System

Abstract

To provide a system according to an embodiment that enables a user to find a skin care routine optimal to an own.SOLUTION: A system according to an embodiment comprises: a reception unit: an analysis unit; and a proposal unit. The reception unit is configured to receive uploading of a picture or video from a user. The analysis unit is configured to analyze the picture or video received by the reception unit, and evaluate a characteristic of a face, or needs of a skin care. The proposal unit is configured to propose a personalized skin care routine on the basis of an analysis result obtained by the analysis unit.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

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

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has made it difficult for users to find the skin care routine that's best for them.

[0005] The system of the embodiment aims to help users find the skin care routine that is best suited for them. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, an analysis unit, and a suggestion unit. The reception unit accepts photos and videos uploaded by a user. The analysis unit analyzes the photos and videos accepted by the reception unit and evaluates facial features or skin care needs. The suggestion unit suggests a personalized skin care routine based on the analysis result obtained by the analysis unit. Effect of the Invention

[0007] The system according to the embodiment allows a user to find a skin care routine that is best suited for them. [Brief description of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

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

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

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

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

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

[0014] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 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." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

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

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

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

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

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

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

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0028] (Example 1) The virtual beauty advisor system according to the embodiment of the present invention is a system that analyzes a user's photos and videos to evaluate individual facial features and skin care needs. This virtual beauty advisor system allows a user to easily upload photos and videos from home and receive analysis results and personalized skin care routine suggestions by AI. For example, a user uploads photos and videos from home. In this case, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal of their face. This allows the AI ​​to perform a more accurate analysis. The uploaded photos and videos are then analyzed by an AI, such as a generative AI. The AI ​​evaluates facial features (e.g., skin tone, wrinkles, age spots, pore condition, etc.) in detail to identify the user's skin care needs. For example, if dry skin is observed, it suggests that moisturizing is necessary. Based on the analysis results, the AI ​​suggests a personalized skin care routine to the user. For example, it suggests morning and evening skin care routines, beauty products to use (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peels once a week). In addition, the AI ​​tracks the user's skin care progress, performs regular analysis, and updates the skin care routine as needed. This allows the user to always have the latest skin care information and take the best care for their skin condition. The system allows users to easily understand their skin care needs from home and helps them choose the best beauty products and treatments. In addition, the analysis and suggestions by AI allow the user to accurately understand their skin condition and take effective skin care. This allows the virtual beauty advisor system to accurately evaluate the user's skin care needs and suggest the best skin care routine.

[0029] The virtual beauty advisor system according to the embodiment includes a reception unit, an analysis unit, and a suggestion unit. The reception unit accepts uploading of photos and videos from a user. The photos and videos from the user include, for example, formats such as JPEG, PNG, MP4, etc., but are not limited to such examples. The reception unit, for example, enables the user to upload photos and videos from home. The reception unit can also accept photos and videos taken from multiple angles. For example, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal of his or her face. This allows the AI ​​to perform a more accurate analysis. The analysis unit uses AI to analyze the photos and videos accepted by the reception unit and evaluate facial features and skin care needs. The analysis is performed, for example, using an image recognition algorithm or a machine learning model, but is not limited to such examples. For example, the analysis unit evaluates facial features (for example, skin tone, wrinkles, spots, pore condition, etc.) in detail to identify the user's skin care needs. For example, if dry skin is observed, it suggests that moisturizing is necessary. The suggestion unit suggests a personalized skin care routine based on the analysis result obtained by the analysis unit. The suggestions include, but are not limited to, morning and evening skin care routines, beauty products to be used (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peeling once a week, etc.). For example, the suggestion unit suggests an optimal skin care routine based on the user's skin condition. This allows the virtual beauty advisor system according to the embodiment to accurately evaluate the user's skin care needs and suggest an optimal skin care routine. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit may make a suggestion using an AI model that inputs the analysis result obtained by the analysis unit and outputs a personalized skin care routine.

[0030] The reception unit accepts uploads of photos and videos from the user. The photos and videos from the user include, but are not limited to, formats such as JPEG, PNG, and MP4. The reception unit, for example, enables the user to upload photos and videos from home. The reception unit can also accept photos and videos taken from multiple angles. For example, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal of his or her face. This allows the AI ​​to perform more accurate analysis. The reception unit is designed to allow the user to easily and intuitively upload photos and videos through a user interface. For example, a drag-and-drop function or a function to upload images and videos taken directly using the smartphone camera on the spot can be provided. Furthermore, the reception unit can check the quality of the uploaded data and accept only images and videos with a resolution and brightness suitable for analysis. This can ensure data for the analysis unit to perform high-precision analysis. The reception unit also has a function to encrypt and securely store uploaded data to protect the user's privacy. This allows the user to provide his or her own photos and videos with peace of mind. Furthermore, the reception unit can provide feedback to the data uploaded by the user, and urge the user to retake or reupload the image if necessary. For example, if the image is blurry or not taken from an appropriate angle, the reception unit can provide specific instructions to the user and urge the user to reupload the image. This allows the reception unit to collect optimal data for the analysis unit to perform a highly accurate analysis.

[0031] The analysis unit uses AI to analyze the photos and videos received by the reception unit to evaluate facial features and skin care needs. The analysis is performed using, for example, an image recognition algorithm or a machine learning model, but is not limited to such examples. For example, the analysis unit evaluates facial features (e.g., skin tone, wrinkles, age spots, pore condition, etc.) in detail to identify the user's skin care needs. For example, if dry skin is observed, it suggests that moisturizing is necessary. The analysis unit can utilize the latest deep learning technology to analyze each part of the face with high accuracy. For example, it can use a convolutional neural network (CNN) to analyze the texture and tone of the skin and identify the location and depth of wrinkles and age spots. In addition, the analysis unit can provide more personalized analysis results by taking into account information such as the user's age, gender, and lifestyle. For example, it can suggest care for acne and oily skin to younger users, and care focused on anti-aging and moisturizing to middle-aged and older users. Additionally, the analytics unit can use historical data and trends to predict changes in the user's skin condition and suggest long-term skin care plans. For example, specific skin care products or treatments can be recommended during seasonal changes or stressful periods. This allows the analytics unit to provide the basis for accurately assessing the user's skin care needs and suggesting optimal skin care routines.

[0032] The suggestion unit suggests a personalized skin care routine based on the analysis results obtained by the analysis unit. The suggestions include, for example, morning and evening skin care routines, beauty products to be used (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peeling once a week, etc.), but are not limited to such examples. For example, the suggestion unit suggests an optimal skin care routine based on the user's skin condition. In this way, the virtual beauty advisor system according to the embodiment can accurately evaluate the user's skin care needs and suggest an optimal skin care routine. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI, or may be performed without using AI. For example, the suggestion unit can make suggestions using an AI model that takes the analysis results obtained by the analysis unit as input and outputs a personalized skin care routine. The suggestion unit can suggest a more practical and sustainable skin care routine by taking into account the user's lifestyle and preferences. For example, it can suggest skin care products and routines that are effective in a short time to a busy user, and suggest a routine including more detailed skin care steps to a user who has plenty of time. In addition, the suggestion unit can select the most suitable product by considering the user's allergy information and preferences for specific ingredients. For example, for a user who is allergic to a specific ingredient, a product that does not contain that ingredient can be suggested, and for a user who prefers natural products, a product that uses organic ingredients can be suggested. Furthermore, the suggestion unit can collect user feedback and continuously improve the accuracy and effectiveness of the suggestions. For example, the user can provide the results of practicing the suggested skin care routine as feedback, and the suggestion unit can analyze the data and reflect it in the next suggestion. This allows the suggestion unit to always provide the most suitable skin care routine to the user and increase the user's satisfaction.

[0033] The reception unit can receive photos and videos of the user from multiple angles. The reception unit recommends that the user provide images and videos taken from multiple angles, such as the front, side, and diagonal view of the user's face. This allows the AI ​​to perform more accurate analysis. For example, the reception unit can display a message encouraging the user to take photos and videos from multiple angles when uploading photos and videos from home. In addition, when the user uploads photos and videos taken from multiple angles, the reception unit can automatically classify images and videos from each angle and provide them to the analysis unit. This allows more accurate analysis by accepting photos and videos from multiple angles. Some or all of the above-mentioned processing in the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that automatically determines the angle of the photos and videos uploaded by the user and provides the analysis unit with images and videos from appropriate angles.

[0034] The analysis unit can specifically evaluate facial features and identify skin care needs. The analysis unit, for example, evaluates facial features (e.g., skin tone, wrinkles, age spots, pore condition, etc.) in detail. For example, the analysis unit can quantify skin tone, measure wrinkle depth, count the number of age spots, and evaluate the condition of pores. The analysis unit can also identify the user's skin care needs based on these evaluation results. For example, if dry skin is observed, it suggests that moisturizing is necessary. The analysis unit can also suggest that whitening care is necessary if the skin tone is uneven. This allows the skin care needs to be accurately identified by evaluating facial features in detail. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform analysis using an AI model that inputs a user's photo or video, evaluates facial features, and identifies skin care needs.

[0035] The suggestion unit can suggest a morning or evening skin care routine. For example, the suggestion unit can suggest the use of a cleanser, toner, moisturizer, and sunscreen as a morning skin care routine. The suggestion unit can also suggest the use of a cleanser, toner, moisturizer, and night cream as an evening skin care routine. This allows the user to be provided with appropriate skin care by suggesting morning and evening skin care routines. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can make a suggestion using an AI model that inputs the analysis results obtained by the analysis unit and outputs morning and evening skin care routines.

[0036] The suggestion unit can suggest recommended beauty products. The suggestion unit can suggest beauty products such as cleansers, toners, moisturizers, and sunscreens based on the user's skin condition, for example. For example, the suggestion unit can suggest a moisturizer with a high moisturizing effect when the skin is dry. Also, the suggestion unit can suggest a toner with a whitening effect when the skin tone is uneven. This makes it possible to provide the user with an optimal skin care product by suggesting a beauty product to be used. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can make suggestions using an AI model that inputs the analysis results obtained by the analysis unit and outputs recommended beauty products.

[0037] The suggestion unit can suggest the specified treatment. The suggestion unit can suggest a specific treatment, such as a face mask or peeling once a week, based on the user's skin condition, for example. For example, the suggestion unit can suggest a face mask with a high moisturizing effect when the skin is dry. Also, the suggestion unit can suggest peeling when the pores are in poor condition. In this way, by suggesting a specific treatment, it is possible to provide the user with an appropriate skin care treatment. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can make a suggestion using an AI model that inputs the analysis result obtained by the analysis unit and outputs a specific treatment.

[0038] The system can track the progress of the user's skin care, periodically perform analysis, and update the skin care routine. For example, the system can cause the user to upload photos and videos periodically to track the progress of the user's skin care. For example, the system can send notifications to the user at periodic timings such as weekly, monthly, and after a specific event, and cause the user to upload the latest photos and videos. This allows the system to track the progress of the user's skin care and periodically perform analysis. Furthermore, the system can update the skin care routine based on the analysis results. For example, the system can suggest a new skin care routine when the user's skin condition improves. Furthermore, the system can suggest a more effective skin care routine when the user's skin condition worsens. This allows the system to always provide the latest skin care information and provide optimal care for the user's skin condition. Part or all of the above-mentioned processing in the system may be performed, for example, using AI, or may be performed without using AI. For example, the system can perform processing using an AI model that uses the user's photos and videos as input, tracks the progress of skin care, and updates the skin care routine.

[0039] The system includes a protection unit that securely stores the user's data and protects privacy. The protection unit can, for example, encrypt and store the user's data. For example, the protection unit encrypts the user's photos and videos and securely stores them in a database. The protection unit can also set access restrictions when accessing the user's data. For example, the protection unit limits users who have the authority to access the user's data and prevents unauthorized access. Furthermore, the protection unit can anonymize the user's data. For example, the protection unit protects privacy by anonymizing the user's personal information and using it for data analysis. This allows the system to securely store the user's data and protect privacy. A part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit can encrypt the user's data, set access restrictions, and perform processing using an AI model that anonymizes the user's data.

[0040] The reception unit can analyze the user's past upload history and select an appropriate upload method. The reception unit can collect data such as upload date and time, frequency, and content in order to analyze the user's past upload history. For example, the reception unit can preferentially suggest an upload method that the user has frequently used in the past. In addition, the reception unit can suggest an optimal upload method for a specific time period from the user's past upload history. Furthermore, the reception unit can select an optimal upload method based on the types of photos and videos that the user has uploaded in the past. In this way, the optimal upload method can be provided to the user by analyzing the past upload history. A part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that inputs the user's past upload history and selects the optimal upload method.

[0041] The reception unit can perform filtering based on the user's current environment when uploading photos and videos. The reception unit can perform filtering of photos and videos, for example, taking into account the user's current environment (for example, lighting conditions and background). For example, the reception unit can automatically adjust the lighting when the user takes a picture in a dark place. In addition, the reception unit can apply a filter that blurs the background when the user takes a picture in a place with a cluttered background. Furthermore, the reception unit can apply a filter that makes use of natural light when the user takes a picture outdoors. This allows more appropriate photos and videos to be uploaded by filtering according to the user's environment. Part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that uses the user's current environmental data as input and performs filtering.

[0042] The reception unit can preferentially accept highly relevant data in consideration of the geographical location information of the user when uploading photos and videos. The reception unit can preferentially accept highly relevant data in consideration of, for example, the geographical location information of the user. For example, when the user is in a specific area, the reception unit can preferentially upload photos and videos related to the area. Furthermore, when the user is traveling, the reception unit can preferentially upload photos and videos of the travel destination. Furthermore, when the user is at home, the reception unit can preferentially upload photos and videos around the home. In this way, highly relevant data can be preferentially accepted by considering the geographical location information of the user. Part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that inputs the geographical location information of the user and preferentially accepts highly relevant data.

[0043] The reception unit can analyze the user's social media activity and accept related data when uploading photos and videos. The reception unit can collect data such as the post content, the number of likes, and comments in order to analyze the user's social media activity. For example, the reception unit can preferentially upload photos and videos shared by the user on social media. The reception unit can also preferentially upload photos and videos tagged by the user on social media. Furthermore, the reception unit can preferentially upload photos and videos related to accounts the user follows on social media. This allows the user's social media activity to be analyzed and related data to be efficiently accepted. A part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that receives the user's social media activity data as an input and accepts related data.

[0044] During the analysis, the analysis unit can track changes in facial features and evaluate long-term skin care needs. The analysis unit can, for example, track changes in wrinkles on the user's face and evaluate the need for long-term moisturizing care. The analysis unit can also track changes in the user's skin tone and evaluate the need for whitening care. Furthermore, the analysis unit can track changes in the state of the user's pores and evaluate the need for pore care. This makes it possible to evaluate long-term skin care needs by tracking changes in facial features. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that uses change data on the user's facial features as input and evaluates long-term skin care needs.

[0045] The analysis unit can identify skin care needs by taking into account the user's lifestyle habits during analysis. The analysis unit can identify skin care needs by taking into account the user's lifestyle habits (e.g., diet and sleep patterns). For example, the analysis unit can analyze the user's dietary patterns and identify skin care needs due to nutritional deficiencies. The analysis unit can also analyze the user's sleep patterns and identify skin care needs due to lack of sleep. Furthermore, the analysis unit can analyze the user's exercise habits and identify skin care needs due to lack of exercise. This makes it possible to identify more appropriate skin care needs by taking into account the user's lifestyle habits. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that inputs the user's lifestyle habit data and identifies skin care needs.

[0046] The analysis unit can identify skin care needs by considering the geographical environment of the user during analysis. The analysis unit can identify skin care needs by considering, for example, the geographical environment of the user (for example, climate and air pollution). For example, the analysis unit can identify the need for moisturizing care if the user lives in a dry climate. Also, the analysis unit can identify the need for oil control if the user lives in a humid climate. Furthermore, the analysis unit can identify the need for antioxidant care if the user lives in an area with high air pollution. This makes it possible to identify more appropriate skin care needs by considering the geographical environment of the user. Part or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that inputs the geographical environment data of the user and identifies skin care needs.

[0047] During the analysis, the analysis unit can identify skin care needs by referring to the user's past medical history. The analysis unit can collect data such as diagnosis results, treatment history, and allergy information to refer to the user's past medical history. For example, the analysis unit can identify the need for allergy-friendly skin care if the user has had an allergy in the past. In addition, the analysis unit can identify the need for skin care that requires specific treatment if the user has had a skin disease in the past. Furthermore, the analysis unit can identify the need for subsequent care if the user has had cosmetic surgery in the past. This makes it possible to identify more appropriate skin care needs by referring to the user's past medical history. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that uses the user's past medical history data as input and identifies skin care needs.

[0048] The suggestion unit can suggest an optimal skin care routine by referring to the user's past skin care history at the time of suggestion. The suggestion unit can collect data such as the product used, the effect, and the frequency in order to refer to the user's past skin care history. For example, the suggestion unit can suggest an optimal skin care routine based on the skin care products used by the user in the past. In addition, the suggestion unit can preferentially suggest effective products from the user's past skin care history. Furthermore, the suggestion unit can analyze the user's past skin care history and identify and suggest areas that need improvement. As a result, a more appropriate skin care routine can be suggested by referring to the user's past skin care history. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that inputs the user's past skin care history data and suggests an optimal skin care routine.

[0049] The suggestion unit can customize the skin care routine based on the user's current living situation at the time of suggestion. The suggestion unit can customize the skin care routine, for example, taking into account the user's current living situation (e.g., stress level, work schedule). For example, the suggestion unit can suggest a skin care routine that is effective in a short time when the user is busy. In addition, the suggestion unit can suggest a skin care routine that takes time when the user is relaxed. Furthermore, the suggestion unit can suggest a skin care product that is convenient to carry when the user is traveling. This allows more appropriate skin care to be provided by customizing the skin care routine based on the user's current living situation. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that uses the user's current living situation data as input and customizes the skin care routine.

[0050] The suggestion unit can suggest an optimal skin care routine in consideration of the geographical location information of the user at the time of suggestion. The suggestion unit can suggest an optimal skin care routine in consideration of, for example, the geographical location information of the user. For example, if the user lives in a dry climate, the suggestion unit can suggest a skin care routine that prioritizes moisturizing care. In addition, if the user lives in a humid climate, the suggestion unit can suggest a skin care routine that prioritizes oil control. Furthermore, if the user lives in an area with high air pollution, the suggestion unit can suggest a skin care routine that prioritizes antioxidant care. This makes it possible to suggest a more appropriate skin care routine by considering the geographical location information of the user. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI, or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that inputs the geographical location information data of the user and proposes an optimal skin care routine.

[0051] At the time of suggestion, the suggestion unit can analyze the user's social media activity to suggest a skin care routine. The suggestion unit can collect data such as the content of posts, the number of likes, and comments to analyze the user's social media activity. For example, the suggestion unit can suggest an optimal skin care routine based on skin care products shared by the user on social media. The suggestion unit can also suggest a skin care routine based on products recommended by beauty influencers that the user follows on social media. Furthermore, the suggestion unit can suggest a skin care routine based on trends in beauty communities in which the user participates on social media. This allows a more appropriate skin care routine to be suggested by analyzing the user's social media activity. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI, or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that inputs the user's social media activity data and suggests an optimal skin care routine.

[0052] The protection unit can select the optimal protection method by referring to the user's past data access history when protecting data. The protection unit can collect data such as access date and time and access content in order to refer to the user's past data access history. For example, the protection unit can preferentially protect data that the user frequently accessed in the past. In addition, the protection unit can adjust the protection level for specific data from the user's past data access history. Furthermore, the protection unit can select the optimal protection method based on the type of data that the user accessed in the past. As a result, a more appropriate data protection method can be selected by referring to the user's past data access history. Part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI or may be performed without using AI. For example, the protection unit can perform processing using an AI model that inputs the user's past data access history data and selects the optimal protection method.

[0053] The protection unit can select the optimal protection method in consideration of the geographical location information of the user when protecting data. The protection unit can select the optimal protection method in consideration of, for example, the geographical location information of the user. For example, when the user is in a specific area, the protection unit can select the protection method based on the data protection regulations of the area. In addition, when the user is traveling, the protection unit can select the protection method based on the data protection regulations of the travel destination. Furthermore, when the user is at home, the protection unit can select the protection method based on the data protection regulations of the home. In this way, a more appropriate data protection method can be selected by considering the geographical location information of the user. Part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit can perform processing using an AI model that inputs the geographical location information data of the user and selects the optimal protection method.

[0054] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0055] The reception unit can suggest an optimal upload method when uploading a user's photos or videos by referring to the user's past skin care history. For example, the reception unit can analyze the upload methods used by the user in the past and suggest the most efficient method. The reception unit can also suggest an optimal upload method for a specific time period based on the user's past skin care history. Furthermore, the reception unit can select an optimal upload method based on the types of photos or videos the user has uploaded in the past. In this way, the optimal upload method can be provided to the user by referring to the past skin care history.

[0056] The analysis unit can identify skin care needs by taking into account the user's lifestyle habits. For example, the analysis unit can analyze the user's eating patterns and identify skin care needs due to nutritional deficiencies. The analysis unit can also analyze the user's sleep patterns and identify skin care needs due to lack of sleep. Furthermore, the analysis unit can analyze the user's exercise habits and identify skin care needs due to lack of exercise. This allows more appropriate skin care needs to be identified by taking into account the user's lifestyle habits.

[0057] The suggestion unit can suggest an optimal skin care routine taking into account the geographic location information of the user. For example, if the user lives in a dry climate, the suggestion unit can suggest a skin care routine that prioritizes moisturizing care. Also, if the user lives in a humid climate, the suggestion unit can suggest a skin care routine that prioritizes oil control. Furthermore, if the user lives in an area with high air pollution, the suggestion unit can suggest a skin care routine that prioritizes antioxidant care. In this way, a more appropriate skin care routine can be suggested by taking into account the geographic location information of the user.

[0058] The analysis unit can identify skin care needs by referring to the user's past medical history. For example, if the user has had allergies in the past, the need for allergy-friendly skin care can be identified. Also, if the user has had a skin disease in the past, the need for skin care that requires a specific treatment can be identified. Furthermore, if the user has had cosmetic surgery in the past, the need for follow-up care can be identified. This allows for more appropriate skin care needs to be identified by referring to the user's past medical history.

[0059] The suggestion unit can suggest a skin care routine by analyzing the user's social media activity. For example, the suggestion unit can suggest an optimal skin care routine based on skin care products shared by the user on social media. The suggestion unit can also suggest a skin care routine based on products recommended by beauty influencers the user follows on social media. Furthermore, the suggestion unit can suggest a skin care routine based on trends in beauty communities in which the user participates on social media. In this way, a more appropriate skin care routine can be suggested by analyzing the user's social media activity.

[0060] The protection unit can select an optimal protection method in consideration of the geographical location information of the user when protecting data. For example, when the user is in a specific region, the protection unit can select a protection method based on the data protection regulations of the region. Also, when the user is traveling, the protection unit can select a protection method based on the data protection regulations of the travel destination. Furthermore, when the user is at home, the protection unit can select a protection method based on the data protection regulations of the home. In this way, a more appropriate data protection method can be selected by considering the geographical location information of the user.

[0061] The process flow of the first embodiment will be briefly described below.

[0062] Step 1: The reception unit accepts uploads of photos and videos from the user. Photos and videos from the user may be in formats such as, but not limited to, JPEG, PNG, MP4, etc. The reception unit may, for example, enable the user to upload photos and videos from their home. The reception unit may also accept photos and videos taken from multiple angles. For example, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal views of their face. This allows the AI ​​to perform more accurate analysis. Step 2: The analysis unit uses AI to analyze the photos and videos received by the reception unit to evaluate facial features and skin care needs. The analysis is performed using, for example, an image recognition algorithm or a machine learning model, but is not limited to such examples. For example, the analysis unit evaluates facial features (e.g., skin tone, wrinkles, blemishes, pore condition, etc.) in detail to identify the user's skin care needs. For example, if the skin is dry, it suggests that moisturizing is necessary. Step 3: The suggestion unit suggests a personalized skin care routine based on the analysis result obtained by the analysis unit. The suggestions include, but are not limited to, morning and evening skin care routines, beauty products to be used (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peeling once a week, etc.). For example, the suggestion unit suggests an optimal skin care routine based on the user's skin condition. This allows the virtual beauty advisor system according to the embodiment to accurately evaluate the user's skin care needs and suggest an optimal skin care routine. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit may make a suggestion using an AI model that inputs the analysis result obtained by the analysis unit and outputs a personalized skin care routine.

[0063] (Example 2) The virtual beauty advisor system according to the embodiment of the present invention is a system that analyzes a user's photos and videos to evaluate individual facial features and skin care needs. This virtual beauty advisor system allows a user to easily upload photos and videos from home and receive analysis results and personalized skin care routine suggestions by AI. For example, a user uploads photos and videos from home. In this case, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal of their face. This allows the AI ​​to perform a more accurate analysis. The uploaded photos and videos are then analyzed by an AI, such as a generative AI. The AI ​​evaluates facial features (e.g., skin tone, wrinkles, age spots, pore condition, etc.) in detail to identify the user's skin care needs. For example, if dry skin is observed, it suggests that moisturizing is necessary. Based on the analysis results, the AI ​​suggests a personalized skin care routine to the user. For example, it suggests morning and evening skin care routines, beauty products to use (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peels once a week). In addition, the AI ​​tracks the user's skin care progress, performs regular analysis, and updates the skin care routine as needed. This allows the user to always have the latest skin care information and take the best care for their skin condition. The system allows users to easily understand their skin care needs from home and helps them choose the best beauty products and treatments. In addition, the analysis and suggestions by AI allow the user to accurately understand their skin condition and take effective skin care. This allows the virtual beauty advisor system to accurately evaluate the user's skin care needs and suggest the best skin care routine.

[0064] The virtual beauty advisor system according to the embodiment includes a reception unit, an analysis unit, and a suggestion unit. The reception unit accepts uploading of photos and videos from a user. The photos and videos from the user include, for example, formats such as JPEG, PNG, MP4, etc., but are not limited to such examples. The reception unit, for example, enables the user to upload photos and videos from home. The reception unit can also accept photos and videos taken from multiple angles. For example, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal of his or her face. This allows the AI ​​to perform a more accurate analysis. The analysis unit uses AI to analyze the photos and videos accepted by the reception unit and evaluate facial features and skin care needs. The analysis is performed, for example, using an image recognition algorithm or a machine learning model, but is not limited to such examples. For example, the analysis unit evaluates facial features (for example, skin tone, wrinkles, spots, pore condition, etc.) in detail to identify the user's skin care needs. For example, if dry skin is observed, it suggests that moisturizing is necessary. The suggestion unit suggests a personalized skin care routine based on the analysis result obtained by the analysis unit. The suggestions include, but are not limited to, morning and evening skin care routines, beauty products to be used (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peeling once a week, etc.). For example, the suggestion unit suggests an optimal skin care routine based on the user's skin condition. This allows the virtual beauty advisor system according to the embodiment to accurately evaluate the user's skin care needs and suggest an optimal skin care routine. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit may make a suggestion using an AI model that inputs the analysis result obtained by the analysis unit and outputs a personalized skin care routine.

[0065] The reception unit accepts uploads of photos and videos from the user. The photos and videos from the user include, but are not limited to, formats such as JPEG, PNG, and MP4. The reception unit, for example, enables the user to upload photos and videos from home. The reception unit can also accept photos and videos taken from multiple angles. For example, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal of his or her face. This allows the AI ​​to perform more accurate analysis. The reception unit is designed to allow the user to easily and intuitively upload photos and videos through a user interface. For example, a drag-and-drop function or a function to upload images and videos taken directly using the smartphone camera on the spot can be provided. Furthermore, the reception unit can check the quality of the uploaded data and accept only images and videos with a resolution and brightness suitable for analysis. This can ensure data for the analysis unit to perform high-precision analysis. The reception unit also has a function to encrypt and securely store uploaded data to protect the user's privacy. This allows the user to provide his or her own photos and videos with peace of mind. Furthermore, the reception unit can provide feedback to the data uploaded by the user, and urge the user to retake or reupload the image if necessary. For example, if the image is blurry or not taken from an appropriate angle, the reception unit can provide specific instructions to the user and urge the user to reupload the image. This allows the reception unit to collect optimal data for the analysis unit to perform a highly accurate analysis.

[0066] The analysis unit uses AI to analyze the photos and videos received by the reception unit to evaluate facial features and skin care needs. The analysis is performed using, for example, an image recognition algorithm or a machine learning model, but is not limited to such examples. For example, the analysis unit evaluates facial features (e.g., skin tone, wrinkles, age spots, pore condition, etc.) in detail to identify the user's skin care needs. For example, if dry skin is observed, it suggests that moisturizing is necessary. The analysis unit can utilize the latest deep learning technology to analyze each part of the face with high accuracy. For example, it can use a convolutional neural network (CNN) to analyze the texture and tone of the skin and identify the location and depth of wrinkles and age spots. In addition, the analysis unit can provide more personalized analysis results by taking into account information such as the user's age, gender, and lifestyle. For example, it can suggest care for acne and oily skin to younger users, and care focused on anti-aging and moisturizing to middle-aged and older users. Additionally, the analytics unit can use historical data and trends to predict changes in the user's skin condition and suggest long-term skin care plans. For example, specific skin care products or treatments can be recommended during seasonal changes or stressful periods. This allows the analytics unit to provide the basis for accurately assessing the user's skin care needs and suggesting optimal skin care routines.

[0067] The suggestion unit suggests a personalized skin care routine based on the analysis results obtained by the analysis unit. The suggestions include, for example, morning and evening skin care routines, beauty products to be used (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peeling once a week, etc.), but are not limited to such examples. For example, the suggestion unit suggests an optimal skin care routine based on the user's skin condition. In this way, the virtual beauty advisor system according to the embodiment can accurately evaluate the user's skin care needs and suggest an optimal skin care routine. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI, or may be performed without using AI. For example, the suggestion unit can make suggestions using an AI model that takes the analysis results obtained by the analysis unit as input and outputs a personalized skin care routine. The suggestion unit can suggest a more practical and sustainable skin care routine by taking into account the user's lifestyle and preferences. For example, it can suggest skin care products and routines that are effective in a short time to a busy user, and suggest a routine including more detailed skin care steps to a user who has plenty of time. In addition, the suggestion unit can select the most suitable product by considering the user's allergy information and preferences for specific ingredients. For example, for a user who is allergic to a specific ingredient, a product that does not contain that ingredient can be suggested, and for a user who prefers natural products, a product that uses organic ingredients can be suggested. Furthermore, the suggestion unit can collect user feedback and continuously improve the accuracy and effectiveness of the suggestions. For example, the user can provide the results of practicing the suggested skin care routine as feedback, and the suggestion unit can analyze the data and reflect it in the next suggestion. This allows the suggestion unit to always provide the most suitable skin care routine to the user and increase the user's satisfaction.

[0068] The reception unit can receive photos and videos of the user from multiple angles. The reception unit recommends that the user provide images and videos taken from multiple angles, such as the front, side, and diagonal view of the user's face. This allows the AI ​​to perform more accurate analysis. For example, the reception unit can display a message encouraging the user to take photos and videos from multiple angles when uploading photos and videos from home. In addition, when the user uploads photos and videos taken from multiple angles, the reception unit can automatically classify images and videos from each angle and provide them to the analysis unit. This allows more accurate analysis by accepting photos and videos from multiple angles. Some or all of the above-mentioned processing in the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that automatically determines the angle of the photos and videos uploaded by the user and provides the analysis unit with images and videos from appropriate angles.

[0069] The analysis unit can specifically evaluate facial features and identify skin care needs. The analysis unit, for example, evaluates facial features (e.g., skin tone, wrinkles, age spots, pore condition, etc.) in detail. For example, the analysis unit can quantify skin tone, measure wrinkle depth, count the number of age spots, and evaluate the condition of pores. The analysis unit can also identify the user's skin care needs based on these evaluation results. For example, if dry skin is observed, it suggests that moisturizing is necessary. The analysis unit can also suggest that whitening care is necessary if the skin tone is uneven. This allows the skin care needs to be accurately identified by evaluating facial features in detail. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform analysis using an AI model that inputs a user's photo or video, evaluates facial features, and identifies skin care needs.

[0070] The suggestion unit can suggest a morning or evening skin care routine. For example, the suggestion unit can suggest the use of a cleanser, toner, moisturizer, and sunscreen as a morning skin care routine. The suggestion unit can also suggest the use of a cleanser, toner, moisturizer, and night cream as an evening skin care routine. This allows the user to be provided with appropriate skin care by suggesting morning and evening skin care routines. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can make a suggestion using an AI model that inputs the analysis results obtained by the analysis unit and outputs morning and evening skin care routines.

[0071] The suggestion unit can suggest recommended beauty products. The suggestion unit can suggest beauty products such as cleansers, toners, moisturizers, and sunscreens based on the user's skin condition, for example. For example, the suggestion unit can suggest a moisturizer with a high moisturizing effect when the skin is dry. Also, the suggestion unit can suggest a toner with a whitening effect when the skin tone is uneven. This makes it possible to provide the user with an optimal skin care product by suggesting a beauty product to be used. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can make suggestions using an AI model that inputs the analysis results obtained by the analysis unit and outputs recommended beauty products.

[0072] The suggestion unit can suggest the specified treatment. The suggestion unit can suggest a specific treatment, such as a face mask or peeling once a week, based on the user's skin condition, for example. For example, the suggestion unit can suggest a face mask with a high moisturizing effect when the skin is dry. Also, the suggestion unit can suggest peeling when the pores are in poor condition. In this way, by suggesting a specific treatment, it is possible to provide the user with an appropriate skin care treatment. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can make a suggestion using an AI model that inputs the analysis result obtained by the analysis unit and outputs a specific treatment.

[0073] The system can track the progress of the user's skin care, periodically perform analysis, and update the skin care routine. For example, the system can cause the user to upload photos and videos periodically to track the progress of the user's skin care. For example, the system can send notifications to the user at periodic timings such as weekly, monthly, and after a specific event, and cause the user to upload the latest photos and videos. This allows the system to track the progress of the user's skin care and periodically perform analysis. Furthermore, the system can update the skin care routine based on the analysis results. For example, the system can suggest a new skin care routine when the user's skin condition improves. Furthermore, the system can suggest a more effective skin care routine when the user's skin condition worsens. This allows the system to always provide the latest skin care information and provide optimal care for the user's skin condition. Part or all of the above-mentioned processing in the system may be performed, for example, using AI, or may be performed without using AI. For example, the system can perform processing using an AI model that uses the user's photos and videos as input, tracks the progress of skin care, and updates the skin care routine.

[0074] The system includes a protection unit that securely stores the user's data and protects privacy. The protection unit can, for example, encrypt and store the user's data. For example, the protection unit encrypts the user's photos and videos and securely stores them in a database. The protection unit can also set access restrictions when accessing the user's data. For example, the protection unit limits users who have the authority to access the user's data and prevents unauthorized access. Furthermore, the protection unit can anonymize the user's data. For example, the protection unit protects privacy by anonymizing the user's personal information and using it for data analysis. This allows the system to securely store the user's data and protect privacy. A part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit can encrypt the user's data, set access restrictions, and perform processing using an AI model that anonymizes the user's data.

[0075] The reception unit can estimate the user's emotion and adjust the upload timing of the photo or video based on the estimated user's emotion. The reception unit can use, for example, facial expression recognition or voice analysis to estimate the user's emotion. For example, the reception unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. The reception unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the reception unit analyzes the tone and speed of the user's voice and calculates an emotion score. Furthermore, the reception unit can adjust the upload timing of the photo or video based on the estimated user's emotion. For example, when the user is relaxed, the user can be allowed to freely choose the timing of uploading. Furthermore, when the user is stressed, the user can be allowed to upload with a simple operation. Furthermore, when the user is in a hurry, the user can be allowed to quickly upload with voice input. This can improve the convenience of the user by adjusting the upload timing according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate emotions.

[0076] The reception unit can analyze the user's past upload history and select an appropriate upload method. The reception unit can collect data such as upload date and time, frequency, and content in order to analyze the user's past upload history. For example, the reception unit can preferentially suggest an upload method that the user has frequently used in the past. In addition, the reception unit can suggest an optimal upload method for a specific time period from the user's past upload history. Furthermore, the reception unit can select an optimal upload method based on the types of photos and videos that the user has uploaded in the past. In this way, the optimal upload method can be provided to the user by analyzing the past upload history. A part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that inputs the user's past upload history and selects the optimal upload method.

[0077] The reception unit can perform filtering based on the user's current environment when uploading photos and videos. The reception unit can perform filtering of photos and videos, for example, taking into account the user's current environment (for example, lighting conditions and background). For example, the reception unit can automatically adjust the lighting when the user takes a picture in a dark place. In addition, the reception unit can apply a filter that blurs the background when the user takes a picture in a place with a cluttered background. Furthermore, the reception unit can apply a filter that makes use of natural light when the user takes a picture outdoors. This allows more appropriate photos and videos to be uploaded by filtering according to the user's environment. Part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that uses the user's current environmental data as input and performs filtering.

[0078] The reception unit can estimate the user's emotion and determine the priority of photos and videos to be uploaded based on the estimated user's emotion. The reception unit can use, for example, facial expression recognition and voice analysis to estimate the user's emotion. For example, the reception unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. The reception unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the reception unit analyzes the tone and speed of the user's voice and calculates an emotion score. Furthermore, the reception unit can determine the priority of photos and videos to be uploaded based on the estimated user's emotion. For example, if the user is relaxed, the latest photos and videos can be uploaded with priority. Furthermore, if the user is stressed, photos and videos taken in the past can be uploaded with priority. Furthermore, if the user is in a hurry, the most important photos and videos can be uploaded with priority. This can improve the convenience of the user by determining the priority of uploads according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate emotions.

[0079] The reception unit can preferentially accept highly relevant data in consideration of the geographical location information of the user when uploading photos and videos. The reception unit can preferentially accept highly relevant data in consideration of, for example, the geographical location information of the user. For example, when the user is in a specific area, the reception unit can preferentially upload photos and videos related to the area. Furthermore, when the user is traveling, the reception unit can preferentially upload photos and videos of the travel destination. Furthermore, when the user is at home, the reception unit can preferentially upload photos and videos around the home. In this way, highly relevant data can be preferentially accepted by considering the geographical location information of the user. Part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that inputs the geographical location information of the user and preferentially accepts highly relevant data.

[0080] The reception unit can analyze the user's social media activity and accept related data when uploading photos and videos. The reception unit can collect data such as the post content, the number of likes, and comments in order to analyze the user's social media activity. For example, the reception unit can preferentially upload photos and videos shared by the user on social media. The reception unit can also preferentially upload photos and videos tagged by the user on social media. Furthermore, the reception unit can preferentially upload photos and videos related to accounts the user follows on social media. This allows the user's social media activity to be analyzed and related data to be efficiently accepted. A part or all of the above-mentioned processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can perform processing using an AI model that receives the user's social media activity data as an input and accepts related data.

[0081] The analysis unit can estimate the user's emotion and adjust the accuracy of the analysis based on the estimated user's emotion. The analysis unit can use, for example, facial expression recognition or voice analysis to estimate the user's emotion. For example, the analysis unit can capture the user's facial expression with a camera and estimate the emotion using an emotion estimation algorithm. The analysis unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the analysis unit can analyze the tone and speed of the user's voice and calculate an emotion score. Furthermore, the analysis unit can adjust the accuracy of the analysis based on the estimated user's emotion. For example, when the user is relaxed, a detailed analysis can be performed. Furthermore, when the user is stressed, a simple analysis can be performed. Furthermore, when the user is in a hurry, a quick analysis can be performed. As a result, by adjusting the accuracy of the analysis according to the user's emotion, a more appropriate analysis result can be provided. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate the emotion.

[0082] During the analysis, the analysis unit can track changes in facial features and evaluate long-term skin care needs. The analysis unit can, for example, track changes in wrinkles on the user's face and evaluate the need for long-term moisturizing care. The analysis unit can also track changes in the user's skin tone and evaluate the need for whitening care. Furthermore, the analysis unit can track changes in the state of the user's pores and evaluate the need for pore care. This makes it possible to evaluate long-term skin care needs by tracking changes in facial features. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that uses change data on the user's facial features as input and evaluates long-term skin care needs.

[0083] The analysis unit can identify skin care needs by taking into account the user's lifestyle habits during analysis. The analysis unit can identify skin care needs by taking into account the user's lifestyle habits (e.g., diet and sleep patterns). For example, the analysis unit can analyze the user's dietary patterns and identify skin care needs due to nutritional deficiencies. The analysis unit can also analyze the user's sleep patterns and identify skin care needs due to lack of sleep. Furthermore, the analysis unit can analyze the user's exercise habits and identify skin care needs due to lack of exercise. This makes it possible to identify more appropriate skin care needs by taking into account the user's lifestyle habits. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that inputs the user's lifestyle habit data and identifies skin care needs.

[0084] The analysis unit can estimate the user's emotion and adjust the display method of the analysis result based on the estimated user's emotion. The analysis unit can use, for example, facial expression recognition or voice analysis to estimate the user's emotion. For example, the analysis unit can take a picture of the user's facial expression with a camera and estimate the emotion using an emotion estimation algorithm. The analysis unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the analysis unit can analyze the tone and speed of the user's voice and calculate an emotion score. Furthermore, the analysis unit can adjust the display method of the analysis result based on the estimated user's emotion. For example, when the user is relaxed, detailed analysis results can be displayed. Furthermore, when the user is stressed, simple analysis results can be displayed. Furthermore, when the user is in a hurry, analysis results that focus on the main points can be displayed. As a result, by adjusting the display method of the analysis result according to the user's emotion, it is possible to display it in a way that is easy for the user to understand. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate emotions.

[0085] The analysis unit can identify skin care needs by considering the geographical environment of the user during analysis. The analysis unit can identify skin care needs by considering, for example, the geographical environment of the user (for example, climate and air pollution). For example, the analysis unit can identify the need for moisturizing care if the user lives in a dry climate. Also, the analysis unit can identify the need for oil control if the user lives in a humid climate. Furthermore, the analysis unit can identify the need for antioxidant care if the user lives in an area with high air pollution. This makes it possible to identify more appropriate skin care needs by considering the geographical environment of the user. Part or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that inputs the geographical environment data of the user and identifies skin care needs.

[0086] During the analysis, the analysis unit can identify skin care needs by referring to the user's past medical history. The analysis unit can collect data such as diagnosis results, treatment history, and allergy information to refer to the user's past medical history. For example, the analysis unit can identify the need for allergy-friendly skin care if the user has had an allergy in the past. In addition, the analysis unit can identify the need for skin care that requires specific treatment if the user has had a skin disease in the past. Furthermore, the analysis unit can identify the need for subsequent care if the user has had cosmetic surgery in the past. This makes it possible to identify more appropriate skin care needs by referring to the user's past medical history. Some or all of the above-mentioned processing in the analysis unit may be performed, for example, using AI, or may be performed without using AI. For example, the analysis unit can perform processing using an AI model that uses the user's past medical history data as input and identifies skin care needs.

[0087] The suggestion unit can estimate the user's emotion and adjust the way of expressing the proposal based on the estimated user's emotion. The suggestion unit can use, for example, facial expression recognition or voice analysis to estimate the user's emotion. For example, the suggestion unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. The suggestion unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the suggestion unit analyzes the tone and speed of the user's voice and calculates an emotion score. Furthermore, the suggestion unit can adjust the way of expressing the proposal based on the estimated user's emotion. For example, if the user is relaxed, a proposal including a detailed explanation can be made. Furthermore, if the user is stressed, a concise proposal can be made. Furthermore, if the user is in a hurry, a proposal that focuses on the main points can be made. As a result, by adjusting the way of expressing the proposal according to the user's emotion, it is possible to make a proposal that is easy for the user to understand. The estimation of the emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI, or may be performed without using AI. For example, the suggestion unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate emotions.

[0088] The suggestion unit can suggest an optimal skin care routine by referring to the user's past skin care history at the time of suggestion. The suggestion unit can collect data such as the product used, the effect, and the frequency in order to refer to the user's past skin care history. For example, the suggestion unit can suggest an optimal skin care routine based on the skin care products used by the user in the past. In addition, the suggestion unit can preferentially suggest effective products from the user's past skin care history. Furthermore, the suggestion unit can analyze the user's past skin care history and identify and suggest areas that need improvement. As a result, a more appropriate skin care routine can be suggested by referring to the user's past skin care history. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that inputs the user's past skin care history data and suggests an optimal skin care routine.

[0089] The suggestion unit can customize the skin care routine based on the user's current living situation at the time of suggestion. The suggestion unit can customize the skin care routine, for example, taking into account the user's current living situation (e.g., stress level, work schedule). For example, the suggestion unit can suggest a skin care routine that is effective in a short time when the user is busy. In addition, the suggestion unit can suggest a skin care routine that takes time when the user is relaxed. Furthermore, the suggestion unit can suggest a skin care product that is convenient to carry when the user is traveling. This allows more appropriate skin care to be provided by customizing the skin care routine based on the user's current living situation. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that uses the user's current living situation data as input and customizes the skin care routine.

[0090] The suggestion unit can estimate the user's emotion and determine the priority of suggestions based on the estimated user's emotion. The suggestion unit can use, for example, facial expression recognition or voice analysis to estimate the user's emotion. For example, the suggestion unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. The suggestion unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the suggestion unit analyzes the tone and speed of the user's voice and calculates an emotion score. Furthermore, the suggestion unit can determine the priority of suggestions based on the estimated user's emotion. For example, if the user is relaxed, detailed suggestions can be prioritized. Furthermore, if the user is stressed, concise suggestions can be prioritized. Furthermore, if the user is in a hurry, the most important suggestions can be prioritized. In this way, by determining the priority of suggestions according to the user's emotion, it is possible to provide optimal suggestions for the user. The estimation of emotions is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the suggestion unit may be performed using, for example, AI, or may be performed without using AI. For example, the suggestion unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate the emotion.

[0091] The suggestion unit can suggest an optimal skin care routine in consideration of the geographical location information of the user at the time of suggestion. The suggestion unit can suggest an optimal skin care routine in consideration of, for example, the geographical location information of the user. For example, if the user lives in a dry climate, the suggestion unit can suggest a skin care routine that prioritizes moisturizing care. In addition, if the user lives in a humid climate, the suggestion unit can suggest a skin care routine that prioritizes oil control. Furthermore, if the user lives in an area with high air pollution, the suggestion unit can suggest a skin care routine that prioritizes antioxidant care. This makes it possible to suggest a more appropriate skin care routine by considering the geographical location information of the user. Part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI, or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that inputs the geographical location information data of the user and proposes an optimal skin care routine.

[0092] At the time of suggestion, the suggestion unit can analyze the user's social media activity to suggest a skin care routine. The suggestion unit can collect data such as the content of posts, the number of likes, and comments to analyze the user's social media activity. For example, the suggestion unit can suggest an optimal skin care routine based on skin care products shared by the user on social media. The suggestion unit can also suggest a skin care routine based on products recommended by beauty influencers that the user follows on social media. Furthermore, the suggestion unit can suggest a skin care routine based on trends in beauty communities in which the user participates on social media. This allows a more appropriate skin care routine to be suggested by analyzing the user's social media activity. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI, or may be performed without using AI. For example, the suggestion unit can perform processing using an AI model that inputs the user's social media activity data and suggests an optimal skin care routine.

[0093] The protection unit can estimate the user's emotion and adjust the level of data protection based on the estimated user's emotion. The protection unit can use, for example, facial expression recognition or voice analysis to estimate the user's emotion. For example, the protection unit can capture the user's facial expression with a camera and estimate the emotion using an emotion estimation algorithm. The protection unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the protection unit can analyze the tone and speed of the user's voice and calculate an emotion score. Furthermore, the protection unit can adjust the level of data protection based on the estimated user's emotion. For example, if the user is relaxed, a standard data protection level can be applied. Furthermore, if the user is stressed, an enhanced data protection level can be applied. Furthermore, if the user is in a hurry, a quick data protection procedure can be provided. As a result, the user's privacy can be appropriately protected by adjusting the level of data protection according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI can be, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the protection unit may be performed using, for example, AI, or may be performed without using AI. For example, the protection unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate the emotion.

[0094] The protection unit can select the optimal protection method by referring to the user's past data access history when protecting data. The protection unit can collect data such as access date and time and access content in order to refer to the user's past data access history. For example, the protection unit can preferentially protect data that the user frequently accessed in the past. In addition, the protection unit can adjust the protection level for specific data from the user's past data access history. Furthermore, the protection unit can select the optimal protection method based on the type of data that the user accessed in the past. As a result, a more appropriate data protection method can be selected by referring to the user's past data access history. Part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI or may be performed without using AI. For example, the protection unit can perform processing using an AI model that inputs the user's past data access history data and selects the optimal protection method.

[0095] The protection unit can estimate the user's emotion and determine the priority of data protection based on the estimated user's emotion. The protection unit can use, for example, facial expression recognition or voice analysis to estimate the user's emotion. For example, the protection unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. The protection unit can also record the user's voice and estimate the emotion using a voice analysis technique. For example, the protection unit analyzes the tone and speed of the user's voice and calculates an emotion score. Furthermore, the protection unit can determine the priority of data protection based on the estimated user's emotion. For example, if the user is relaxed, standard data protection can be prioritized. Furthermore, if the user is stressed, protection of important data can be prioritized. Furthermore, if the user is in a hurry, quick data protection can be prioritized. As a result, the user's privacy can be appropriately protected by determining the priority of data protection according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit may input the user's facial expression and voice data to the generation AI and cause the generation AI to estimate emotions.

[0096] The protection unit can select the optimal protection method in consideration of the geographical location information of the user when protecting data. The protection unit can select the optimal protection method in consideration of, for example, the geographical location information of the user. For example, when the user is in a specific area, the protection unit can select the protection method based on the data protection regulations of the area. In addition, when the user is traveling, the protection unit can select the protection method based on the data protection regulations of the travel destination. Furthermore, when the user is at home, the protection unit can select the protection method based on the data protection regulations of the home. In this way, a more appropriate data protection method can be selected by considering the geographical location information of the user. Part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit can perform processing using an AI model that inputs the geographical location information data of the user and selects the optimal protection method.

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

[0098] The reception unit can suggest an optimal upload method when uploading a user's photos or videos by referring to the user's past skin care history. For example, the reception unit can analyze the upload methods used by the user in the past and suggest the most efficient method. The reception unit can also suggest an optimal upload method for a specific time period based on the user's past skin care history. Furthermore, the reception unit can select an optimal upload method based on the types of photos or videos the user has uploaded in the past. In this way, the optimal upload method can be provided to the user by referring to the past skin care history.

[0099] The analysis unit can identify skin care needs by taking into account the user's lifestyle habits. For example, the analysis unit can analyze the user's eating patterns and identify skin care needs due to nutritional deficiencies. The analysis unit can also analyze the user's sleep patterns and identify skin care needs due to lack of sleep. Furthermore, the analysis unit can analyze the user's exercise habits and identify skin care needs due to lack of exercise. This allows more appropriate skin care needs to be identified by taking into account the user's lifestyle habits.

[0100] The suggestion unit can estimate the user's emotion and adjust the way in which the suggestion is expressed based on the estimated user's emotion. For example, when the user is relaxed, the suggestion unit can make a suggestion including a detailed explanation. When the user is stressed, the suggestion unit can make a concise suggestion. When the user is in a hurry, the suggestion unit can make a suggestion that focuses on the main points. In this way, by adjusting the way in which the suggestion is expressed depending on the user's emotion, it is possible to make a suggestion that is easy for the user to understand.

[0101] The suggestion unit can suggest an optimal skin care routine taking into account the geographic location information of the user. For example, if the user lives in a dry climate, the suggestion unit can suggest a skin care routine that prioritizes moisturizing care. Also, if the user lives in a humid climate, the suggestion unit can suggest a skin care routine that prioritizes oil control. Furthermore, if the user lives in an area with high air pollution, the suggestion unit can suggest a skin care routine that prioritizes antioxidant care. In this way, a more appropriate skin care routine can be suggested by taking into account the geographic location information of the user.

[0102] The protection unit can estimate the user's emotion and adjust the level of data protection based on the estimated user's emotion. For example, if the user is relaxed, a standard data protection level can be applied. Also, if the user is stressed, an enhanced data protection level can be applied. Furthermore, if the user is in a hurry, a quick data protection procedure can be provided. In this way, the user's privacy can be appropriately protected by adjusting the level of data protection according to the user's emotion.

[0103] The analysis unit can identify skin care needs by referring to the user's past medical history. For example, if the user has had allergies in the past, the need for allergy-friendly skin care can be identified. Also, if the user has had a skin disease in the past, the need for skin care that requires a specific treatment can be identified. Furthermore, if the user has had cosmetic surgery in the past, the need for follow-up care can be identified. This allows for more appropriate skin care needs to be identified by referring to the user's past medical history.

[0104] The suggestion unit can suggest a skin care routine by analyzing the user's social media activity. For example, the suggestion unit can suggest an optimal skin care routine based on skin care products shared by the user on social media. The suggestion unit can also suggest a skin care routine based on products recommended by beauty influencers the user follows on social media. Furthermore, the suggestion unit can suggest a skin care routine based on trends in beauty communities in which the user participates on social media. In this way, a more appropriate skin care routine can be suggested by analyzing the user's social media activity.

[0105] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the estimated user's emotions. For example, if the user is relaxed, detailed analysis results can be displayed. If the user is stressed, simple analysis results can be displayed. If the user is in a hurry, analysis results that focus on the main points can be displayed. In this way, by adjusting the display method of the analysis results according to the user's emotions, it is possible to display the analysis results in a way that is easy for the user to understand.

[0106] The protection unit can select an optimal protection method in consideration of the geographical location information of the user when protecting data. For example, when the user is in a specific region, the protection unit can select a protection method based on the data protection regulations of the region. Also, when the user is traveling, the protection unit can select a protection method based on the data protection regulations of the travel destination. Furthermore, when the user is at home, the protection unit can select a protection method based on the data protection regulations of the home. In this way, a more appropriate data protection method can be selected by considering the geographical location information of the user.

[0107] The suggestion unit can estimate the user's emotion and determine the priority order of suggestions based on the estimated user's emotion. For example, when the user is relaxed, detailed suggestions can be prioritized. When the user is stressed, brief suggestions can be prioritized. When the user is in a hurry, the most important suggestions can be prioritized. In this way, the priority order of suggestions can be determined according to the user's emotion, thereby providing optimal suggestions for the user.

[0108] The process flow of the second embodiment will be briefly described below.

[0109] Step 1: The reception unit accepts uploads of photos and videos from the user. Photos and videos from the user may be in formats such as, but not limited to, JPEG, PNG, MP4, etc. The reception unit may, for example, enable the user to upload photos and videos from their home. The reception unit may also accept photos and videos taken from multiple angles. For example, the user is encouraged to provide images and videos taken from multiple angles, such as the front, side, and diagonal views of their face. This allows the AI ​​to perform more accurate analysis. Step 2: The analysis unit uses AI to analyze the photos and videos received by the reception unit to evaluate facial features and skin care needs. The analysis is performed using, for example, an image recognition algorithm or a machine learning model, but is not limited to such examples. For example, the analysis unit evaluates facial features (e.g., skin tone, wrinkles, blemishes, pore condition, etc.) in detail to identify the user's skin care needs. For example, if the skin is dry, it suggests that moisturizing is necessary. Step 3: The suggestion unit suggests a personalized skin care routine based on the analysis result obtained by the analysis unit. The suggestions include, but are not limited to, morning and evening skin care routines, beauty products to be used (e.g., cleanser, toner, moisturizer, sunscreen, etc.), and specific treatments (e.g., face masks and peeling once a week, etc.). For example, the suggestion unit suggests an optimal skin care routine based on the user's skin condition. This allows the virtual beauty advisor system according to the embodiment to accurately evaluate the user's skin care needs and suggest an optimal skin care routine. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using AI or may be performed without using AI. For example, the suggestion unit may make a suggestion using an AI model that inputs the analysis result obtained by the analysis unit and outputs a personalized skin care routine.

[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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0111] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) are input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may also be an AI agent. In addition, when the processes of each of the above-mentioned parts are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples.In addition, processing performed by AI including the generation AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI including the generation AI.

[0112] Furthermore, the above-described processing by the data processing system 10 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information required for processing from the data processing device 12 or an external device.

[0113] Each of the multiple elements including the above-mentioned reception unit, analysis unit, suggestion unit, and protection unit is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart device 14 and accepts uploads of photos and videos from the user. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the photos and videos using AI to evaluate facial features and skin care needs. The suggestion unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and suggests a personalized skin care routine based on the analysis results. The protection unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and encrypts the user's data and stores it safely. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

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

[0115] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0116] 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0117] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0118] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0119] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0120] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0121] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0122] The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0123] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0124] In the smart glasses 214, the 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 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0125] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0127] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may be executed 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 required for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device.

[0129] Each of the multiple elements including the above-mentioned reception unit, analysis unit, suggestion unit, and protection unit is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart glasses 214 and accepts uploads of photos and videos from the user. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the photos and videos using AI to evaluate facial features and skin care needs. The suggestion unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and suggests a personalized skin care routine based on the analysis results. The protection unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and encrypts and securely stores the user's data. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

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

[0131] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0132] 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0133] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0134] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0135] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0136] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0137] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0138] The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0139] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0140] In the headset type terminal 314, the 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 operating as the control unit 46A in accordance with the specific program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0141] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0142] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0143] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device.

[0145] Each of the multiple elements including the above-mentioned reception unit, analysis unit, suggestion unit, and protection unit is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the headset type terminal 314, and accepts uploads of photos and videos from the user. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and analyzes the photos and videos using AI to evaluate facial features and skin care needs. The suggestion unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and suggests a personalized skin care routine based on the analysis results. The protection unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and encrypts the user's data and stores it safely. The correspondence between each unit and the device and control unit is not limited to the above-mentioned example, and various changes are possible.

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

[0147] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0148] 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0149] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0150] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0151] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of a typical healthy person).

[0152] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0153] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and legs. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, and legs. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0154] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0155] The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0156] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0157] In the robot 414, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads out the specific program 60 from the storage 50, and executes the specific program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0158] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[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 control target 443 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0160] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may be executed 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 required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0162] Each of the multiple elements including the above-mentioned reception unit, analysis unit, suggestion unit, and protection unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the robot 414 and accepts uploads of photos and videos from the user. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the photos and videos using AI to evaluate facial features and skin care needs. The suggestion unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and suggests a personalized skin care routine based on the analysis results. The protection unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and encrypts the user's data and stores it safely. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0163] The emotion identification model 59 as an emotion engine may determine the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 may determine the emotion of the user according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the emotion of the robot, and the identification processing unit 290 may perform identification processing using the emotion of the robot.

[0164] FIG. 9 is a diagram showing an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from a state of mind are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0165] These emotions are distributed in the 3 o'clock direction of emotion map 400 and usually fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0166] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0167] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[0168] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this 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 positive emotion around "desire" on the response side. In other words, this 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 the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the emotion of the user. This neural network is pre-trained based on multiple learning data that are combinations of the user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in Fig. 10. Fig. 10 shows an example in which multiple emotions, "relief," "calm," and "encouraging," have similar emotion values.

[0170] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers, including computer 22.

[0171] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable computer-readable non-transitory storage medium such as a Universal Serial Bus (USB) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0172] In addition, 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 upon request from the data processing device 12.

[0173] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0174] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing a specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[0175] The hardware resource that executes the specific process may be one of these various processors, or may be a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0176] As an example of a configuration using one processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a configuration using a processor that realizes the functions of the entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0177] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The specific processes described above are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[0178] In the above example, the first to fourth embodiments are described separately, but some or all of these embodiments may be combined. The smart device 14, the smart glasses 214, the headset terminal 314, and the robot 414 are only examples, and they may be combined with each other, or may be other devices. In the above example, the first and second embodiments are described separately, but they may be combined.

[0179] The above description and illustrations are detailed descriptions of the parts related to the technology of the present disclosure, and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, function, action, and effect is an example of the configuration, function, action, and effect of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replaced with respect to the description and illustrations shown above, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the description and illustrations shown above omit explanations of technical common sense that do not require particular explanation in enabling the implementation of the technology of the present disclosure.

[0180] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, and standard was specifically and individually indicated to be incorporated by reference.

[0181] (Appendix 1) a reception unit for receiving uploads of photos and videos from users; an analysis unit that analyzes the photos and videos received by the reception unit and evaluates facial features or skin care needs; A suggestion unit that suggests a personalized skin care routine based on the analysis result obtained by the analysis unit. A system characterized by: (Appendix 2) The reception unit is Accepts user photos and videos from multiple angles 2. The system of claim 1, (Appendix 3) The analysis unit is Specific assessment of facial features to identify skin care needs 2. The system of claim 1, (Appendix 4) The suggestion unit, Suggest a morning or evening skin care routine 2. The system of claim 1, (Appendix 5) The suggestion unit, Suggest beauty product recommendations 2. The system of claim 1, (Appendix 6) The suggestion unit, Suggest specific treatments 2. The system of claim 1, (Appendix 7) The system comprises: Track your skincare progress and periodically analyze and update your skincare routine 2. The system of claim 1, (Appendix 8) The system comprises: Equipped with a protection section that securely stores user data and protects privacy 2. The system of claim 1, (Appendix 9) The reception unit is Estimate user emotions and adjust the timing of photo and video uploads based on the estimated user emotions 2. The system of claim 1, (Appendix 10) The reception unit is Analyze the user's past upload history and select the appropriate upload method 2. The system of claim 1, (Appendix 11) The reception unit is Filtering photos and videos when uploading based on the user's current environment 2. The system of claim 1, (Appendix 12) The reception unit is Infer user emotions and prioritize photos and videos to be uploaded based on the estimated user emotions 2. The system of claim 1, (Appendix 13) The reception unit is When uploading photos and videos, the app takes into account your geographic location to prioritize the most relevant data. 2. The system of claim 1, (Appendix 14) The reception unit is Analyze your social media activity and accept relevant data when you upload photos and videos 2. The system of claim 1, (Appendix 15) The analysis unit is Estimate user emotions and adjust analysis accuracy based on the estimated user emotions 2. The system of claim 1, (Appendix 16) The analysis unit is During analysis, it tracks changes in facial features and evaluates long-term skin care needs 2. The system of claim 1, (Appendix 17) The analysis unit is During analysis, the system takes into account the user's lifestyle habits to identify skin care needs 2. The system of claim 1, (Appendix 18) The analysis unit is Infer user emotions and adjust the way analysis results are displayed based on the inferred user emotions 2. The system of claim 1, (Appendix 19) The analysis unit is During analysis, the geographical location of the user is taken into account to identify skin care needs 2. The system of claim 1, (Appendix 20) The analysis unit is During analysis, the user's past medical history is referenced to identify skin care needs 2. The system of claim 1, (Appendix 21) The suggestion unit, Infer user emotions and adjust the presentation of suggestions based on the inferred user emotions 2. The system of claim 1, (Appendix 22) The suggestion unit, When making suggestions, the system refers to the user's past skin care history to suggest the optimal skin care routine. 2. The system of claim 1, (Appendix 23) The suggestion unit, At the time of suggestion, it customizes a skincare routine based on the user's current living situation. 2. The system of claim 1, (Appendix 24) The suggestion unit, Infer user sentiment and prioritize suggestions based on the inferred user sentiment 2. The system of claim 1, (Appendix 25) The suggestion unit, When making suggestions, the system takes into account the user's geographic location to recommend the optimal skincare routine. 2. The system of claim 1, (Appendix 26) The suggestion unit, When making suggestions, the app analyzes users' social media activity to provide skin care routine suggestions. 2. The system of claim 1, (Appendix 27) The protective part is Inferring user sentiment and adjusting the level of data protection based on the inferred user sentiment 2. The system of claim 1, (Appendix 28) The protective part is When protecting data, the system selects the optimal protection method by referring to the user's past data access history. 2. The system of claim 1, (Appendix 29) The protective part is Inferring user sentiment and determining priorities for data protection based on the inferred user sentiment 2. The system of claim 1, (Appendix 30) The protective part is When protecting data, the optimal protection method is selected taking into account the user's geographic location information 2. The system of claim 1, [Explanation of symbols]

[0182] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a reception unit for receiving uploads of photos and videos from users; an analysis unit that analyzes the photos and videos received by the reception unit and evaluates facial features or skin care needs; A suggestion unit that suggests a personalized skin care routine based on the analysis result obtained by the analysis unit. A system characterized by:

2. The reception unit is Accepts user photos and videos from multiple angles 2. The system of claim 1 .

3. The analysis unit is Specific assessment of facial features to identify skin care needs 2. The system of claim 1 .

4. The suggestion unit, Suggest a morning or evening skin care routine 2. The system of claim 1 .

5. The suggestion unit, Suggest beauty product recommendations 2. The system of claim 1 .

6. The suggestion unit, Suggest specific treatments 2. The system of claim 1 .

7. The system comprises: Track your skincare progress and periodically analyze and update your skincare routine 2. The system of claim 1 .

8. The system comprises: Equipped with a protection section that securely stores user data and protects privacy 2. The system of claim 1 .

Images