System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving an image captured by a mobile terminal; means for analyzing the received image to identify a species; means for obtaining information related to the identified species; means for transmitting the obtained information to the mobile terminal and a remote terminal; means for displaying the information transmitted to the mobile terminal and the remote terminal; and means for storing the displayed information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Until now, there have been limited ways for children to easily learn about plants, animals, insects, and other organisms they discover in the natural environment. Furthermore, methods for parents to support their children's learning have also been ineffective. As a result, it has been difficult for children to maintain their interest in nature, and opportunities for communication and learning between parents and children have tended to decrease. Therefore, there is a need for a system that can instantly obtain information about organisms that children discover in the natural environment and organize and store it as a digital encyclopedia. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means: A system including means for receiving images captured by a mobile device, means for analyzing the received images to identify a biological species, means for acquiring information about the identified biological species, means for transmitting the acquired information to the mobile device and a remote device, means for displaying the information transmitted to the mobile device and the remote device, means for saving the displayed information, and means for backing up the acquired information to cloud storage. Furthermore, by including means for synchronizing between the mobile device and the remote device, cooperation with parents and guardians is facilitated, promoting learning and communication between parents and children.

[0006] A "mobile terminal" is a portable electronic device that has a camera function and a communication function.

[0007] A "remote device" is another device that can communicate with a mobile device, typically a device used by a parent or guardian that has powerful processing power and a large screen.

[0008] "Means for receiving images" refers to a mechanism for transmitting image data captured by a mobile terminal to a server and for the server to receive the data.

[0009] "Means for analyzing images to identify biological species" refers to a method for processing received image data using analytical techniques such as machine learning models to identify specific organisms.

[0010] "Means of obtaining information" refers to the mechanism by which detailed information about the identified organism is collected from databases or external sources.

[0011] The "means for transmitting to the mobile terminal and the remote terminal" refers to a function for transmitting the acquired information to the mobile terminal and the remote terminal via a communication network.

[0012] "Means for displaying information" refers to a method for visualizing the transmitted information on the screen of a mobile terminal or remote terminal to inform the user.

[0013] "Means for saving information" refers to a mechanism for recording the displayed information and additional information on a mobile device, a remote device, or cloud storage.

[0014] "Cloud storage" is an online service for storing and managing data over the Internet.

[0015] A "means of synchronization" is a method for maintaining data consistency between multiple devices and ensuring that the same content is reflected. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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).

[0028] 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.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] 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.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system analyzes images taken with a mobile device, identifies the species, and collects, displays, stores, and shares related information.

[0038] Program Generation and Processing Description

[0039] Image capture and upload

[0040] 1. The user takes an image of a plant, animal, insect, etc. using a smartwatch (mobile device).

[0041] 2. The device temporarily stores the captured image data locally, and if an Internet connection is confirmed, uploads the image data to the server.

[0042] Image analysis

[0043] 3. The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[0044] 4. After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[0045] Information Return and Storage

[0046] 5. The server compiles the acquired information into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[0047] 6. The device analyzes the received data and notifies the user, including the name of the species and related information.

[0048] 7. The device saves the received information as a digital encyclopedia, and also uploads the saved information to cloud storage in the background for backup.

[0049] Cooperation with parents

[0050] 8. The device synchronizes the updated information of the digital encyclopedia with the remote device (parent's smartphone), allowing parents to check information about the creatures their child has photographed in real time.

[0051] Specific examples

[0052] Image Capture Example

[0053] 1. The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[0054] 2. The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0055] Image analysis example

[0056] 1. The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[0057] 2. The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from the database.

[0058] Information Return and Storage Examples

[0059] 1. The server sends the acquired information to the smartwatch and the parent's smartphone.

[0060] 2. The device notifies the user of the received information and saves it in the digital encyclopedia.

[0061] 3. Back up the information stored on your device to the cloud.

[0062] Examples of cooperation with parents

[0063] 1. The device synchronizes the digital encyclopedia information with the parent's smartphone.

[0064] 2. The user (parent) uses their smartphone to view information about the cabbage white butterfly photographed by their child.

[0065] This enriches children's learning experiences and promotes communication with parents.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[0069] Step 2:

[0070] A user presses the camera shutter to capture an image.

[0071] Step 3:

[0072] The device saves the captured image in temporary storage.

[0073] Step 4:

[0074] The device checks for an Internet connection, and if a connection is confirmed, uploads the captured images from temporary storage to the server.

[0075] Step 5:

[0076] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[0077] Step 6:

[0078] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[0079] Step 7:

[0080] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat, etc.) related to that organism from the database.

[0081] Step 8:

[0082] The server collates the results of the image analysis and related information and generates a data packet to send back to the user.

[0083] Step 9:

[0084] The server sends the generated data packets to the mobile device and the remote device (parent's smartphone).

[0085] Step 10:

[0086] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and a brief description.

[0087] Step 11:

[0088] The terminal stores the received biometric information and additional information in a digital encyclopedia.

[0089] Step 12:

[0090] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[0091] Step 13:

[0092] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[0093] Step 14:

[0094] The user (parent) opens the app and checks the biological information captured by their child.

[0095] Example 1

[0096] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0097] With conventional technology, there are limited means for acquiring, organizing, and storing information about plants, animals, insects, and other organisms discovered in the natural environment, making it particularly difficult for children to identify the species they discover and easily acquire and share that information. Other issues include the difficulty of storing and backing up acquired information and sharing it with parents in real time.

[0098] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0099] In this invention, the server includes means for receiving images captured by a mobile information terminal, means for analyzing the received images to identify biological species, means for retrieving information about the identified biological species from a database, means for transmitting the retrieved information to the mobile information terminal and a remote information terminal, means for displaying the information transmitted to the mobile information terminal and the remote information terminal, means for saving the displayed information in a digital picture book format, means for backing up the retrieved information to cloud storage, and means for synchronizing between the mobile information terminal and the remote information terminal. This enables consistent processing from identifying biological species to retrieving, displaying, saving, and sharing information, thereby enriching children's learning experiences and promoting communication with parents.

[0100] A "portable information terminal" is an electronic device that can be carried by a user, and is a terminal device that has functions such as image capture, data communication, and information display.

[0101] The "means for receiving images" refers to a mechanism by which the server obtains image data sent from the mobile information terminal.

[0102] The "means for analyzing images" is a mechanism that includes an algorithm that analyzes received image data using a machine learning model and identifies the species of the organism.

[0103] "Means for identifying" refers to a mechanism for identifying the biological species identified by image analysis and outputting the identification results.

[0104] "Means for obtaining data from a database" refers to a mechanism for searching and obtaining data from a database that stores detailed information and associated information about an identified biological species.

[0105] The "means for transmitting information" is a mechanism for transmitting data of the acquired organism information to the portable information terminal and the remote information terminal.

[0106] The "means for displaying information" is a mechanism for displaying the transmitted information about the living thing on the screen of the portable information terminal and the remote information terminal.

[0107] "Means for saving in digital encyclopedia format" refers to a mechanism for organizing and saving the displayed information in electronic format and storing it in a form that can be viewed later.

[0108] "Means for backing up to cloud storage" refers to a mechanism for transmitting stored information to an external cloud storage service via the Internet to ensure the safety and durability of data.

[0109] A "synchronization means" is a mechanism for matching data between a mobile information terminal and a remote information terminal and sharing information in real time.

[0110] A "server" is a central management device that accepts requests from a large number of client terminals and provides services and data in response to those requests.

[0111] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system has the function of analyzing images taken with a mobile information terminal, identifying the species, and collecting, displaying, saving, and sharing related information.

[0112] Hardware and software used

[0113] The system is implemented using the following major hardware and software:

[0114] Hardware:

[0115] 1. Personal digital assistant: A portable device capable of taking images and transmitting data, such as a smartphone or smartwatch.

[0116] 2. Server: A centralized management unit that provides high-performance data processing and storage.

[0117] 3. Remote information terminal: A device that can receive and display data, such as a parent's smartphone.

[0118] software:

[0119] 1. Camera application: An application for taking pictures on a mobile device.

[0120] 2. Image analysis library: Software that analyzes images using machine learning models such as Convolutional Neural Networks (CNNs).

[0121] 3. Database system: A database for storing information about living organisms.

[0122] 4. Cloud storage service: Online storage for backing up acquired information.

[0123] Specific Embodiments

[0124] Image capture and upload

[0125] The user (child) takes pictures of creatures they find in the natural environment using a mobile information device (e.g., a smartwatch). The images are temporarily stored on the device and then automatically uploaded to the server when an internet connection is confirmed.

[0126] Image analysis

[0127] The server uses a machine learning model (such as CNN) to analyze the image data it receives. The analysis results identify the species, and that information is then queried against a database.

[0128] Displaying and saving information

[0129] The server retrieves information about the identified species from the database and sends it as a data packet to the mobile information device and the parent's remote information device. The received information is notified to the mobile information device and saved in a digital encyclopedia format. The saved information is then backed up to cloud storage.

[0130] Sync and Share

[0131] The device synchronizes updated information from the digital encyclopedia with a remote information terminal, allowing parents to check information about the creatures their children have photographed in real time.

[0132] Specific examples

[0133] Image Capture Example

[0134] A user (child) takes a photo of a cabbage white butterfly they find in a park with their smartwatch. The device temporarily saves the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0135] Image analysis example

[0136] The server analyzes the uploaded image and identifies it as a cabbage white butterfly. The server then retrieves biological information about the butterfly (such as its name, characteristics, and feeding habits) and additional information (such as its habitat and classification) from a database.

[0137] Examples of displaying and saving information

[0138] The server sends the acquired information to the smartwatch and the parent's smartphone. The device notifies the user of the received information and saves it in a digital encyclopedia. The information saved on the device is also backed up to the cloud.

[0139] Examples of cooperation with parents

[0140] The device synchronizes the information in the digital encyclopedia with the parent's smartphone, who then uses the smartphone to view information about the cabbage white butterfly that their child photographed.

[0141] Prompt Sentence Examples

[0142] The system description can be generated by inputting the following prompt sentence into the generative AI model.

[0143] "Please explain the system's process: analyze images of the natural environment taken by a child with a smartwatch, identify and record biological species, and store the image data temporarily on the device. The image data is then analyzed using a machine learning model on the server. During this process, related information is also retrieved from a database, and ultimately the system notifies the user and guardian and stores the information in a digital encyclopedia."

[0144] This enriches children's learning experiences and promotes communication with parents.

[0145] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0146] System program processing flow

[0147] Step 1: Capture an image and save it locally

[0148] A user takes pictures of plants, animals, insects, etc. that they find in a natural environment, such as a park, using a smartwatch (personal digital assistant). When the captured image data is input into the device, the device temporarily stores the image data in local storage. Specifically, it is saved as an image file in the device's built-in memory.

[0149] Input: Image data of a living creature taken by the user with their smartwatch

[0150] Output: Image file saved in local storage

[0151] Step 2: Check your internet connection and upload images

[0152] The device automatically checks for an Internet connection. If Wi-Fi or mobile data communication is enabled, the temporarily stored image data is uploaded to the server. Specifically, the image files on the device are sent to the server using the HTTPS protocol.

[0153] Input: Image file stored in local storage

[0154] Output: Image data sent to the server

[0155] Step 3: Receiving and saving image data

[0156] The server receives the image data sent from the terminal and temporarily stores it. The server stores the received image data as is in a database or file system.

[0157] Input: Image data sent from the device

[0158] Output: Image data stored on the server

[0159] Step 4: Image analysis using machine learning models

[0160] The server analyzes the stored image data using a machine learning model (e.g., a convolutional neural network) to identify the biological species. Specifically, the image data is received as input, the machine learning model analyzes the image, and outputs the identified biological species.

[0161] Input: Image data stored on the server

[0162] Output: Identified species

[0163] Step 5: Get information

[0164] Based on the identified species, the server retrieves related biological information and additional information (such as name, characteristics, and habitat) from the database and executes a database query to extract the required information.

[0165] Input: Identified species

[0166] Output: Detailed information about the organism retrieved from the database

[0167] Step 6: Packaging and sending information

[0168] The server compiles the acquired information into data packets and sends them to the mobile information terminal and remote information terminal. The data packets contain information such as the organism's name, characteristics, and habitat.

[0169] Input: Detailed information about the organism retrieved from the database

[0170] Output: Data packets sent to the mobile device and remote device

[0171] Step 7: Notification and display of information

[0172] The terminal analyzes the data received from the server and notifies the user, who then sees the name of the species and related information on the terminal's display.

[0173] Input: Data packet sent by the server

[0174] Output: Information about the creature displayed on the device's display

[0175] Step 8: Save as a digital encyclopedia

[0176] The device organizes the information it receives in a digital encyclopedia format and saves it in local storage, where it can be referenced later.

[0177] Input: Data packet received from the server

[0178] Output: Information saved in a digital encyclopedia format

[0179] Step 9: Back up to cloud storage

[0180] Back up the digital encyclopedia information stored on your device to cloud storage. Use cloud storage services to send and store data via the Internet.

[0181] Input: Information stored in a digital encyclopedia format

[0182] Output: Information backed up to cloud storage

[0183] Step 10: Sync information with parents

[0184] The device synchronizes updated information about the digital encyclopedia with a remote information device (parent's smartphone). The synchronized data is displayed in real time on the parent's device, allowing the parent to check information about the creatures their child has photographed.

[0185] Input: Digital encyclopedia update information

[0186] Output: Information about the creature displayed on the parent's device

[0187] The above is the specific processing flow of this system.

[0188] (Application example 1)

[0189] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0190] Conventional food delivery services lacked a means for users to easily obtain detailed information about the food and ingredients they purchased, particularly information about their nutritional value, origin, and cultivation method. This meant that users could not fully trust the background information about the ingredients provided, which sometimes led to anxiety when making food choices. Furthermore, the process of efficiently collecting and saving detailed information about ingredients and using it for future orders was cumbersome.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0192] In this invention, the server includes means for receiving images taken by a mobile device, means for analyzing the received images to identify objects, and means for acquiring information about the identified objects, allowing users to easily acquire and save detailed information about foods and ingredients and use it for their next food delivery order.

[0193] A "mobile terminal" is a portable communication device, such as a smartphone or tablet, that can capture and receive image data.

[0194] "Means for receiving" refers to the process of transmitting image data captured by a mobile terminal to a server and having the server receive the data.

[0195] "Means for analyzing and identifying objects" refers to the process of analyzing received image data using a machine learning model to identify objects appearing in the image.

[0196] "Means for obtaining information" refers to the process of gathering detailed information about the identified object from a database.

[0197] "Means for transmitting" refers to the process of transmitting the acquired information to the mobile terminal and the remote terminal.

[0198] "Means for displaying" refers to the process of displaying the transmitted information on the screens of the mobile terminal and the remote terminal.

[0199] "Means of storage" refers to the process of saving the displayed information in a digital encyclopedia or cloud storage.

[0200] "Cloud storage backup method" refers to the process of automatically storing stored information in remote storage via the Internet.

[0201] "Means for synchronizing" refers to the process of matching up-to-date information between the mobile device and the remote device.

[0202] "Objects" refer to items that are the subject of identification, such as plants, animals, food, and ingredients, contained in image data.

[0203] "Detailed information" refers to attribute information related to the identified object, such as its name, nutritional value, place of origin, and cultivation method.

[0204] The embodiment of the present invention is a system including a mobile terminal, a remote terminal, a server, a machine learning model, and cloud storage, the details of which are described below.

[0205] Hardware and software used

[0206] Hardware

[0207] Mobile device: A smartphone (iOS / ANDROID (registered trademark) is used. The device allows the user to take pictures of food and ingredients and send the data to the server.

[0208] Server: An AWS (registered trademark) EC2 instance is used to receive and analyze data.

[0209] Cloud storage: Use AWS S3 to back up the information you retrieve.

[0210] software

[0211] Image analysis: Using machine learning models (e.g., YOLO, SSD), the received image data is analyzed to identify the type of object (plant, animal, food, ingredient).

[0212] Database: AWS DynamoDB is used to obtain detailed information about the identified objects (such as name, nutritional value, origin, and cultivation method).

[0213] System Configuration and Operation

[0214] 1. Image capture and upload

[0215] A user takes an image of food or ingredients using a mobile device, which temporarily stores the captured image data locally and uploads it to a server when an internet connection is confirmed.

[0216] 2. Image Analysis

[0217] The server analyzes the received image data using machine learning models (YOLO, SSD) to identify objects (food or ingredients) contained in the image. After identifying the object, it retrieves detailed information about it from AWS DynamoDB.

[0218] 3. Return and Display of Information

[0219] The server assembles the acquired information into data packets and transmits them to the mobile and remote terminals. The mobile and remote terminals analyze the received information and notify the user. This information is displayed on the screens of the mobile and remote terminals.

[0220] 4. Information storage and backup

[0221] The mobile device saves the displayed information as a digital encyclopedia, and the saved information is backed up to AWS S3 in the background.

[0222] 5. Synchronization

[0223] By synchronizing the latest information between mobile and remote devices, users can access information consistently from any device.

[0224] Examples of specific examples and prompt usage

[0225] Specific examples

[0226] The user takes a picture of the tomatoes they purchased with their smartphone.

[0227] The smartphone uploads the images to the AWS cloud.

[0228] The machine learning model identifies it as a tomato and retrieves information about its origin, cultivation method, and nutritional value from a database.

[0229] This information is communicated to the user and stored in their profile within the food delivery service.

[0230] Prompt Sentence Examples

[0231] "Please identify the vegetable in this image and provide details about its origin and nutritional value."

[0232] In this way, by linking mobile devices, remote devices, servers, and cloud storage, users can easily obtain and save detailed information about food and ingredients, and use it the next time they order.

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1:

[0235] A user uses a smartphone to take a picture of food or ingredients. At this time, the smartphone's camera application is opened and the user presses the button to take a photo, generating image data. Input: Image taken by the user. Output: Image data saved in the smartphone's local storage.

[0236] Step 2:

[0237] The device checks for an Internet connection and uploads the captured image data to the server. Specifically, it reads the image data from local storage and sends it to the server using an HTTP request. Input: Image data saved in local storage. Output: Image data uploaded to the server.

[0238] Step 3:

[0239] The server analyzes the received image data and identifies the object. Here, a machine learning model (e.g., YOLO, SSD) is used to identify the object (food or ingredient) in the image. Input: Image data uploaded to the server. Output: Identification information of the identified object.

[0240] Step 4:

[0241] The server retrieves detailed information about the identified object from the database. It executes a database query to collect information such as the name of the food or ingredient, its nutritional value, origin, and cultivation method. Input: Identification information of the identified object. Output: Detailed information about the object retrieved from the database.

[0242] Step 5:

[0243] The server compiles the obtained detailed information into a data packet and sends it to the mobile device and remote device. Specifically, it generates the data packet in JSON format and returns it to the device as an HTTP response. Input: Detailed information obtained from the database. Output: Detailed information sent to the mobile device and remote device.

[0244] Step 6:

[0245] The device analyzes the details received and notifies the user. It uses the smartphone's notification system to display the details as a pop-up notification or in-app notification. Input: Details sent from the server. Output: Details notified to the user.

[0246] Step 7:

[0247] The device saves the displayed information as a digital encyclopedia and backs it up to cloud storage. The information is saved in local storage and then uploaded to AWS S3 for backup. Input: Detailed information notified to the user. Output: Detailed information saved in local storage and cloud storage.

[0248] Step 8:

[0249] The device synchronizes between the mobile device and the remote device. Sends the latest information to the remote device to keep the data consistent. Input: Details stored in local storage. Output: Details synchronized to the remote device.

[0250] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0251] This invention is a system that acquires information about plants, animals, insects, and other living things that children discover in the natural environment, and by combining it with an emotion engine, recognizes the user's emotions and provides optimal information based on their reaction. This system analyzes images taken by a mobile device, identifies the species of living things, and acquires, displays, saves, and shares related information, and also provides information that takes the user's emotions into consideration.

[0252] Program Generation and Processing Description

[0253] Image capture and upload

[0254] The user takes pictures of plants, animals, insects, etc. using a smartwatch (mobile device).

[0255] The device temporarily stores the captured image data locally, and when an Internet connection is confirmed, the image data is uploaded to the server.

[0256] Image analysis

[0257] The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[0258] After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[0259] Emotion recognition and information provision

[0260] The emotion engine installed in the device analyzes the user's facial expressions and voice to recognize their emotions. Emotion recognition is performed using a camera and microphone.

[0261] The server takes into account the emotional information it obtains and adjusts the content and format of the information displayed. For example, if the user shows interest, it provides detailed information, and if the user is anxious, it complements the explanation with gentler words.

[0262] The server compiles the information reflecting emotions into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[0263] Information Return and Storage

[0264] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and related information.

[0265] The information received by the device is saved as a digital encyclopedia, and the saved information is also uploaded to cloud storage in the background for backup.

[0266] Cooperation with parents

[0267] The device synchronizes updates to the digital encyclopedia with a remote device (parent's smartphone), allowing parents to check information about the creatures their children have photographed in real time.

[0268] The device (parent's smartphone) will be able to check changes in the child's emotions, including the results of the emotion engine's recognition.

[0269] Specific examples

[0270] Image Capture Example

[0271] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[0272] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0273] Image analysis example

[0274] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[0275] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[0276] Emotion Recognition Example

[0277] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[0278] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[0279] Information Return and Storage Examples

[0280] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[0281] The terminal notifies the user of the received information and stores it in a digital picture book.

[0282] The information stored on the device is also backed up to the cloud.

[0283] Examples of cooperation with parents

[0284] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[0285] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[0286] This system not only enriches children's learning experiences and promotes communication with parents, but also makes it possible to provide information that takes children's emotions into consideration.

[0287] The processing flow will be explained below.

[0288] Step 1:

[0289] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[0290] Step 2:

[0291] A user presses the camera shutter to capture an image.

[0292] Step 3:

[0293] The device saves the captured image in temporary storage.

[0294] Step 4:

[0295] The device checks for an internet connection.

[0296] Step 5:

[0297] If the device is connected to the Internet, the captured images are uploaded from temporary storage to a server.

[0298] Step 6:

[0299] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[0300] Step 7:

[0301] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[0302] Step 8:

[0303] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat) associated with that organism from the database.

[0304] Step 9:

[0305] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by an emotion engine.

[0306] Step 10:

[0307] The emotion engine recognizes the user's emotions (e.g., surprise, joy, interest, anxiety).

[0308] Step 11:

[0309] The server receives the recognized emotion information and adjusts the content and presentation method of the information to be displayed according to the user's emotion.

[0310] Step 12:

[0311] The server assembles the adjusted information into data packets and sends them to the mobile device and remote device (parent's smartphone).

[0312] Step 13:

[0313] The device (smartwatch) analyzes the received data and notifies the user, including the species name, a brief description, and complementary information based on the emotion.

[0314] Step 14:

[0315] The device stores the received biometric information, additional information, and complementary information according to emotions in a digital encyclopedia.

[0316] Step 15:

[0317] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[0318] Step 16:

[0319] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[0320] Step 17:

[0321] The user (parent) opens the app and checks the biological information captured by their child along with the recognized emotional changes.

[0322] In this way, the combined emotion engine optimizes children's learning experiences according to their emotional responses and also facilitates communication with parents.

[0323] Example 2

[0324] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0325] Previous systems simply collected information about organisms found in the natural environment, but did not provide information that reflected the user's feelings. Furthermore, saving and sharing information was time-consuming, which sometimes hindered smooth communication between parents and children. This posed a risk of reducing children's motivation to learn, and also led to issues such as the quality of information provided not being sufficiently improved.

[0326] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0327] In this invention, the server includes: means for receiving an image taken by a user using a mobile terminal; means for analyzing the received image and identifying a biological species using a machine learning model; and means for acquiring information about the identified biological species from a database.

[0328] The system has an emotion engine that recognizes the user's emotions, and includes means for analyzing the user's facial expressions and voice, means for adjusting the content and format of the information to be provided based on the emotion information, means for transmitting the acquired information to the mobile terminal and the remote terminal, means for displaying the information transmitted to the mobile terminal and the remote terminal, and means for saving the displayed information. This makes it possible to provide appropriate information according to the user's emotions, and makes it easy to share and manage saved information, which facilitates communication between parents and children and increases motivation to learn.

[0329] A "mobile terminal" is a portable electronic device, such as a smartphone or smartwatch, that is capable of sending and receiving data and running applications.

[0330] "Means for receiving images" refers to a function that allows the server to receive image data captured by the mobile terminal.

[0331] "Means for analyzing images" refers to algorithms or software used to process image data and determine its content.

[0332] A "machine learning model" is a statistical model of an algorithm that learns from data and makes inferences or classifications.

[0333] "Means for identifying biological species" refers to technology for determining the type of organism from analyzed image data.

[0334] A "database" is a structured collection of digital information for efficient storage and management of information.

[0335] "Means of obtaining information" refers to the processes and techniques used to extract the necessary data from the database.

[0336] An "emotion engine" is a software or hardware component that analyzes and recognizes a user's emotions.

[0337] "Means for analyzing facial expressions and voice" refers to technology that identifies emotions from facial expressions captured by a camera and voice captured by a microphone.

[0338] "Means for adjusting the content and format of information" is a function that optimizes the data provided based on the user's emotions.

[0339] A "data packet" is a unit for dividing digital information into small pieces and sending and receiving it over a communication network.

[0340] "Means of storage" refers to the technology for recording acquired information in local storage or cloud storage.

[0341] "Means of synchronization" refers to technology that automatically updates and shares information to maintain data consistency across multiple devices.

[0342] This invention is a system that acquires information on plants, animals, insects, etc. that users discover in the natural environment and combines it with an emotion engine to provide optimal information that takes the user's emotions into consideration. This system analyzes images taken with a mobile device, identifies the species, and acquires, displays, saves, and shares related information.

[0343] Hardware and software used

[0344] The main hardware includes smartphones and smartwatches. These mobile devices are used for photography and emotion recognition, and communicate with a server via an internet connection. The server is responsible for communication, data analysis, and database management, and utilizes cloud storage for backing up and synchronizing information.

[0345] Specific data processing and calculation methods

[0346] Image capture and upload

[0347] The user uses the smartwatch camera to take pictures of plants and animals.

[0348] The device stores the image data locally and uploads it to the server once an internet connection is confirmed.

[0349] Image analysis

[0350] The image data received by the server is analyzed using machine learning models such as Convolutional Neural Networks (CNNs). During the analysis process, image features are extracted and the biological species is identified.

[0351] The server retrieves information about the identified species from a database, including its name, characteristics, and habitat.

[0352] Emotion recognition and information provision

[0353] The device's built-in camera and microphone are used to capture the user's facial expressions and voice.

[0354] The device uses an emotion engine to analyze the captured data and identify the user's emotion.

[0355] The server adjusts the content and format of the information it provides based on emotional information to generate optimal information.

[0356] Information Return and Storage

[0357] The information generated by the server is compiled into data packets and sent to the mobile device and remote device (parent's smartphone).

[0358] The device notifies the user of the received information, saves it in a digital encyclopedia, and also uploads the saved information to cloud storage.

[0359] Cooperation with parents

[0360] The device synchronizes updated information from the digital encyclopedia with a remote device, allowing parents to check their child's activities in real time. It also provides information, including emotion recognition results.

[0361] Specific examples

[0362] Image Capture Example

[0363] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[0364] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0365] Image analysis example

[0366] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[0367] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[0368] Emotion Recognition Example

[0369] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[0370] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[0371] Information Return and Storage Examples

[0372] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[0373] The terminal notifies the user of the received information and stores it in a digital picture book.

[0374] The information stored on the device is also backed up to the cloud.

[0375] Examples of cooperation with parents

[0376] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[0377] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[0378] This will enrich children's learning experiences, promote communication between parents and children, and also make it possible to provide information that takes children's emotions into consideration.

[0379] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0380] Step 1:

[0381] Image capture

[0382] Input: Plants, animals, and other objects that the user discovers in the natural environment.

[0383] How it works: A user taps the device screen to capture an image of an object using the smartwatch camera.

[0384] Output: Image data temporarily stored on the smartwatch.

[0385] Step 2:

[0386] Local storage

[0387] Input: Image data captured by the user.

[0388] How it works: The device saves the captured image data to temporary storage on the smartwatch. This process takes place within a few seconds.

[0389] Output: Image data stored in the device's local storage.

[0390] Step 3:

[0391] Image upload

[0392] Input: Image data stored on the smartwatch.

[0393] What it does: The device checks for an internet connection and, if one is available, uploads the image data to the server. It also checks for a Wi-Fi or mobile data connection and sends the data securely.

[0394] Output: Image data transferred to the server.

[0395] Step 4:

[0396] Image data reception

[0397] Input: Image data sent from the device.

[0398] Operation: The server receives the image data and saves it in the specified directory.

[0399] Output: Image data stored on the server.

[0400] Step 5:

[0401] Species identification

[0402] Input: Image data stored on the server.

[0403] How it works: The server analyzes images using machine learning models (e.g., convolutional neural networks for image classification). During the analysis, image features are extracted and the species is identified.

[0404] Output: Identified species.

[0405] Step 6:

[0406] Related information acquisition

[0407] Input: Identified species.

[0408] How it works: The server accesses a database to retrieve detailed information about the organism (e.g., name, characteristics, habitat, etc.) using an SQL query.

[0409] Output: Information about the organism retrieved.

[0410] Step 7:

[0411] Emotional Data Capture

[0412] Input: User's facial expressions and voice.

[0413] How it works: The device uses its camera and microphone to capture the user's facial and voice data.

[0414] Output: User's facial expression and voice data.

[0415] Step 8:

[0416] Emotion analysis

[0417] Input: Captured user facial and voice data.

[0418] How it works: The device uses an emotion engine to analyze the captured data and recognize the user's emotions, determining whether the user is surprised, excited, anxious, etc.

[0419] Output: User's emotional information.

[0420] Step 9:

[0421] Providing optimal information

[0422] Input: Information about the identified organism and user's emotion information.

[0423] How it works: The server adjusts the content and format of the information it provides based on the emotional information, generating information that best suits the user's state. For example, it changes the depth of information depending on whether a detailed explanation is required or not.

[0424] Output: The adjusted information.

[0425] Step 10:

[0426] Data packet generation and transmission

[0427] Input: Reconciled information.

[0428] How it works: The server packages the tailored information into data packets and sends them to the mobile and remote devices. The data is sent using the HTTP protocol.

[0429] Output: Data packets sent to the mobile and remote devices.

[0430] Step 11:

[0431] Notification and Retention

[0432] Input: Data packets sent to mobile and remote devices.

[0433] Operation: The device analyzes the received data and notifies the user. The notification includes the name of the species and related information. The received information is also saved in local storage as a digital encyclopedia, and is backed up to cloud storage in the background.

[0434] Output: Notification to the user and data backed up to the cloud.

[0435] Step 12:

[0436] Data Synchronization

[0437] Input: Data from local storage and cloud storage.

[0438] How it works: The device synchronizes the updated information of the digital encyclopedia with the remote device. The latest digital encyclopedia data is uploaded via the cloud server, and the parent's smartphone app retrieves it.

[0439] Output: Data synchronized to the remote device.

[0440] Step 13:

[0441] Checking for emotional changes

[0442] Input: Synchronized data and emotion recognition results.

[0443] Operation: The device (parent's smartphone) displays the emotion engine's recognition results, allowing parents to check their child's emotional changes. The emotion recognition results are included in the information sent to the parent's smartphone app.

[0444] Output: Emotional change information that can be checked by parents.

[0445] (Application example 2)

[0446] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0447] The present invention aims to enrich educational experiences by quickly obtaining information about organisms that children discover in natural environments, educational facilities, etc., and by providing appropriate information that responds to the child's emotions. Conventional technologies can identify organisms and provide information, but do not provide information that takes the user's emotions into consideration, making it difficult to flexibly respond to children's interests and level of understanding. Therefore, there is a need for an improved user experience and more effective educational support.

[0448] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving images taken by a mobile terminal, means for analyzing the received images to identify the biological species, means for acquiring information about the identified biological species, means for analyzing the user's emotions using an emotion engine, and means for dynamically adjusting information based on the user's emotions. This makes it possible to quickly identify the biological species based on images taken by a child and provide information that corresponds to the child's emotions.

[0449] A "mobile device" is a portable electronic device such as a smartphone or tablet.

[0450] The "means for receiving images" is a function for transferring captured image data from the mobile terminal to the server and receiving the data.

[0451] "Means for analyzing images" refers to a function that processes received image data using algorithms or machine learning models to analyze its contents.

[0452] "Means for identifying biological species" refers to the function of identifying specific biological species such as plants, animals, insects, etc. from the contents of analyzed image data.

[0453] "Means for obtaining information" refers to a function for searching and obtaining detailed information about the identified biological species from a database, etc.

[0454] The "means for transmitting information" is a function for transferring acquired information to the mobile terminal and the remote terminal.

[0455] The "means for displaying information" is a function for displaying the transmitted information on the display of the mobile terminal or the remote terminal.

[0456] "Means for saving information" refers to a function for saving the displayed information in an internal memory or an external storage device.

[0457] An "emotion engine" is software and hardware that analyzes the user's facial expressions and voice and recognizes their emotions.

[0458] The "means for analyzing emotions" is a function that analyzes the user's emotions using an emotion engine.

[0459] The "means for adjusting information" is a function that dynamically changes the content and format of information according to the user's emotions.

[0460] "Cloud storage" is an online data storage service accessible via the Internet.

[0461] "Means for synchronizing" refers to a function for matching data between multiple terminals in real time or periodically.

[0462] This invention is a system that quickly acquires information about creatures that children discover in the natural environment or educational facilities, and provides appropriate information according to the children's emotions. Specific embodiments for carrying out this invention will be described below.

[0463] Hardware and Software Configuration

[0464] Hardware used

[0465] Mobile Device: A portable electronic device such as smart glasses or a smartphone.

[0466] Remote device: A smartphone or tablet used by a parent or guardian.

[0467] Server: A central computer system for image analysis, sentiment analysis, and information provision.

[0468] Software used

[0469] Image processing: Image analysis using OpenCV.

[0470] Emotion Recognition: Emotion recognition libraries (e.g., FER).

[0471] Machine learning model: Convolutional Neural Network (CNN) used to identify biological species.

[0472] Backend: A web framework such as Flask or Django for sending, receiving, and processing information.

[0473] Cloud storage: Online data storage services such as Amazon S3.

[0474] Database: A database system that manages information, such as MongoDB or MySQL (registered trademark).

[0475] Data processing and calculation

[0476] Image Capture

[0477] Images of living organisms are taken using a mobile device, and the captured image data is saved locally.

[0478] Image upload

[0479] Once a Wi-Fi connection is confirmed, the captured image data is uploaded to the server, where it is stored.

[0480] Image analysis

[0481] The server analyzes the images using machine learning models to identify the species, using a Convolutional Neural Network (CNN) for highly accurate image recognition.

[0482] emotion recognition

[0483] The camera and microphone on the mobile device are used to capture the user's facial expressions and voice, and emotion recognition software (e.g., FER) is used to recognize the user's emotions.

[0484] Information Acquisition and Display

[0485] The server retrieves related information from the database based on the species identification results. This information is formatted in an optimal way based on the user's emotions and sent to mobile and remote devices. The information is displayed on the device and, if necessary, saved in a digital encyclopedia or cloud storage.

[0486] Specific examples

[0487] Photographing cabbage white butterflies in the park

[0488] 1. A child finds a cabbage white butterfly in the park and takes a picture of it with smart glasses.

[0489] 2. The captured images are uploaded from the smart glasses to the server.

[0490] 3. The server performs image analysis and identifies it as a cabbage white butterfly.

[0491] 4. The robot recognizes the user's (child's) emotions from their facial expressions and voice and determines that they are excited.

[0492] 5. The server formats the detailed information and sends it to the smart glasses and the parent's smartphone.

[0493] 6. The transmitted information will be displayed on the device and also saved in the digital encyclopedia.

[0494] Prompt Sentence Examples

[0495] As an example, you can input the following prompts to a generative AI model:

[0496] "Please tell me how to provide information in response to the excitement and emotions of children who take photos of pandas."

[0497] As described above, this system makes it possible to quickly and appropriately provide information about organisms that children are interested in. Furthermore, cooperation with parents will enrich the educational experience for children.

[0498] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0499] Step 1:

[0500] The user (child) takes a photo of a target organism in a natural environment or an educational facility using the camera in the smart glasses. The user's actions include capturing and saving the image of the organism. The input is the image of the organism, and the output is the locally saved image data.

[0501] Step 2:

[0502] When the device (smart glasses) confirms an Internet connection, it uploads the captured image data to the server. The input is the locally stored image data, and the output is the image data transferred to the server.

[0503] Step 3:

[0504] The server receives the uploaded image data and analyzes the image using a Convolutional Neural Network (CNN). This analysis identifies the biological species. The input is the image data transferred to the server, and the output is the identified biological species information.

[0505] Step 4:

[0506] The server retrieves detailed information about the identified species from the database. The input is the identified species information, and the output is detailed information about the species (such as name, characteristics, habitat, etc.).

[0507] Step 5:

[0508] If the user is interested after taking a photo, the device (smart glasses) will capture the user's facial expressions and voice using a camera and microphone. An emotion engine will analyze this data and identify the user's emotions. The input is the user's facial expressions and voice data, and the output is the identified user's emotions (excitement, interest, etc.).

[0509] Step 6:

[0510] The server considers the user's emotional information and adjusts the information about the species to an appropriate format depending on the emotion. For example, if the user is excited, more detailed information is provided. The input is the user's emotional information and detailed information about the species, and the output is information adjusted according to the emotion.

[0511] Step 7:

[0512] The server compiles the adjusted information about the species into a data packet and sends it to a mobile device (smart glasses) and a remote device (parent's smartphone). The input is the adjusted information, and the output is the data sent to the mobile device and the remote device.

[0513] Step 8:

[0514] The devices (smart glasses and parent's smartphone) analyze and display the received data appropriately. The data is displayed as notifications and detailed information to the user, and the child's activities and emotional information to the parent. The input is the transmitted data, and the output is the information displayed to the user and parent.

[0515] Step 9:

[0516] The device saves the displayed information in a digital encyclopedia and also backs it up to cloud storage. The input is the displayed information, and the output is data stored locally and in the cloud.

[0517] Step 10:

[0518] The terminal synchronizes the digital picture book information and the user's emotional information with the remote terminal (parent's smartphone). The input is the update information and emotional information of the digital picture book, and the output is the synchronization result with the remote terminal.

[0519] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0520] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) 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 voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0521] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0522] [Second embodiment]

[0523] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0524] 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.

[0525] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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).

[0526] 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.

[0527] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0528] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0529] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0530] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0531] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0532] 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.

[0533] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0534] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0535] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system analyzes images taken with a mobile device, identifies the species, and collects, displays, stores, and shares related information.

[0536] Program Generation and Processing Description

[0537] Image capture and upload

[0538] 1. The user takes an image of a plant, animal, insect, etc. using a smartwatch (mobile device).

[0539] 2. The device temporarily stores the captured image data locally, and if an Internet connection is confirmed, uploads the image data to the server.

[0540] Image analysis

[0541] 3. The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[0542] 4. After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[0543] Information Return and Storage

[0544] 5. The server compiles the acquired information into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[0545] 6. The device analyzes the received data and notifies the user, including the name of the species and related information.

[0546] 7. The device saves the received information as a digital encyclopedia, and also uploads the saved information to cloud storage in the background for backup.

[0547] Cooperation with parents

[0548] 8. The device synchronizes the updated information of the digital encyclopedia with the remote device (parent's smartphone), allowing parents to check information about the creatures their child has photographed in real time.

[0549] Specific examples

[0550] Image Capture Example

[0551] 1. The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[0552] 2. The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0553] Image analysis example

[0554] 1. The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[0555] 2. The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from the database.

[0556] Information Return and Storage Examples

[0557] 1. The server sends the acquired information to the smartwatch and the parent's smartphone.

[0558] 2. The device notifies the user of the received information and saves it in the digital encyclopedia.

[0559] 3. Back up the information stored on your device to the cloud.

[0560] Examples of cooperation with parents

[0561] 1. The device synchronizes the digital encyclopedia information with the parent's smartphone.

[0562] 2. The user (parent) uses their smartphone to view information about the cabbage white butterfly photographed by their child.

[0563] This enriches children's learning experiences and promotes communication with parents.

[0564] The processing flow will be explained below.

[0565] Step 1:

[0566] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[0567] Step 2:

[0568] A user presses the camera shutter to capture an image.

[0569] Step 3:

[0570] The device saves the captured image in temporary storage.

[0571] Step 4:

[0572] The device checks for an Internet connection, and if a connection is confirmed, uploads the captured images from temporary storage to the server.

[0573] Step 5:

[0574] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[0575] Step 6:

[0576] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[0577] Step 7:

[0578] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat, etc.) related to that organism from the database.

[0579] Step 8:

[0580] The server collates the results of the image analysis and related information and generates a data packet to send back to the user.

[0581] Step 9:

[0582] The server sends the generated data packets to the mobile device and the remote device (parent's smartphone).

[0583] Step 10:

[0584] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and a brief description.

[0585] Step 11:

[0586] The terminal stores the received biometric information and additional information in a digital encyclopedia.

[0587] Step 12:

[0588] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[0589] Step 13:

[0590] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[0591] Step 14:

[0592] The user (parent) opens the app and checks the biological information captured by their child.

[0593] Example 1

[0594] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0595] With conventional technology, there are limited means for acquiring, organizing, and storing information about plants, animals, insects, and other organisms discovered in the natural environment, making it particularly difficult for children to identify the species they discover and easily acquire and share that information. Other issues include the difficulty of storing and backing up acquired information and sharing it with parents in real time.

[0596] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0597] In this invention, the server includes means for receiving images captured by a mobile information terminal, means for analyzing the received images to identify biological species, means for retrieving information about the identified biological species from a database, means for transmitting the retrieved information to the mobile information terminal and a remote information terminal, means for displaying the information transmitted to the mobile information terminal and the remote information terminal, means for saving the displayed information in a digital picture book format, means for backing up the retrieved information to cloud storage, and means for synchronizing between the mobile information terminal and the remote information terminal. This enables consistent processing from identifying biological species to retrieving, displaying, saving, and sharing information, thereby enriching children's learning experiences and promoting communication with parents.

[0598] A "portable information terminal" is an electronic device that can be carried by a user, and is a terminal device that has functions such as image capture, data communication, and information display.

[0599] The "means for receiving images" refers to a mechanism by which the server obtains image data sent from the mobile information terminal.

[0600] The "means for analyzing images" is a mechanism that includes an algorithm that analyzes received image data using a machine learning model and identifies the species of the organism.

[0601] "Means for identifying" refers to a mechanism for identifying the biological species identified by image analysis and outputting the identification results.

[0602] "Means for obtaining data from a database" refers to a mechanism for searching and obtaining data from a database that stores detailed information and associated information about an identified biological species.

[0603] The "means for transmitting information" is a mechanism for transmitting data of the acquired organism information to the portable information terminal and the remote information terminal.

[0604] The "means for displaying information" is a mechanism for displaying the transmitted information about the living thing on the screen of the portable information terminal and the remote information terminal.

[0605] "Means for saving in digital encyclopedia format" refers to a mechanism for organizing and saving the displayed information in electronic format and storing it in a form that can be viewed later.

[0606] "Means for backing up to cloud storage" refers to a mechanism for transmitting stored information to an external cloud storage service via the Internet to ensure the safety and durability of data.

[0607] A "synchronization means" is a mechanism for matching data between a mobile information terminal and a remote information terminal and sharing information in real time.

[0608] A "server" is a central management device that accepts requests from a large number of client terminals and provides services and data in response to those requests.

[0609] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system has the function of analyzing images taken with a mobile information terminal, identifying the species, and collecting, displaying, saving, and sharing related information.

[0610] Hardware and software used

[0611] The system is implemented using the following major hardware and software:

[0612] Hardware:

[0613] 1. Personal digital assistant: A portable device capable of taking images and transmitting data, such as a smartphone or smartwatch.

[0614] 2. Server: A centralized management unit that provides high-performance data processing and storage.

[0615] 3. Remote information terminal: A device that can receive and display data, such as a parent's smartphone.

[0616] software:

[0617] 1. Camera application: An application for taking pictures on a mobile device.

[0618] 2. Image analysis library: Software that analyzes images using machine learning models such as Convolutional Neural Networks (CNNs).

[0619] 3. Database system: A database for storing information about living organisms.

[0620] 4. Cloud storage service: Online storage for backing up acquired information.

[0621] Specific Embodiments

[0622] Image capture and upload

[0623] The user (child) takes pictures of creatures they find in the natural environment using a mobile information device (e.g., a smartwatch). The images are temporarily stored on the device and then automatically uploaded to the server when an internet connection is confirmed.

[0624] Image analysis

[0625] The server uses a machine learning model (such as CNN) to analyze the image data it receives. The analysis results identify the species, and that information is then queried against a database.

[0626] Displaying and saving information

[0627] The server retrieves information about the identified species from the database and sends it as a data packet to the mobile information device and the parent's remote information device. The received information is notified to the mobile information device and saved in a digital encyclopedia format. The saved information is then backed up to cloud storage.

[0628] Sync and Share

[0629] The device synchronizes updated information from the digital encyclopedia with a remote information terminal, allowing parents to check information about the creatures their children have photographed in real time.

[0630] Specific examples

[0631] Image Capture Example

[0632] A user (child) takes a photo of a cabbage white butterfly they find in a park with their smartwatch. The device temporarily saves the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0633] Image analysis example

[0634] The server analyzes the uploaded image and identifies it as a cabbage white butterfly. The server then retrieves biological information about the butterfly (such as its name, characteristics, and feeding habits) and additional information (such as its habitat and classification) from a database.

[0635] Examples of displaying and saving information

[0636] The server sends the acquired information to the smartwatch and the parent's smartphone. The device notifies the user of the received information and saves it in a digital encyclopedia. The information saved on the device is also backed up to the cloud.

[0637] Examples of cooperation with parents

[0638] The device synchronizes the information in the digital encyclopedia with the parent's smartphone, who then uses the smartphone to view information about the cabbage white butterfly that their child photographed.

[0639] Prompt Sentence Examples

[0640] The system description can be generated by inputting the following prompt sentence into the generative AI model.

[0641] "Please explain the system's process: analyze images of the natural environment taken by a child with a smartwatch, identify and record biological species, and store the image data temporarily on the device. The image data is then analyzed using a machine learning model on the server. During this process, related information is also retrieved from a database, and ultimately the system notifies the user and guardian and stores the information in a digital encyclopedia."

[0642] This enriches children's learning experiences and promotes communication with parents.

[0643] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0644] System program processing flow

[0645] Step 1: Capture an image and save it locally

[0646] A user takes pictures of plants, animals, insects, etc. that they find in a natural environment, such as a park, using a smartwatch (personal digital assistant). When the captured image data is input into the device, the device temporarily stores the image data in local storage. Specifically, it is saved as an image file in the device's built-in memory.

[0647] Input: Image data of a living creature taken by the user with their smartwatch

[0648] Output: Image file saved in local storage

[0649] Step 2: Check your internet connection and upload images

[0650] The device automatically checks for an Internet connection. If Wi-Fi or mobile data communication is enabled, the temporarily stored image data is uploaded to the server. Specifically, the image files on the device are sent to the server using the HTTPS protocol.

[0651] Input: Image file stored in local storage

[0652] Output: Image data sent to the server

[0653] Step 3: Receiving and saving image data

[0654] The server receives the image data sent from the terminal and temporarily stores it. The server stores the received image data as is in a database or file system.

[0655] Input: Image data sent from the device

[0656] Output: Image data stored on the server

[0657] Step 4: Image analysis using machine learning models

[0658] The server analyzes the stored image data using a machine learning model (e.g., a convolutional neural network) to identify the biological species. Specifically, the image data is received as input, the machine learning model analyzes the image, and outputs the identified biological species.

[0659] Input: Image data stored on the server

[0660] Output: Identified species

[0661] Step 5: Get information

[0662] Based on the identified species, the server retrieves related biological information and additional information (such as name, characteristics, and habitat) from the database and executes a database query to extract the required information.

[0663] Input: Identified species

[0664] Output: Detailed information about the organism retrieved from the database

[0665] Step 6: Packaging and sending information

[0666] The server compiles the acquired information into data packets and sends them to the mobile information terminal and remote information terminal. The data packets contain information such as the organism's name, characteristics, and habitat.

[0667] Input: Detailed information about the organism retrieved from the database

[0668] Output: Data packets sent to the mobile device and remote device

[0669] Step 7: Notification and display of information

[0670] The terminal analyzes the data received from the server and notifies the user, who then sees the name of the species and related information on the terminal's display.

[0671] Input: Data packet sent by the server

[0672] Output: Information about the creature displayed on the device's display

[0673] Step 8: Save as a digital encyclopedia

[0674] The device organizes the information it receives in a digital encyclopedia format and saves it in local storage, where it can be referenced later.

[0675] Input: Data packet received from the server

[0676] Output: Information saved in a digital encyclopedia format

[0677] Step 9: Back up to cloud storage

[0678] Back up the digital encyclopedia information stored on your device to cloud storage. Use cloud storage services to send and store data via the Internet.

[0679] Input: Information stored in a digital encyclopedia format

[0680] Output: Information backed up to cloud storage

[0681] Step 10: Sync information with parents

[0682] The device synchronizes updated information about the digital encyclopedia with a remote information device (parent's smartphone). The synchronized data is displayed in real time on the parent's device, allowing the parent to check information about the creatures their child has photographed.

[0683] Input: Digital encyclopedia update information

[0684] Output: Information about the creature displayed on the parent's device

[0685] The above is the specific processing flow of this system.

[0686] (Application example 1)

[0687] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0688] Conventional food delivery services lacked a means for users to easily obtain detailed information about the food and ingredients they purchased, particularly information about their nutritional value, origin, and cultivation method. This meant that users could not fully trust the background information about the ingredients provided, which sometimes led to anxiety when making food choices. Furthermore, the process of efficiently collecting and saving detailed information about ingredients and using it for future orders was cumbersome.

[0689] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0690] In this invention, the server includes means for receiving images taken by a mobile device, means for analyzing the received images to identify objects, and means for acquiring information about the identified objects, allowing users to easily acquire and save detailed information about foods and ingredients and use it for their next food delivery order.

[0691] A "mobile terminal" is a portable communication device, such as a smartphone or tablet, that can capture and receive image data.

[0692] "Means for receiving" refers to the process of transmitting image data captured by a mobile terminal to a server and having the server receive the data.

[0693] "Means for analyzing and identifying objects" refers to the process of analyzing received image data using a machine learning model to identify objects appearing in the image.

[0694] "Means for obtaining information" refers to the process of gathering detailed information about the identified object from a database.

[0695] "Means for transmitting" refers to the process of transmitting the acquired information to the mobile terminal and the remote terminal.

[0696] "Means for displaying" refers to the process of displaying the transmitted information on the screens of the mobile terminal and the remote terminal.

[0697] "Means of storage" refers to the process of saving the displayed information in a digital encyclopedia or cloud storage.

[0698] "Cloud storage backup method" refers to the process of automatically storing stored information in remote storage via the Internet.

[0699] "Means for synchronizing" refers to the process of matching up-to-date information between the mobile device and the remote device.

[0700] "Objects" refer to items that are the subject of identification, such as plants, animals, food, and ingredients, contained in image data.

[0701] "Detailed information" refers to attribute information related to the identified object, such as its name, nutritional value, place of origin, and cultivation method.

[0702] The embodiment of the present invention is a system including a mobile terminal, a remote terminal, a server, a machine learning model, and cloud storage, the details of which are described below.

[0703] Hardware and software used

[0704] Hardware

[0705] Mobile device: A smartphone (iOS / Android) is used. The device allows the user to take pictures of food and ingredients and send the data to the server.

[0706] Server: Uses an AWS EC2 instance to receive and analyze data.

[0707] Cloud storage: Use AWS S3 to back up the information you retrieve.

[0708] software

[0709] Image analysis: Using machine learning models (e.g., YOLO, SSD), the received image data is analyzed to identify the type of object (plant, animal, food, ingredient).

[0710] Database: AWS DynamoDB is used to obtain detailed information about the identified objects (such as name, nutritional value, origin, and cultivation method).

[0711] System Configuration and Operation

[0712] 1. Image capture and upload

[0713] A user takes an image of food or ingredients using a mobile device, which temporarily stores the captured image data locally and uploads it to a server when an internet connection is confirmed.

[0714] 2. Image Analysis

[0715] The server analyzes the received image data using machine learning models (YOLO, SSD) to identify objects (food or ingredients) contained in the image. After identifying the object, it retrieves detailed information about it from AWS DynamoDB.

[0716] 3. Return and Display of Information

[0717] The server assembles the acquired information into data packets and transmits them to the mobile and remote terminals. The mobile and remote terminals analyze the received information and notify the user. This information is displayed on the screens of the mobile and remote terminals.

[0718] 4. Information storage and backup

[0719] The mobile device saves the displayed information as a digital encyclopedia, and the saved information is backed up to AWS S3 in the background.

[0720] 5. Synchronization

[0721] By synchronizing the latest information between mobile and remote devices, users can access information consistently from any device.

[0722] Examples of specific examples and prompt usage

[0723] Specific examples

[0724] The user takes a picture of the tomatoes they purchased with their smartphone.

[0725] The smartphone uploads the images to the AWS cloud.

[0726] The machine learning model identifies it as a tomato and retrieves information about its origin, cultivation method, and nutritional value from a database.

[0727] This information is communicated to the user and stored in their profile within the food delivery service.

[0728] Prompt Sentence Examples

[0729] "Please identify the vegetable in this image and provide details about its origin and nutritional value."

[0730] In this way, by linking mobile devices, remote devices, servers, and cloud storage, users can easily obtain and save detailed information about food and ingredients, and use it the next time they order.

[0731] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0732] Step 1:

[0733] A user uses a smartphone to take a picture of food or ingredients. At this time, the smartphone's camera application is opened and the user presses the button to take a photo, generating image data. Input: Image taken by the user. Output: Image data saved in the smartphone's local storage.

[0734] Step 2:

[0735] The device checks for an Internet connection and uploads the captured image data to the server. Specifically, it reads the image data from local storage and sends it to the server using an HTTP request. Input: Image data saved in local storage. Output: Image data uploaded to the server.

[0736] Step 3:

[0737] The server analyzes the received image data and identifies the object. Here, a machine learning model (e.g., YOLO, SSD) is used to identify the object (food or ingredient) in the image. Input: Image data uploaded to the server. Output: Identification information of the identified object.

[0738] Step 4:

[0739] The server retrieves detailed information about the identified object from the database. It executes a database query to collect information such as the name of the food or ingredient, its nutritional value, origin, and cultivation method. Input: Identification information of the identified object. Output: Detailed information about the object retrieved from the database.

[0740] Step 5:

[0741] The server compiles the obtained detailed information into a data packet and sends it to the mobile device and remote device. Specifically, it generates the data packet in JSON format and returns it to the device as an HTTP response. Input: Detailed information obtained from the database. Output: Detailed information sent to the mobile device and remote device.

[0742] Step 6:

[0743] The device analyzes the details received and notifies the user. It uses the smartphone's notification system to display the details as a pop-up notification or in-app notification. Input: Details sent from the server. Output: Details notified to the user.

[0744] Step 7:

[0745] The device saves the displayed information as a digital encyclopedia and backs it up to cloud storage. The information is saved in local storage and then uploaded to AWS S3 for backup. Input: Detailed information notified to the user. Output: Detailed information saved in local storage and cloud storage.

[0746] Step 8:

[0747] The device synchronizes between the mobile device and the remote device. Sends the latest information to the remote device to keep the data consistent. Input: Details stored in local storage. Output: Details synchronized to the remote device.

[0748] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0749] This invention is a system that acquires information about plants, animals, insects, and other living things that children discover in the natural environment, and by combining it with an emotion engine, recognizes the user's emotions and provides optimal information based on their reaction. This system analyzes images taken by a mobile device, identifies the species of living things, and acquires, displays, saves, and shares related information, and also provides information that takes the user's emotions into consideration.

[0750] Program Generation and Processing Description

[0751] Image capture and upload

[0752] The user takes pictures of plants, animals, insects, etc. using a smartwatch (mobile device).

[0753] The device temporarily stores the captured image data locally, and when an Internet connection is confirmed, the image data is uploaded to the server.

[0754] Image analysis

[0755] The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[0756] After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[0757] Emotion recognition and information provision

[0758] The emotion engine installed in the device analyzes the user's facial expressions and voice to recognize their emotions. Emotion recognition is performed using a camera and microphone.

[0759] The server takes into account the emotional information it obtains and adjusts the content and format of the information displayed. For example, if the user shows interest, it provides detailed information, and if the user is anxious, it complements the explanation with gentler words.

[0760] The server compiles the information reflecting emotions into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[0761] Information Return and Storage

[0762] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and related information.

[0763] The information received by the device is saved as a digital encyclopedia, and the saved information is also uploaded to cloud storage in the background for backup.

[0764] Cooperation with parents

[0765] The device synchronizes updates to the digital encyclopedia with a remote device (parent's smartphone), allowing parents to check information about the creatures their children have photographed in real time.

[0766] The device (parent's smartphone) will be able to check changes in the child's emotions, including the results of the emotion engine's recognition.

[0767] Specific examples

[0768] Image Capture Example

[0769] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[0770] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0771] Image analysis example

[0772] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[0773] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[0774] Emotion Recognition Example

[0775] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[0776] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[0777] Information Return and Storage Examples

[0778] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[0779] The terminal notifies the user of the received information and stores it in a digital picture book.

[0780] The information stored on the device is also backed up to the cloud.

[0781] Examples of cooperation with parents

[0782] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[0783] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[0784] This system not only enriches children's learning experiences and promotes communication with parents, but also makes it possible to provide information that takes children's emotions into consideration.

[0785] The processing flow will be explained below.

[0786] Step 1:

[0787] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[0788] Step 2:

[0789] A user presses the camera shutter to capture an image.

[0790] Step 3:

[0791] The device saves the captured image in temporary storage.

[0792] Step 4:

[0793] The device checks for an internet connection.

[0794] Step 5:

[0795] If the device is connected to the Internet, the captured images are uploaded from temporary storage to a server.

[0796] Step 6:

[0797] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[0798] Step 7:

[0799] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[0800] Step 8:

[0801] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat) associated with that organism from the database.

[0802] Step 9:

[0803] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by an emotion engine.

[0804] Step 10:

[0805] The emotion engine recognizes the user's emotions (e.g., surprise, joy, interest, anxiety).

[0806] Step 11:

[0807] The server receives the recognized emotion information and adjusts the content and presentation method of the information to be displayed according to the user's emotion.

[0808] Step 12:

[0809] The server assembles the adjusted information into data packets and sends them to the mobile device and remote device (parent's smartphone).

[0810] Step 13:

[0811] The device (smartwatch) analyzes the received data and notifies the user, including the species name, a brief description, and complementary information based on the emotion.

[0812] Step 14:

[0813] The device stores the received biometric information, additional information, and complementary information according to emotions in a digital encyclopedia.

[0814] Step 15:

[0815] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[0816] Step 16:

[0817] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[0818] Step 17:

[0819] The user (parent) opens the app and checks the biological information captured by their child along with the recognized emotional changes.

[0820] In this way, the combined emotion engine optimizes children's learning experiences according to their emotional responses and also facilitates communication with parents.

[0821] Example 2

[0822] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0823] Previous systems simply collected information about organisms found in the natural environment, but did not provide information that reflected the user's feelings. Furthermore, saving and sharing information was time-consuming, which sometimes hindered smooth communication between parents and children. This posed a risk of reducing children's motivation to learn, and also led to issues such as the quality of information provided not being sufficiently improved.

[0824] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0825] In this invention, the server includes: means for receiving an image taken by a user using a mobile terminal; means for analyzing the received image and identifying a biological species using a machine learning model; and means for acquiring information about the identified biological species from a database.

[0826] The system has an emotion engine that recognizes the user's emotions, and includes means for analyzing the user's facial expressions and voice, means for adjusting the content and format of the information to be provided based on the emotion information, means for transmitting the acquired information to the mobile terminal and the remote terminal, means for displaying the information transmitted to the mobile terminal and the remote terminal, and means for saving the displayed information. This makes it possible to provide appropriate information according to the user's emotions, and makes it easy to share and manage saved information, which facilitates communication between parents and children and increases motivation to learn.

[0827] A "mobile terminal" is a portable electronic device, such as a smartphone or smartwatch, that is capable of sending and receiving data and running applications.

[0828] "Means for receiving images" refers to a function that allows the server to receive image data captured by the mobile terminal.

[0829] "Means for analyzing images" refers to algorithms or software used to process image data and determine its content.

[0830] A "machine learning model" is a statistical model of an algorithm that learns from data and makes inferences or classifications.

[0831] "Means for identifying biological species" refers to technology for determining the type of organism from analyzed image data.

[0832] A "database" is a structured collection of digital information for efficient storage and management of information.

[0833] "Means of obtaining information" refers to the processes and techniques used to extract the necessary data from the database.

[0834] An "emotion engine" is a software or hardware component that analyzes and recognizes a user's emotions.

[0835] "Means for analyzing facial expressions and voice" refers to technology that identifies emotions from facial expressions captured by a camera and voice captured by a microphone.

[0836] "Means for adjusting the content and format of information" is a function that optimizes the data provided based on the user's emotions.

[0837] A "data packet" is a unit for dividing digital information into small pieces and sending and receiving it over a communication network.

[0838] "Means of storage" refers to the technology for recording acquired information in local storage or cloud storage.

[0839] "Means of synchronization" refers to technology that automatically updates and shares information to maintain data consistency across multiple devices.

[0840] This invention is a system that acquires information on plants, animals, insects, etc. that users discover in the natural environment and combines it with an emotion engine to provide optimal information that takes the user's emotions into consideration. This system analyzes images taken with a mobile device, identifies the species, and acquires, displays, saves, and shares related information.

[0841] Hardware and software used

[0842] The main hardware includes smartphones and smartwatches. These mobile devices are used for photography and emotion recognition, and communicate with a server via an internet connection. The server is responsible for communication, data analysis, and database management, and utilizes cloud storage for backing up and synchronizing information.

[0843] Specific data processing and calculation methods

[0844] Image capture and upload

[0845] The user uses the smartwatch camera to take pictures of plants and animals.

[0846] The device stores the image data locally and uploads it to the server once an internet connection is confirmed.

[0847] Image analysis

[0848] The image data received by the server is analyzed using machine learning models such as Convolutional Neural Networks (CNNs). During the analysis process, image features are extracted and the biological species is identified.

[0849] The server retrieves information about the identified species from a database, including its name, characteristics, and habitat.

[0850] Emotion recognition and information provision

[0851] The device's built-in camera and microphone are used to capture the user's facial expressions and voice.

[0852] The device uses an emotion engine to analyze the captured data and identify the user's emotion.

[0853] The server adjusts the content and format of the information it provides based on emotional information to generate optimal information.

[0854] Information Return and Storage

[0855] The information generated by the server is compiled into data packets and sent to the mobile device and remote device (parent's smartphone).

[0856] The device notifies the user of the received information, saves it in a digital encyclopedia, and also uploads the saved information to cloud storage.

[0857] Cooperation with parents

[0858] The device synchronizes updated information from the digital encyclopedia with a remote device, allowing parents to check their child's activities in real time. It also provides information, including emotion recognition results.

[0859] Specific examples

[0860] Image Capture Example

[0861] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[0862] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[0863] Image analysis example

[0864] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[0865] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[0866] Emotion Recognition Example

[0867] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[0868] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[0869] Information Return and Storage Examples

[0870] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[0871] The terminal notifies the user of the received information and stores it in a digital picture book.

[0872] The information stored on the device is also backed up to the cloud.

[0873] Examples of cooperation with parents

[0874] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[0875] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[0876] This will enrich children's learning experiences, promote communication between parents and children, and also make it possible to provide information that takes children's emotions into consideration.

[0877] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0878] Step 1:

[0879] Image capture

[0880] Input: Plants, animals, and other objects that the user discovers in the natural environment.

[0881] How it works: A user taps the device screen to capture an image of an object using the smartwatch camera.

[0882] Output: Image data temporarily stored on the smartwatch.

[0883] Step 2:

[0884] Local storage

[0885] Input: Image data captured by the user.

[0886] How it works: The device saves the captured image data to temporary storage on the smartwatch. This process takes place within a few seconds.

[0887] Output: Image data stored in the device's local storage.

[0888] Step 3:

[0889] Image upload

[0890] Input: Image data stored on the smartwatch.

[0891] What it does: The device checks for an internet connection and, if one is available, uploads the image data to the server. It also checks for a Wi-Fi or mobile data connection and sends the data securely.

[0892] Output: Image data transferred to the server.

[0893] Step 4:

[0894] Image data reception

[0895] Input: Image data sent from the device.

[0896] Operation: The server receives the image data and saves it in the specified directory.

[0897] Output: Image data stored on the server.

[0898] Step 5:

[0899] Species identification

[0900] Input: Image data stored on the server.

[0901] How it works: The server analyzes images using machine learning models (e.g., convolutional neural networks for image classification). During the analysis, image features are extracted and the species is identified.

[0902] Output: Identified species.

[0903] Step 6:

[0904] Related information acquisition

[0905] Input: Identified species.

[0906] How it works: The server accesses a database to retrieve detailed information about the organism (e.g., name, characteristics, habitat, etc.) using an SQL query.

[0907] Output: Information about the organism retrieved.

[0908] Step 7:

[0909] Emotional Data Capture

[0910] Input: User's facial expressions and voice.

[0911] How it works: The device uses its camera and microphone to capture the user's facial and voice data.

[0912] Output: User's facial expression and voice data.

[0913] Step 8:

[0914] Emotion analysis

[0915] Input: Captured user facial and voice data.

[0916] How it works: The device uses an emotion engine to analyze the captured data and recognize the user's emotions, determining whether the user is surprised, excited, anxious, etc.

[0917] Output: User's emotional information.

[0918] Step 9:

[0919] Providing optimal information

[0920] Input: Information about the identified organism and user's emotion information.

[0921] How it works: The server adjusts the content and format of the information it provides based on the emotional information, generating information that best suits the user's state. For example, it changes the depth of information depending on whether a detailed explanation is required or not.

[0922] Output: The adjusted information.

[0923] Step 10:

[0924] Data packet generation and transmission

[0925] Input: Reconciled information.

[0926] How it works: The server packages the tailored information into data packets and sends them to the mobile and remote devices. The data is sent using the HTTP protocol.

[0927] Output: Data packets sent to the mobile and remote devices.

[0928] Step 11:

[0929] Notification and Retention

[0930] Input: Data packets sent to mobile and remote devices.

[0931] Operation: The device analyzes the received data and notifies the user. The notification includes the name of the species and related information. The received information is also saved in local storage as a digital encyclopedia, and is backed up to cloud storage in the background.

[0932] Output: Notification to the user and data backed up to the cloud.

[0933] Step 12:

[0934] Data Synchronization

[0935] Input: Data from local storage and cloud storage.

[0936] How it works: The device synchronizes the updated information of the digital encyclopedia with the remote device. The latest digital encyclopedia data is uploaded via the cloud server, and the parent's smartphone app retrieves it.

[0937] Output: Data synchronized to the remote device.

[0938] Step 13:

[0939] Checking for emotional changes

[0940] Input: Synchronized data and emotion recognition results.

[0941] Operation: The device (parent's smartphone) displays the emotion engine's recognition results, allowing parents to check their child's emotional changes. The emotion recognition results are included in the information sent to the parent's smartphone app.

[0942] Output: Emotional change information that can be checked by parents.

[0943] (Application example 2)

[0944] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0945] The present invention aims to enrich educational experiences by quickly obtaining information about organisms that children discover in natural environments, educational facilities, etc., and by providing appropriate information that responds to the child's emotions. Conventional technologies can identify organisms and provide information, but do not provide information that takes the user's emotions into consideration, making it difficult to flexibly respond to children's interests and level of understanding. Therefore, there is a need for an improved user experience and more effective educational support.

[0946] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving images taken by a mobile terminal, means for analyzing the received images to identify the biological species, means for acquiring information about the identified biological species, means for analyzing the user's emotions using an emotion engine, and means for dynamically adjusting information based on the user's emotions. This makes it possible to quickly identify the biological species based on images taken by a child and provide information that corresponds to the child's emotions.

[0947] A "mobile device" is a portable electronic device such as a smartphone or tablet.

[0948] The "means for receiving images" is a function for transferring captured image data from the mobile terminal to the server and receiving the data.

[0949] "Means for analyzing images" refers to a function that processes received image data using algorithms or machine learning models to analyze its contents.

[0950] "Means for identifying biological species" refers to the function of identifying specific biological species such as plants, animals, insects, etc. from the contents of analyzed image data.

[0951] "Means for obtaining information" refers to a function for searching and obtaining detailed information about the identified biological species from a database, etc.

[0952] The "means for transmitting information" is a function for transferring acquired information to the mobile terminal and the remote terminal.

[0953] The "means for displaying information" is a function for displaying the transmitted information on the display of the mobile terminal or the remote terminal.

[0954] "Means for saving information" refers to a function for saving the displayed information in an internal memory or an external storage device.

[0955] An "emotion engine" is software and hardware that analyzes the user's facial expressions and voice and recognizes their emotions.

[0956] The "means for analyzing emotions" is a function that analyzes the user's emotions using an emotion engine.

[0957] The "means for adjusting information" is a function that dynamically changes the content and format of information according to the user's emotions.

[0958] "Cloud storage" is an online data storage service accessible via the Internet.

[0959] "Means for synchronizing" refers to a function for matching data between multiple terminals in real time or periodically.

[0960] This invention is a system that quickly acquires information about creatures that children discover in the natural environment or educational facilities, and provides appropriate information according to the children's emotions. Specific embodiments for carrying out this invention will be described below.

[0961] Hardware and Software Configuration

[0962] Hardware used

[0963] Mobile Device: A portable electronic device such as smart glasses or a smartphone.

[0964] Remote device: A smartphone or tablet used by a parent or guardian.

[0965] Server: A central computer system for image analysis, sentiment analysis, and information provision.

[0966] Software used

[0967] Image processing: Image analysis using OpenCV.

[0968] Emotion Recognition: Emotion recognition libraries (e.g., FER).

[0969] Machine learning model: Convolutional Neural Network (CNN) used to identify biological species.

[0970] Backend: A web framework such as Flask or Django for sending, receiving, and processing information.

[0971] Cloud storage: Online data storage services such as Amazon S3.

[0972] Database: A database system for managing information, such as MongoDB or MySQL.

[0973] Data processing and calculation

[0974] Image Capture

[0975] Images of living organisms are taken using a mobile device, and the captured image data is saved locally.

[0976] Image upload

[0977] Once a Wi-Fi connection is confirmed, the captured image data is uploaded to the server, where it is stored.

[0978] Image analysis

[0979] The server analyzes the images using machine learning models to identify the species, using a Convolutional Neural Network (CNN) for highly accurate image recognition.

[0980] emotion recognition

[0981] The camera and microphone on the mobile device are used to capture the user's facial expressions and voice, and emotion recognition software (e.g., FER) is used to recognize the user's emotions.

[0982] Information Acquisition and Display

[0983] The server retrieves related information from the database based on the species identification results. This information is formatted in an optimal way based on the user's emotions and sent to mobile and remote devices. The information is displayed on the device and, if necessary, saved in a digital encyclopedia or cloud storage.

[0984] Specific examples

[0985] Photographing cabbage white butterflies in the park

[0986] 1. A child finds a cabbage white butterfly in the park and takes a picture of it with smart glasses.

[0987] 2. The captured images are uploaded from the smart glasses to the server.

[0988] 3. The server performs image analysis and identifies it as a cabbage white butterfly.

[0989] 4. The robot recognizes the user's (child's) emotions from their facial expressions and voice and determines that they are excited.

[0990] 5. The server formats the detailed information and sends it to the smart glasses and the parent's smartphone.

[0991] 6. The transmitted information will be displayed on the device and also saved in the digital encyclopedia.

[0992] Prompt Sentence Examples

[0993] As an example, you can input the following prompts to a generative AI model:

[0994] "Please tell me how to provide information in response to the excitement and emotions of children who take photos of pandas."

[0995] As described above, this system makes it possible to quickly and appropriately provide information about organisms that children are interested in. Furthermore, cooperation with parents will enrich the educational experience for children.

[0996] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0997] Step 1:

[0998] The user (child) takes a photo of a target organism in a natural environment or an educational facility using the camera in the smart glasses. The user's actions include capturing and saving the image of the organism. The input is the image of the organism, and the output is the locally saved image data.

[0999] Step 2:

[1000] When the device (smart glasses) confirms an Internet connection, it uploads the captured image data to the server. The input is the locally stored image data, and the output is the image data transferred to the server.

[1001] Step 3:

[1002] The server receives the uploaded image data and analyzes the image using a Convolutional Neural Network (CNN). This analysis identifies the biological species. The input is the image data transferred to the server, and the output is the identified biological species information.

[1003] Step 4:

[1004] The server retrieves detailed information about the identified species from the database. The input is the identified species information, and the output is detailed information about the species (such as name, characteristics, habitat, etc.).

[1005] Step 5:

[1006] If the user is interested after taking a photo, the device (smart glasses) will capture the user's facial expressions and voice using a camera and microphone. An emotion engine will analyze this data and identify the user's emotions. The input is the user's facial expressions and voice data, and the output is the identified user's emotions (excitement, interest, etc.).

[1007] Step 6:

[1008] The server considers the user's emotional information and adjusts the information about the species to an appropriate format depending on the emotion. For example, if the user is excited, more detailed information is provided. The input is the user's emotional information and detailed information about the species, and the output is information adjusted according to the emotion.

[1009] Step 7:

[1010] The server compiles the adjusted information about the species into a data packet and sends it to a mobile device (smart glasses) and a remote device (parent's smartphone). The input is the adjusted information, and the output is the data sent to the mobile device and the remote device.

[1011] Step 8:

[1012] The devices (smart glasses and parent's smartphone) analyze and display the received data appropriately. The data is displayed as notifications and detailed information to the user, and the child's activities and emotional information to the parent. The input is the transmitted data, and the output is the information displayed to the user and parent.

[1013] Step 9:

[1014] The device saves the displayed information in a digital encyclopedia and also backs it up to cloud storage. The input is the displayed information, and the output is data stored locally and in the cloud.

[1015] Step 10:

[1016] The terminal synchronizes the digital picture book information and the user's emotional information with the remote terminal (parent's smartphone). The input is the update information and emotional information of the digital picture book, and the output is the synchronization result with the remote terminal.

[1017] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1018] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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 voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1019] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1020] [Third embodiment]

[1021] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1022] 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.

[1023] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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).

[1024] 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.

[1025] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1026] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1027] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1028] 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.

[1029] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1030] 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.

[1031] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1032] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1033] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system analyzes images taken with a mobile device, identifies the species, and collects, displays, stores, and shares related information.

[1034] Program Generation and Processing Description

[1035] Image capture and upload

[1036] 1. The user takes an image of a plant, animal, insect, etc. using a smartwatch (mobile device).

[1037] 2. The device temporarily stores the captured image data locally, and if an Internet connection is confirmed, uploads the image data to the server.

[1038] Image analysis

[1039] 3. The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[1040] 4. After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[1041] Information Return and Storage

[1042] 5. The server compiles the acquired information into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[1043] 6. The device analyzes the received data and notifies the user, including the name of the species and related information.

[1044] 7. The device saves the received information as a digital encyclopedia, and also uploads the saved information to cloud storage in the background for backup.

[1045] Cooperation with parents

[1046] 8. The device synchronizes the updated information of the digital encyclopedia with the remote device (parent's smartphone), allowing parents to check information about the creatures their child has photographed in real time.

[1047] Specific examples

[1048] Image Capture Example

[1049] 1. The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[1050] 2. The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1051] Image analysis example

[1052] 1. The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[1053] 2. The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from the database.

[1054] Information Return and Storage Examples

[1055] 1. The server sends the acquired information to the smartwatch and the parent's smartphone.

[1056] 2. The device notifies the user of the received information and saves it in the digital encyclopedia.

[1057] 3. Back up the information stored on your device to the cloud.

[1058] Examples of cooperation with parents

[1059] 1. The device synchronizes the digital encyclopedia information with the parent's smartphone.

[1060] 2. The user (parent) uses their smartphone to view information about the cabbage white butterfly photographed by their child.

[1061] This enriches children's learning experiences and promotes communication with parents.

[1062] The processing flow will be explained below.

[1063] Step 1:

[1064] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[1065] Step 2:

[1066] A user presses the camera shutter to capture an image.

[1067] Step 3:

[1068] The device saves the captured image in temporary storage.

[1069] Step 4:

[1070] The device checks for an Internet connection, and if a connection is confirmed, uploads the captured images from temporary storage to the server.

[1071] Step 5:

[1072] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[1073] Step 6:

[1074] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[1075] Step 7:

[1076] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat, etc.) related to that organism from the database.

[1077] Step 8:

[1078] The server collates the results of the image analysis and related information and generates a data packet to send back to the user.

[1079] Step 9:

[1080] The server sends the generated data packets to the mobile device and the remote device (parent's smartphone).

[1081] Step 10:

[1082] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and a brief description.

[1083] Step 11:

[1084] The terminal stores the received biometric information and additional information in a digital encyclopedia.

[1085] Step 12:

[1086] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[1087] Step 13:

[1088] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[1089] Step 14:

[1090] The user (parent) opens the app and checks the biological information captured by their child.

[1091] Example 1

[1092] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1093] With conventional technology, there are limited means for acquiring, organizing, and storing information about plants, animals, insects, and other organisms discovered in the natural environment, making it particularly difficult for children to identify the species they discover and easily acquire and share that information. Other issues include the difficulty of storing and backing up acquired information and sharing it with parents in real time.

[1094] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1095] In this invention, the server includes means for receiving images captured by a mobile information terminal, means for analyzing the received images to identify biological species, means for retrieving information about the identified biological species from a database, means for transmitting the retrieved information to the mobile information terminal and a remote information terminal, means for displaying the information transmitted to the mobile information terminal and the remote information terminal, means for saving the displayed information in a digital picture book format, means for backing up the retrieved information to cloud storage, and means for synchronizing between the mobile information terminal and the remote information terminal. This enables consistent processing from identifying biological species to retrieving, displaying, saving, and sharing information, thereby enriching children's learning experiences and promoting communication with parents.

[1096] A "portable information terminal" is an electronic device that can be carried by a user, and is a terminal device that has functions such as image capture, data communication, and information display.

[1097] The "means for receiving images" refers to a mechanism by which the server obtains image data sent from the mobile information terminal.

[1098] The "means for analyzing images" is a mechanism that includes an algorithm that analyzes received image data using a machine learning model and identifies the species of the organism.

[1099] "Means for identifying" refers to a mechanism for identifying the biological species identified by image analysis and outputting the identification results.

[1100] "Means for obtaining data from a database" refers to a mechanism for searching and obtaining data from a database that stores detailed information and associated information about an identified biological species.

[1101] The "means for transmitting information" is a mechanism for transmitting data of the acquired organism information to the portable information terminal and the remote information terminal.

[1102] The "means for displaying information" is a mechanism for displaying the transmitted information about the living thing on the screen of the portable information terminal and the remote information terminal.

[1103] "Means for saving in digital encyclopedia format" refers to a mechanism for organizing and saving the displayed information in electronic format and storing it in a form that can be viewed later.

[1104] "Means for backing up to cloud storage" refers to a mechanism for transmitting stored information to an external cloud storage service via the Internet to ensure the safety and durability of data.

[1105] A "synchronization means" is a mechanism for matching data between a mobile information terminal and a remote information terminal and sharing information in real time.

[1106] A "server" is a central management device that accepts requests from a large number of client terminals and provides services and data in response to those requests.

[1107] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system has the function of analyzing images taken with a mobile information terminal, identifying the species, and collecting, displaying, saving, and sharing related information.

[1108] Hardware and software used

[1109] The system is implemented using the following major hardware and software:

[1110] Hardware:

[1111] 1. Personal digital assistant: A portable device capable of taking images and transmitting data, such as a smartphone or smartwatch.

[1112] 2. Server: A centralized management unit that provides high-performance data processing and storage.

[1113] 3. Remote information terminal: A device that can receive and display data, such as a parent's smartphone.

[1114] software:

[1115] 1. Camera application: An application for taking pictures on a mobile device.

[1116] 2. Image analysis library: Software that analyzes images using machine learning models such as Convolutional Neural Networks (CNNs).

[1117] 3. Database system: A database for storing information about living organisms.

[1118] 4. Cloud storage service: Online storage for backing up acquired information.

[1119] Specific Embodiments

[1120] Image capture and upload

[1121] The user (child) takes pictures of creatures they find in the natural environment using a mobile information device (e.g., a smartwatch). The images are temporarily stored on the device and then automatically uploaded to the server when an internet connection is confirmed.

[1122] Image analysis

[1123] The server uses a machine learning model (such as CNN) to analyze the image data it receives. The analysis results identify the species, and that information is then queried against a database.

[1124] Displaying and saving information

[1125] The server retrieves information about the identified species from the database and sends it as a data packet to the mobile information device and the parent's remote information device. The received information is notified to the mobile information device and saved in a digital encyclopedia format. The saved information is then backed up to cloud storage.

[1126] Sync and Share

[1127] The device synchronizes updated information from the digital encyclopedia with a remote information terminal, allowing parents to check information about the creatures their children have photographed in real time.

[1128] Specific examples

[1129] Image Capture Example

[1130] A user (child) takes a photo of a cabbage white butterfly they find in a park with their smartwatch. The device temporarily saves the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1131] Image analysis example

[1132] The server analyzes the uploaded image and identifies it as a cabbage white butterfly. The server then retrieves biological information about the butterfly (such as its name, characteristics, and feeding habits) and additional information (such as its habitat and classification) from a database.

[1133] Examples of displaying and saving information

[1134] The server sends the acquired information to the smartwatch and the parent's smartphone. The device notifies the user of the received information and saves it in a digital encyclopedia. The information saved on the device is also backed up to the cloud.

[1135] Examples of cooperation with parents

[1136] The device synchronizes the information in the digital encyclopedia with the parent's smartphone, who then uses the smartphone to view information about the cabbage white butterfly that their child photographed.

[1137] Prompt Sentence Examples

[1138] The system description can be generated by inputting the following prompt sentence into the generative AI model.

[1139] "Please explain the system's process: analyze images of the natural environment taken by a child with a smartwatch, identify and record biological species, and store the image data temporarily on the device. The image data is then analyzed using a machine learning model on the server. During this process, related information is also retrieved from a database, and ultimately the system notifies the user and guardian and stores the information in a digital encyclopedia."

[1140] This enriches children's learning experiences and promotes communication with parents.

[1141] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1142] System program processing flow

[1143] Step 1: Capture an image and save it locally

[1144] A user takes pictures of plants, animals, insects, etc. that they find in a natural environment, such as a park, using a smartwatch (personal digital assistant). When the captured image data is input into the device, the device temporarily stores the image data in local storage. Specifically, it is saved as an image file in the device's built-in memory.

[1145] Input: Image data of a living creature taken by the user with their smartwatch

[1146] Output: Image file saved in local storage

[1147] Step 2: Check your internet connection and upload images

[1148] The device automatically checks for an Internet connection. If Wi-Fi or mobile data communication is enabled, the temporarily stored image data is uploaded to the server. Specifically, the image files on the device are sent to the server using the HTTPS protocol.

[1149] Input: Image file stored in local storage

[1150] Output: Image data sent to the server

[1151] Step 3: Receiving and saving image data

[1152] The server receives the image data sent from the terminal and temporarily stores it. The server stores the received image data as is in a database or file system.

[1153] Input: Image data sent from the device

[1154] Output: Image data stored on the server

[1155] Step 4: Image analysis using machine learning models

[1156] The server analyzes the stored image data using a machine learning model (e.g., a convolutional neural network) to identify the biological species. Specifically, the image data is received as input, the machine learning model analyzes the image, and outputs the identified biological species.

[1157] Input: Image data stored on the server

[1158] Output: Identified species

[1159] Step 5: Get information

[1160] Based on the identified species, the server retrieves related biological information and additional information (such as name, characteristics, and habitat) from the database and executes a database query to extract the required information.

[1161] Input: Identified species

[1162] Output: Detailed information about the organism retrieved from the database

[1163] Step 6: Packaging and sending information

[1164] The server compiles the acquired information into data packets and sends them to the mobile information terminal and remote information terminal. The data packets contain information such as the organism's name, characteristics, and habitat.

[1165] Input: Detailed information about the organism retrieved from the database

[1166] Output: Data packets sent to the mobile device and remote device

[1167] Step 7: Notification and display of information

[1168] The terminal analyzes the data received from the server and notifies the user, who then sees the name of the species and related information on the terminal's display.

[1169] Input: Data packet sent by the server

[1170] Output: Information about the creature displayed on the device's display

[1171] Step 8: Save as a digital encyclopedia

[1172] The device organizes the information it receives in a digital encyclopedia format and saves it in local storage, where it can be referenced later.

[1173] Input: Data packet received from the server

[1174] Output: Information saved in a digital encyclopedia format

[1175] Step 9: Back up to cloud storage

[1176] Back up the digital encyclopedia information stored on your device to cloud storage. Use cloud storage services to send and store data via the Internet.

[1177] Input: Information stored in a digital encyclopedia format

[1178] Output: Information backed up to cloud storage

[1179] Step 10: Sync information with parents

[1180] The device synchronizes updated information about the digital encyclopedia with a remote information device (parent's smartphone). The synchronized data is displayed in real time on the parent's device, allowing the parent to check information about the creatures their child has photographed.

[1181] Input: Digital encyclopedia update information

[1182] Output: Information about the creature displayed on the parent's device

[1183] The above is the specific processing flow of this system.

[1184] (Application example 1)

[1185] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1186] Conventional food delivery services lacked a means for users to easily obtain detailed information about the food and ingredients they purchased, particularly information about their nutritional value, origin, and cultivation method. This meant that users could not fully trust the background information about the ingredients provided, which sometimes led to anxiety when making food choices. Furthermore, the process of efficiently collecting and saving detailed information about ingredients and using it for future orders was cumbersome.

[1187] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1188] In this invention, the server includes means for receiving images taken by a mobile device, means for analyzing the received images to identify objects, and means for acquiring information about the identified objects, allowing users to easily acquire and save detailed information about foods and ingredients and use it for their next food delivery order.

[1189] A "mobile terminal" is a portable communication device, such as a smartphone or tablet, that can capture and receive image data.

[1190] "Means for receiving" refers to the process of transmitting image data captured by a mobile terminal to a server and having the server receive the data.

[1191] "Means for analyzing and identifying objects" refers to the process of analyzing received image data using a machine learning model to identify objects appearing in the image.

[1192] "Means for obtaining information" refers to the process of gathering detailed information about the identified object from a database.

[1193] "Means for transmitting" refers to the process of transmitting the acquired information to the mobile terminal and the remote terminal.

[1194] "Means for displaying" refers to the process of displaying the transmitted information on the screens of the mobile terminal and the remote terminal.

[1195] "Means of storage" refers to the process of saving the displayed information in a digital encyclopedia or cloud storage.

[1196] "Cloud storage backup method" refers to the process of automatically storing stored information in remote storage via the Internet.

[1197] "Means for synchronizing" refers to the process of matching up-to-date information between the mobile device and the remote device.

[1198] "Objects" refer to items that are the subject of identification, such as plants, animals, food, and ingredients, contained in image data.

[1199] "Detailed information" refers to attribute information related to the identified object, such as its name, nutritional value, place of origin, and cultivation method.

[1200] The embodiment of the present invention is a system including a mobile terminal, a remote terminal, a server, a machine learning model, and cloud storage, the details of which are described below.

[1201] Hardware and software used

[1202] Hardware

[1203] Mobile device: A smartphone (iOS / Android) is used. The device allows the user to take pictures of food and ingredients and send the data to the server.

[1204] Server: Uses an AWS EC2 instance to receive and analyze data.

[1205] Cloud storage: Use AWS S3 to back up the information you retrieve.

[1206] software

[1207] Image analysis: Using machine learning models (e.g., YOLO, SSD), the received image data is analyzed to identify the type of object (plant, animal, food, ingredient).

[1208] Database: AWS DynamoDB is used to obtain detailed information about the identified objects (such as name, nutritional value, origin, and cultivation method).

[1209] System Configuration and Operation

[1210] 1. Image capture and upload

[1211] A user takes an image of food or ingredients using a mobile device, which temporarily stores the captured image data locally and uploads it to a server when an internet connection is confirmed.

[1212] 2. Image Analysis

[1213] The server analyzes the received image data using machine learning models (YOLO, SSD) to identify objects (food or ingredients) contained in the image. After identifying the object, it retrieves detailed information about it from AWS DynamoDB.

[1214] 3. Return and Display of Information

[1215] The server assembles the acquired information into data packets and transmits them to the mobile and remote terminals. The mobile and remote terminals analyze the received information and notify the user. This information is displayed on the screens of the mobile and remote terminals.

[1216] 4. Information storage and backup

[1217] The mobile device saves the displayed information as a digital encyclopedia, and the saved information is backed up to AWS S3 in the background.

[1218] 5. Synchronization

[1219] By synchronizing the latest information between mobile and remote devices, users can access information consistently from any device.

[1220] Examples of specific examples and prompt usage

[1221] Specific examples

[1222] The user takes a picture of the tomatoes they purchased with their smartphone.

[1223] The smartphone uploads the images to the AWS cloud.

[1224] The machine learning model identifies it as a tomato and retrieves information about its origin, cultivation method, and nutritional value from a database.

[1225] This information is communicated to the user and stored in their profile within the food delivery service.

[1226] Prompt Sentence Examples

[1227] "Please identify the vegetable in this image and provide details about its origin and nutritional value."

[1228] In this way, by linking mobile devices, remote devices, servers, and cloud storage, users can easily obtain and save detailed information about food and ingredients, and use it the next time they order.

[1229] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1230] Step 1:

[1231] A user uses a smartphone to take a picture of food or ingredients. At this time, the smartphone's camera application is opened and the user presses the button to take a photo, generating image data. Input: Image taken by the user. Output: Image data saved in the smartphone's local storage.

[1232] Step 2:

[1233] The device checks for an Internet connection and uploads the captured image data to the server. Specifically, it reads the image data from local storage and sends it to the server using an HTTP request. Input: Image data saved in local storage. Output: Image data uploaded to the server.

[1234] Step 3:

[1235] The server analyzes the received image data and identifies the object. Here, a machine learning model (e.g., YOLO, SSD) is used to identify the object (food or ingredient) in the image. Input: Image data uploaded to the server. Output: Identification information of the identified object.

[1236] Step 4:

[1237] The server retrieves detailed information about the identified object from the database. It executes a database query to collect information such as the name of the food or ingredient, its nutritional value, origin, and cultivation method. Input: Identification information of the identified object. Output: Detailed information about the object retrieved from the database.

[1238] Step 5:

[1239] The server compiles the obtained detailed information into a data packet and sends it to the mobile device and remote device. Specifically, it generates the data packet in JSON format and returns it to the device as an HTTP response. Input: Detailed information obtained from the database. Output: Detailed information sent to the mobile device and remote device.

[1240] Step 6:

[1241] The device analyzes the details received and notifies the user. It uses the smartphone's notification system to display the details as a pop-up notification or in-app notification. Input: Details sent from the server. Output: Details notified to the user.

[1242] Step 7:

[1243] The device saves the displayed information as a digital encyclopedia and backs it up to cloud storage. The information is saved in local storage and then uploaded to AWS S3 for backup. Input: Detailed information notified to the user. Output: Detailed information saved in local storage and cloud storage.

[1244] Step 8:

[1245] The device synchronizes between the mobile device and the remote device. Sends the latest information to the remote device to keep the data consistent. Input: Details stored in local storage. Output: Details synchronized to the remote device.

[1246] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1247] This invention is a system that acquires information about plants, animals, insects, and other living things that children discover in the natural environment, and by combining it with an emotion engine, recognizes the user's emotions and provides optimal information based on their reaction. This system analyzes images taken by a mobile device, identifies the species of living things, and acquires, displays, saves, and shares related information, and also provides information that takes the user's emotions into consideration.

[1248] Program Generation and Processing Description

[1249] Image capture and upload

[1250] The user takes pictures of plants, animals, insects, etc. using a smartwatch (mobile device).

[1251] The device temporarily stores the captured image data locally, and when an Internet connection is confirmed, the image data is uploaded to the server.

[1252] Image analysis

[1253] The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[1254] After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[1255] Emotion recognition and information provision

[1256] The emotion engine installed in the device analyzes the user's facial expressions and voice to recognize their emotions. Emotion recognition is performed using a camera and microphone.

[1257] The server takes into account the emotional information it obtains and adjusts the content and format of the information displayed. For example, if the user shows interest, it provides detailed information, and if the user is anxious, it complements the explanation with gentler words.

[1258] The server compiles the information reflecting emotions into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[1259] Information Return and Storage

[1260] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and related information.

[1261] The information received by the device is saved as a digital encyclopedia, and the saved information is also uploaded to cloud storage in the background for backup.

[1262] Cooperation with parents

[1263] The device synchronizes updates to the digital encyclopedia with a remote device (parent's smartphone), allowing parents to check information about the creatures their children have photographed in real time.

[1264] The device (parent's smartphone) will be able to check changes in the child's emotions, including the results of the emotion engine's recognition.

[1265] Specific examples

[1266] Image Capture Example

[1267] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[1268] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1269] Image analysis example

[1270] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[1271] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[1272] Emotion Recognition Example

[1273] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[1274] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[1275] Information Return and Storage Examples

[1276] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[1277] The terminal notifies the user of the received information and stores it in a digital picture book.

[1278] The information stored on the device is also backed up to the cloud.

[1279] Examples of cooperation with parents

[1280] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[1281] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[1282] This system not only enriches children's learning experiences and promotes communication with parents, but also makes it possible to provide information that takes children's emotions into consideration.

[1283] The processing flow will be explained below.

[1284] Step 1:

[1285] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[1286] Step 2:

[1287] A user presses the camera shutter to capture an image.

[1288] Step 3:

[1289] The device saves the captured image in temporary storage.

[1290] Step 4:

[1291] The device checks for an internet connection.

[1292] Step 5:

[1293] If the device is connected to the Internet, the captured images are uploaded from temporary storage to a server.

[1294] Step 6:

[1295] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[1296] Step 7:

[1297] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[1298] Step 8:

[1299] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat) associated with that organism from the database.

[1300] Step 9:

[1301] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by an emotion engine.

[1302] Step 10:

[1303] The emotion engine recognizes the user's emotions (e.g., surprise, joy, interest, anxiety).

[1304] Step 11:

[1305] The server receives the recognized emotion information and adjusts the content and presentation method of the information to be displayed according to the user's emotion.

[1306] Step 12:

[1307] The server assembles the adjusted information into data packets and sends them to the mobile device and remote device (parent's smartphone).

[1308] Step 13:

[1309] The device (smartwatch) analyzes the received data and notifies the user, including the species name, a brief description, and complementary information based on the emotion.

[1310] Step 14:

[1311] The device stores the received biometric information, additional information, and complementary information according to emotions in a digital encyclopedia.

[1312] Step 15:

[1313] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[1314] Step 16:

[1315] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[1316] Step 17:

[1317] The user (parent) opens the app and checks the biological information captured by their child along with the recognized emotional changes.

[1318] In this way, the combined emotion engine optimizes children's learning experiences according to their emotional responses and also facilitates communication with parents.

[1319] Example 2

[1320] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1321] Previous systems simply collected information about organisms found in the natural environment, but did not provide information that reflected the user's feelings. Furthermore, saving and sharing information was time-consuming, which sometimes hindered smooth communication between parents and children. This posed a risk of reducing children's motivation to learn, and also led to issues such as the quality of information provided not being sufficiently improved.

[1322] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1323] In this invention, the server includes: means for receiving an image taken by a user using a mobile terminal; means for analyzing the received image and identifying a biological species using a machine learning model; and means for acquiring information about the identified biological species from a database.

[1324] The system has an emotion engine that recognizes the user's emotions, and includes means for analyzing the user's facial expressions and voice, means for adjusting the content and format of the information to be provided based on the emotion information, means for transmitting the acquired information to the mobile terminal and the remote terminal, means for displaying the information transmitted to the mobile terminal and the remote terminal, and means for saving the displayed information. This makes it possible to provide appropriate information according to the user's emotions, and makes it easy to share and manage saved information, which facilitates communication between parents and children and increases motivation to learn.

[1325] A "mobile terminal" is a portable electronic device, such as a smartphone or smartwatch, that is capable of sending and receiving data and running applications.

[1326] "Means for receiving images" refers to a function that allows the server to receive image data captured by the mobile terminal.

[1327] "Means for analyzing images" refers to algorithms or software used to process image data and determine its content.

[1328] A "machine learning model" is a statistical model of an algorithm that learns from data and makes inferences or classifications.

[1329] "Means for identifying biological species" refers to technology for determining the type of organism from analyzed image data.

[1330] A "database" is a structured collection of digital information for efficient storage and management of information.

[1331] "Means of obtaining information" refers to the processes and techniques used to extract the necessary data from the database.

[1332] An "emotion engine" is a software or hardware component that analyzes and recognizes a user's emotions.

[1333] "Means for analyzing facial expressions and voice" refers to technology that identifies emotions from facial expressions captured by a camera and voice captured by a microphone.

[1334] "Means for adjusting the content and format of information" is a function that optimizes the data provided based on the user's emotions.

[1335] A "data packet" is a unit for dividing digital information into small pieces and sending and receiving it over a communication network.

[1336] "Means of storage" refers to the technology for recording acquired information in local storage or cloud storage.

[1337] "Means of synchronization" refers to technology that automatically updates and shares information to maintain data consistency across multiple devices.

[1338] This invention is a system that acquires information on plants, animals, insects, etc. that users discover in the natural environment and combines it with an emotion engine to provide optimal information that takes the user's emotions into consideration. This system analyzes images taken with a mobile device, identifies the species, and acquires, displays, saves, and shares related information.

[1339] Hardware and software used

[1340] The main hardware includes smartphones and smartwatches. These mobile devices are used for photography and emotion recognition, and communicate with a server via an internet connection. The server is responsible for communication, data analysis, and database management, and utilizes cloud storage for backing up and synchronizing information.

[1341] Specific data processing and calculation methods

[1342] Image capture and upload

[1343] The user uses the smartwatch camera to take pictures of plants and animals.

[1344] The device stores the image data locally and uploads it to the server once an internet connection is confirmed.

[1345] Image analysis

[1346] The image data received by the server is analyzed using machine learning models such as Convolutional Neural Networks (CNNs). During the analysis process, image features are extracted and the biological species is identified.

[1347] The server retrieves information about the identified species from a database, including its name, characteristics, and habitat.

[1348] Emotion recognition and information provision

[1349] The device's built-in camera and microphone are used to capture the user's facial expressions and voice.

[1350] The device uses an emotion engine to analyze the captured data and identify the user's emotion.

[1351] The server adjusts the content and format of the information it provides based on emotional information to generate optimal information.

[1352] Information Return and Storage

[1353] The information generated by the server is compiled into data packets and sent to the mobile device and remote device (parent's smartphone).

[1354] The device notifies the user of the received information, saves it in a digital encyclopedia, and also uploads the saved information to cloud storage.

[1355] Cooperation with parents

[1356] The device synchronizes updated information from the digital encyclopedia with a remote device, allowing parents to check their child's activities in real time. It also provides information, including emotion recognition results.

[1357] Specific examples

[1358] Image Capture Example

[1359] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[1360] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1361] Image analysis example

[1362] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[1363] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[1364] Emotion Recognition Example

[1365] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[1366] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[1367] Information Return and Storage Examples

[1368] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[1369] The terminal notifies the user of the received information and stores it in a digital picture book.

[1370] The information stored on the device is also backed up to the cloud.

[1371] Examples of cooperation with parents

[1372] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[1373] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[1374] This will enrich children's learning experiences, promote communication between parents and children, and also make it possible to provide information that takes children's emotions into consideration.

[1375] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1376] Step 1:

[1377] Image capture

[1378] Input: Plants, animals, and other objects that the user discovers in the natural environment.

[1379] How it works: A user taps the device screen to capture an image of an object using the smartwatch camera.

[1380] Output: Image data temporarily stored on the smartwatch.

[1381] Step 2:

[1382] Local storage

[1383] Input: Image data captured by the user.

[1384] How it works: The device saves the captured image data to temporary storage on the smartwatch. This process takes place within a few seconds.

[1385] Output: Image data stored in the device's local storage.

[1386] Step 3:

[1387] Image upload

[1388] Input: Image data stored on the smartwatch.

[1389] What it does: The device checks for an internet connection and, if one is available, uploads the image data to the server. It also checks for a Wi-Fi or mobile data connection and sends the data securely.

[1390] Output: Image data transferred to the server.

[1391] Step 4:

[1392] Image data reception

[1393] Input: Image data sent from the device.

[1394] Operation: The server receives the image data and saves it in the specified directory.

[1395] Output: Image data stored on the server.

[1396] Step 5:

[1397] Species identification

[1398] Input: Image data stored on the server.

[1399] How it works: The server analyzes images using machine learning models (e.g., convolutional neural networks for image classification). During the analysis, image features are extracted and the species is identified.

[1400] Output: Identified species.

[1401] Step 6:

[1402] Related information acquisition

[1403] Input: Identified species.

[1404] How it works: The server accesses a database to retrieve detailed information about the organism (e.g., name, characteristics, habitat, etc.) using an SQL query.

[1405] Output: Information about the organism retrieved.

[1406] Step 7:

[1407] Emotional Data Capture

[1408] Input: User's facial expressions and voice.

[1409] How it works: The device uses its camera and microphone to capture the user's facial and voice data.

[1410] Output: User's facial expression and voice data.

[1411] Step 8:

[1412] Emotion analysis

[1413] Input: Captured user facial and voice data.

[1414] How it works: The device uses an emotion engine to analyze the captured data and recognize the user's emotions, determining whether the user is surprised, excited, anxious, etc.

[1415] Output: User's emotional information.

[1416] Step 9:

[1417] Providing optimal information

[1418] Input: Information about the identified organism and user's emotion information.

[1419] How it works: The server adjusts the content and format of the information it provides based on the emotional information, generating information that best suits the user's state. For example, it changes the depth of information depending on whether a detailed explanation is required or not.

[1420] Output: The adjusted information.

[1421] Step 10:

[1422] Data packet generation and transmission

[1423] Input: Reconciled information.

[1424] How it works: The server packages the tailored information into data packets and sends them to the mobile and remote devices. The data is sent using the HTTP protocol.

[1425] Output: Data packets sent to the mobile and remote devices.

[1426] Step 11:

[1427] Notification and Retention

[1428] Input: Data packets sent to mobile and remote devices.

[1429] Operation: The device analyzes the received data and notifies the user. The notification includes the name of the species and related information. The received information is also saved in local storage as a digital encyclopedia, and is backed up to cloud storage in the background.

[1430] Output: Notification to the user and data backed up to the cloud.

[1431] Step 12:

[1432] Data Synchronization

[1433] Input: Data from local storage and cloud storage.

[1434] How it works: The device synchronizes the updated information of the digital encyclopedia with the remote device. The latest digital encyclopedia data is uploaded via the cloud server, and the parent's smartphone app retrieves it.

[1435] Output: Data synchronized to the remote device.

[1436] Step 13:

[1437] Checking for emotional changes

[1438] Input: Synchronized data and emotion recognition results.

[1439] Operation: The device (parent's smartphone) displays the emotion engine's recognition results, allowing parents to check their child's emotional changes. The emotion recognition results are included in the information sent to the parent's smartphone app.

[1440] Output: Emotional change information that can be checked by parents.

[1441] (Application example 2)

[1442] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1443] The present invention aims to enrich educational experiences by quickly obtaining information about organisms that children discover in natural environments, educational facilities, etc., and by providing appropriate information that responds to the child's emotions. Conventional technologies can identify organisms and provide information, but do not provide information that takes the user's emotions into consideration, making it difficult to flexibly respond to children's interests and level of understanding. Therefore, there is a need for an improved user experience and more effective educational support.

[1444] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving images taken by a mobile terminal, means for analyzing the received images to identify the biological species, means for acquiring information about the identified biological species, means for analyzing the user's emotions using an emotion engine, and means for dynamically adjusting information based on the user's emotions. This makes it possible to quickly identify the biological species based on images taken by a child and provide information that corresponds to the child's emotions.

[1445] A "mobile device" is a portable electronic device such as a smartphone or tablet.

[1446] The "means for receiving images" is a function for transferring captured image data from the mobile terminal to the server and receiving the data.

[1447] "Means for analyzing images" refers to a function that processes received image data using algorithms or machine learning models to analyze its contents.

[1448] "Means for identifying biological species" refers to the function of identifying specific biological species such as plants, animals, insects, etc. from the contents of analyzed image data.

[1449] "Means for obtaining information" refers to a function for searching and obtaining detailed information about the identified biological species from a database, etc.

[1450] The "means for transmitting information" is a function for transferring acquired information to the mobile terminal and the remote terminal.

[1451] The "means for displaying information" is a function for displaying the transmitted information on the display of the mobile terminal or the remote terminal.

[1452] "Means for saving information" refers to a function for saving the displayed information in an internal memory or an external storage device.

[1453] An "emotion engine" is software and hardware that analyzes the user's facial expressions and voice and recognizes their emotions.

[1454] The "means for analyzing emotions" is a function that analyzes the user's emotions using an emotion engine.

[1455] The "means for adjusting information" is a function that dynamically changes the content and format of information according to the user's emotions.

[1456] "Cloud storage" is an online data storage service accessible via the Internet.

[1457] "Means for synchronizing" refers to a function for matching data between multiple terminals in real time or periodically.

[1458] This invention is a system that quickly acquires information about creatures that children discover in the natural environment or educational facilities, and provides appropriate information according to the children's emotions. Specific embodiments for carrying out this invention will be described below.

[1459] Hardware and Software Configuration

[1460] Hardware used

[1461] Mobile Device: A portable electronic device such as smart glasses or a smartphone.

[1462] Remote device: A smartphone or tablet used by a parent or guardian.

[1463] Server: A central computer system for image analysis, sentiment analysis, and information provision.

[1464] Software used

[1465] Image processing: Image analysis using OpenCV.

[1466] Emotion Recognition: Emotion recognition libraries (e.g., FER).

[1467] Machine learning model: Convolutional Neural Network (CNN) used to identify biological species.

[1468] Backend: A web framework such as Flask or Django for sending, receiving, and processing information.

[1469] Cloud storage: Online data storage services such as Amazon S3.

[1470] Database: A database system for managing information, such as MongoDB or MySQL.

[1471] Data processing and calculation

[1472] Image Capture

[1473] Images of living organisms are taken using a mobile device, and the captured image data is saved locally.

[1474] Image upload

[1475] Once a Wi-Fi connection is confirmed, the captured image data is uploaded to the server, where it is stored.

[1476] Image analysis

[1477] The server analyzes the images using machine learning models to identify the species, using a Convolutional Neural Network (CNN) for highly accurate image recognition.

[1478] emotion recognition

[1479] The camera and microphone on the mobile device are used to capture the user's facial expressions and voice, and emotion recognition software (e.g., FER) is used to recognize the user's emotions.

[1480] Information Acquisition and Display

[1481] The server retrieves related information from the database based on the species identification results. This information is formatted in an optimal way based on the user's emotions and sent to mobile and remote devices. The information is displayed on the device and, if necessary, saved in a digital encyclopedia or cloud storage.

[1482] Specific examples

[1483] Photographing cabbage white butterflies in the park

[1484] 1. A child finds a cabbage white butterfly in the park and takes a picture of it with smart glasses.

[1485] 2. The captured images are uploaded from the smart glasses to the server.

[1486] 3. The server performs image analysis and identifies it as a cabbage white butterfly.

[1487] 4. The robot recognizes the user's (child's) emotions from their facial expressions and voice and determines that they are excited.

[1488] 5. The server formats the detailed information and sends it to the smart glasses and the parent's smartphone.

[1489] 6. The transmitted information will be displayed on the device and also saved in the digital encyclopedia.

[1490] Prompt Sentence Examples

[1491] As an example, you can input the following prompts to a generative AI model:

[1492] "Please tell me how to provide information in response to the excitement and emotions of children who take photos of pandas."

[1493] As described above, this system makes it possible to quickly and appropriately provide information about organisms that children are interested in. Furthermore, cooperation with parents will enrich the educational experience for children.

[1494] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1495] Step 1:

[1496] The user (child) takes a photo of a target organism in a natural environment or an educational facility using the camera in the smart glasses. The user's actions include capturing and saving the image of the organism. The input is the image of the organism, and the output is the locally saved image data.

[1497] Step 2:

[1498] When the device (smart glasses) confirms an Internet connection, it uploads the captured image data to the server. The input is the locally stored image data, and the output is the image data transferred to the server.

[1499] Step 3:

[1500] The server receives the uploaded image data and analyzes the image using a Convolutional Neural Network (CNN). This analysis identifies the biological species. The input is the image data transferred to the server, and the output is the identified biological species information.

[1501] Step 4:

[1502] The server retrieves detailed information about the identified species from the database. The input is the identified species information, and the output is detailed information about the species (such as name, characteristics, habitat, etc.).

[1503] Step 5:

[1504] If the user is interested after taking a photo, the device (smart glasses) will capture the user's facial expressions and voice using a camera and microphone. An emotion engine will analyze this data and identify the user's emotions. The input is the user's facial expressions and voice data, and the output is the identified user's emotions (excitement, interest, etc.).

[1505] Step 6:

[1506] The server considers the user's emotional information and adjusts the information about the species to an appropriate format depending on the emotion. For example, if the user is excited, more detailed information is provided. The input is the user's emotional information and detailed information about the species, and the output is information adjusted according to the emotion.

[1507] Step 7:

[1508] The server compiles the adjusted information about the species into a data packet and sends it to a mobile device (smart glasses) and a remote device (parent's smartphone). The input is the adjusted information, and the output is the data sent to the mobile device and the remote device.

[1509] Step 8:

[1510] The devices (smart glasses and parent's smartphone) analyze and display the received data appropriately. The data is displayed as notifications and detailed information to the user, and the child's activities and emotional information to the parent. The input is the transmitted data, and the output is the information displayed to the user and parent.

[1511] Step 9:

[1512] The device saves the displayed information in a digital encyclopedia and also backs it up to cloud storage. The input is the displayed information, and the output is data stored locally and in the cloud.

[1513] Step 10:

[1514] The terminal synchronizes the digital picture book information and the user's emotional information with the remote terminal (parent's smartphone). The input is the update information and emotional information of the digital picture book, and the output is the synchronization result with the remote terminal.

[1515] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1516] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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 voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1517] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1518] [Fourth embodiment]

[1519] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1520] 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.

[1521] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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).

[1522] 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.

[1523] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1524] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1525] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1526] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1527] 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.

[1528] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1529] 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.

[1530] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1531] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1532] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system analyzes images taken with a mobile device, identifies the species, and collects, displays, stores, and shares related information.

[1533] Program Generation and Processing Description

[1534] Image capture and upload

[1535] 1. The user takes an image of a plant, animal, insect, etc. using a smartwatch (mobile device).

[1536] 2. The device temporarily stores the captured image data locally, and if an Internet connection is confirmed, uploads the image data to the server.

[1537] Image analysis

[1538] 3. The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[1539] 4. After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[1540] Information Return and Storage

[1541] 5. The server compiles the acquired information into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[1542] 6. The device analyzes the received data and notifies the user, including the name of the species and related information.

[1543] 7. The device saves the received information as a digital encyclopedia, and also uploads the saved information to cloud storage in the background for backup.

[1544] Cooperation with parents

[1545] 8. The device synchronizes the updated information of the digital encyclopedia with the remote device (parent's smartphone), allowing parents to check information about the creatures their child has photographed in real time.

[1546] Specific examples

[1547] Image Capture Example

[1548] 1. The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[1549] 2. The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1550] Image analysis example

[1551] 1. The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[1552] 2. The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from the database.

[1553] Information Return and Storage Examples

[1554] 1. The server sends the acquired information to the smartwatch and the parent's smartphone.

[1555] 2. The device notifies the user of the received information and saves it in the digital encyclopedia.

[1556] 3. Back up the information stored on your device to the cloud.

[1557] Examples of cooperation with parents

[1558] 1. The device synchronizes the digital encyclopedia information with the parent's smartphone.

[1559] 2. The user (parent) uses their smartphone to view information about the cabbage white butterfly photographed by their child.

[1560] This enriches children's learning experiences and promotes communication with parents.

[1561] The processing flow will be explained below.

[1562] Step 1:

[1563] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[1564] Step 2:

[1565] A user presses the camera shutter to capture an image.

[1566] Step 3:

[1567] The device saves the captured image in temporary storage.

[1568] Step 4:

[1569] The device checks for an Internet connection, and if a connection is confirmed, uploads the captured images from temporary storage to the server.

[1570] Step 5:

[1571] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[1572] Step 6:

[1573] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[1574] Step 7:

[1575] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat, etc.) related to that organism from the database.

[1576] Step 8:

[1577] The server collates the results of the image analysis and related information and generates a data packet to send back to the user.

[1578] Step 9:

[1579] The server sends the generated data packets to the mobile device and the remote device (parent's smartphone).

[1580] Step 10:

[1581] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and a brief description.

[1582] Step 11:

[1583] The terminal stores the received biometric information and additional information in a digital encyclopedia.

[1584] Step 12:

[1585] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[1586] Step 13:

[1587] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[1588] Step 14:

[1589] The user (parent) opens the app and checks the biological information captured by their child.

[1590] Example 1

[1591] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1592] With conventional technology, there are limited means for acquiring, organizing, and storing information about plants, animals, insects, and other organisms discovered in the natural environment, making it particularly difficult for children to identify the species they discover and easily acquire and share that information. Other issues include the difficulty of storing and backing up acquired information and sharing it with parents in real time.

[1593] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1594] In this invention, the server includes means for receiving images captured by a mobile information terminal, means for analyzing the received images to identify biological species, means for retrieving information about the identified biological species from a database, means for transmitting the retrieved information to the mobile information terminal and a remote information terminal, means for displaying the information transmitted to the mobile information terminal and the remote information terminal, means for saving the displayed information in a digital picture book format, means for backing up the retrieved information to cloud storage, and means for synchronizing between the mobile information terminal and the remote information terminal. This enables consistent processing from identifying biological species to retrieving, displaying, saving, and sharing information, thereby enriching children's learning experiences and promoting communication with parents.

[1595] A "portable information terminal" is an electronic device that can be carried by a user, and is a terminal device that has functions such as image capture, data communication, and information display.

[1596] The "means for receiving images" refers to a mechanism by which the server obtains image data sent from the mobile information terminal.

[1597] The "means for analyzing images" is a mechanism that includes an algorithm that analyzes received image data using a machine learning model and identifies the species of the organism.

[1598] "Means for identifying" refers to a mechanism for identifying the biological species identified by image analysis and outputting the identification results.

[1599] "Means for obtaining data from a database" refers to a mechanism for searching and obtaining data from a database that stores detailed information and associated information about an identified biological species.

[1600] The "means for transmitting information" is a mechanism for transmitting data of the acquired organism information to the portable information terminal and the remote information terminal.

[1601] The "means for displaying information" is a mechanism for displaying the transmitted information about the living thing on the screen of the portable information terminal and the remote information terminal.

[1602] "Means for saving in digital encyclopedia format" refers to a mechanism for organizing and saving the displayed information in electronic format and storing it in a form that can be viewed later.

[1603] "Means for backing up to cloud storage" refers to a mechanism for transmitting stored information to an external cloud storage service via the Internet to ensure the safety and durability of data.

[1604] A "synchronization means" is a mechanism for matching data between a mobile information terminal and a remote information terminal and sharing information in real time.

[1605] A "server" is a central management device that accepts requests from a large number of client terminals and provides services and data in response to those requests.

[1606] This invention is a system that can collect information about plants, animals, insects, and other living things that children discover in the natural environment, and organize and store it as a digital picture book. This system has the function of analyzing images taken with a mobile information terminal, identifying the species, and collecting, displaying, saving, and sharing related information.

[1607] Hardware and software used

[1608] The system is implemented using the following major hardware and software:

[1609] Hardware:

[1610] 1. Personal digital assistant: A portable device capable of taking images and transmitting data, such as a smartphone or smartwatch.

[1611] 2. Server: A centralized management unit that provides high-performance data processing and storage.

[1612] 3. Remote information terminal: A device that can receive and display data, such as a parent's smartphone.

[1613] software:

[1614] 1. Camera application: An application for taking pictures on a mobile device.

[1615] 2. Image analysis library: Software that analyzes images using machine learning models such as Convolutional Neural Networks (CNNs).

[1616] 3. Database system: A database for storing information about living organisms.

[1617] 4. Cloud storage service: Online storage for backing up acquired information.

[1618] Specific Embodiments

[1619] Image capture and upload

[1620] The user (child) takes pictures of creatures they find in the natural environment using a mobile information device (e.g., a smartwatch). The images are temporarily stored on the device and then automatically uploaded to the server when an internet connection is confirmed.

[1621] Image analysis

[1622] The server uses a machine learning model (such as CNN) to analyze the image data it receives. The analysis results identify the species, and that information is then queried against a database.

[1623] Displaying and saving information

[1624] The server retrieves information about the identified species from the database and sends it as a data packet to the mobile information device and the parent's remote information device. The received information is notified to the mobile information device and saved in a digital encyclopedia format. The saved information is then backed up to cloud storage.

[1625] Sync and Share

[1626] The device synchronizes updated information from the digital encyclopedia with a remote information terminal, allowing parents to check information about the creatures their children have photographed in real time.

[1627] Specific examples

[1628] Image Capture Example

[1629] A user (child) takes a photo of a cabbage white butterfly they find in a park with their smartwatch. The device temporarily saves the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1630] Image analysis example

[1631] The server analyzes the uploaded image and identifies it as a cabbage white butterfly. The server then retrieves biological information about the butterfly (such as its name, characteristics, and feeding habits) and additional information (such as its habitat and classification) from a database.

[1632] Examples of displaying and saving information

[1633] The server sends the acquired information to the smartwatch and the parent's smartphone. The device notifies the user of the received information and saves it in a digital encyclopedia. The information saved on the device is also backed up to the cloud.

[1634] Examples of cooperation with parents

[1635] The device synchronizes the information in the digital encyclopedia with the parent's smartphone, who then uses the smartphone to view information about the cabbage white butterfly that their child photographed.

[1636] Prompt Sentence Examples

[1637] The system description can be generated by inputting the following prompt sentence into the generative AI model.

[1638] "Please explain the system's process: analyze images of the natural environment taken by a child with a smartwatch, identify and record biological species, and store the image data temporarily on the device. The image data is then analyzed using a machine learning model on the server. During this process, related information is also retrieved from a database, and ultimately the system notifies the user and guardian and stores the information in a digital encyclopedia."

[1639] This enriches children's learning experiences and promotes communication with parents.

[1640] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1641] System program processing flow

[1642] Step 1: Capture an image and save it locally

[1643] A user takes pictures of plants, animals, insects, etc. that they find in a natural environment, such as a park, using a smartwatch (personal digital assistant). When the captured image data is input into the device, the device temporarily stores the image data in local storage. Specifically, it is saved as an image file in the device's built-in memory.

[1644] Input: Image data of a living creature taken by the user with their smartwatch

[1645] Output: Image file saved in local storage

[1646] Step 2: Check your internet connection and upload images

[1647] The device automatically checks for an Internet connection. If Wi-Fi or mobile data communication is enabled, the temporarily stored image data is uploaded to the server. Specifically, the image files on the device are sent to the server using the HTTPS protocol.

[1648] Input: Image file stored in local storage

[1649] Output: Image data sent to the server

[1650] Step 3: Receiving and saving image data

[1651] The server receives the image data sent from the terminal and temporarily stores it. The server stores the received image data as is in a database or file system.

[1652] Input: Image data sent from the device

[1653] Output: Image data stored on the server

[1654] Step 4: Image analysis using machine learning models

[1655] The server analyzes the stored image data using a machine learning model (e.g., a convolutional neural network) to identify the biological species. Specifically, the image data is received as input, the machine learning model analyzes the image, and outputs the identified biological species.

[1656] Input: Image data stored on the server

[1657] Output: Identified species

[1658] Step 5: Get information

[1659] Based on the identified species, the server retrieves related biological information and additional information (such as name, characteristics, and habitat) from the database and executes a database query to extract the required information.

[1660] Input: Identified species

[1661] Output: Detailed information about the organism retrieved from the database

[1662] Step 6: Packaging and sending information

[1663] The server compiles the acquired information into data packets and sends them to the mobile information terminal and remote information terminal. The data packets contain information such as the organism's name, characteristics, and habitat.

[1664] Input: Detailed information about the organism retrieved from the database

[1665] Output: Data packets sent to the mobile device and remote device

[1666] Step 7: Notification and display of information

[1667] The terminal analyzes the data received from the server and notifies the user, who then sees the name of the species and related information on the terminal's display.

[1668] Input: Data packet sent by the server

[1669] Output: Information about the creature displayed on the device's display

[1670] Step 8: Save as a digital encyclopedia

[1671] The device organizes the information it receives in a digital encyclopedia format and saves it in local storage, where it can be referenced later.

[1672] Input: Data packet received from the server

[1673] Output: Information saved in a digital encyclopedia format

[1674] Step 9: Back up to cloud storage

[1675] Back up the digital encyclopedia information stored on your device to cloud storage. Use cloud storage services to send and store data via the Internet.

[1676] Input: Information stored in a digital encyclopedia format

[1677] Output: Information backed up to cloud storage

[1678] Step 10: Sync information with parents

[1679] The device synchronizes updated information about the digital encyclopedia with a remote information device (parent's smartphone). The synchronized data is displayed in real time on the parent's device, allowing the parent to check information about the creatures their child has photographed.

[1680] Input: Digital encyclopedia update information

[1681] Output: Information about the creature displayed on the parent's device

[1682] The above is the specific processing flow of this system.

[1683] (Application example 1)

[1684] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1685] Conventional food delivery services lacked a means for users to easily obtain detailed information about the food and ingredients they purchased, particularly information about their nutritional value, origin, and cultivation method. This meant that users could not fully trust the background information about the ingredients provided, which sometimes led to anxiety when making food choices. Furthermore, the process of efficiently collecting and saving detailed information about ingredients and using it for future orders was cumbersome.

[1686] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1687] In this invention, the server includes means for receiving images taken by a mobile device, means for analyzing the received images to identify objects, and means for acquiring information about the identified objects, allowing users to easily acquire and save detailed information about foods and ingredients and use it for their next food delivery order.

[1688] A "mobile terminal" is a portable communication device, such as a smartphone or tablet, that can capture and receive image data.

[1689] "Means for receiving" refers to the process of transmitting image data captured by a mobile terminal to a server and having the server receive the data.

[1690] "Means for analyzing and identifying objects" refers to the process of analyzing received image data using a machine learning model to identify objects appearing in the image.

[1691] "Means for obtaining information" refers to the process of gathering detailed information about the identified object from a database.

[1692] "Means for transmitting" refers to the process of transmitting the acquired information to the mobile terminal and the remote terminal.

[1693] "Means for displaying" refers to the process of displaying the transmitted information on the screens of the mobile terminal and the remote terminal.

[1694] "Means of storage" refers to the process of saving the displayed information in a digital encyclopedia or cloud storage.

[1695] "Cloud storage backup method" refers to the process of automatically storing stored information in remote storage via the Internet.

[1696] "Means for synchronizing" refers to the process of matching up-to-date information between the mobile device and the remote device.

[1697] "Objects" refer to items that are the subject of identification, such as plants, animals, food, and ingredients, contained in image data.

[1698] "Detailed information" refers to attribute information related to the identified object, such as its name, nutritional value, place of origin, and cultivation method.

[1699] The embodiment of the present invention is a system including a mobile terminal, a remote terminal, a server, a machine learning model, and cloud storage, the details of which are described below.

[1700] Hardware and software used

[1701] Hardware

[1702] Mobile device: A smartphone (iOS / Android) is used. The device allows the user to take pictures of food and ingredients and send the data to the server.

[1703] Server: Uses an AWS EC2 instance to receive and analyze data.

[1704] Cloud storage: Use AWS S3 to back up the information you retrieve.

[1705] software

[1706] Image analysis: Using machine learning models (e.g., YOLO, SSD), the received image data is analyzed to identify the type of object (plant, animal, food, ingredient).

[1707] Database: AWS DynamoDB is used to obtain detailed information about the identified objects (such as name, nutritional value, origin, and cultivation method).

[1708] System Configuration and Operation

[1709] 1. Image capture and upload

[1710] A user takes an image of food or ingredients using a mobile device, which temporarily stores the captured image data locally and uploads it to a server when an internet connection is confirmed.

[1711] 2. Image Analysis

[1712] The server analyzes the received image data using machine learning models (YOLO, SSD) to identify objects (food or ingredients) contained in the image. After identifying the object, it retrieves detailed information about it from AWS DynamoDB.

[1713] 3. Return and Display of Information

[1714] The server assembles the acquired information into data packets and transmits them to the mobile and remote terminals. The mobile and remote terminals analyze the received information and notify the user. This information is displayed on the screens of the mobile and remote terminals.

[1715] 4. Information storage and backup

[1716] The mobile device saves the displayed information as a digital encyclopedia, and the saved information is backed up to AWS S3 in the background.

[1717] 5. Synchronization

[1718] By synchronizing the latest information between mobile and remote devices, users can access information consistently from any device.

[1719] Examples of specific examples and prompt usage

[1720] Specific examples

[1721] The user takes a picture of the tomatoes they purchased with their smartphone.

[1722] The smartphone uploads the images to the AWS cloud.

[1723] The machine learning model identifies it as a tomato and retrieves information about its origin, cultivation method, and nutritional value from a database.

[1724] This information is communicated to the user and stored in their profile within the food delivery service.

[1725] Prompt Sentence Examples

[1726] "Please identify the vegetable in this image and provide details about its origin and nutritional value."

[1727] In this way, by linking mobile devices, remote devices, servers, and cloud storage, users can easily obtain and save detailed information about food and ingredients, and use it the next time they order.

[1728] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1729] Step 1:

[1730] A user uses a smartphone to take a picture of food or ingredients. At this time, the smartphone's camera application is opened and the user presses the button to take a photo, generating image data. Input: Image taken by the user. Output: Image data saved in the smartphone's local storage.

[1731] Step 2:

[1732] The device checks for an Internet connection and uploads the captured image data to the server. Specifically, it reads the image data from local storage and sends it to the server using an HTTP request. Input: Image data saved in local storage. Output: Image data uploaded to the server.

[1733] Step 3:

[1734] The server analyzes the received image data and identifies the object. Here, a machine learning model (e.g., YOLO, SSD) is used to identify the object (food or ingredient) in the image. Input: Image data uploaded to the server. Output: Identification information of the identified object.

[1735] Step 4:

[1736] The server retrieves detailed information about the identified object from the database. It executes a database query to collect information such as the name of the food or ingredient, its nutritional value, origin, and cultivation method. Input: Identification information of the identified object. Output: Detailed information about the object retrieved from the database.

[1737] Step 5:

[1738] The server compiles the obtained detailed information into a data packet and sends it to the mobile device and remote device. Specifically, it generates the data packet in JSON format and returns it to the device as an HTTP response. Input: Detailed information obtained from the database. Output: Detailed information sent to the mobile device and remote device.

[1739] Step 6:

[1740] The device analyzes the details received and notifies the user. It uses the smartphone's notification system to display the details as a pop-up notification or in-app notification. Input: Details sent from the server. Output: Details notified to the user.

[1741] Step 7:

[1742] The device saves the displayed information as a digital encyclopedia and backs it up to cloud storage. The information is saved in local storage and then uploaded to AWS S3 for backup. Input: Detailed information notified to the user. Output: Detailed information saved in local storage and cloud storage.

[1743] Step 8:

[1744] The device synchronizes between the mobile device and the remote device. Sends the latest information to the remote device to keep the data consistent. Input: Details stored in local storage. Output: Details synchronized to the remote device.

[1745] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1746] This invention is a system that acquires information about plants, animals, insects, and other living things that children discover in the natural environment, and by combining it with an emotion engine, recognizes the user's emotions and provides optimal information based on their reaction. This system analyzes images taken by a mobile device, identifies the species of living things, and acquires, displays, saves, and shares related information, and also provides information that takes the user's emotions into consideration.

[1747] Program Generation and Processing Description

[1748] Image capture and upload

[1749] The user takes pictures of plants, animals, insects, etc. using a smartwatch (mobile device).

[1750] The device temporarily stores the captured image data locally, and when an Internet connection is confirmed, the image data is uploaded to the server.

[1751] Image analysis

[1752] The server analyzes the received image data and uses a machine learning model (e.g., a convolutional neural network for image classification) to identify the biological species. This analysis includes a species identification algorithm.

[1753] After the server identifies the species, it retrieves detailed biological information and additional information about the organism (such as its name, characteristics, and habitat) from the database.

[1754] Emotion recognition and information provision

[1755] The emotion engine installed in the device analyzes the user's facial expressions and voice to recognize their emotions. Emotion recognition is performed using a camera and microphone.

[1756] The server takes into account the emotional information it obtains and adjusts the content and format of the information displayed. For example, if the user shows interest, it provides detailed information, and if the user is anxious, it complements the explanation with gentler words.

[1757] The server compiles the information reflecting emotions into a data packet and sends it to the mobile device and remote device (parent's smartphone).

[1758] Information Return and Storage

[1759] The device (smartwatch) analyzes the received data and notifies the user, including the name of the species and related information.

[1760] The information received by the device is saved as a digital encyclopedia, and the saved information is also uploaded to cloud storage in the background for backup.

[1761] Cooperation with parents

[1762] The device synchronizes updates to the digital encyclopedia with a remote device (parent's smartphone), allowing parents to check information about the creatures their children have photographed in real time.

[1763] The device (parent's smartphone) will be able to check changes in the child's emotions, including the results of the emotion engine's recognition.

[1764] Specific examples

[1765] Image Capture Example

[1766] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[1767] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1768] Image analysis example

[1769] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[1770] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[1771] Emotion Recognition Example

[1772] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[1773] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[1774] Information Return and Storage Examples

[1775] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[1776] The terminal notifies the user of the received information and stores it in a digital picture book.

[1777] The information stored on the device is also backed up to the cloud.

[1778] Examples of cooperation with parents

[1779] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[1780] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[1781] This system not only enriches children's learning experiences and promotes communication with parents, but also makes it possible to provide information that takes children's emotions into consideration.

[1782] The processing flow will be explained below.

[1783] Step 1:

[1784] The user finds an object such as a plant, animal, or insect on their smartwatch and activates the camera function.

[1785] Step 2:

[1786] A user presses the camera shutter to capture an image.

[1787] Step 3:

[1788] The device saves the captured image in temporary storage.

[1789] Step 4:

[1790] The device checks for an internet connection.

[1791] Step 5:

[1792] If the device is connected to the Internet, the captured images are uploaded from temporary storage to a server.

[1793] Step 6:

[1794] The server checks the format of the received image data, and if it is a compatible format, starts image processing.

[1795] Step 7:

[1796] The server uses a machine learning model (e.g., a convolutional neural network for image classification) to identify species from the image.

[1797] Step 8:

[1798] If the server successfully identifies the species, it retrieves the biological information and additional information (e.g., name, characteristics, habitat) associated with that organism from the database.

[1799] Step 9:

[1800] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by an emotion engine.

[1801] Step 10:

[1802] The emotion engine recognizes the user's emotions (e.g., surprise, joy, interest, anxiety).

[1803] Step 11:

[1804] The server receives the recognized emotion information and adjusts the content and presentation method of the information to be displayed according to the user's emotion.

[1805] Step 12:

[1806] The server assembles the adjusted information into data packets and sends them to the mobile device and remote device (parent's smartphone).

[1807] Step 13:

[1808] The device (smartwatch) analyzes the received data and notifies the user, including the species name, a brief description, and complementary information based on the emotion.

[1809] Step 14:

[1810] The device stores the received biometric information, additional information, and complementary information according to emotions in a digital encyclopedia.

[1811] Step 15:

[1812] The updated digital encyclopedia on the device is also uploaded to cloud storage in the background for backup.

[1813] Step 16:

[1814] The device synchronizes updated information from the digital encyclopedia with the remote device (parent's smartphone).

[1815] Step 17:

[1816] The user (parent) opens the app and checks the biological information captured by their child along with the recognized emotional changes.

[1817] In this way, the combined emotion engine optimizes children's learning experiences according to their emotional responses and also facilitates communication with parents.

[1818] Example 2

[1819] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1820] Previous systems simply collected information about organisms found in the natural environment, but did not provide information that reflected the user's feelings. Furthermore, saving and sharing information was time-consuming, which sometimes hindered smooth communication between parents and children. This posed a risk of reducing children's motivation to learn, and also led to issues such as the quality of information provided not being sufficiently improved.

[1821] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1822] In this invention, the server includes: means for receiving an image taken by a user using a mobile terminal; means for analyzing the received image and identifying a biological species using a machine learning model; and means for acquiring information about the identified biological species from a database.

[1823] The system has an emotion engine that recognizes the user's emotions, and includes means for analyzing the user's facial expressions and voice, means for adjusting the content and format of the information to be provided based on the emotion information, means for transmitting the acquired information to the mobile terminal and the remote terminal, means for displaying the information transmitted to the mobile terminal and the remote terminal, and means for saving the displayed information. This makes it possible to provide appropriate information according to the user's emotions, and makes it easy to share and manage saved information, which facilitates communication between parents and children and increases motivation to learn.

[1824] A "mobile terminal" is a portable electronic device, such as a smartphone or smartwatch, that is capable of sending and receiving data and running applications.

[1825] "Means for receiving images" refers to a function that allows the server to receive image data captured by the mobile terminal.

[1826] "Means for analyzing images" refers to algorithms or software used to process image data and determine its content.

[1827] A "machine learning model" is a statistical model of an algorithm that learns from data and makes inferences or classifications.

[1828] "Means for identifying biological species" refers to technology for determining the type of organism from analyzed image data.

[1829] A "database" is a structured collection of digital information for efficient storage and management of information.

[1830] "Means of obtaining information" refers to the processes and techniques used to extract the necessary data from the database.

[1831] An "emotion engine" is a software or hardware component that analyzes and recognizes a user's emotions.

[1832] "Means for analyzing facial expressions and voice" refers to technology that identifies emotions from facial expressions captured by a camera and voice captured by a microphone.

[1833] "Means for adjusting the content and format of information" is a function that optimizes the data provided based on the user's emotions.

[1834] A "data packet" is a unit for dividing digital information into small pieces and sending and receiving it over a communication network.

[1835] "Means of storage" refers to the technology for recording acquired information in local storage or cloud storage.

[1836] "Means of synchronization" refers to technology that automatically updates and shares information to maintain data consistency across multiple devices.

[1837] This invention is a system that acquires information on plants, animals, insects, etc. that users discover in the natural environment and combines it with an emotion engine to provide optimal information that takes the user's emotions into consideration. This system analyzes images taken with a mobile device, identifies the species, and acquires, displays, saves, and shares related information.

[1838] Hardware and software used

[1839] The main hardware includes smartphones and smartwatches. These mobile devices are used for photography and emotion recognition, and communicate with a server via an internet connection. The server is responsible for communication, data analysis, and database management, and utilizes cloud storage for backing up and synchronizing information.

[1840] Specific data processing and calculation methods

[1841] Image capture and upload

[1842] The user uses the smartwatch camera to take pictures of plants and animals.

[1843] The device stores the image data locally and uploads it to the server once an internet connection is confirmed.

[1844] Image analysis

[1845] The image data received by the server is analyzed using machine learning models such as Convolutional Neural Networks (CNNs). During the analysis process, image features are extracted and the biological species is identified.

[1846] The server retrieves information about the identified species from a database, including its name, characteristics, and habitat.

[1847] Emotion recognition and information provision

[1848] The device's built-in camera and microphone are used to capture the user's facial expressions and voice.

[1849] The device uses an emotion engine to analyze the captured data and identify the user's emotion.

[1850] The server adjusts the content and format of the information it provides based on emotional information to generate optimal information.

[1851] Information Return and Storage

[1852] The information generated by the server is compiled into data packets and sent to the mobile device and remote device (parent's smartphone).

[1853] The device notifies the user of the received information, saves it in a digital encyclopedia, and also uploads the saved information to cloud storage.

[1854] Cooperation with parents

[1855] The device synchronizes updated information from the digital encyclopedia with a remote device, allowing parents to check their child's activities in real time. It also provides information, including emotion recognition results.

[1856] Specific examples

[1857] Image Capture Example

[1858] The user (child) takes a photo of a cabbage white butterfly they find in the park with their smartwatch.

[1859] The device temporarily stores the image and uploads it to the server once a Wi-Fi connection is confirmed.

[1860] Image analysis example

[1861] The server analyzes the uploaded image and identifies it as a cabbage white butterfly.

[1862] The server retrieves biological information (such as name, characteristics, feeding habits, etc.) and additional information (such as habitat and classification) about the cabbage white butterfly from a database.

[1863] Emotion Recognition Example

[1864] The device's camera and microphone are used to analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[1865] If the user is impressed, provide detailed information; if they are anxious, explain in gentle terms.

[1866] Information Return and Storage Examples

[1867] The server sends emotionally sensitive information to the smartwatch and the parent's smartphone.

[1868] The terminal notifies the user of the received information and stores it in a digital picture book.

[1869] The information stored on the device is also backed up to the cloud.

[1870] Examples of cooperation with parents

[1871] The device synchronizes the information from the digital encyclopedia with the parent's smartphone.

[1872] The user (parent) checks the changes in emotions along with information about the cabbage white butterfly photographed by the child on their smartphone.

[1873] This will enrich children's learning experiences, promote communication between parents and children, and also make it possible to provide information that takes children's emotions into consideration.

[1874] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1875] Step 1:

[1876] Image capture

[1877] Input: Plants, animals, and other objects that the user discovers in the natural environment.

[1878] How it works: A user taps the device screen to capture an image of an object using the smartwatch camera.

[1879] Output: Image data temporarily stored on the smartwatch.

[1880] Step 2:

[1881] Local storage

[1882] Input: Image data captured by the user.

[1883] How it works: The device saves the captured image data to temporary storage on the smartwatch. This process takes place within a few seconds.

[1884] Output: Image data stored in the device's local storage.

[1885] Step 3:

[1886] Image upload

[1887] Input: Image data stored on the smartwatch.

[1888] What it does: The device checks for an internet connection and, if one is available, uploads the image data to the server. It also checks for a Wi-Fi or mobile data connection and sends the data securely.

[1889] Output: Image data transferred to the server.

[1890] Step 4:

[1891] Image data reception

[1892] Input: Image data sent from the device.

[1893] Operation: The server receives the image data and saves it in the specified directory.

[1894] Output: Image data stored on the server.

[1895] Step 5:

[1896] Species identification

[1897] Input: Image data stored on the server.

[1898] How it works: The server analyzes images using machine learning models (e.g., convolutional neural networks for image classification). During the analysis, image features are extracted and the species is identified.

[1899] Output: Identified species.

[1900] Step 6:

[1901] Related information acquisition

[1902] Input: Identified species.

[1903] How it works: The server accesses a database to retrieve detailed information about the organism (e.g., name, characteristics, habitat, etc.) using an SQL query.

[1904] Output: Information about the organism retrieved.

[1905] Step 7:

[1906] Emotional Data Capture

[1907] Input: User's facial expressions and voice.

[1908] How it works: The device uses its camera and microphone to capture the user's facial and voice data.

[1909] Output: User's facial expression and voice data.

[1910] Step 8:

[1911] Emotion analysis

[1912] Input: Captured user facial and voice data.

[1913] How it works: The device uses an emotion engine to analyze the captured data and recognize the user's emotions, determining whether the user is surprised, excited, anxious, etc.

[1914] Output: User's emotional information.

[1915] Step 9:

[1916] Providing optimal information

[1917] Input: Information about the identified organism and user's emotion information.

[1918] How it works: The server adjusts the content and format of the information it provides based on the emotional information, generating information that best suits the user's state. For example, it changes the depth of information depending on whether a detailed explanation is required or not.

[1919] Output: The adjusted information.

[1920] Step 10:

[1921] Data packet generation and transmission

[1922] Input: Reconciled information.

[1923] How it works: The server packages the tailored information into data packets and sends them to the mobile and remote devices. The data is sent using the HTTP protocol.

[1924] Output: Data packets sent to the mobile and remote devices.

[1925] Step 11:

[1926] Notification and Retention

[1927] Input: Data packets sent to mobile and remote devices.

[1928] Operation: The device analyzes the received data and notifies the user. The notification includes the name of the species and related information. The received information is also saved in local storage as a digital encyclopedia, and is backed up to cloud storage in the background.

[1929] Output: Notification to the user and data backed up to the cloud.

[1930] Step 12:

[1931] Data Synchronization

[1932] Input: Data from local storage and cloud storage.

[1933] How it works: The device synchronizes the updated information of the digital encyclopedia with the remote device. The latest digital encyclopedia data is uploaded via the cloud server, and the parent's smartphone app retrieves it.

[1934] Output: Data synchronized to the remote device.

[1935] Step 13:

[1936] Checking for emotional changes

[1937] Input: Synchronized data and emotion recognition results.

[1938] Operation: The device (parent's smartphone) displays the emotion engine's recognition results, allowing parents to check their child's emotional changes. The emotion recognition results are included in the information sent to the parent's smartphone app.

[1939] Output: Emotional change information that can be checked by parents.

[1940] (Application example 2)

[1941] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1942] The present invention aims to enrich educational experiences by quickly obtaining information about organisms that children discover in natural environments, educational facilities, etc., and by providing appropriate information that responds to the child's emotions. Conventional technologies can identify organisms and provide information, but do not provide information that takes the user's emotions into consideration, making it difficult to flexibly respond to children's interests and level of understanding. Therefore, there is a need for an improved user experience and more effective educational support.

[1943] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving images taken by a mobile terminal, means for analyzing the received images to identify the biological species, means for acquiring information about the identified biological species, means for analyzing the user's emotions using an emotion engine, and means for dynamically adjusting information based on the user's emotions. This makes it possible to quickly identify the biological species based on images taken by a child and provide information that corresponds to the child's emotions.

[1944] A "mobile device" is a portable electronic device such as a smartphone or tablet.

[1945] The "means for receiving images" is a function for transferring captured image data from the mobile terminal to the server and receiving the data.

[1946] "Means for analyzing images" refers to a function that processes received image data using algorithms or machine learning models to analyze its contents.

[1947] "Means for identifying biological species" refers to the function of identifying specific biological species such as plants, animals, insects, etc. from the contents of analyzed image data.

[1948] "Means for obtaining information" refers to a function for searching and obtaining detailed information about the identified biological species from a database, etc.

[1949] The "means for transmitting information" is a function for transferring acquired information to the mobile terminal and the remote terminal.

[1950] The "means for displaying information" is a function for displaying the transmitted information on the display of the mobile terminal or the remote terminal.

[1951] "Means for saving information" refers to a function for saving the displayed information in an internal memory or an external storage device.

[1952] An "emotion engine" is software and hardware that analyzes the user's facial expressions and voice and recognizes their emotions.

[1953] The "means for analyzing emotions" is a function that analyzes the user's emotions using an emotion engine.

[1954] The "means for adjusting information" is a function that dynamically changes the content and format of information according to the user's emotions.

[1955] "Cloud storage" is an online data storage service accessible via the Internet.

[1956] "Means for synchronizing" refers to a function for matching data between multiple terminals in real time or periodically.

[1957] This invention is a system that quickly acquires information about creatures that children discover in the natural environment or educational facilities, and provides appropriate information according to the children's emotions. Specific embodiments for carrying out this invention will be described below.

[1958] Hardware and Software Configuration

[1959] Hardware used

[1960] Mobile Device: A portable electronic device such as smart glasses or a smartphone.

[1961] Remote device: A smartphone or tablet used by a parent or guardian.

[1962] Server: A central computer system for image analysis, sentiment analysis, and information provision.

[1963] Software used

[1964] Image processing: Image analysis using OpenCV.

[1965] Emotion Recognition: Emotion recognition libraries (e.g., FER).

[1966] Machine learning model: Convolutional Neural Network (CNN) used to identify biological species.

[1967] Backend: A web framework such as Flask or Django for sending, receiving, and processing information.

[1968] Cloud storage: Online data storage services such as Amazon S3.

[1969] Database: A database system for managing information, such as MongoDB or MySQL.

[1970] Data processing and calculation

[1971] Image Capture

[1972] Images of living organisms are taken using a mobile device, and the captured image data is saved locally.

[1973] Image upload

[1974] Once a Wi-Fi connection is confirmed, the captured image data is uploaded to the server, where it is stored.

[1975] Image analysis

[1976] The server analyzes the images using machine learning models to identify the species, using a Convolutional Neural Network (CNN) for highly accurate image recognition.

[1977] emotion recognition

[1978] The camera and microphone on the mobile device are used to capture the user's facial expressions and voice, and emotion recognition software (e.g., FER) is used to recognize the user's emotions.

[1979] Information Acquisition and Display

[1980] The server retrieves related information from the database based on the species identification results. This information is formatted in an optimal way based on the user's emotions and sent to mobile and remote devices. The information is displayed on the device and, if necessary, saved in a digital encyclopedia or cloud storage.

[1981] Specific examples

[1982] Photographing cabbage white butterflies in the park

[1983] 1. A child finds a cabbage white butterfly in the park and takes a picture of it with smart glasses.

[1984] 2. The captured images are uploaded from the smart glasses to the server.

[1985] 3. The server performs image analysis and identifies it as a cabbage white butterfly.

[1986] 4. The robot recognizes the user's (child's) emotions from their facial expressions and voice and determines that they are excited.

[1987] 5. The server formats the detailed information and sends it to the smart glasses and the parent's smartphone.

[1988] 6. The transmitted information will be displayed on the device and also saved in the digital encyclopedia.

[1989] Prompt Sentence Examples

[1990] As an example, you can input the following prompts to a generative AI model:

[1991] "Please tell me how to provide information in response to the excitement and emotions of children who take photos of pandas."

[1992] As described above, this system makes it possible to quickly and appropriately provide information about organisms that children are interested in. Furthermore, cooperation with parents will enrich the educational experience for children.

[1993] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1994] Step 1:

[1995] The user (child) takes a photo of a target organism in a natural environment or an educational facility using the camera in the smart glasses. The user's actions include capturing and saving the image of the organism. The input is the image of the organism, and the output is the locally saved image data.

[1996] Step 2:

[1997] When the device (smart glasses) confirms an Internet connection, it uploads the captured image data to the server. The input is the locally stored image data, and the output is the image data transferred to the server.

[1998] Step 3:

[1999] The server receives the uploaded image data and analyzes the image using a Convolutional Neural Network (CNN). This analysis identifies the biological species. The input is the image data transferred to the server, and the output is the identified biological species information.

[2000] Step 4:

[2001] The server retrieves detailed information about the identified species from the database. The input is the identified species information, and the output is detailed information about the species (such as name, characteristics, habitat, etc.).

[2002] Step 5:

[2003] If the user is interested after taking a photo, the device (smart glasses) will capture the user's facial expressions and voice using a camera and microphone. An emotion engine will analyze this data and identify the user's emotions. The input is the user's facial expressions and voice data, and the output is the identified user's emotions (excitement, interest, etc.).

[2004] Step 6:

[2005] The server considers the user's emotional information and adjusts the information about the species to an appropriate format depending on the emotion. For example, if the user is excited, more detailed information is provided. The input is the user's emotional information and detailed information about the species, and the output is information adjusted according to the emotion.

[2006] Step 7:

[2007] The server compiles the adjusted information about the species into a data packet and sends it to a mobile device (smart glasses) and a remote device (parent's smartphone). The input is the adjusted information, and the output is the data sent to the mobile device and the remote device.

[2008] Step 8:

[2009] The devices (smart glasses and parent's smartphone) analyze and display the received data appropriately. The data is displayed as notifications and detailed information to the user, and the child's activities and emotional information to the parent. The input is the transmitted data, and the output is the information displayed to the user and parent.

[2010] Step 9:

[2011] The device saves the displayed information in a digital encyclopedia and also backs it up to cloud storage. The input is the displayed information, and the output is data stored locally and in the cloud.

[2012] Step 10:

[2013] The terminal synchronizes the digital picture book information and the user's emotional information with the remote terminal (parent's smartphone). The input is the update information and emotional information of the digital picture book, and the output is the synchronization result with the remote terminal.

[2014] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2015] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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 voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2016] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2017] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2018] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2019] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2020] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2021] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2022] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2023] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2024] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2025] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2026] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2027] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2028] 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.

[2029] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2030] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2031] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2032] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2033] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2034] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2035] The following is further disclosed regarding the above embodiment.

[2036] (Claim 1)

[2037] means for receiving images captured by the mobile terminal;

[2038] means for analyzing the received image to identify the biological species;

[2039] a means for obtaining information about the identified species;

[2040] means for transmitting the acquired information to the mobile terminal and the remote terminal;

[2041] means for displaying the information transmitted to the mobile terminal and the remote terminal;

[2042] means for saving the displayed information;

[2043] A system including:

[2044] (Claim 2)

[2045] 10. The system of claim 1, further comprising means for backing up the retrieved information to cloud storage.

[2046] (Claim 3)

[2047] 10. The system of claim 1, further comprising means for synchronizing between the mobile terminal and the remote terminal.

[2048] "Example 1"

[2049] (Claim 1)

[2050] means for receiving an image captured by a portable information terminal;

[2051] means for analyzing the received image to identify the biological species;

[2052] means for retrieving information about the identified species from a database;

[2053] means for transmitting the acquired information to the mobile information terminal and the remote information terminal;

[2054] means for displaying the information transmitted to the portable information terminal and the remote information terminal;

[2055] means for saving the displayed information in a digital picture book format;

[2056] A system including:

[2057] (Claim 2)

[2058] 10. The system of claim 1, further comprising means for backing up the retrieved information to cloud storage.

[2059] (Claim 3)

[2060] 10. The system of claim 1, further comprising means for synchronizing between the handheld information terminal and the remote information terminal.

[2061] "Application Example 1"

[2062] (Claim 1)

[2063] means for receiving images captured by the mobile terminal;

[2064] means for analyzing the received image to identify the object;

[2065] means for obtaining information about the identified object;

[2066] means for transmitting the acquired information to the mobile terminal and the remote terminal;

[2067] means for displaying the information transmitted to the mobile terminal and the remote terminal;

[2068] means for saving the displayed information;

[2069] a means for obtaining detailed information about food and ingredients;

[2070] A system including:

[2071] (Claim 2)

[2072] 10. The system of claim 1, further comprising means for backing up the retrieved information to cloud storage.

[2073] (Claim 3)

[2074] 10. The system of claim 1, further comprising means for synchronizing between the mobile terminal and the remote terminal.

[2075] "Example 2: Combining Emotion Engines"

[2076] (Claim 1)

[2077] means for receiving images taken by a user using a mobile terminal;

[2078] means for analyzing the received images and identifying the biological species using a machine learning model;

[2079] means for retrieving information about the identified species from a database;

[2080] It has an emotion engine that recognizes the user's emotions and has a means of analyzing the user's facial expressions and voice;

[2081] A means for adjusting the content and format of information provided based on emotional information;

[2082] means for transmitting the acquired information to the mobile terminal and the remote terminal;

[2083] means for displaying the information transmitted to the mobile terminal and the remote terminal;

[2084] means for saving the displayed information;

[2085] A system including:

[2086] (Claim 2)

[2087] 10. The system of claim 1, further comprising means for backing up the retrieved information to cloud storage.

[2088] (Claim 3)

[2089] 10. The system of claim 1, further comprising means for synchronizing between the mobile terminal and the remote terminal.

[2090] "Application example 2 when combining emotion engines"

[2091] (Claim 1)

[2092] means for receiving images captured by the mobile terminal;

[2093] means for analyzing the received image to identify the biological species;

[2094] a means for obtaining information about the identified species;

[2095] means for transmitting the acquired information to the mobile terminal and the remote terminal;

[2096] means for displaying the information transmitted to the mobile terminal and the remote terminal;

[2097] means for saving the displayed information;

[2098] means for analyzing a user's emotions using an emotion engine;

[2099] means for dynamically adjusting information based on user emotions;

[2100] A system including:

[2101] (Claim 2)

[2102] 10. The system of claim 1, further comprising means for backing up the retrieved information to cloud storage.

[2103] (Claim 3)

[2104] 10. The system of claim 1, further comprising means for synchronizing between the mobile terminal and the remote terminal. [Explanation of symbols]

[2105] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving images captured by the mobile terminal; means for analyzing the received image to identify the biological species; a means for obtaining information about the identified species; means for transmitting the acquired information to the mobile terminal and the remote terminal; means for displaying the information transmitted to the mobile terminal and the remote terminal; means for saving the displayed information; A system including:

2. The system of claim 1 , further comprising means for backing up the retrieved information to cloud storage.

3. 10. The system of claim 1, further comprising means for synchronizing between the mobile terminal and the remote terminal.

Images