. Some or all of the above processing in the collection unit may be performed using AI, for example, or not using AI. For example, the collection unit can input the parent's past experience story submission history into AI, and the AI ​​can select the optimal collection method.

[0076] The data collection unit can filter the collected personal stories based on the parents' current living situation and areas of interest. For example, the data collection unit collects personal stories based on the parents' current living situation (work, family, etc.). For example, the data collection unit collects personal stories based on the parents' areas of interest (hobbies, interests, etc.). The data collection unit can also filter the collected personal stories based on the parents' current living situation and areas of interest. For example, the data collection unit prioritizes collecting personal stories that are highly relevant based on the parents' current living situation and areas of interest. This allows for the collection of more relevant personal stories by filtering them based on the parents' current living situation and areas of interest. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input the parents' current living situation and areas of interest into an AI, which can then filter the personal stories.

[0077] The data collection unit can estimate the parent's emotions and determine the priority of the stories to collect based on the estimated parent's emotions. For example, the data collection unit can capture the parent's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For example, the data collection unit can calculate an emotion score based on changes in facial expressions and determine the priority of the stories. The data collection unit can also record the parent's voice and estimate their emotions using voice analysis technology. For example, the data collection unit can analyze the tone and speed of the voice, calculate an emotion score, and determine the priority of the stories. Furthermore, the data collection unit can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, the data collection unit can calculate an emotion score based on fluctuations in heart rate and determine the priority of the stories. This allows for the priority of collecting stories based on the parent's emotions, thereby prioritizing the collection of more important stories. Emotion estimation is achieved using emotion estimation functions, such as an emotion engine or generative AI. The generating AI may be, but is not limited to, text-generating AI (e.g., LLM) or multimodal generating AI. Some or all of the processing described above in the collection unit may be performed using AI, or not using AI. For example, the collection unit can input parental emotion data into an AI, which can then determine the priority of the experiences.

[0078] The collection unit can prioritize the collection of highly relevant testimonials by considering the parents' geographical location information when collecting testimonials. For example, the collection unit can prioritize the collection of testimonials related to a specific region based on the parents' geographical location information. For example, the collection unit can prioritize the collection of testimonials related to local events based on the parents' geographical location information. The collection unit can also prioritize the collection of testimonials related to local culture and customs based on the parents' geographical location information. For example, the collection unit can prioritize the collection of testimonials related to local culture and customs based on the parents' geographical location information. This allows for the priority collection of region-related testimonials by considering the parents' geographical location information when collecting testimonials. Some or all of the above processing in the collection unit may be performed using AI, for example, or without AI. For example, the collection unit can input the parents' geographical location information into AI, which can then prioritize the collection of highly relevant testimonials.

[0079] The data collection unit can analyze parents' social media activity and collect relevant testimonials when collecting testimonials. For example, the data collection unit can analyze parents' social media activity and collect relevant testimonials. For example, the data collection unit can collect testimonials of high interest based on parents' social media activity. The data collection unit can also analyze parents' social media activity and select the optimal collection method. For example, the data collection unit can select the optimal collection method based on parents' social media activity. This allows for the collection of relevant testimonials by analyzing parents' social media activity. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input parents' social media activity into AI, and the AI ​​can collect relevant testimonials.

[0080] The analysis unit can estimate the parent's emotions and adjust the presentation of the shooting theme based on the estimated parent's emotions. For example, the analysis unit can capture the parent's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For example, the analysis unit can calculate an emotion score based on changes in facial expressions and adjust the presentation of the shooting theme. The analysis unit can also record the parent's voice and estimate their emotions using voice analysis technology. For example, the analysis unit can analyze the tone and speed of the voice, calculate an emotion score, and adjust the presentation of the shooting theme. Furthermore, the analysis unit can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, the analysis unit can calculate an emotion score based on fluctuations in heart rate and adjust the presentation of the shooting theme. By adjusting the presentation of the shooting theme based on the parent's emotions, more appropriate shooting themes can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generating AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the processing described above in the analysis unit may be performed using AI, or not using AI. For example, the analysis unit can input parent emotion data into the AI, which can then adjust how the shooting theme is expressed.

[0081] The analysis unit can adjust the level of detail of a shooting theme based on the importance of the testimonials when setting the shooting theme. For example, the analysis unit can set a detailed shooting theme based on a highly important testimonial. For example, the analysis unit can set a simple shooting theme based on a less important testimonial. The analysis unit can also adjust the level of detail of a theme based on the importance of the testimonial. For example, the analysis unit can adjust the level of detail of a theme based on the importance of the testimonial. This allows for setting more important themes in detail by adjusting the level of detail of the theme based on the importance of the testimonial. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the importance of the testimonials into the AI, and the AI ​​can adjust the level of detail of the theme.

[0082] The analysis unit can apply different analysis algorithms depending on the category of the testimonial when setting the shooting theme. For example, the analysis unit can apply different analysis algorithms depending on the category of the testimonial. For example, the analysis unit can select the optimal analysis algorithm depending on the category of the testimonial. The analysis unit can also customize the analysis algorithm depending on the category of the testimonial. For example, the analysis unit can customize the analysis algorithm depending on the category of the testimonial. This allows for the setting of more appropriate shooting themes by applying different analysis algorithms depending on the category of the testimonial. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the category of the testimonial into the AI, and the AI ​​can apply the optimal analysis algorithm.

[0083] The analysis unit can estimate the parent's emotions and adjust the length of the shooting theme based on the estimated parent's emotions. For example, the analysis unit can capture the parent's facial expressions with a camera and estimate the emotions using an emotion estimation algorithm. For example, the analysis unit can calculate an emotion score based on changes in facial expressions and adjust the length of the shooting theme. The analysis unit can also record the parent's voice and estimate emotions using voice analysis technology. For example, the analysis unit can analyze the tone and speed of the voice, calculate an emotion score, and adjust the length of the shooting theme. Furthermore, the analysis unit can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate emotions using an emotion estimation algorithm. For example, the analysis unit can calculate an emotion score based on fluctuations in heart rate and adjust the length of the shooting theme. This allows for the provision of shooting themes of a more appropriate length by adjusting the length of the shooting theme based on the parent's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input parental emotion data into the AI, which can then adjust the length of the shooting theme.

[0084] The analysis unit can determine the priority of shooting themes based on the submission timing of testimonials. For example, the analysis unit can determine the priority of themes based on the submission timing of testimonials. For example, the analysis unit can select the optimal theme based on the submission timing of testimonials. The analysis unit can also adjust the priority of themes based on the submission timing of testimonials. For example, the analysis unit can adjust the priority of themes based on the submission timing of testimonials. This allows for the prioritization of more appropriate themes by determining the priority of themes based on the submission timing of testimonials. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the submission timing of testimonials into the AI, and the AI ​​can determine the priority of themes.

[0085] The analysis unit can adjust the order of themes based on the relevance of the testimonials when setting themes for shooting. For example, the analysis unit adjusts the order of themes based on the relevance of the testimonials. For example, the analysis unit determines the optimal order of themes based on the relevance of the testimonials. The analysis unit can also customize the order of themes based on the relevance of the testimonials. For example, the analysis unit customizes the order of themes based on the relevance of the testimonials. This allows themes to be provided in a more appropriate order by adjusting the order of themes based on the relevance of the testimonials. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the relevance of the testimonials into the AI, and the AI ​​can adjust the order of themes.

[0086] The storage unit can estimate the parent's emotions and adjust the storage method for photos and videos based on the estimated emotions. For example, the storage unit can capture the parent's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For example, the storage unit can calculate an emotion score based on changes in facial expressions and adjust the storage method. The storage unit can also record the parent's voice and estimate their emotions using voice analysis technology. For example, the storage unit can analyze the tone and speed of the voice, calculate an emotion score, and adjust the storage method. Furthermore, the storage unit can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, the storage unit can calculate an emotion score based on fluctuations in heart rate and adjust the storage method. This allows for more appropriate storage methods by adjusting the storage method for photos and videos based on the parent's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input parent emotion data into the AI, which can then adjust the storage method.

[0087] The storage unit can select the optimal storage method when saving photos or videos by referring to the parent's past saving history. For example, the storage unit selects the optimal storage method based on the parent's past saving history. For example, the storage unit customizes the storage method based on the parent's past saving history. The storage unit can also suggest a storage method based on the parent's past saving history. For example, the storage unit suggests a storage method based on the parent's past saving history. This allows the optimal storage method to be selected by referring to the parent's past saving history. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's past saving history into AI, and the AI ​​can select the optimal storage method.

[0088] The storage unit can customize the storage method based on the parent's current living situation when saving photos and videos. For example, the storage unit can suggest the optimal storage method based on the parent's current living situation. For example, the storage unit can customize the storage method based on the parent's current living situation. The storage unit can also select a storage method based on the parent's current living situation. For example, the storage unit can select a storage method based on the parent's current living situation. This allows for the provision of a more appropriate storage method by customizing the storage method based on the parent's current living situation. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's current living situation into AI, and the AI ​​can customize the storage method.

[0089] The storage unit can estimate the parent's emotions and determine the priority for saving photos and videos based on the estimated emotions. For example, the storage unit can capture the parent's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For example, the storage unit can calculate an emotion score based on changes in facial expressions and determine the saving priority. The storage unit can also record the parent's voice and estimate their emotions using voice analysis technology. For example, the storage unit can analyze the tone and speed of the voice, calculate an emotion score, and determine the saving priority. Furthermore, the storage unit can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, the storage unit can calculate an emotion score based on fluctuations in heart rate and determine the saving priority. This allows for prioritizing the saving of more important photos and videos based on the parent's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. The generating AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the storage unit may be performed using AI, or not using AI. For example, the storage unit can input parent sentiment data into the AI, which can then determine the storage priority.

[0090] The storage unit can select the optimal storage method when saving photos and videos, taking into account the parent's geographical location information. For example, the storage unit selects the optimal storage method based on the parent's geographical location information. For example, the storage unit customizes the storage method based on the parent's geographical location information. The storage unit can also suggest a storage method based on the parent's geographical location information. For example, the storage unit suggests a storage method based on the parent's geographical location information. By selecting a storage method that takes the parent's geographical location information into account, the storage unit can provide the most appropriate storage method for the region. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's geographical location information into AI, which can then select the optimal storage method.

[0091] The storage unit can analyze the parent's social media activity and suggest a storage method when saving photos and videos. For example, the storage unit can suggest the optimal storage method based on the parent's social media activity. For example, the storage unit can customize the storage method based on the parent's social media activity. The storage unit can also select a storage method based on the parent's social media activity. For example, the storage unit selects a storage method based on the parent's social media activity. This allows the storage unit to suggest the optimal storage method by analyzing the parent's social media activity. Some or all of the above processing in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the parent's social media activity into AI, and the AI ​​can suggest the optimal storage method.

[0092] The service provider can provide optimal advice by referring to the parent's past advice history when providing shooting advice. For example, the service provider can provide optimal shooting advice based on the parent's past advice history. For example, the service provider can customize the advice content based on the parent's past advice history. The service provider can also select an advice method based on the parent's past advice history. For example, the service provider can select an advice method based on the parent's past advice history. This allows the service provider to provide optimal shooting advice by referring to the parent's past advice history. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI. For example, the service provider can input the parent's past advice history into AI, and the AI ​​can provide optimal advice.

[0093] The service provider can customize the advice given when providing photography advice based on the parents' current living situation. For example, the service provider can suggest the most suitable advice based on the parents' current living situation. For example, the service provider can customize the advice based on the parents' current living situation. The service provider can also select an advice based on the parents' current living situation. For example, the service provider can select an advice based on the parents' current living situation. By customizing the advice based on the parents' current living situation, more appropriate advice can be provided. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can input the parents' current living situation into the AI, and the AI ​​can customize the advice.

[0094] The service provider can estimate the parent's emotions and prioritize photography advice based on those emotions. For example, the service provider can capture the parent's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For example, the service provider can calculate an emotion score based on changes in facial expressions and determine the priority of advice. The service provider can also record the parent's voice and estimate their emotions using voice analysis technology. For example, the service provider can analyze the tone and speed of the voice, calculate an emotion score, and determine the priority of advice. Furthermore, the service provider can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, the service provider can calculate an emotion score based on fluctuations in heart rate and determine the priority of advice. This allows the service provider to prioritize photography advice based on the parent's emotions, thereby providing more important advice first. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the service provider may be performed using AI, for example, or without AI. For example, the service provider can input parental emotional data into the AI, which can then determine the priority of advice.

[0095] The service provider can provide optimal advice by considering the parent's geographical location information when providing shooting advice. For example, the service provider can provide optimal shooting advice based on the parent's geographical location information. For example, the service provider can customize the advice content based on the parent's geographical location information. The service provider can also select an advice method based on the parent's geographical location information. For example, the service provider can select an advice method based on the parent's geographical location information. By providing advice while considering the parent's geographical location information, the service provider can provide optimal advice relevant to the region. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI. For example, the service provider can input the parent's geographical location information into AI, and the AI ​​can provide optimal advice.

[0096] The service provider can analyze the parents' social media activity and propose advice methods when providing photography advice. For example, the service provider can propose the most suitable advice method based on the parents' social media activity. For example, the service provider can customize the advice method based on the parents' social media activity. The service provider can also select an advice method based on the parents' social media activity. For example, the service provider can select an advice method based on the parents' social media activity. This allows the service provider to propose the most suitable advice method by analyzing the parents' social media activity. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can input the parents' social media activity into AI, and the AI ​​can propose the most suitable advice method.

[0097] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0098] The analysis unit can estimate the parent's emotions and adjust the difficulty of the shooting theme based on the estimated emotions. For example, if the parent is stressed, the analysis unit can set an easy shooting theme, and if the parent is relaxed, it can set a more challenging theme. The analysis unit captures the parent's facial expressions with a camera and estimates their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions and adjusts the difficulty of the shooting theme. It can also record the parent's voice and estimate their emotions using voice analysis technology. For example, it analyzes the tone and speed of their voice to calculate an emotion score and adjust the difficulty of the shooting theme. Furthermore, it can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on fluctuations in heart rate and adjusts the difficulty of the shooting theme. In this way, by adjusting the difficulty of the shooting theme based on the parent's emotions, parents can enjoy shooting without feeling overwhelmed.

[0099] The system can estimate the parent's emotions and adjust the content of the photography advice based on those emotions. For example, if the parent is tired, the system can provide simple and quick photography advice, while if the parent is energetic, it can provide more detailed and time-consuming advice. The system captures the parent's facial expressions with a camera and estimates their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions and adjusts the advice accordingly. It can also record the parent's voice and estimate their emotions using voice analysis technology. For example, it analyzes the tone and speed of their voice to calculate an emotion score and adjust the advice accordingly. Furthermore, it can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on fluctuations in heart rate and adjusts the advice accordingly. By adjusting the photography advice based on the parent's emotions, the system allows parents to enjoy photography without feeling overwhelmed.

[0100] The storage unit can estimate the parent's emotions and suggest a storage format for photos and videos based on the estimated emotions. For example, if the parent is emotional, the storage unit can suggest a high-resolution storage format, while if the parent took the photos casually, it can suggest a standard-resolution storage format. The storage unit captures the parent's facial expressions with a camera and estimates their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions and suggests a storage format. It can also record the parent's voice and estimate their emotions using voice analysis technology. For example, it analyzes the tone and speed of their voice, calculates an emotion score, and suggests a storage format. Furthermore, it can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on fluctuations in heart rate and suggests a storage format. This allows for the provision of more appropriate storage methods by suggesting a storage format for photos and videos based on the parent's emotions.

[0101] The analysis unit can estimate the parent's emotions and adjust the frequency of photo shoots based on those emotions. For example, if the parent is busy, the analysis unit can reduce the frequency of photo shoots, and if the parent has free time, it can increase the frequency. The analysis unit captures the parent's facial expressions with a camera and estimates their emotions using an emotion estimation algorithm. For example, it can calculate an emotion score based on changes in facial expressions and adjust the frequency of photo shoots. It can also record the parent's voice and estimate their emotions using voice analysis technology. For example, it can analyze the tone and speed of their voice to calculate an emotion score and adjust the frequency of photo shoots. Furthermore, it can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, it can calculate an emotion score based on fluctuations in heart rate and adjust the frequency of photo shoots. By adjusting the frequency of photo shoots based on the parent's emotions, the system allows parents to enjoy taking photos without feeling pressured.

[0102] The system can estimate the parent's emotions and adjust the format of the filming advice based on those emotions. For example, if the parent is relaxed, the system can provide video advice; if the parent is busy, it can provide text advice. The system captures the parent's facial expressions with a camera and estimates their emotions using an emotion estimation algorithm. For example, it can calculate an emotion score based on changes in facial expressions and adjust the format of the advice. It can also record the parent's voice and estimate their emotions using voice analysis technology. For example, it can analyze the tone and speed of their voice to calculate an emotion score and adjust the format of the advice. Furthermore, it can collect the parent's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, it can calculate an emotion score based on fluctuations in heart rate and adjust the format of the advice. By adjusting the format of filming advice based on the parent's emotions, the system allows parents to enjoy filming without feeling pressured.

[0103] The analysis unit can analyze the parent's past shooting theme history and suggest the most suitable shooting theme. For example, it can analyze the frequency and content of themes the parent has photographed in the past and prioritize suggesting themes the parent prefers. The analysis unit collects the parent's past shooting theme history and analyzes it using AI. For example, it suggests the most suitable theme based on the frequency of themes the parent has photographed in the past. It can also analyze the content of themes the parent has photographed in the past and prioritize suggesting themes the parent prefers. Furthermore, it can adjust the order of shooting themes based on the parent's past shooting theme history. For example, it suggests themes in the optimal order based on the order of themes the parent has photographed in the past. In this way, by analyzing the parent's past shooting theme history, it can suggest more appropriate shooting themes.

[0104] The service provider can analyze a parent's past history of photography advice and suggest the most appropriate advice. For example, it can analyze the content and frequency of advice parents have received in the past and prioritize suggesting advice that parents prefer. The service provider collects a parent's past history of photography advice and analyzes it using AI. For example, it suggests the most appropriate advice based on the content of advice parents have received in the past. It can also analyze the frequency of advice parents have received in the past and prioritize suggesting advice that parents prefer. Furthermore, it can adjust the order of advice based on a parent's past history of photography advice. For example, it can suggest advice in the optimal order based on the order in which parents have received advice in the past. In this way, by analyzing a parent's past history of photography advice, more appropriate advice can be suggested.

[0105] The storage unit can analyze the parent's past saving history and suggest the optimal saving method. For example, it can analyze the format and frequency of photos and videos the parent has saved in the past and prioritize suggesting the saving method the parent prefers. The storage unit collects the parent's past saving history and analyzes it using AI. For example, it suggests the optimal saving method based on the format of photos and videos the parent has saved in the past. It can also analyze the frequency of photos and videos the parent has saved in the past and prioritize suggesting the saving method the parent prefers. Furthermore, it can adjust the order of saving methods based on the parent's past saving history. For example, it suggests saving methods in the optimal order based on the order of photos and videos the parent has saved in the past. In this way, by analyzing the parent's past saving history, it can suggest a more appropriate saving method.

[0106] The analysis unit can analyze the parents' current living situation and suggest the most suitable shooting themes. For example, if the parents are busy, the analysis unit can suggest simple and quick shooting themes, and if the parents have more time, it can suggest more detailed and time-consuming shooting themes. The analysis unit collects information on the parents' current living situation and analyzes it using AI. For example, it suggests the most suitable shooting themes based on the parents' work and family circumstances. It can also analyze the parents' current living situation and adjust the frequency of shooting themes. For example, if the parents are busy, it reduces the frequency of shooting themes, and if the parents have more time, it increases the frequency. In this way, by analyzing the parents' current living situation, it can suggest more appropriate shooting themes.

[0107] The service provider can analyze the parents' current living situation and propose optimal photography advice. For example, if the parents are busy, the service provider can propose simple, short-duration photography advice, and if the parents have more time, it can propose more detailed, time-consuming photography advice. The service provider collects information on the parents' current living situation and analyzes it using AI. For example, it proposes optimal photography advice based on the parents' work and family circumstances. It can also analyze the parents' current living situation and adjust the frequency of advice. For example, if the parents are busy, the frequency of advice is reduced, and if the parents have more time, the frequency is increased. In this way, by analyzing the parents' current living situation, it can propose more appropriate photography advice.

[0108] The following briefly describes the processing flow for example form 2.

[0109] Step 1: The data collection team gathers parental experiences and children's opinions. Parental experiences include comments like "I'm glad I took the photos" and "I regret not taking more photos," while children's opinions include comments like "I wish I had more photos like this." The data collection team gathers information from online comments, survey results, and advice from professional photographers. These processes can also be performed using AI. Step 2: The analysis unit analyzes the information collected by the collection unit and sets a shooting theme. For example, it sets a specific theme such as "Take close-up photos showing the size of the child's hands and feet by placing a parent's hand next to them" or "Take photos of the baby in a diaper by lowering the camera to the same eye level as the baby." These processes can also be performed using AI. Step 3: The storage unit saves photos and videos taken by the user. For example, it saves photos and videos to an online album. These processes can also be performed using AI. Step 4: The service provider offers photography advice from professionals. For example, they might offer professional photography advice for a fee. These processes can also be performed using AI.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] Each of the multiple elements described above, including the collection unit, analysis unit, storage unit, and provision unit, is implemented in at least one of the smart device 14 and the data processing device 12. For example, the collection unit is implemented by the control unit 46A of the smart device 14 and collects comments and survey results from the internet. The analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the collected information to set a shooting theme. The storage unit is implemented by the control unit 46A of the smart device 14 and saves the captured photos and videos to an online album. The provision unit is implemented by the specific processing unit 290 of the data processing device 12 and provides shooting advice from professionals. 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.

[0114] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] The microphone 238 receives voice signals from the user and accepts instructions from the user. 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.

[0119] 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).

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.).

[0126] 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.

[0127] 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.

[0128] 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.

[0129] Each of the multiple elements described above, including the collection unit, analysis unit, storage unit, and provision unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the collection unit is implemented by the control unit 46A of the smart glasses 214 and collects comments and survey results from the internet. The analysis unit is implemented by the specific processing unit 290 of the data processing unit 12 and analyzes the collected information to set a shooting theme. The storage unit is implemented by the control unit 46A of the smart glasses 214 and saves the captured photos and videos to an online album. The provision unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides shooting advice from professionals. 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.

[0130] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] The microphone 238 receives voice signals from the user and accepts instructions from the user. 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.

[0135] 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).

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] Each of the multiple elements described above, including the collection unit, analysis unit, storage unit, and provision unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the collection unit is implemented by the control unit 46A of the headset terminal 314 and collects comments and survey results from the internet. The analysis unit is implemented by the specific processing unit 290 of the data processing unit 12 and analyzes the collected information to set a shooting theme. The storage unit is implemented by the control unit 46A of the headset terminal 314 and saves the captured photos and videos to an online album. The provision unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides shooting advice from professionals. 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.

[0146] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] The microphone 238 receives voice signals from the user and accepts instructions from the user. 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.

[0151] 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).

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.).

[0159] 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.

[0160] 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.

[0161] 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.

[0162] Each of the multiple elements described above, including the collection unit, analysis unit, storage unit, and provision unit, is implemented in at least one of the robot 414 and the data processing unit 12. For example, the collection unit is implemented by the control unit 46A of the robot 414 and collects comments and survey results from the internet. The analysis unit is implemented by the specific processing unit 290 of the data processing unit 12 and analyzes the collected information to set a shooting theme. The storage unit is implemented by the control unit 46A of the robot 414 and saves the captured photos and videos to an online album. The provision unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides shooting advice from professionals. 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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."

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] (Note 1) A collection department that gathers parents' experiences and children's opinions, An analysis unit analyzes the information collected by the aforementioned collection unit to set a shooting theme, A storage unit for saving photos and videos taken by the user, It includes a section that provides photography advice from professionals. A system characterized by the following features. (Note 2) The aforementioned storage unit is Save the photos and videos you've taken to an online album. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned supply unit is, Professional photography advice is available for a fee. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned analysis unit, The shooting theme is determined based on online comments, survey results, and advice from professional photographers. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned storage unit is Add comments to the photos and videos you take to create a record of their growth. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned supply unit is, It provides functions for developing photos and creating photo books. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned collection unit is We estimate the parents' emotions and adjust the timing of collecting personal anecdotes based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned collection unit is We will analyze the history of parents submitting past experiences and select the most suitable collection method. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned collection unit is When collecting personal stories, filtering is performed based on the parents' current living situation and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned collection unit is We estimate the parents' emotions and prioritize the stories to collect based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned collection unit is When collecting personal accounts, we prioritize collecting highly relevant accounts by considering the parents' geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned collection unit is When collecting personal stories, we analyze parents' social media activity and gather relevant stories. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned analysis unit, The system estimates the parents' emotions and adjusts the way the filming theme is expressed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned analysis unit, When setting the shooting theme, adjust the level of detail of the theme based on the importance of the personal experience. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned analysis unit, When setting the shooting theme, different analysis algorithms are applied depending on the category of the experience story. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned analysis unit, The system estimates the parent's emotions and adjusts the length of the filming theme based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned analysis unit, When setting themes for the photoshoot, prioritize themes based on when the personal stories will be submitted. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned analysis unit, When setting themes for a photoshoot, adjust the order of themes based on the relevance of the personal experiences shared. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned storage unit is It estimates the parent's emotions and adjusts how photos and videos are saved based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned storage unit is When saving photos and videos, the system will refer to the parent's past saving history to select the optimal saving method. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned storage unit is When saving photos and videos, the saving method is customized based on the parent's current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned storage unit is It estimates the parent's emotions and determines the priority for saving photos and videos based on the estimated parent's emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned storage unit is When saving photos and videos, the system selects the optimal saving method by considering the parent's geographical location information. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned storage unit is When saving photos and videos, we analyze parents' social media activity and suggest storage methods. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned supply unit is, When providing photography advice, we refer to the parents' past advice history to provide the most suitable advice. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned supply unit is, When providing photography advice, we customize the advice based on the parents' current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned supply unit is, The system estimates the parents' emotions and prioritizes photography advice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned supply unit is, When providing photography advice, we take into account the parents' geographical location to provide the most appropriate advice. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned supply unit is, When providing photography advice, we analyze parents' social media activity and suggest appropriate advice strategies. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0182] 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 collection department that gathers parents' experiences and children's opinions, An analysis unit analyzes the information collected by the aforementioned collection unit to set a shooting theme, A storage unit for saving photos and videos taken by the user, It includes a section that provides photography advice from professionals. A system characterized by the following features.

2. The aforementioned storage unit is Save the photos and videos you've taken to an online album. The system according to feature 1.

3. The aforementioned supply unit is, Professional photography advice is available for a fee. The system according to feature 1.

4. The aforementioned analysis unit, The shooting theme is determined based on online comments, survey results, and advice from professional photographers. The system according to feature 1.

5. The aforementioned storage unit is Add comments to the photos and videos you take to create a record of their growth. The system according to feature 1.

6. The aforementioned supply unit is, It provides functions for developing photos and creating photo books. The system according to feature 1.

7. The aforementioned collection unit is We estimate the parents' emotions and adjust the timing of collecting personal anecdotes based on those estimated emotions. The system according to feature 1.

8. The aforementioned collection unit is We will analyze the history of parents submitting past experiences and select the most suitable collection method. The system according to feature 1.

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