system

Abstract

We provide the system. [Solution] A means of receiving handwritten input and converting it into digital data, A means for analyzing converted digital data to identify character or graphic information, A means of generating feedback using artificial intelligence based on identified information, A means of sending the generated feedback to the user's device and displaying it visually, A means of receiving further handwritten input from the user and repeating the process in the same way, A system that includes this.

Description

Technical Field

[0004] , , , ,

[0005] , , , , , ,

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

Background Art

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional learning and thinking development methods using a handwritten blackboard or notes, there is a problem that the user has limitations when deepening thinking or obtaining new perspectives. In particular, it is difficult to cross-reference the handwritten records of ideas and concepts, and there is a lack of support for promoting flexible and creative thinking. The object of this invention is to overcome these limitations by utilizing handwritten input to deepen the user's ideas in real time and provide new perspectives.

Means for Solving the Problems

[0005] This invention provides a system that receives handwritten input as digital data, analyzes this data, and uses artificial intelligence to generate feedback based on the identified information. This allows users to perform handwritten input in a natural way and deepen their thinking based on the resulting feedback. The system generates feedback in real time and displays it visually on the user's device, promoting interaction and supporting memory retention and the acquisition of new perspectives. Furthermore, by learning from past handwritten input history and feedback history, it provides more optimized feedback, promoting flexible and creative thinking.

[0006] "Handwriting input" is the process by which a digital system reads analog data generated when a user manually draws letters or shapes.

[0007] "Digital data" refers to data that represents analog information in a digital format and is in a format that can be processed by a computer.

[0008] "Analysis" is the process of analyzing digital data to extract useful information and obtain specific results or outputs.

[0009] Artificial intelligence is a technology that imitates or complements human intellectual processes, and is a system that performs data analysis, judgment, and learning.

[0010] "Feedback" refers to responses or information provided in response to specific inputs or actions that help to improve user understanding and behavior.

[0011] A "touch panel" is an input device that users can operate by directly touching it, and is used to input digital data using fingers or a stylus.

[0012] "Coordinate data" refers to a numerical representation used to define a specific location, typically expressed as a combination of the x and y axes. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention implements a digital blackboard system by configuring a computer system centered on user handwriting input. The specific processing and usage methods of the system will be described below from the perspectives of the server, terminal, and user.

[0035] 1. User operation

[0036] Users handwrite ideas on specific themes or issues onto a digital whiteboard. This operation is performed using a touch panel or stylus, allowing for intuitive drawing.

[0037] 2. Device functions

[0038] The terminal captures handwritten input from the user. The captured data is temporarily stored as coordinate data. Next, the terminal formats the data and sends it to a server via the internet. This formatted data is suitable for OCR and pattern recognition.

[0039] 3. Server processing

[0040] The server receives handwritten data sent from the terminal and performs analysis. This analysis process uses OCR (Optical Character Recognition) technology to identify characters and recognizes shapes and symbols through pattern recognition. Based on the recognized information, artificial intelligence generates appropriate feedback. This feedback includes information, suggestions, and solutions related to what the user has written.

[0041] 4. Providing feedback

[0042] Feedback generated from the server is sent to the terminal. The terminal displays the feedback in a user-friendly format. This display may include text information and, in some cases, additional graphics.

[0043] 5. User interaction

[0044] Based on the feedback provided by the device, users can develop new ideas or ask further questions. The process restarts once the user provides additional input.

[0045] As a concrete example, when a user is brainstorming proposals on the theme of "energy efficiency," they write relevant shapes and keywords on a digital whiteboard. The server then analyzes this and provides feedback on information and the latest technologies that can help improve energy efficiency. Based on this feedback, the user can further develop their ideas and find new approaches.

[0046] Thus, the embodiment of the present invention provides an interactive learning and idea development system that utilizes handwriting input, enabling real-time knowledge deepening and support for creative thinking.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] The device captures handwritten input from the user on the digital whiteboard. The handwritten data is recorded as coordinates and strokes and formatted into text or shapes.

[0050] Step 2:

[0051] The terminal performs preprocessing on the formatted handwritten data. This process involves noise reduction and data normalization to prepare the data for improved analysis accuracy.

[0052] Step 3:

[0053] The terminal sends pre-processed handwritten data to the server via the internet. The data is encrypted before transmission to prevent data corruption during transit.

[0054] Step 4:

[0055] The server receives handwritten data sent from the terminal. This data is analyzed using OCR technology to identify characters and graphic information.

[0056] Step 5:

[0057] The server activates artificial intelligence based on the analysis results to generate feedback tailored to the user's handwritten content. This feedback includes relevant information, suggestions, and explanations.

[0058] Step 6:

[0059] The server packages the generated feedback and sends it to the terminal in an encrypted format. It monitors the transmission status and confirms that the transmission was successful.

[0060] Step 7:

[0061] The device receives feedback sent from the server. The received feedback is then structured as text and graphics for easy viewing by the user.

[0062] Step 8:

[0063] The user reviews the feedback displayed on the device and enters new ideas or additional questions by hand. This action restarts the process, allowing the dialogue to continue.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] Conventional systems that analyze handwriting input have struggled to provide real-time, intuitive user interaction, resulting in insufficient support for effective learning and creative thinking. This challenge needs to be addressed by achieving high-precision handwriting recognition and providing relevant information immediately.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes means for receiving handwritten input and converting it into data, means for analyzing the converted data and identifying information, means for generating a response using machine learning based on the identified information, means for acquiring coordinate data in real time and temporarily recording it, and means for formatting the data and transmitting it through a communication network. This enables effective information provision and continuous interaction based on handwritten input by the user.

[0069] "Handwriting input" refers to a method for users to manually draw or write characters or shapes.

[0070] "Data" refers to information representation obtained by converting handwritten input into a digital format.

[0071] "Information" refers to the identification results, such as characters and shapes, obtained from analyzed data.

[0072] "Machine learning" is a technology that recognizes patterns and rules from data and automatically generates feedback.

[0073] A "response" is a feedback message generated by the server for the user.

[0074] "Real-time" refers to the property of an action or process occurring immediately.

[0075] "Coordinate data" refers to numerical information that indicates the position of handwritten input.

[0076] A "communication network" is a digital network used for exchanging data.

[0077] This invention constitutes a system that analyzes a user's handwritten data via a digital input system and provides real-time feedback. Specific embodiments of the system are described below from the perspectives of the server, terminal, and user.

[0078] User actions:

[0079] Users input text and shapes by hand on a digital device using a touch panel or stylus pen. For example, this digital system can be used in educational settings to visualize ideas related to "energy efficiency."

[0080] Device features:

[0081] The terminal detects the user's handwritten input and converts it into digital coordinate data. The converted data is temporarily stored in the device memory. Next, the terminal formats the coordinate data into a format that can be used by OCR (optical character recognition) and pattern recognition technologies, and sends it to a server via the internet.

[0082] Server processing:

[0083] The server receives formatted data sent from the terminal and uses OCR technology to analyze the text and shapes. Based on the analyzed information, the server generates relevant feedback using a generative AI model. This feedback is provided to the user in the form of suggestions and solutions.

[0084] For example, if a user writes sketches or keywords related to "energy efficiency" on a digital board, the server analyzes the input and suggests the latest technological information and efficiency methods related to it. This allows the user to gain new insights.

[0085] Example of a prompt:

[0086] "Please provide feedback on the latest technologies and methods related to ideas about energy efficiency."

[0087] Thus, this invention provides an interactive learning environment that utilizes the user's handwriting input, and plays a role in supporting problem-solving and creative thinking.

[0088] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0089] Step 1:

[0090] Users input ideas and shapes by hand on a digital device using a touch panel or stylus pen. The input is in the form of analog lines and letters, and is drawn on the device in real time. This is the initial data input for this system.

[0091] Step 2:

[0092] The device detects the user's handwriting input and collects the positional information of the entered lines and characters as coordinate data. This coordinate data is temporarily stored in the device's memory. Specifically, it continuously acquires coordinate points instantaneously in accordance with the user's movements.

[0093] Step 3:

[0094] The terminal formats the stored coordinate data and converts it into a format suitable for OCR and pattern recognition. It aligns the coordinates of the input handwritten data and outputs the result in a digital format that is easy to analyze. This formatted data is then passed on to subsequent processing.

[0095] Step 4:

[0096] The terminal transmits the formatted digital data to the server via the internet. Specifically, the terminal performs a procedure to transfer the data reliably and quickly using a transmission protocol. This prepares the data for the server to use in the next analysis step.

[0097] Step 5:

[0098] The server receives data transmitted from the terminal, identifies characters using OCR technology, and analyzes shapes and symbols using pattern recognition technology. The input is pre-formatted digital data, and the output is the interpreted strings and structured data resulting from the analysis. Specifically, the recognized characters and shapes are compared against known patterns in a database.

[0099] Step 6:

[0100] The server generates feedback using a generative AI model based on the analyzed information. The input is analyzed text and graphic information, which the server uses to create feedback containing appropriate information and suggestions. The AI ​​model references past data and related information to output the most relevant response.

[0101] Step 7:

[0102] The feedback generated from the server is sent back to the terminal. The terminal displays this feedback in a user-friendly format. This is usually presented as text information, but may include additional graphics or charts in some cases. This allows the user to visually obtain information and continue interacting with the device based on the output.

[0103] (Application Example 1)

[0104] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0105] Traditional handwriting input systems primarily relied on individual users independently inputting information and receiving feedback separately, making it difficult to achieve effective interaction in real-world gatherings and workshops involving multiple users. Furthermore, there was a lack of effective means to share ideas among participants and facilitate collaborative work.

[0106] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0107] In this invention, the server includes means for receiving handwritten input and converting it into digital information, means for analyzing the converted digital information to identify symbolic or graphic information, and means for generating a response using a machine learning model based on the identified information. This makes it possible to synchronize and share information among multiple users, and can support collaborative work in real-world gatherings.

[0108] "Handwriting input" refers to a method in which users manually input symbols and shapes using a tactile panel or similar device.

[0109] "Means of converting to digital information" refers to a device or process that converts handwritten input into an electronic format.

[0110] "Means for identifying symbolic or graphic information" refers to a device or program for recognizing characters or graphics from converted digital information.

[0111] "Means for generating responses using machine learning models" refers to a device or program that uses a trained algorithm based on recognized information to derive an appropriate response to the user.

[0112] A "user terminal" is an electronic device used by a user to receive or input information.

[0113] "Means for synchronizing and sharing information" refers to a device or program that integrates data entered by multiple users in real time, making it accessible to all simultaneously.

[0114] "Collaborative work in real-world gatherings" refers to activities in which many participants work together in a physical setting to generate new ideas.

[0115] This invention relates to a system including a terminal that allows a user to input handwritten information using a tactile panel and converts it into digital information. The terminal captures the user's input as location information, formats the data, and sends it to a server. The server analyzes the received digital information and identifies symbols or graphic information. Based on the identified information, it uses a machine learning model to generate an appropriate response for the user.

[0116] Specifically, the terminal uses software such as PIL (Python Imaging Library) and pytesseract to efficiently process handwritten data and convert it into digital data. The converted data is sent to a server via the internet. The server utilizes OCR technology and machine learning algorithms to analyze this data and generate the information and suggestions the user requests.

[0117] The server sends the generated response to the user's terminal, which then visually presents the response to the user. The user can then refer to this feedback and make further handwritten input. This process supports collaborative work in real-world gatherings and provides a means for synchronizing and sharing information among multiple users.

[0118] For example, if participants are discussing "energy efficiency" in a workshop, they can deepen the discussion by having the server analyze their handwritten ideas and related diagrams and immediately return relevant, up-to-date technical information and suggestions.

[0119] An example of a prompt for a generative AI model is shown below: "Analyze the given handwritten input image and generate proposals for new energy efficiency technologies."

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The user uses a haptic panel to input handwriting. The input data consists of characters and shapes drawn by the user, which the device captures as location information. This location information then serves as foundational data for later digitization.

[0123] Step 2:

[0124] The device uses the captured location information to convert it into digital data using PIL (Python Imaging Library) and pytesseract. The input here is the location information obtained in step 1, and the output is text data processed through optical character recognition. The converted text data is temporarily stored locally.

[0125] Step 3:

[0126] The terminal sends the converted text data to the server via the internet. The input is text data, and the output is a signal indicating that the transmission to the server is complete. The requests library is used for this communication.

[0127] Step 4:

[0128] The server receives text data sent from the terminal and performs analysis using OCR technology and machine learning algorithms. The input for the analysis is the text data received by the server, and the output is the generation of response information based on the analysis results. At this stage, prompt sentences are formed to understand the meaning of the text data and generate possible suggestions.

[0129] Step 5:

[0130] The server processes the prompt using a generative AI model and creates a response that can be provided to the user. The prompt created in step 4 is used as input, and appropriate information or solutions are returned as output.

[0131] Step 6:

[0132] The server sends the generated response to the terminal. In this transmission process, the prepared response is redirected to the terminal. The input is the generated response data, and the output is the acknowledgment signal.

[0133] Step 7:

[0134] The terminal visually displays the response received from the server to the user. The user can then use this feedback to make further handwritten input. The input is the response data from the server, and the output is the action of displaying it on the screen.

[0135] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0136] This invention combines a digital interactive blackboard system with an emotion engine to provide feedback that simultaneously considers the user's handwritten input and their emotional state. In implementing this invention, the server, terminal, and user elements work in coordination.

[0137] 1. User operation

[0138] Users write letters and draw diagrams by hand on a digital whiteboard to record their thoughts. This operation is performed using the device's touch panel, and actions and patterns that may influence the user's emotional state are recorded in real time.

[0139] 2. Device functions

[0140] The device captures the user's handwritten data and converts it into digital data. Furthermore, it collects data to infer the user's emotional state from factors such as writing speed and pressure. An emotion engine analyzes this data to identify the user's emotional state.

[0141] 3. Server processing

[0142] The server receives handwritten data sent from the terminal and analyzes the character and graphic information using OCR technology. Based on the analyzed data, artificial intelligence generates relevant feedback. At the same time, it incorporates emotional state information from the emotion engine to adjust the content and tone of the feedback.

[0143] 4. Providing and displaying feedback

[0144] The server generates feedback, which is then sent to the terminal. The terminal visually displays the feedback to the user, providing emotionally resonant content. This enables flexible communication that responds to the user's reactions.

[0145] 5. User interaction

[0146] Based on the displayed feedback, users make new inputs, deepen their thinking, and work on solving further problems. Throughout this process, the emotion engine constantly monitors the user's emotional state to ensure the feedback is appropriate for them.

[0147] For example, when a user is contemplating a difficult concept, if the emotion engine detects the user's frustration, the server provides gentle, encouraging feedback that reflects that emotional state. In this way, the present invention functions as an interactive digital whiteboard that enhances the conversational experience while considering the user's emotions.

[0148] The following describes the processing flow.

[0149] Step 1:

[0150] The device captures handwritten data entered by the user on the digital whiteboard. This data includes information such as writing speed, pen pressure, and stroke direction.

[0151] Step 2:

[0152] The device converts the collected handwritten data into a digital format while simultaneously formatting auxiliary data (such as speed and pressure) that suggests emotion for the emotion engine.

[0153] Step 3:

[0154] The device transmits formatted handwritten data and sentiment-indicating data to a server via the internet. Data transmission is protected by encryption.

[0155] Step 4:

[0156] The server analyzes the handwritten data received from the terminal using OCR technology to identify characters and graphic information. Based on this analysis, it generates appropriate feedback candidates.

[0157] Step 5:

[0158] The server activates the emotion engine and analyzes emotion suggestion data to determine the user's emotional state. Emotional states such as frustration, interest, and concentration are identified.

[0159] Step 6:

[0160] The server adjusts the content and tone of feedback based on the user's emotional state. For example, if frustration is detected, it generates feedback that includes encouragement.

[0161] Step 7:

[0162] The server sends the refined feedback to the terminal. This feedback may include relevant information, suggestions, or specific responses to the user.

[0163] Step 8:

[0164] The device visually displays feedback received from the server in a user-friendly format. This feedback display includes colors and messages tailored to the user's emotional state.

[0165] Step 9:

[0166] The user reviews the displayed feedback and enters new questions or ideas by hand. The process is then repeated based on the user's actions.

[0167] (Example 2)

[0168] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0169] Conventional digital blackboard systems simply convert and display handwritten input as digital data, failing to provide feedback that takes into account the user's emotional state. Therefore, it was difficult to provide appropriate support tailored to the user's thoughts and feelings, and thus, an interactive learning experience could not be realized.

[0170] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0171] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the digital data to identify character or graphic information, and means for inferring the user's emotional state based on the user's input speed and pen pressure information. This enables the provision of feedback that is sensitive to the user's emotions and facilitates interactive communication.

[0172] "Handwriting input" refers to the act of a user drawing letters or shapes on a touch panel device using a pen or their finger.

[0173] "Converting to digital data" refers to the process of converting analog input information into an electronic data format, making it data that can be processed by a computer.

[0174] "Emotional state" refers to the user's psychological state, encompassing the totality of emotions inferred from factors such as input speed and pen pressure.

[0175] "Feedback" refers to the responses and advice that a system generates and provides to a user in response to their input and emotional state.

[0176] "Artificial intelligence" refers to a computer system that analyzes input data and automatically solves problems or makes decisions based on the information it has learned.

[0177] A "generative AI model" refers to an algorithmic model that learns from diverse data and generates output tailored to a specific task.

[0178] "Visual display" refers to showing information to the user through the device screen, and includes presentation in the form of text, images, and animations.

[0179] This invention allows users to express their thoughts and emotional states on a digital whiteboard by using a touch panel-equipped terminal to input handwritten information. The terminal is equipped with a pressure sensor that collects data such as the position, pressure, and speed of the characters and figures written by the user with high precision and converts it into digital data.

[0180] This converted data is sent to a server, which uses OCR technology to identify the information in the characters and shapes. Furthermore, by analyzing the user's input speed and pen pressure data obtained from the terminal, the emotion engine infers the user's emotional state.

[0181] Based on this data, the server generates feedback using a generative AI model that has learned from diverse data. The generated feedback takes emotional states into account and is delivered to the user in an appropriate tone. This feedback is sent to the device and displayed visually to the user. As a result, the user receives emotionally resonant, interactive feedback and deepens their thinking by providing further input.

[0182] For example, if a user types "I don't understand" while thinking about a difficult concept, the emotion engine detects the user's frustration, and the server provides gentle, encouraging feedback such as "You're almost there, keep trying." This allows the system to deeply understand the user's thoughts and feelings, enabling it to provide appropriate support in learning and work.

[0183] An example of a prompt message is, "Generate gentle and encouraging feedback to help the user solve the challenge they are currently facing." In this way, the present invention enables emotion-based interactive communication.

[0184] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0185] Step 1:

[0186] Users input characters and shapes by hand on a touch-panel device. The device receives this handwriting input via a pressure sensor and collects data such as position, pressure, and speed in real time. This converts the input data from analog to digital format and stores it in a database.

[0187] Step 2:

[0188] The terminal sends the collected digital data to the server. The server applies OCR technology to analyze the received data, identifying information in characters and shapes. This identified data is organized within the server and stored in a database. As a result, the handwritten content is output as structured digital information.

[0189] Step 3:

[0190] The server receives input speed and pressure information from the terminal and analyzes it using an emotion engine. The analysis results in an inference of the user's emotional state. Specifically, fast input speed and high pressure may indicate tension or stress, which the emotion engine detects. This analysis result is then prepared for the next step.

[0191] Step 4:

[0192] The server generates feedback using a generative AI model based on the identified handwritten data and sentiment analysis results. This prompt text and generative AI model are used to derive content that takes the user's emotions into consideration. For example, if the user writes "I don't understand," the AI ​​will generate an encouraging message such as "Calm down and try again." This ensures that the user receives appropriate feedback.

[0193] Step 5:

[0194] The generated feedback is sent from the server to the device, which displays it visually. The user receives this feedback and either provides further input or deepens their thinking. In this process, the generated feedback plays a role in understanding the user's feelings and providing a better experience.

[0195] (Application Example 2)

[0196] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0197] Digital interactive blackboard systems are required to provide feedback that not only accepts the user's handwritten input but also takes into account their emotional state at the time of input. Implementing such functionality can improve support for participants in workshops and educational seminars, thereby enhancing learning and comprehension.

[0198] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0199] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the converted digital data to identify character or graphic information, and means for inferring the user's emotional state using an emotion analysis engine and adjusting the feedback based on that information. This enables flexible communication and feedback provision that takes into account both the user's handwritten input and emotional state.

[0200] "Handwriting input" refers to the act of a user drawing letters or shapes by hand using a touch panel or pen device.

[0201] "Digital data" refers to information that has been converted from handwritten input into a digital format, and is in a format that can be processed within a computer system.

[0202] An "artificial intelligence engine" is an algorithm or program used to analyze input data and generate appropriate feedback.

[0203] "Feedback" refers to information such as responses and comments that are generated in response to user input or status.

[0204] An "emotion analysis engine" is an algorithm or program that infers a user's psychological or emotional state from their input data and uses that information to adjust the system's response.

[0205] "Information equipment" refers to terminals and devices used for various information processing, including the display of digital data, and generally includes smartphones and tablets.

[0206] A "contact detection device" is a device used to detect a user's handwritten input, and typically uses a touchscreen or stylus pen.

[0207] The system implementing this invention consists of a terminal that receives user handwritten input and converts it into digital data, a server that analyzes the digital data, and a device that provides feedback. The specific operation of each of these elements is described below.

[0208] The device converts information entered by the user via handwriting using a touchscreen or stylus pen into digital data in real time. The user's handwriting speed and pressure are also captured simultaneously, and this data is used to infer the user's emotional state.

[0209] The server processes the digital data transmitted from the terminal. First, it uses OCR technology to identify characters and shapes, and then applies a generative AI model using this information to generate feedback. Furthermore, it uses an emotion analysis engine to infer the user's emotional state from data such as handwriting speed and pressure, and adjusts the feedback accordingly.

[0210] The generated feedback is transmitted to information devices and displayed visually to the user. In this process, the feedback is provided in a way that takes the user's emotional state into consideration, playing a role in facilitating smooth communication.

[0211] For example, if the emotion analysis engine infers that a participant is feeling impatient while learning a new concept in a workshop, the server will generate and display gentle feedback such as, "Let's calm down and learn one step at a time."

[0212] As a concrete example, an example of a prompt message is shown below.

[0213] "Strong pen pressure and fast input have been detected. Please generate feedback to promote relaxation."

[0214] Thus, the present invention makes it possible to provide an interactive learning experience through emotion-responsive feedback.

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] Users input handwritten data using a touchscreen on an information device. This input behavior is captured, and characteristic data such as pen pressure and speed are collected simultaneously. This generates digital data of the handwritten characters and shapes.

[0218] Step 2:

[0219] The terminal converts the collected handwritten input data into a digital format and sends that digital data to the server. The characteristics of the input data (speed, pressure) are transmitted separately for sentiment analysis. The handwritten data is supplied to the server as input and identified as handwritten information and characteristic data.

[0220] Step 3:

[0221] The server uses OCR technology to recognize and analyze characters and shapes from incoming digital data. This analysis process generates specific character information as output. The calculated character information forms the basis for feedback generation.

[0222] Step 4:

[0223] The server uses an emotion analysis engine to analyze feature data and infer the user's emotional state. It performs data calculations based on the pressure and speed information of the input data and outputs the inferred emotional state.

[0224] Step 5:

[0225] The server utilizes a generative AI model to generate feedback based on analyzed text information and emotional states. A prompt sentence reflecting the emotional state is used as input, and text information is output as feedback.

[0226] Step 6:

[0227] The server sends the generated feedback to the information device, where it is displayed. This feedback is visualized in a way that takes the user's emotional state into consideration, guiding further handwriting input. The received output text is then displayed on the information device.

[0228] Step 7:

[0229] The user uses the displayed feedback to perform the next handwriting input, and this process is repeated. New handwriting input is provided by the user, and the output returns to step 1 again.

[0230] This process provides users with flexible, emotionally resonant feedback in real time.

[0231] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0232] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0233] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0234] [Second Embodiment]

[0235] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0236] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0237] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0238] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0239] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0240] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0241] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0242] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0243] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0244] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0245] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0246] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0247] This invention implements a digital blackboard system by configuring a computer system centered on user handwriting input. The specific processing and usage methods of the system will be described below from the perspectives of the server, terminal, and user.

[0248] 1. User operation

[0249] Users handwrite ideas on specific themes or issues onto a digital whiteboard. This operation is performed using a touch panel or stylus, allowing for intuitive drawing.

[0250] 2. Device functions

[0251] The terminal captures handwritten input from the user. The captured data is temporarily stored as coordinate data. Next, the terminal formats the data and sends it to a server via the internet. This formatted data is suitable for OCR and pattern recognition.

[0252] 3. Server processing

[0253] The server receives handwritten data sent from the terminal and performs analysis. This analysis process uses OCR (Optical Character Recognition) technology to identify characters and recognizes shapes and symbols through pattern recognition. Based on the recognized information, artificial intelligence generates appropriate feedback. This feedback includes information, suggestions, and solutions related to what the user has written.

[0254] 4. Providing feedback

[0255] Feedback generated from the server is sent to the terminal. The terminal displays the feedback in a user-friendly format. This display may include text information and, in some cases, additional graphics.

[0256] 5. User interaction

[0257] Based on the feedback provided by the device, users can develop new ideas or ask further questions. The process restarts once the user provides additional input.

[0258] As a concrete example, when a user is brainstorming proposals on the theme of "energy efficiency," they write relevant shapes and keywords on a digital whiteboard. The server then analyzes this and provides feedback on information and the latest technologies that can help improve energy efficiency. Based on this feedback, the user can further develop their ideas and find new approaches.

[0259] Thus, the embodiment of the present invention provides an interactive learning and idea development system that utilizes handwriting input, enabling real-time knowledge deepening and support for creative thinking.

[0260] The following describes the processing flow.

[0261] Step 1:

[0262] The device captures handwritten input from the user on the digital whiteboard. The handwritten data is recorded as coordinates and strokes and formatted into text or shapes.

[0263] Step 2:

[0264] The terminal performs preprocessing on the formatted handwritten data. This process involves noise reduction and data normalization to prepare the data for improved analysis accuracy.

[0265] Step 3:

[0266] The terminal sends pre-processed handwritten data to the server via the internet. The data is encrypted before transmission to prevent data corruption during transit.

[0267] Step 4:

[0268] The server receives handwritten data sent from the terminal. This data is analyzed using OCR technology to identify characters and graphic information.

[0269] Step 5:

[0270] The server activates artificial intelligence based on the analysis results to generate feedback tailored to the user's handwritten content. This feedback includes relevant information, suggestions, and explanations.

[0271] Step 6:

[0272] The server packages the generated feedback and sends it to the terminal in an encrypted format. It monitors the transmission status and confirms that the transmission was successful.

[0273] Step 7:

[0274] The device receives feedback sent from the server. The received feedback is then structured as text and graphics for easy viewing by the user.

[0275] Step 8:

[0276] The user reviews the feedback displayed on the device and enters new ideas or additional questions by hand. This action restarts the process, allowing the dialogue to continue.

[0277] (Example 1)

[0278] Next, we will describe Example 1. 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."

[0279] Conventional systems that analyze handwriting input have struggled to provide real-time, intuitive user interaction, resulting in insufficient support for effective learning and creative thinking. This challenge needs to be addressed by achieving high-precision handwriting recognition and providing relevant information immediately.

[0280] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0281] In this invention, the server includes means for receiving handwritten input and converting it into data, means for analyzing the converted data to identify information, means for generating a response using machine learning based on the identified information, means for acquiring and temporarily recording coordinate data in real time, and means for formatting the data and transmitting it through a communication network. This enables effective information provision and continuous interaction based on the user's handwritten input.

[0282] "Handwritten input" refers to means by which a user manually draws or writes characters and graphics.

[0283] "Data" refers to an information representation obtained by converting handwritten input into a digital format.

[0284] "Information" refers to an identification result such as characters and graphics obtained from the analyzed data.

[0285] "Machine learning" refers to a technology that recognizes patterns and rules from data and automatically generates feedback.

[0286] "Response" refers to a feedback message to the user generated by the server.

[0287] "Real time" refers to the property that an operation or process is performed immediately.

[0288] "Coordinate data" refers to numerical information indicating the position of handwritten input.

[0289] "Communication network" refers to a digital network for data exchange.

[0290] This invention constitutes a system that analyzes the user's handwritten data via a digital input system and provides feedback in real time. Specific embodiments of the system are shown below from the perspectives of the server, terminal, and user.

[0291] User operations:

[0292] Users input text and shapes by hand on a digital device using a touch panel or stylus pen. For example, this digital system can be used in educational settings to visualize ideas related to "energy efficiency."

[0293] Device features:

[0294] The terminal detects the user's handwritten input and converts it into digital coordinate data. The converted data is temporarily stored in the device memory. Next, the terminal formats the coordinate data into a format that can be used by OCR (optical character recognition) and pattern recognition technologies, and sends it to a server via the internet.

[0295] Server processing:

[0296] The server receives formatted data sent from the terminal and uses OCR technology to analyze the text and shapes. Based on the analyzed information, the server generates relevant feedback using a generative AI model. This feedback is provided to the user in the form of suggestions and solutions.

[0297] For example, if a user writes sketches or keywords related to "energy efficiency" on a digital board, the server analyzes the input and suggests the latest technological information and efficiency methods related to it. This allows the user to gain new insights.

[0298] Example of a prompt:

[0299] "Please provide feedback on the latest technologies and methods related to ideas about energy efficiency."

[0300] Thus, this invention provides an interactive learning environment that utilizes the user's handwriting input, and plays a role in supporting problem-solving and creative thinking.

[0301] The flow of the specific process in Example 1 will be described using FIG. 11.

[0302] Step 1:

[0303] The user uses a touch panel or a stylus pen to input ideas and figures by handwriting on a digital device. The input is in the form of analog lines and characters and is drawn in real time on the device. This is the first data input of this system.

[0304] Step 2:

[0305] The terminal detects the user's handwritten input and collects the position information of the input lines and characters as coordinate data. This coordinate data is temporarily stored in the terminal memory. As a specific operation, it continuously obtains coordinate points instantaneously in a form that follows the user's movement.

[0306] Step 3:

[0307] The terminal formats the stored coordinate data and converts it into a form suitable for OCR and pattern recognition. The coordinates of the input handwritten data are aligned, and the result of converting it into a digital form that is easy to analyze is output. This formatted data is passed on to subsequent processing.

[0308] Step 4:

[0309] The terminal sends the formatted digital data to the server via the Internet. As a specific operation of the terminal, it executes a procedure to transfer the data stably and quickly using a transmission protocol. This prepares the server for use in the next analysis step.

[0310] Step 5:

[0311] The server receives data transmitted from the terminal, identifies characters using OCR technology, and analyzes shapes and symbols using pattern recognition technology. The input is pre-formatted digital data, and the output is the interpreted strings and structured data resulting from the analysis. Specifically, the recognized characters and shapes are compared against known patterns in a database.

[0312] Step 6:

[0313] The server generates feedback using a generative AI model based on the analyzed information. The input is analyzed text and graphic information, which the server uses to create feedback containing appropriate information and suggestions. The AI ​​model references past data and related information to output the most relevant response.

[0314] Step 7:

[0315] The feedback generated from the server is sent back to the terminal. The terminal displays this feedback in a user-friendly format. This is usually presented as text information, but may include additional graphics or charts in some cases. This allows the user to visually obtain information and continue interacting with the device based on the output.

[0316] (Application Example 1)

[0317] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0318] Traditional handwriting input systems primarily relied on individual users independently inputting information and receiving feedback separately, making it difficult to achieve effective interaction in real-world gatherings and workshops involving multiple users. Furthermore, there was a lack of effective means to share ideas among participants and facilitate collaborative work.

[0319] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0320] In this invention, the server includes means for receiving handwritten input and converting it into digital information, means for analyzing the converted digital information to identify symbolic or graphic information, and means for generating a response using a machine learning model based on the identified information. This makes it possible to synchronize and share information among multiple users, and can support collaborative work in real-world gatherings.

[0321] "Handwriting input" refers to a method in which users manually input symbols and shapes using a tactile panel or similar device.

[0322] "Means of converting to digital information" refers to a device or process that converts handwritten input into an electronic format.

[0323] "Means for identifying symbolic or graphic information" refers to a device or program for recognizing characters or graphics from converted digital information.

[0324] "Means for generating responses using machine learning models" refers to a device or program that uses a trained algorithm based on recognized information to derive an appropriate response to the user.

[0325] A "user terminal" is an electronic device used by a user to receive or input information.

[0326] "Means for synchronizing and sharing information" refers to a device or program that integrates data entered by multiple users in real time, making it accessible to all simultaneously.

[0327] "Collaborative work in real-world gatherings" refers to activities in which many participants work together in a physical setting to generate new ideas.

[0328] This invention relates to a system including a terminal that allows a user to input handwritten information using a tactile panel and converts it into digital information. The terminal captures the user's input as location information, formats the data, and sends it to a server. The server analyzes the received digital information and identifies symbols or graphic information. Based on the identified information, it uses a machine learning model to generate an appropriate response for the user.

[0329] Specifically, the terminal uses software such as PIL (Python Imaging Library) and pytesseract to efficiently process handwritten data and convert it into digital data. The converted data is sent to a server via the internet. The server utilizes OCR technology and machine learning algorithms to analyze this data and generate the information and suggestions the user requests.

[0330] The server sends the generated response to the user's terminal, which then visually presents the response to the user. The user can then refer to this feedback and make further handwritten input. This process supports collaborative work in real-world gatherings and provides a means for synchronizing and sharing information among multiple users.

[0331] For example, if participants are discussing "energy efficiency" in a workshop, they can deepen the discussion by having the server analyze their handwritten ideas and related diagrams and immediately return relevant, up-to-date technical information and suggestions.

[0332] An example of a prompt for a generative AI model is shown below: "Analyze the given handwritten input image and generate proposals for new energy efficiency technologies."

[0333] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0334] Step 1:

[0335] The user uses a haptic panel to input handwriting. The input data consists of characters and shapes drawn by the user, which the device captures as location information. This location information then serves as foundational data for later digitization.

[0336] Step 2:

[0337] The device uses the captured location information to convert it into digital data using PIL (Python Imaging Library) and pytesseract. The input here is the location information obtained in step 1, and the output is text data processed through optical character recognition. The converted text data is temporarily stored locally.

[0338] Step 3:

[0339] The terminal sends the converted text data to the server via the internet. The input is text data, and the output is a signal indicating that the transmission to the server is complete. The requests library is used for this communication.

[0340] Step 4:

[0341] The server receives text data sent from the terminal and performs analysis using OCR technology and machine learning algorithms. The input for the analysis is the text data received by the server, and the output is the generation of response information based on the analysis results. At this stage, prompt sentences are formed to understand the meaning of the text data and generate possible suggestions.

[0342] Step 5:

[0343] The server processes the prompt using a generative AI model and creates a response that can be provided to the user. The prompt created in step 4 is used as input, and appropriate information or solutions are returned as output.

[0344] Step 6:

[0345] The server sends the generated response to the terminal. In this transmission process, the prepared response is redirected to the terminal. The input is the generated response data, and the output is the acknowledgment signal.

[0346] Step 7:

[0347] The terminal visually displays the response received from the server to the user. The user can then use this feedback to make further handwritten input. The input is the response data from the server, and the output is the action of displaying it on the screen.

[0348] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0349] This invention combines a digital interactive blackboard system with an emotion engine to provide feedback that simultaneously considers the user's handwritten input and their emotional state. In implementing this invention, the server, terminal, and user elements work in coordination.

[0350] 1. User operation

[0351] Users write letters and draw diagrams by hand on a digital whiteboard to record their thoughts. This operation is performed using the device's touch panel, and actions and patterns that may influence the user's emotional state are recorded in real time.

[0352] 2. Device functions

[0353] The device captures the user's handwritten data and converts it into digital data. Furthermore, it collects data to infer the user's emotional state from factors such as writing speed and pressure. An emotion engine analyzes this data to identify the user's emotional state.

[0354] 3. Server processing

[0355] The server receives handwritten data sent from the terminal and analyzes the character and graphic information using OCR technology. Based on the analyzed data, artificial intelligence generates relevant feedback. At the same time, it incorporates emotional state information from the emotion engine to adjust the content and tone of the feedback.

[0356] 4. Providing and displaying feedback

[0357] The server generates feedback, which is then sent to the terminal. The terminal visually displays the feedback to the user, providing emotionally resonant content. This enables flexible communication that responds to the user's reactions.

[0358] 5. User interaction

[0359] Based on the displayed feedback, users make new inputs, deepen their thinking, and work on solving further problems. Throughout this process, the emotion engine constantly monitors the user's emotional state to ensure the feedback is appropriate for them.

[0360] For example, when a user is contemplating a difficult concept, if the emotion engine detects the user's frustration, the server provides gentle, encouraging feedback that reflects that emotional state. In this way, the present invention functions as an interactive digital whiteboard that enhances the conversational experience while considering the user's emotions.

[0361] The following describes the processing flow.

[0362] Step 1:

[0363] The device captures handwritten data entered by the user on the digital whiteboard. This data includes information such as writing speed, pen pressure, and stroke direction.

[0364] Step 2:

[0365] The device converts the collected handwritten data into a digital format while simultaneously formatting auxiliary data (such as speed and pressure) that suggests emotion for the emotion engine.

[0366] Step 3:

[0367] The device transmits formatted handwritten data and sentiment-indicating data to a server via the internet. Data transmission is protected by encryption.

[0368] Step 4:

[0369] The server analyzes the handwritten data received from the terminal using OCR technology to identify characters and graphic information. Based on this analysis, it generates appropriate feedback candidates.

[0370] Step 5:

[0371] The server activates the emotion engine and analyzes emotion suggestion data to determine the user's emotional state. Emotional states such as frustration, interest, and concentration are identified.

[0372] Step 6:

[0373] The server adjusts the content and tone of feedback based on the user's emotional state. For example, if frustration is detected, it generates feedback that includes encouragement.

[0374] Step 7:

[0375] The server sends the refined feedback to the terminal. This feedback may include relevant information, suggestions, or specific responses to the user.

[0376] Step 8:

[0377] The device visually displays feedback received from the server in a user-friendly format. This feedback display includes colors and messages tailored to the user's emotional state.

[0378] Step 9:

[0379] The user reviews the displayed feedback and enters new questions or ideas by hand. The process is then repeated based on the user's actions.

[0380] (Example 2)

[0381] Next, we will describe Example 2. 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".

[0382] Conventional digital blackboard systems simply convert and display handwritten input as digital data, failing to provide feedback that takes into account the user's emotional state. Therefore, it was difficult to provide appropriate support tailored to the user's thoughts and feelings, and thus, an interactive learning experience could not be realized.

[0383] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0384] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the digital data to identify character or graphic information, and means for inferring the user's emotional state based on the user's input speed and pen pressure information. This enables the provision of feedback that is sensitive to the user's emotions and facilitates interactive communication.

[0385] "Handwriting input" refers to the act of a user drawing letters or shapes on a touch panel device using a pen or their finger.

[0386] "Converting to digital data" refers to the process of converting analog input information into an electronic data format, making it data that can be processed by a computer.

[0387] "Emotional state" refers to the user's psychological state, encompassing the totality of emotions inferred from factors such as input speed and pen pressure.

[0388] "Feedback" refers to the responses and advice that a system generates and provides to a user in response to their input and emotional state.

[0389] "Artificial intelligence" refers to a computer system that analyzes input data and automatically solves problems or makes decisions based on the information it has learned.

[0390] A "generative AI model" refers to an algorithmic model that learns from diverse data and generates output tailored to a specific task.

[0391] "Visual display" refers to showing information to the user through the device screen, and includes presentation in the form of text, images, and animations.

[0392] This invention allows users to express their thoughts and emotional states on a digital whiteboard by using a touch panel-equipped terminal to input handwritten information. The terminal is equipped with a pressure sensor that collects data such as the position, pressure, and speed of the characters and figures written by the user with high precision and converts it into digital data.

[0393] This converted data is sent to a server, which uses OCR technology to identify the information in the characters and shapes. Furthermore, by analyzing the user's input speed and pen pressure data obtained from the terminal, the emotion engine infers the user's emotional state.

[0394] Based on this data, the server generates feedback using a generative AI model that has learned from diverse data. The generated feedback takes emotional states into account and is delivered to the user in an appropriate tone. This feedback is sent to the device and displayed visually to the user. As a result, the user receives emotionally resonant, interactive feedback and deepens their thinking by providing further input.

[0395] For example, if a user types "I don't understand" while thinking about a difficult concept, the emotion engine detects the user's frustration, and the server provides gentle, encouraging feedback such as "You're almost there, keep trying." This allows the system to deeply understand the user's thoughts and feelings, enabling it to provide appropriate support in learning and work.

[0396] An example of a prompt message is, "Generate gentle and encouraging feedback to help the user solve the challenge they are currently facing." In this way, the present invention enables emotion-based interactive communication.

[0397] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0398] Step 1:

[0399] Users input characters and shapes by hand on a touch-panel device. The device receives this handwriting input via a pressure sensor and collects data such as position, pressure, and speed in real time. This converts the input data from analog to digital format and stores it in a database.

[0400] Step 2:

[0401] The terminal sends the collected digital data to the server. The server applies OCR technology to analyze the received data, identifying information in characters and shapes. This identified data is organized within the server and stored in a database. As a result, the handwritten content is output as structured digital information.

[0402] Step 3:

[0403] The server receives input speed and pressure information from the terminal and analyzes it using an emotion engine. The analysis results in an inference of the user's emotional state. Specifically, fast input speed and high pressure may indicate tension or stress, which the emotion engine detects. This analysis result is then prepared for the next step.

[0404] Step 4:

[0405] The server generates feedback using a generative AI model based on the identified handwritten data and sentiment analysis results. This prompt text and generative AI model are used to derive content that takes the user's emotions into consideration. For example, if the user writes "I don't understand," the AI ​​will generate an encouraging message such as "Calm down and try again." This ensures that the user receives appropriate feedback.

[0406] Step 5:

[0407] The generated feedback is sent from the server to the device, which displays it visually. The user receives this feedback and either provides further input or deepens their thinking. In this process, the generated feedback plays a role in understanding the user's feelings and providing a better experience.

[0408] (Application Example 2)

[0409] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0410] Digital interactive blackboard systems are required to provide feedback that not only accepts the user's handwritten input but also takes into account their emotional state at the time of input. Implementing such functionality can improve support for participants in workshops and educational seminars, thereby enhancing learning and comprehension.

[0411] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0412] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the converted digital data to identify character or graphic information, and means for inferring the user's emotional state using an emotion analysis engine and adjusting the feedback based on that information. This enables flexible communication and feedback provision that takes into account both the user's handwritten input and emotional state.

[0413] "Handwriting input" refers to the act of a user drawing letters or shapes by hand using a touch panel or pen device.

[0414] "Digital data" refers to information that has been converted from handwritten input into a digital format, and is in a format that can be processed within a computer system.

[0415] An "artificial intelligence engine" is an algorithm or program used to analyze input data and generate appropriate feedback.

[0416] "Feedback" refers to information such as responses and comments that are generated in response to user input or status.

[0417] An "emotion analysis engine" is an algorithm or program that infers a user's psychological or emotional state from their input data and uses that information to adjust the system's response.

[0418] "Information equipment" refers to terminals and devices used for various information processing, including the display of digital data, and generally includes smartphones and tablets.

[0419] A "contact detection device" is a device used to detect a user's handwritten input, and typically uses a touchscreen or stylus pen.

[0420] The system implementing this invention consists of a terminal that receives user handwritten input and converts it into digital data, a server that analyzes the digital data, and a device that provides feedback. The specific operation of each of these elements is described below.

[0421] The device converts information entered by the user via handwriting using a touchscreen or stylus pen into digital data in real time. The user's handwriting speed and pressure are also captured simultaneously, and this data is used to infer the user's emotional state.

[0422] The server processes the digital data transmitted from the terminal. First, it uses OCR technology to identify characters and shapes, and then applies a generative AI model using this information to generate feedback. Furthermore, it uses an emotion analysis engine to infer the user's emotional state from data such as handwriting speed and pressure, and adjusts the feedback accordingly.

[0423] The generated feedback is transmitted to information devices and displayed visually to the user. In this process, the feedback is provided in a way that takes the user's emotional state into consideration, playing a role in facilitating smooth communication.

[0424] For example, if the emotion analysis engine infers that a participant is feeling impatient while learning a new concept in a workshop, the server will generate and display gentle feedback such as, "Let's calm down and learn one step at a time."

[0425] As a concrete example, an example of a prompt message is shown below.

[0426] "Strong pen pressure and fast input have been detected. Please generate feedback to promote relaxation."

[0427] Thus, the present invention makes it possible to provide an interactive learning experience through emotion-responsive feedback.

[0428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0429] Step 1:

[0430] Users input handwritten data using a touchscreen on an information device. This input behavior is captured, and characteristic data such as pen pressure and speed are collected simultaneously. This generates digital data of the handwritten characters and shapes.

[0431] Step 2:

[0432] The terminal converts the collected handwritten input data into a digital format and sends that digital data to the server. The characteristics of the input data (speed, pressure) are transmitted separately for sentiment analysis. The handwritten data is supplied to the server as input and identified as handwritten information and characteristic data.

[0433] Step 3:

[0434] The server uses OCR technology to recognize and analyze characters and shapes from incoming digital data. This analysis process generates specific character information as output. The calculated character information forms the basis for feedback generation.

[0435] Step 4:

[0436] The server uses an emotion analysis engine to analyze feature data and infer the user's emotional state. It performs data calculations based on the pressure and speed information of the input data and outputs the inferred emotional state.

[0437] Step 5:

[0438] The server utilizes a generative AI model to generate feedback based on analyzed text information and emotional states. A prompt sentence reflecting the emotional state is used as input, and text information is output as feedback.

[0439] Step 6:

[0440] The server sends the generated feedback to the information device, where it is displayed. This feedback is visualized in a way that takes the user's emotional state into consideration, guiding further handwriting input. The received output text is then displayed on the information device.

[0441] Step 7:

[0442] The user uses the displayed feedback to perform the next handwriting input, and this process is repeated. New handwriting input is provided by the user, and the output returns to step 1 again.

[0443] This process provides users with flexible, emotionally resonant feedback in real time.

[0444] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0445] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0446] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0447] [Third Embodiment]

[0448] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0449] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0450] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0451] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0452] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0453] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0454] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0455] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0456] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0457] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0458] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0459] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0460] This invention implements a digital blackboard system by configuring a computer system centered on user handwriting input. The specific processing and usage methods of the system will be described below from the perspectives of the server, terminal, and user.

[0461] 1. User operation

[0462] Users handwrite ideas on specific themes or issues onto a digital whiteboard. This operation is performed using a touch panel or stylus, allowing for intuitive drawing.

[0463] 2. Device functions

[0464] The terminal captures handwritten input from the user. The captured data is temporarily stored as coordinate data. Next, the terminal formats the data and sends it to a server via the internet. This formatted data is suitable for OCR and pattern recognition.

[0465] 3. Server processing

[0466] The server receives handwritten data sent from the terminal and performs analysis. This analysis process uses OCR (Optical Character Recognition) technology to identify characters and recognizes shapes and symbols through pattern recognition. Based on the recognized information, artificial intelligence generates appropriate feedback. This feedback includes information, suggestions, and solutions related to what the user has written.

[0467] 4. Providing feedback

[0468] Feedback generated from the server is sent to the terminal. The terminal displays the feedback in a user-friendly format. This display may include text information and, in some cases, additional graphics.

[0469] 5. User interaction

[0470] Based on the feedback provided by the device, users can develop new ideas or ask further questions. The process restarts once the user provides additional input.

[0471] As a concrete example, when a user is brainstorming proposals on the theme of "energy efficiency," they write relevant shapes and keywords on a digital whiteboard. The server then analyzes this and provides feedback on information and the latest technologies that can help improve energy efficiency. Based on this feedback, the user can further develop their ideas and find new approaches.

[0472] Thus, the embodiment of the present invention provides an interactive learning and idea development system that utilizes handwriting input, enabling real-time knowledge deepening and support for creative thinking.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The device captures handwritten input from the user on the digital whiteboard. The handwritten data is recorded as coordinates and strokes and formatted into text or shapes.

[0476] Step 2:

[0477] The terminal performs preprocessing on the formatted handwritten data. This process involves noise reduction and data normalization to prepare the data for improved analysis accuracy.

[0478] Step 3:

[0479] The terminal sends pre-processed handwritten data to the server via the internet. The data is encrypted before transmission to prevent data corruption during transit.

[0480] Step 4:

[0481] The server receives handwritten data sent from the terminal. This data is analyzed using OCR technology to identify characters and graphic information.

[0482] Step 5:

[0483] The server activates artificial intelligence based on the analysis results to generate feedback tailored to the user's handwritten content. This feedback includes relevant information, suggestions, and explanations.

[0484] Step 6:

[0485] The server packages the generated feedback and sends it to the terminal in an encrypted format. It monitors the transmission status and confirms that the transmission was successful.

[0486] Step 7:

[0487] The device receives feedback sent from the server. The received feedback is then structured as text and graphics for easy viewing by the user.

[0488] Step 8:

[0489] The user reviews the feedback displayed on the device and enters new ideas or additional questions by hand. This action restarts the process, allowing the dialogue to continue.

[0490] (Example 1)

[0491] Next, we will describe Example 1. 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."

[0492] Conventional systems that analyze handwriting input have struggled to provide real-time, intuitive user interaction, resulting in insufficient support for effective learning and creative thinking. This challenge needs to be addressed by achieving high-precision handwriting recognition and providing relevant information immediately.

[0493] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0494] In this invention, the server includes means for receiving handwritten input and converting it into data, means for analyzing the converted data and identifying information, means for generating a response using machine learning based on the identified information, means for acquiring coordinate data in real time and temporarily recording it, and means for formatting the data and transmitting it through a communication network. This enables effective information provision and continuous interaction based on handwritten input by the user.

[0495] "Handwriting input" refers to a method for users to manually draw or write characters or shapes.

[0496] "Data" refers to information representation obtained by converting handwritten input into a digital format.

[0497] "Information" refers to the identification results, such as characters and shapes, obtained from analyzed data.

[0498] "Machine learning" is a technology that recognizes patterns and rules from data and automatically generates feedback.

[0499] A "response" is a feedback message generated by the server for the user.

[0500] "Real-time" refers to the property of an action or process occurring immediately.

[0501] "Coordinate data" refers to numerical information that indicates the position of handwritten input.

[0502] A "communication network" is a digital network used for exchanging data.

[0503] This invention constitutes a system that analyzes a user's handwritten data via a digital input system and provides real-time feedback. Specific embodiments of the system are described below from the perspectives of the server, terminal, and user.

[0504] User actions:

[0505] Users input text and shapes by hand on a digital device using a touch panel or stylus pen. For example, this digital system can be used in educational settings to visualize ideas related to "energy efficiency."

[0506] Device features:

[0507] The terminal detects the user's handwritten input and converts it into digital coordinate data. The converted data is temporarily stored in the device memory. Next, the terminal formats the coordinate data into a format that can be used by OCR (optical character recognition) and pattern recognition technologies, and sends it to a server via the internet.

[0508] Server processing:

[0509] The server receives formatted data sent from the terminal and uses OCR technology to analyze the text and shapes. Based on the analyzed information, the server generates relevant feedback using a generative AI model. This feedback is provided to the user in the form of suggestions and solutions.

[0510] For example, if a user writes sketches or keywords related to "energy efficiency" on a digital board, the server analyzes the input and suggests the latest technological information and efficiency methods related to it. This allows the user to gain new insights.

[0511] Example of a prompt:

[0512] "Please provide feedback on the latest technologies and methods related to ideas about energy efficiency."

[0513] Thus, this invention provides an interactive learning environment that utilizes the user's handwriting input, and plays a role in supporting problem-solving and creative thinking.

[0514] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0515] Step 1:

[0516] Users input ideas and shapes by hand on a digital device using a touch panel or stylus pen. The input is in the form of analog lines and letters, and is drawn on the device in real time. This is the initial data input for this system.

[0517] Step 2:

[0518] The device detects the user's handwriting input and collects the positional information of the entered lines and characters as coordinate data. This coordinate data is temporarily stored in the device's memory. Specifically, it continuously acquires coordinate points instantaneously in accordance with the user's movements.

[0519] Step 3:

[0520] The terminal formats the stored coordinate data and converts it into a format suitable for OCR and pattern recognition. It aligns the coordinates of the input handwritten data and outputs the result in a digital format that is easy to analyze. This formatted data is then passed on to subsequent processing.

[0521] Step 4:

[0522] The terminal transmits the formatted digital data to the server via the internet. Specifically, the terminal performs a procedure to transfer the data reliably and quickly using a transmission protocol. This prepares the data for the server to use in the next analysis step.

[0523] Step 5:

[0524] The server receives data transmitted from the terminal, identifies characters using OCR technology, and analyzes shapes and symbols using pattern recognition technology. The input is pre-formatted digital data, and the output is the interpreted strings and structured data resulting from the analysis. Specifically, the recognized characters and shapes are compared against known patterns in a database.

[0525] Step 6:

[0526] The server generates feedback using a generative AI model based on the analyzed information. The input is analyzed text and graphic information, which the server uses to create feedback containing appropriate information and suggestions. The AI ​​model references past data and related information to output the most relevant response.

[0527] Step 7:

[0528] The feedback generated from the server is sent back to the terminal. The terminal displays this feedback in a user-friendly format. This is usually presented as text information, but may include additional graphics or charts in some cases. This allows the user to visually obtain information and continue interacting with the device based on the output.

[0529] (Application Example 1)

[0530] Next, we will explain Application Example 1. In the following explanation, 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."

[0531] Traditional handwriting input systems primarily relied on individual users independently inputting information and receiving feedback separately, making it difficult to achieve effective interaction in real-world gatherings and workshops involving multiple users. Furthermore, there was a lack of effective means to share ideas among participants and facilitate collaborative work.

[0532] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0533] In this invention, the server includes means for receiving handwritten input and converting it into digital information, means for analyzing the converted digital information to identify symbolic or graphic information, and means for generating a response using a machine learning model based on the identified information. This makes it possible to synchronize and share information among multiple users, and can support collaborative work in real-world gatherings.

[0534] "Handwriting input" refers to a method in which users manually input symbols and shapes using a tactile panel or similar device.

[0535] "Means of converting to digital information" refers to a device or process that converts handwritten input into an electronic format.

[0536] "Means for identifying symbolic or graphic information" refers to a device or program for recognizing characters or graphics from converted digital information.

[0537] "Means for generating responses using machine learning models" refers to a device or program that uses a trained algorithm based on recognized information to derive an appropriate response to the user.

[0538] A "user terminal" is an electronic device used by a user to receive or input information.

[0539] "Means for synchronizing and sharing information" refers to a device or program that integrates data entered by multiple users in real time, making it accessible to all simultaneously.

[0540] "Collaborative work in real-world gatherings" refers to activities in which many participants work together in a physical setting to generate new ideas.

[0541] This invention relates to a system including a terminal that allows a user to input handwritten information using a tactile panel and converts it into digital information. The terminal captures the user's input as location information, formats the data, and sends it to a server. The server analyzes the received digital information and identifies symbols or graphic information. Based on the identified information, it uses a machine learning model to generate an appropriate response for the user.

[0542] Specifically, the terminal uses software such as PIL (Python Imaging Library) and pytesseract to efficiently process handwritten data and convert it into digital data. The converted data is sent to a server via the internet. The server utilizes OCR technology and machine learning algorithms to analyze this data and generate the information and suggestions the user requests.

[0543] The server sends the generated response to the user's terminal, which then visually presents the response to the user. The user can then refer to this feedback and make further handwritten input. This process supports collaborative work in real-world gatherings and provides a means for synchronizing and sharing information among multiple users.

[0544] For example, if participants are discussing "energy efficiency" in a workshop, they can deepen the discussion by having the server analyze their handwritten ideas and related diagrams and immediately return relevant, up-to-date technical information and suggestions.

[0545] An example of a prompt for a generative AI model is shown below: "Analyze the given handwritten input image and generate proposals for new energy efficiency technologies."

[0546] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0547] Step 1:

[0548] The user uses a haptic panel to input handwriting. The input data consists of characters and shapes drawn by the user, which the device captures as location information. This location information then serves as foundational data for later digitization.

[0549] Step 2:

[0550] The device uses the captured location information to convert it into digital data using PIL (Python Imaging Library) and pytesseract. The input here is the location information obtained in step 1, and the output is text data processed through optical character recognition. The converted text data is temporarily stored locally.

[0551] Step 3:

[0552] The terminal sends the converted text data to the server via the internet. The input is text data, and the output is a signal indicating that the transmission to the server is complete. The requests library is used for this communication.

[0553] Step 4:

[0554] The server receives text data sent from the terminal and performs analysis using OCR technology and machine learning algorithms. The input for the analysis is the text data received by the server, and the output is the generation of response information based on the analysis results. At this stage, prompt sentences are formed to understand the meaning of the text data and generate possible suggestions.

[0555] Step 5:

[0556] The server processes the prompt using a generative AI model and creates a response that can be provided to the user. The prompt created in step 4 is used as input, and appropriate information or solutions are returned as output.

[0557] Step 6:

[0558] The server sends the generated response to the terminal. In this transmission process, the prepared response is redirected to the terminal. The input is the generated response data, and the output is the acknowledgment signal.

[0559] Step 7:

[0560] The terminal visually displays the response received from the server to the user. The user can then use this feedback to make further handwritten input. The input is the response data from the server, and the output is the action of displaying it on the screen.

[0561] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0562] This invention combines a digital interactive blackboard system with an emotion engine to provide feedback that simultaneously considers the user's handwritten input and their emotional state. In implementing this invention, the server, terminal, and user elements work in coordination.

[0563] 1. User operation

[0564] Users write letters and draw diagrams by hand on a digital whiteboard to record their thoughts. This operation is performed using the device's touch panel, and actions and patterns that may influence the user's emotional state are recorded in real time.

[0565] 2. Device functions

[0566] The device captures the user's handwritten data and converts it into digital data. Furthermore, it collects data to infer the user's emotional state from factors such as writing speed and pressure. An emotion engine analyzes this data to identify the user's emotional state.

[0567] 3. Server processing

[0568] The server receives handwritten data sent from the terminal and analyzes the character and graphic information using OCR technology. Based on the analyzed data, artificial intelligence generates relevant feedback. At the same time, it incorporates emotional state information from the emotion engine to adjust the content and tone of the feedback.

[0569] 4. Providing and displaying feedback

[0570] The server generates feedback, which is then sent to the terminal. The terminal visually displays the feedback to the user, providing emotionally resonant content. This enables flexible communication that responds to the user's reactions.

[0571] 5. User interaction

[0572] Based on the displayed feedback, users make new inputs, deepen their thinking, and work on solving further problems. Throughout this process, the emotion engine constantly monitors the user's emotional state to ensure the feedback is appropriate for them.

[0573] For example, when a user is contemplating a difficult concept, if the emotion engine detects the user's frustration, the server provides gentle, encouraging feedback that reflects that emotional state. In this way, the present invention functions as an interactive digital whiteboard that enhances the conversational experience while considering the user's emotions.

[0574] The following describes the processing flow.

[0575] Step 1:

[0576] The device captures handwritten data entered by the user on the digital whiteboard. This data includes information such as writing speed, pen pressure, and stroke direction.

[0577] Step 2:

[0578] The device converts the collected handwritten data into a digital format while simultaneously formatting auxiliary data (such as speed and pressure) that suggests emotion for the emotion engine.

[0579] Step 3:

[0580] The device transmits formatted handwritten data and sentiment-indicating data to a server via the internet. Data transmission is protected by encryption.

[0581] Step 4:

[0582] The server analyzes the handwritten data received from the terminal using OCR technology to identify characters and graphic information. Based on this analysis, it generates appropriate feedback candidates.

[0583] Step 5:

[0584] The server activates the emotion engine and analyzes emotion suggestion data to determine the user's emotional state. Emotional states such as frustration, interest, and concentration are identified.

[0585] Step 6:

[0586] The server adjusts the content and tone of feedback based on the user's emotional state. For example, if frustration is detected, it generates feedback that includes encouragement.

[0587] Step 7:

[0588] The server sends the refined feedback to the terminal. This feedback may include relevant information, suggestions, or specific responses to the user.

[0589] Step 8:

[0590] The device visually displays feedback received from the server in a user-friendly format. This feedback display includes colors and messages tailored to the user's emotional state.

[0591] Step 9:

[0592] The user reviews the displayed feedback and enters new questions or ideas by hand. The process is then repeated based on the user's actions.

[0593] (Example 2)

[0594] Next, we will describe Example 2. 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."

[0595] Conventional digital blackboard systems simply convert and display handwritten input as digital data, failing to provide feedback that takes into account the user's emotional state. Therefore, it was difficult to provide appropriate support tailored to the user's thoughts and feelings, and thus, an interactive learning experience could not be realized.

[0596] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0597] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the digital data to identify character or graphic information, and means for inferring the user's emotional state based on the user's input speed and pen pressure information. This enables the provision of feedback that is sensitive to the user's emotions and facilitates interactive communication.

[0598] "Handwriting input" refers to the act of a user drawing letters or shapes on a touch panel device using a pen or their finger.

[0599] "Converting to digital data" refers to the process of converting analog input information into an electronic data format, making it data that can be processed by a computer.

[0600] "Emotional state" refers to the user's psychological state, encompassing the totality of emotions inferred from factors such as input speed and pen pressure.

[0601] "Feedback" refers to the responses and advice that a system generates and provides to a user in response to their input and emotional state.

[0602] "Artificial intelligence" refers to a computer system that analyzes input data and automatically solves problems or makes decisions based on the information it has learned.

[0603] A "generative AI model" refers to an algorithmic model that learns from diverse data and generates output tailored to a specific task.

[0604] "Visual display" refers to showing information to the user through the device screen, and includes presentation in the form of text, images, and animations.

[0605] This invention allows users to express their thoughts and emotional states on a digital whiteboard by using a touch panel-equipped terminal to input handwritten information. The terminal is equipped with a pressure sensor that collects data such as the position, pressure, and speed of the characters and figures written by the user with high precision and converts it into digital data.

[0606] This converted data is sent to a server, which uses OCR technology to identify the information in the characters and shapes. Furthermore, by analyzing the user's input speed and pen pressure data obtained from the terminal, the emotion engine infers the user's emotional state.

[0607] Based on this data, the server generates feedback using a generative AI model that has learned from diverse data. The generated feedback takes emotional states into account and is delivered to the user in an appropriate tone. This feedback is sent to the device and displayed visually to the user. As a result, the user receives emotionally resonant, interactive feedback and deepens their thinking by providing further input.

[0608] For example, if a user types "I don't understand" while thinking about a difficult concept, the emotion engine detects the user's frustration, and the server provides gentle, encouraging feedback such as "You're almost there, keep trying." This allows the system to deeply understand the user's thoughts and feelings, enabling it to provide appropriate support in learning and work.

[0609] An example of a prompt message is, "Generate gentle and encouraging feedback to help the user solve the challenge they are currently facing." In this way, the present invention enables emotion-based interactive communication.

[0610] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0611] Step 1:

[0612] Users input characters and shapes by hand on a touch-panel device. The device receives this handwriting input via a pressure sensor and collects data such as position, pressure, and speed in real time. This converts the input data from analog to digital format and stores it in a database.

[0613] Step 2:

[0614] The terminal sends the collected digital data to the server. The server applies OCR technology to analyze the received data, identifying information in characters and shapes. This identified data is organized within the server and stored in a database. As a result, the handwritten content is output as structured digital information.

[0615] Step 3:

[0616] The server receives input speed and pressure information from the terminal and analyzes it using an emotion engine. The analysis results in an inference of the user's emotional state. Specifically, fast input speed and high pressure may indicate tension or stress, which the emotion engine detects. This analysis result is then prepared for the next step.

[0617] Step 4:

[0618] The server generates feedback using a generative AI model based on the identified handwritten data and sentiment analysis results. This prompt text and generative AI model are used to derive content that takes the user's emotions into consideration. For example, if the user writes "I don't understand," the AI ​​will generate an encouraging message such as "Calm down and try again." This ensures that the user receives appropriate feedback.

[0619] Step 5:

[0620] The generated feedback is sent from the server to the device, which displays it visually. The user receives this feedback and either provides further input or deepens their thinking. In this process, the generated feedback plays a role in understanding the user's feelings and providing a better experience.

[0621] (Application Example 2)

[0622] Next, we will explain application example 2. In the following explanation, 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."

[0623] Digital interactive blackboard systems are required to provide feedback that not only accepts the user's handwritten input but also takes into account their emotional state at the time of input. Implementing such functionality can improve support for participants in workshops and educational seminars, thereby enhancing learning and comprehension.

[0624] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0625] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the converted digital data to identify character or graphic information, and means for inferring the user's emotional state using an emotion analysis engine and adjusting the feedback based on that information. This enables flexible communication and feedback provision that takes into account both the user's handwritten input and emotional state.

[0626] "Handwriting input" refers to the act of a user drawing letters or shapes by hand using a touch panel or pen device.

[0627] "Digital data" refers to information that has been converted from handwritten input into a digital format, and is in a format that can be processed within a computer system.

[0628] An "artificial intelligence engine" is an algorithm or program used to analyze input data and generate appropriate feedback.

[0629] "Feedback" refers to information such as responses and comments that are generated in response to user input or status.

[0630] An "emotion analysis engine" is an algorithm or program that infers a user's psychological or emotional state from their input data and uses that information to adjust the system's response.

[0631] "Information equipment" refers to terminals and devices used for various information processing, including the display of digital data, and generally includes smartphones and tablets.

[0632] A "contact detection device" is a device used to detect a user's handwritten input, and typically uses a touchscreen or stylus pen.

[0633] The system implementing this invention consists of a terminal that receives user handwritten input and converts it into digital data, a server that analyzes the digital data, and a device that provides feedback. The specific operation of each of these elements is described below.

[0634] The device converts information entered by the user via handwriting using a touchscreen or stylus pen into digital data in real time. The user's handwriting speed and pressure are also captured simultaneously, and this data is used to infer the user's emotional state.

[0635] The server processes the digital data transmitted from the terminal. First, it uses OCR technology to identify characters and shapes, and then applies a generative AI model using this information to generate feedback. Furthermore, it uses an emotion analysis engine to infer the user's emotional state from data such as handwriting speed and pressure, and adjusts the feedback accordingly.

[0636] The generated feedback is transmitted to information devices and displayed visually to the user. In this process, the feedback is provided in a way that takes the user's emotional state into consideration, playing a role in facilitating smooth communication.

[0637] For example, if the emotion analysis engine infers that a participant is feeling impatient while learning a new concept in a workshop, the server will generate and display gentle feedback such as, "Let's calm down and learn one step at a time."

[0638] As a concrete example, an example of a prompt message is shown below.

[0639] "Strong pen pressure and fast input have been detected. Please generate feedback to promote relaxation."

[0640] Thus, the present invention makes it possible to provide an interactive learning experience through emotion-responsive feedback.

[0641] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0642] Step 1:

[0643] Users input handwritten data using a touchscreen on an information device. This input behavior is captured, and characteristic data such as pen pressure and speed are collected simultaneously. This generates digital data of the handwritten characters and shapes.

[0644] Step 2:

[0645] The terminal converts the collected handwritten input data into a digital format and sends that digital data to the server. The characteristics of the input data (speed, pressure) are transmitted separately for sentiment analysis. The handwritten data is supplied to the server as input and identified as handwritten information and characteristic data.

[0646] Step 3:

[0647] The server uses OCR technology to recognize and analyze characters and shapes from incoming digital data. This analysis process generates specific character information as output. The calculated character information forms the basis for feedback generation.

[0648] Step 4:

[0649] The server uses an emotion analysis engine to analyze feature data and infer the user's emotional state. It performs data calculations based on the pressure and speed information of the input data and outputs the inferred emotional state.

[0650] Step 5:

[0651] The server utilizes a generative AI model to generate feedback based on analyzed text information and emotional states. A prompt sentence reflecting the emotional state is used as input, and text information is output as feedback.

[0652] Step 6:

[0653] The server sends the generated feedback to the information device, where it is displayed. This feedback is visualized in a way that takes the user's emotional state into consideration, guiding further handwriting input. The received output text is then displayed on the information device.

[0654] Step 7:

[0655] The user uses the displayed feedback to perform the next handwriting input, and this process is repeated. New handwriting input is provided by the user, and the output returns to step 1 again.

[0656] This process provides users with flexible, emotionally resonant feedback in real time.

[0657] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0658] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0659] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0660] [Fourth Embodiment]

[0661] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0662] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0663] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0664] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0665] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0666] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0667] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0668] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0669] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0670] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0671] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0672] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0673] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0674] This invention implements a digital blackboard system by configuring a computer system centered on user handwriting input. The specific processing and usage methods of the system will be described below from the perspectives of the server, terminal, and user.

[0675] 1. User operation

[0676] Users handwrite ideas on specific themes or issues onto a digital whiteboard. This operation is performed using a touch panel or stylus, allowing for intuitive drawing.

[0677] 2. Device functions

[0678] The terminal captures handwritten input from the user. The captured data is temporarily stored as coordinate data. Next, the terminal formats the data and sends it to a server via the internet. This formatted data is suitable for OCR and pattern recognition.

[0679] 3. Server processing

[0680] The server receives handwritten data sent from the terminal and performs analysis. This analysis process uses OCR (Optical Character Recognition) technology to identify characters and recognizes shapes and symbols through pattern recognition. Based on the recognized information, artificial intelligence generates appropriate feedback. This feedback includes information, suggestions, and solutions related to what the user has written.

[0681] 4. Providing feedback

[0682] Feedback generated from the server is sent to the terminal. The terminal displays the feedback in a user-friendly format. This display may include text information and, in some cases, additional graphics.

[0683] 5. User interaction

[0684] Based on the feedback provided by the device, users can develop new ideas or ask further questions. The process restarts once the user provides additional input.

[0685] As a concrete example, when a user is brainstorming proposals on the theme of "energy efficiency," they write relevant shapes and keywords on a digital whiteboard. The server then analyzes this and provides feedback on information and the latest technologies that can help improve energy efficiency. Based on this feedback, the user can further develop their ideas and find new approaches.

[0686] Thus, the embodiment of the present invention provides an interactive learning and idea development system that utilizes handwriting input, enabling real-time knowledge deepening and support for creative thinking.

[0687] The following describes the processing flow.

[0688] Step 1:

[0689] The device captures handwritten input from the user on the digital whiteboard. The handwritten data is recorded as coordinates and strokes and formatted into text or shapes.

[0690] Step 2:

[0691] The terminal performs preprocessing on the formatted handwritten data. This process involves noise reduction and data normalization to prepare the data for improved analysis accuracy.

[0692] Step 3:

[0693] The terminal sends pre-processed handwritten data to the server via the internet. The data is encrypted before transmission to prevent data corruption during transit.

[0694] Step 4:

[0695] The server receives handwritten data sent from the terminal. This data is analyzed using OCR technology to identify characters and graphic information.

[0696] Step 5:

[0697] The server activates artificial intelligence based on the analysis results to generate feedback tailored to the user's handwritten content. This feedback includes relevant information, suggestions, and explanations.

[0698] Step 6:

[0699] The server packages the generated feedback and sends it to the terminal in an encrypted format. It monitors the transmission status and confirms that the transmission was successful.

[0700] Step 7:

[0701] The device receives feedback sent from the server. The received feedback is then structured as text and graphics for easy viewing by the user.

[0702] Step 8:

[0703] The user reviews the feedback displayed on the device and enters new ideas or additional questions by hand. This action restarts the process, allowing the dialogue to continue.

[0704] (Example 1)

[0705] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] Conventional systems that analyze handwriting input have struggled to provide real-time, intuitive user interaction, resulting in insufficient support for effective learning and creative thinking. This challenge needs to be addressed by achieving high-precision handwriting recognition and providing relevant information immediately.

[0707] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0708] In this invention, the server includes means for receiving handwritten input and converting it into data, means for analyzing the converted data and identifying information, means for generating a response using machine learning based on the identified information, means for acquiring coordinate data in real time and temporarily recording it, and means for formatting the data and transmitting it through a communication network. This enables effective information provision and continuous interaction based on handwritten input by the user.

[0709] "Handwriting input" refers to a method for users to manually draw or write characters or shapes.

[0710] "Data" refers to information representation obtained by converting handwritten input into a digital format.

[0711] "Information" refers to the identification results, such as characters and shapes, obtained from analyzed data.

[0712] "Machine learning" is a technology that recognizes patterns and rules from data and automatically generates feedback.

[0713] A "response" is a feedback message generated by the server for the user.

[0714] "Real-time" refers to the property of an action or process occurring immediately.

[0715] "Coordinate data" refers to numerical information that indicates the position of handwritten input.

[0716] A "communication network" is a digital network used for exchanging data.

[0717] This invention constitutes a system that analyzes a user's handwritten data via a digital input system and provides real-time feedback. Specific embodiments of the system are described below from the perspectives of the server, terminal, and user.

[0718] User actions:

[0719] Users input text and shapes by hand on a digital device using a touch panel or stylus pen. For example, this digital system can be used in educational settings to visualize ideas related to "energy efficiency."

[0720] Device features:

[0721] The terminal detects the user's handwritten input and converts it into digital coordinate data. The converted data is temporarily stored in the device memory. Next, the terminal formats the coordinate data into a format that can be used by OCR (optical character recognition) and pattern recognition technologies, and sends it to a server via the internet.

[0722] Server processing:

[0723] The server receives formatted data sent from the terminal and uses OCR technology to analyze the text and shapes. Based on the analyzed information, the server generates relevant feedback using a generative AI model. This feedback is provided to the user in the form of suggestions and solutions.

[0724] For example, if a user writes sketches or keywords related to "energy efficiency" on a digital board, the server analyzes the input and suggests the latest technological information and efficiency methods related to it. This allows the user to gain new insights.

[0725] Example of a prompt:

[0726] "Please provide feedback on the latest technologies and methods related to ideas about energy efficiency."

[0727] Thus, this invention provides an interactive learning environment that utilizes the user's handwriting input, and plays a role in supporting problem-solving and creative thinking.

[0728] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0729] Step 1:

[0730] Users input ideas and shapes by hand on a digital device using a touch panel or stylus pen. The input is in the form of analog lines and letters, and is drawn on the device in real time. This is the initial data input for this system.

[0731] Step 2:

[0732] The device detects the user's handwriting input and collects the positional information of the entered lines and characters as coordinate data. This coordinate data is temporarily stored in the device's memory. Specifically, it continuously acquires coordinate points instantaneously in accordance with the user's movements.

[0733] Step 3:

[0734] The terminal formats the stored coordinate data and converts it into a format suitable for OCR and pattern recognition. It aligns the coordinates of the input handwritten data and outputs the result in a digital format that is easy to analyze. This formatted data is then passed on to subsequent processing.

[0735] Step 4:

[0736] The terminal transmits the formatted digital data to the server via the internet. Specifically, the terminal performs a procedure to transfer the data reliably and quickly using a transmission protocol. This prepares the data for the server to use in the next analysis step.

[0737] Step 5:

[0738] The server receives data transmitted from the terminal, identifies characters using OCR technology, and analyzes shapes and symbols using pattern recognition technology. The input is pre-formatted digital data, and the output is the interpreted strings and structured data resulting from the analysis. Specifically, the recognized characters and shapes are compared against known patterns in a database.

[0739] Step 6:

[0740] The server generates feedback using a generative AI model based on the analyzed information. The input is analyzed text and graphic information, which the server uses to create feedback containing appropriate information and suggestions. The AI ​​model references past data and related information to output the most relevant response.

[0741] Step 7:

[0742] The feedback generated from the server is sent back to the terminal. The terminal displays this feedback in a user-friendly format. This is usually presented as text information, but may include additional graphics or charts in some cases. This allows the user to visually obtain information and continue interacting with the device based on the output.

[0743] (Application Example 1)

[0744] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0745] Traditional handwriting input systems primarily relied on individual users independently inputting information and receiving feedback separately, making it difficult to achieve effective interaction in real-world gatherings and workshops involving multiple users. Furthermore, there was a lack of effective means to share ideas among participants and facilitate collaborative work.

[0746] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0747] In this invention, the server includes means for receiving handwritten input and converting it into digital information, means for analyzing the converted digital information to identify symbolic or graphic information, and means for generating a response using a machine learning model based on the identified information. This makes it possible to synchronize and share information among multiple users, and can support collaborative work in real-world gatherings.

[0748] "Handwriting input" refers to a method in which users manually input symbols and shapes using a tactile panel or similar device.

[0749] "Means of converting to digital information" refers to a device or process that converts handwritten input into an electronic format.

[0750] "Means for identifying symbolic or graphic information" refers to a device or program for recognizing characters or graphics from converted digital information.

[0751] "Means for generating responses using machine learning models" refers to a device or program that uses a trained algorithm based on recognized information to derive an appropriate response to the user.

[0752] A "user terminal" is an electronic device used by a user to receive or input information.

[0753] "Means for synchronizing and sharing information" refers to a device or program that integrates data entered by multiple users in real time, making it accessible to all simultaneously.

[0754] "Collaborative work in real-world gatherings" refers to activities in which many participants work together in a physical setting to generate new ideas.

[0755] This invention relates to a system including a terminal that allows a user to input handwritten information using a tactile panel and converts it into digital information. The terminal captures the user's input as location information, formats the data, and sends it to a server. The server analyzes the received digital information and identifies symbols or graphic information. Based on the identified information, it uses a machine learning model to generate an appropriate response for the user.

[0756] Specifically, the terminal uses software such as PIL (Python Imaging Library) and pytesseract to efficiently process handwritten data and convert it into digital data. The converted data is sent to a server via the internet. The server utilizes OCR technology and machine learning algorithms to analyze this data and generate the information and suggestions the user requests.

[0757] The server sends the generated response to the user's terminal, which then visually presents the response to the user. The user can then refer to this feedback and make further handwritten input. This process supports collaborative work in real-world gatherings and provides a means for synchronizing and sharing information among multiple users.

[0758] For example, if participants are discussing "energy efficiency" in a workshop, they can deepen the discussion by having the server analyze their handwritten ideas and related diagrams and immediately return relevant, up-to-date technical information and suggestions.

[0759] An example of a prompt for a generative AI model is shown below: "Analyze the given handwritten input image and generate proposals for new energy efficiency technologies."

[0760] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0761] Step 1:

[0762] The user uses a haptic panel to input handwriting. The input data consists of characters and shapes drawn by the user, which the device captures as location information. This location information then serves as foundational data for later digitization.

[0763] Step 2:

[0764] The device uses the captured location information to convert it into digital data using PIL (Python Imaging Library) and pytesseract. The input here is the location information obtained in step 1, and the output is text data processed through optical character recognition. The converted text data is temporarily stored locally.

[0765] Step 3:

[0766] The terminal sends the converted text data to the server via the internet. The input is text data, and the output is a signal indicating that the transmission to the server is complete. The requests library is used for this communication.

[0767] Step 4:

[0768] The server receives text data sent from the terminal and performs analysis using OCR technology and machine learning algorithms. The input for the analysis is the text data received by the server, and the output is the generation of response information based on the analysis results. At this stage, prompt sentences are formed to understand the meaning of the text data and generate possible suggestions.

[0769] Step 5:

[0770] The server processes the prompt using a generative AI model and creates a response that can be provided to the user. The prompt created in step 4 is used as input, and appropriate information or solutions are returned as output.

[0771] Step 6:

[0772] The server sends the generated response to the terminal. In this transmission process, the prepared response is redirected to the terminal. The input is the generated response data, and the output is the acknowledgment signal.

[0773] Step 7:

[0774] The terminal visually displays the response received from the server to the user. The user can then use this feedback to make further handwritten input. The input is the response data from the server, and the output is the action of displaying it on the screen.

[0775] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0776] This invention combines a digital interactive blackboard system with an emotion engine to provide feedback that simultaneously considers the user's handwritten input and their emotional state. In implementing this invention, the server, terminal, and user elements work in coordination.

[0777] 1. User operation

[0778] Users write letters and draw diagrams by hand on a digital whiteboard to record their thoughts. This operation is performed using the device's touch panel, and actions and patterns that may influence the user's emotional state are recorded in real time.

[0779] 2. Device functions

[0780] The device captures the user's handwritten data and converts it into digital data. Furthermore, it collects data to infer the user's emotional state from factors such as writing speed and pressure. An emotion engine analyzes this data to identify the user's emotional state.

[0781] 3. Server processing

[0782] The server receives handwritten data sent from the terminal and analyzes the character and graphic information using OCR technology. Based on the analyzed data, artificial intelligence generates relevant feedback. At the same time, it incorporates emotional state information from the emotion engine to adjust the content and tone of the feedback.

[0783] 4. Providing and displaying feedback

[0784] The server generates feedback, which is then sent to the terminal. The terminal visually displays the feedback to the user, providing emotionally resonant content. This enables flexible communication that responds to the user's reactions.

[0785] 5. User interaction

[0786] Based on the displayed feedback, users make new inputs, deepen their thinking, and work on solving further problems. Throughout this process, the emotion engine constantly monitors the user's emotional state to ensure the feedback is appropriate for them.

[0787] For example, when a user is contemplating a difficult concept, if the emotion engine detects the user's frustration, the server provides gentle, encouraging feedback that reflects that emotional state. In this way, the present invention functions as an interactive digital whiteboard that enhances the conversational experience while considering the user's emotions.

[0788] The following describes the processing flow.

[0789] Step 1:

[0790] The device captures handwritten data entered by the user on the digital whiteboard. This data includes information such as writing speed, pen pressure, and stroke direction.

[0791] Step 2:

[0792] The device converts the collected handwritten data into a digital format while simultaneously formatting auxiliary data (such as speed and pressure) that suggests emotion for the emotion engine.

[0793] Step 3:

[0794] The device transmits formatted handwritten data and sentiment-indicating data to a server via the internet. Data transmission is protected by encryption.

[0795] Step 4:

[0796] The server analyzes the handwritten data received from the terminal using OCR technology to identify characters and graphic information. Based on this analysis, it generates appropriate feedback candidates.

[0797] Step 5:

[0798] The server activates the emotion engine and analyzes emotion suggestion data to determine the user's emotional state. Emotional states such as frustration, interest, and concentration are identified.

[0799] Step 6:

[0800] The server adjusts the content and tone of feedback based on the user's emotional state. For example, if frustration is detected, it generates feedback that includes encouragement.

[0801] Step 7:

[0802] The server sends the refined feedback to the terminal. This feedback may include relevant information, suggestions, or specific responses to the user.

[0803] Step 8:

[0804] The device visually displays feedback received from the server in a user-friendly format. This feedback display includes colors and messages tailored to the user's emotional state.

[0805] Step 9:

[0806] The user reviews the displayed feedback and enters new questions or ideas by hand. The process is then repeated based on the user's actions.

[0807] (Example 2)

[0808] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0809] Conventional digital blackboard systems simply convert and display handwritten input as digital data, failing to provide feedback that takes into account the user's emotional state. Therefore, it was difficult to provide appropriate support tailored to the user's thoughts and feelings, and thus, an interactive learning experience could not be realized.

[0810] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0811] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the digital data to identify character or graphic information, and means for inferring the user's emotional state based on the user's input speed and pen pressure information. This enables the provision of feedback that is sensitive to the user's emotions and facilitates interactive communication.

[0812] "Handwriting input" refers to the act of a user drawing letters or shapes on a touch panel device using a pen or their finger.

[0813] "Converting to digital data" refers to the process of converting analog input information into an electronic data format, making it data that can be processed by a computer.

[0814] "Emotional state" refers to the user's psychological state, encompassing the totality of emotions inferred from factors such as input speed and pen pressure.

[0815] "Feedback" refers to the responses and advice that a system generates and provides to a user in response to their input and emotional state.

[0816] "Artificial intelligence" refers to a computer system that analyzes input data and automatically solves problems or makes decisions based on the information it has learned.

[0817] A "generative AI model" refers to an algorithmic model that learns from diverse data and generates output tailored to a specific task.

[0818] "Visual display" refers to showing information to the user through the device screen, and includes presentation in the form of text, images, and animations.

[0819] This invention allows users to express their thoughts and emotional states on a digital whiteboard by using a touch panel-equipped terminal to input handwritten information. The terminal is equipped with a pressure sensor that collects data such as the position, pressure, and speed of the characters and figures written by the user with high precision and converts it into digital data.

[0820] This converted data is sent to a server, which uses OCR technology to identify the information in the characters and shapes. Furthermore, by analyzing the user's input speed and pen pressure data obtained from the terminal, the emotion engine infers the user's emotional state.

[0821] Based on this data, the server generates feedback using a generative AI model that has learned from diverse data. The generated feedback takes emotional states into account and is delivered to the user in an appropriate tone. This feedback is sent to the device and displayed visually to the user. As a result, the user receives emotionally resonant, interactive feedback and deepens their thinking by providing further input.

[0822] For example, if a user types "I don't understand" while thinking about a difficult concept, the emotion engine detects the user's frustration, and the server provides gentle, encouraging feedback such as "You're almost there, keep trying." This allows the system to deeply understand the user's thoughts and feelings, enabling it to provide appropriate support in learning and work.

[0823] An example of a prompt message is, "Generate gentle and encouraging feedback to help the user solve the challenge they are currently facing." In this way, the present invention enables emotion-based interactive communication.

[0824] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0825] Step 1:

[0826] Users input characters and shapes by hand on a touch-panel device. The device receives this handwriting input via a pressure sensor and collects data such as position, pressure, and speed in real time. This converts the input data from analog to digital format and stores it in a database.

[0827] Step 2:

[0828] The terminal sends the collected digital data to the server. The server applies OCR technology to analyze the received data, identifying information in characters and shapes. This identified data is organized within the server and stored in a database. As a result, the handwritten content is output as structured digital information.

[0829] Step 3:

[0830] The server receives input speed and pressure information from the terminal and analyzes it using an emotion engine. The analysis results in an inference of the user's emotional state. Specifically, fast input speed and high pressure may indicate tension or stress, which the emotion engine detects. This analysis result is then prepared for the next step.

[0831] Step 4:

[0832] The server generates feedback using a generative AI model based on the identified handwritten data and sentiment analysis results. This prompt text and generative AI model are used to derive content that takes the user's emotions into consideration. For example, if the user writes "I don't understand," the AI ​​will generate an encouraging message such as "Calm down and try again." This ensures that the user receives appropriate feedback.

[0833] Step 5:

[0834] The generated feedback is sent from the server to the device, which displays it visually. The user receives this feedback and either provides further input or deepens their thinking. In this process, the generated feedback plays a role in understanding the user's feelings and providing a better experience.

[0835] (Application Example 2)

[0836] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0837] Digital interactive blackboard systems are required to provide feedback that not only accepts the user's handwritten input but also takes into account their emotional state at the time of input. Implementing such functionality can improve support for participants in workshops and educational seminars, thereby enhancing learning and comprehension.

[0838] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0839] In this invention, the server includes means for receiving handwritten input and converting it into digital data, means for analyzing the converted digital data to identify character or graphic information, and means for inferring the user's emotional state using an emotion analysis engine and adjusting the feedback based on that information. This enables flexible communication and feedback provision that takes into account both the user's handwritten input and emotional state.

[0840] "Handwriting input" refers to the act of a user drawing letters or shapes by hand using a touch panel or pen device.

[0841] "Digital data" refers to information that has been converted from handwritten input into a digital format, and is in a format that can be processed within a computer system.

[0842] An "artificial intelligence engine" is an algorithm or program used to analyze input data and generate appropriate feedback.

[0843] "Feedback" refers to information such as responses and comments that are generated in response to user input or status.

[0844] An "emotion analysis engine" is an algorithm or program that infers a user's psychological or emotional state from their input data and uses that information to adjust the system's response.

[0845] "Information equipment" refers to terminals and devices used for various information processing, including the display of digital data, and generally includes smartphones and tablets.

[0846] A "contact detection device" is a device used to detect a user's handwritten input, and typically uses a touchscreen or stylus pen.

[0847] The system implementing this invention consists of a terminal that receives user handwritten input and converts it into digital data, a server that analyzes the digital data, and a device that provides feedback. The specific operation of each of these elements is described below.

[0848] The device converts information entered by the user via handwriting using a touchscreen or stylus pen into digital data in real time. The user's handwriting speed and pressure are also captured simultaneously, and this data is used to infer the user's emotional state.

[0849] The server processes the digital data transmitted from the terminal. First, it uses OCR technology to identify characters and shapes, and then applies a generative AI model using this information to generate feedback. Furthermore, it uses an emotion analysis engine to infer the user's emotional state from data such as handwriting speed and pressure, and adjusts the feedback accordingly.

[0850] The generated feedback is transmitted to information devices and displayed visually to the user. In this process, the feedback is provided in a way that takes the user's emotional state into consideration, playing a role in facilitating smooth communication.

[0851] For example, if the emotion analysis engine infers that a participant is feeling impatient while learning a new concept in a workshop, the server will generate and display gentle feedback such as, "Let's calm down and learn one step at a time."

[0852] As a concrete example, an example of a prompt message is shown below.

[0853] "Strong pen pressure and fast input have been detected. Please generate feedback to promote relaxation."

[0854] Thus, the present invention makes it possible to provide an interactive learning experience through emotion-responsive feedback.

[0855] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0856] Step 1:

[0857] Users input handwritten data using a touchscreen on an information device. This input behavior is captured, and characteristic data such as pen pressure and speed are collected simultaneously. This generates digital data of the handwritten characters and shapes.

[0858] Step 2:

[0859] The terminal converts the collected handwritten input data into a digital format and sends that digital data to the server. The characteristics of the input data (speed, pressure) are transmitted separately for sentiment analysis. The handwritten data is supplied to the server as input and identified as handwritten information and characteristic data.

[0860] Step 3:

[0861] The server uses OCR technology to recognize and analyze characters and shapes from incoming digital data. This analysis process generates specific character information as output. The calculated character information forms the basis for feedback generation.

[0862] Step 4:

[0863] The server uses an emotion analysis engine to analyze feature data and infer the user's emotional state. It performs data calculations based on the pressure and speed information of the input data and outputs the inferred emotional state.

[0864] Step 5:

[0865] The server utilizes a generative AI model to generate feedback based on analyzed text information and emotional states. A prompt sentence reflecting the emotional state is used as input, and text information is output as feedback.

[0866] Step 6:

[0867] The server sends the generated feedback to the information device, where it is displayed. This feedback is visualized in a way that takes the user's emotional state into consideration, guiding further handwriting input. The received output text is then displayed on the information device.

[0868] Step 7:

[0869] The user uses the displayed feedback to perform the next handwriting input, and this process is repeated. New handwriting input is provided by the user, and the output returns to step 1 again.

[0870] This process provides users with flexible, emotionally resonant feedback in real time.

[0871] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0872] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0873] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0874] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0875] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0876] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0877] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0878] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0879] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0880] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0881] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0882] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0883] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0884] 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.

[0885] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0886] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0887] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0888] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0889] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0890] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0891] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0892] The following is further disclosed regarding the embodiments described above.

[0893] (Claim 1)

[0894] A means of receiving handwritten input and converting it into digital data,

[0895] A means for analyzing converted digital data to identify character or graphic information,

[0896] A means of generating feedback using artificial intelligence based on identified information,

[0897] A means of sending the generated feedback to the user's device and displaying it visually,

[0898] A means of receiving further handwritten input from the user and repeating the process in the same way,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, wherein the artificial intelligence comprises means for optimizing feedback based on the user's past handwriting input history and feedback history.

[0902] (Claim 3)

[0903] The system according to claim 1, wherein the means for receiving the handwritten input includes means for capturing the user's input from a touch panel and saving it as coordinate data.

[0904] "Example 1"

[0905] (Claim 1)

[0906] A means of receiving handwritten input and converting it into data,

[0907] A means of analyzing the converted data to identify information,

[0908] A means of generating a response using machine learning based on identified information,

[0909] Means for sending and displaying the generated response on the user's device,

[0910] A means of receiving further handwritten input from the user and repeating the process in the same way,

[0911] A means of acquiring coordinate data in real time and temporarily recording it,

[0912] A means of formatting data and transmitting it through a communication network,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, wherein the machine learning comprises means for optimizing the response based on the user's past handwriting input history and response history.

[0916] (Claim 3)

[0917] The system according to claim 1, wherein the means for receiving the handwritten input includes means for capturing the user's input from a pressure-sensitive device and storing it as coordinate data.

[0918] "Application Example 1"

[0919] (Claim 1)

[0920] A means of receiving handwritten input and converting it into digital information,

[0921] A means for analyzing converted digital information to identify symbolic or graphic information,

[0922] A means of generating a response using a machine learning model based on identified information,

[0923] A means of sending the generated response to the user terminal and displaying it visually,

[0924] A means of receiving further handwritten input from the user and repeating the process in the same way,

[0925] To support collaborative work in real-world gatherings, a means of synchronizing input and sharing displays among multiple users,

[0926] A system that includes this.

[0927] (Claim 2)

[0928] The system according to claim 1, wherein the machine learning model includes means for optimizing responses based on the user's past handwriting input history and response history.

[0929] (Claim 3)

[0930] The system according to claim 1, wherein the means for receiving the handwritten input includes means for capturing the user's input from a tactile panel and storing it as location information.

[0931] "Example 2 of combining an emotion engine"

[0932] (Claim 1)

[0933] A device that receives handwritten input and converts it into digital data,

[0934] A device that analyzes converted digital data to identify character or graphic information,

[0935] A device that infers emotional state based on identified information and the user's input speed and pen pressure information,

[0936] A device that generates feedback using artificial intelligence based on emotional state and identification information,

[0937] A device that transmits the generated feedback to the user's terminal in an appropriate tone and displays it visually,

[0938] While providing feedback that aligns with the user's emotions, it also accepts further handwritten input.

[0939] A device that repeats the same process,

[0940] A system that includes this.

[0941] (Claim 2)

[0942] The system according to claim 1, wherein the estimation of the emotional state includes means for analyzing the user's handwriting speed and pressure data.

[0943] (Claim 3)

[0944] The system according to claim 1, wherein the artificial intelligence is equipped with a device that optimizes feedback based on past user handwritten input and emotional state data.

[0945] "Application example 2 when combining with an emotional engine"

[0946] (Claim 1)

[0947] A means of receiving handwritten input and converting it into digital data,

[0948] A means for analyzing converted digital data to identify character or graphic information,

[0949] A means of generating feedback using an artificial intelligence engine based on identified information,

[0950] A means of using an emotion analysis engine to estimate the user's emotional state and adjusting feedback based on the estimated emotional state,

[0951] A means for transmitting generated feedback and emotionally-based adjustment information to the user's information device and displaying it visually,

[0952] A means of receiving further handwritten input from the user and repeating the process in the same way,

[0953] A system that includes this.

[0954] (Claim 2)

[0955] The system according to claim 1, wherein the artificial intelligence engine comprises means for optimizing feedback based on the user's past handwriting input history, feedback history, and emotional state history.

[0956] (Claim 3)

[0957] The system according to claim 1, wherein the means for receiving the handwritten input includes means for capturing the user's input from a contact detection device and storing it as coordinate data. [Explanation of Symbols]

[0958] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving handwritten input and converting it into digital data, A means for analyzing converted digital data to identify character or graphic information, A means of generating feedback using artificial intelligence based on identified information, A means of sending the generated feedback to the user's device and displaying it visually, A means of receiving further handwritten input from the user and repeating the process in the same way, A system that includes this.

2. The system according to claim 1, wherein the artificial intelligence is provided with means for optimizing feedback based on the user's past handwriting input history and feedback history.

3. The system according to claim 1, wherein the means for receiving the handwritten input includes means for capturing the user's input from a touch panel and saving it as coordinate data.

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