system

Abstract

A system is provided.SOLUTION: A system including a unit that acquires image data from a paper medium, analyzes the image data, and extracts text data, a unit that converts the text data into electronic data, stores the electronic data in a JSON format, a unit that generates a QR code based on the electronic data in the JSON format, a unit that stores the QR code and the electronic data in the JSON format, a unit that searches for the electronic data in the JSON format based on a user input, and a unit that analyzes the electronic data and extracts a specific pattern or a trend.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, many companies use paper media, which often makes data management, search, and analysis difficult. The process of manually digitizing paper data is particularly time-consuming and labor-intensive, and prone to errors. Furthermore, the digitized data itself is not centrally managed, making it difficult to quickly search and analyze the necessary information. The purpose of this invention is to solve these problems by efficiently and accurately digitizing paper data and centrally managing that data, thereby facilitating quality control, analysis, and search. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for acquiring image data from paper media, analyzing the image data, and extracting text data. It also includes a means for converting the text data into electronic data and saving it in JSON format, a means for generating a QR Code (registered trademark) based on the JSON-formatted electronic data, a means for saving the QR code and the JSON-formatted electronic data, a means for searching the JSON-formatted electronic data based on user input, and a means for analyzing the electronic data to extract specific patterns and trends. This allows for efficient digitization of paper-based data and centralized management using QR codes. It also facilitates data search and analysis, improving the efficiency of a company's quality control operations.

[0006] "Paper media" refers to information materials printed or written on paper.

[0007] "Image data" refers to digital data in the form of an image acquired using a scanner, camera, or the like.

[0008] "OCR (Optical Character Recognition)" refers to a technology that analyzes characters contained in image data and converts them into text data.

[0009] "Text data" refers to data in which characters and sentences are represented in digital form.

[0010] "Electronic data" refers to data in digital form that is stored, analyzed, and processed in a computer system.

[0011] "JSON format" refers to a structured data format characterized by representing data objects as attribute-value pairs.

[0012] "QR code" refers to a two-dimensional barcode represented by a square pattern that encodes information.

[0013] "Storage means" refers to a method or device for storing data physically or digitally.

[0014] "Search means" refers to a method or device for searching data based on specified conditions and extracting relevant data.

[0015] "Analytical means" refers to a method or device that analyzes data and extracts specific patterns or trends.

[0016] "User input" refers to the act of a user providing information to a system using a keyboard, touch panel, etc. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The embodiments of the present invention will be specifically described below.

[0039] System Configuration

[0040] The present invention is a system that efficiently digitizes paper-based data and centrally manages it using QR codes. This system mainly includes the following main processing steps.

[0041] 1. Data extraction from paper documents

[0042] 2. Conversion and structuring of electronic data

[0043] 3. Generate and save a QR code

[0044] 4. Data retrieval and analysis

[0045] Data extraction examples

[0046] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[0047] Data digitization and storage

[0048] The device converts the text data extracted from the image into electronic data and stores it in JSON format. This structured data makes it easier to manage, search, and analyze. For example, the following JSON format data is generated:

[0049] {

[0050] "Invoice Number": "001",

[0051] "Date": "2023-09-20",

[0052] "Amount": "10000"

[0053] }

[0054] The device stores this data in a storage directory and simultaneously generates a QR code.

[0055] QR code generation and output

[0056] The terminal generates a QR code based on the JSON-formatted digital data. This QR code is an encoded form of the digital data, and the user can print it or save it digitally. For example, it can be saved as "invoice_001_qr.png."

[0057] Searching for Data

[0058] When a user enters a search keyword into the system, the device searches the saved JSON data. For example, if you search for data for "May 2022," the device will scan all JSON files in the specified directory and extract the relevant entries. The search results are then provided to the user, allowing them to quickly access the desired information.

[0059] Analyzing the data

[0060] If a user requests data analysis, the server analyzes the stored data. This analysis may involve extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their operations.

[0061] As described above, the system of the present invention efficiently digitizes paper-based data and centrally manages it, making it easy to search and analyze information. Users can use the system with simple operations, which can significantly improve business efficiency in companies.

[0062] The processing flow will be explained below.

[0063] Step 1: Importing image data

[0064] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[0065] Step 2: Extract text using OCR

[0066] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[0067] Step 3: Structuring the electronic data

[0068] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[0069] Step 4: Generate a QR code

[0070] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[0071] Step 5: Save your data

[0072] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[0073] Step 6: Search for data

[0074] The user enters specific keywords or conditions into the system to perform a data search, and the device searches for JSON files in the storage directory and extracts data that matches the keywords.

[0075] Step 7: Viewing search results

[0076] The device displays the search results to the user, who can then access the information they need and use it in their work.

[0077] Step 8: Analyze the data

[0078] When a user requests that their data be analyzed, the server receives the stored data and performs the analysis, which includes extracting specific patterns or trends.

[0079] Step 9: Provide analysis results

[0080] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[0081] In this way, the processing steps of this system work in cooperation with each user, terminal, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis.

[0082] Example 1

[0083] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0084] Traditional systems that extract information from paper media, digitize it, and then manage and search it are inefficient because they require a lot of manual work and time. Furthermore, there are many issues, such as incorrect recognition of extracted data, low search accuracy, and difficulty in data analysis. This reduces the efficiency of information management and makes it difficult to respond quickly to business requests.

[0085] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0086] In this invention, the server includes means for acquiring image data from paper media, analyzing the image data, and extracting text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON-formatted electronic data, means for saving the QR code and the JSON-formatted electronic data, means for searching the JSON-formatted electronic data based on user input, means for analyzing the electronic data and extracting specific patterns or trends, means for extracting text data using OCR technology, means for providing the saved QR code to a user, means for saving the electronic data in a database and making it accessible, means for notifying the user of the generated data, and means for encoding the generated QR code and visually displaying it, thereby enabling efficient digitization of information from paper media, centralized management, and rapid search and analysis.

[0087] "Paper media" refers to physically printed documents and materials.

[0088] "Image data" refers to information captured from paper media and expressed visually, such as in bitmap format.

[0089] "Analysis" refers to the general process of extracting useful information from acquired image data.

[0090] "Text data" refers to character information extracted from analyzed image data.

[0091] "Electronic data" means information stored in digital form.

[0092] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and is a type of lightweight data exchange format.

[0093] A "QR code" is a type of two-dimensional barcode that is used to read information quickly.

[0094] "Storage" means storing data in a certain location or storage device.

[0095] "User input" refers to instructions or commands from anyone using the system.

[0096] "Searching" is the act of finding specific information in a database or stored files.

[0097] An "analytical tool" is a method or device that reads data and finds specific patterns or trends within it.

[0098] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that reads character information from image data.

[0099] "Output means" refers to a mechanism for outputting processed data or generated information by displaying, printing, or the like.

[0100] A "database" is a system for systematically organizing data and efficiently storing and searching it.

[0101] "Notification" is the act of informing a user of certain information.

[0102] "Encoding" is the process of converting information into a particular format.

[0103] "Visual display" means graphically expressing the generated data and information and providing it in a form that is easy for the user to understand.

[0104] The following is a detailed description of an embodiment of the present invention. The present invention is a system that efficiently digitizes data on paper media and centrally manages it using QR codes. This system is operated mainly by three entities: a server, a terminal, and a user.

[0105] System Configuration

[0106] The system of the present invention comprises the following main processing steps:

[0107] 1. Data extraction from paper documents

[0108] 2. Conversion and structuring of electronic data

[0109] 3. Generate and save a QR code

[0110] 4. Data retrieval and analysis

[0111] Hardware and Software Use

[0112] The implementation of the present invention uses the following hardware and software:

[0113] Scanner or smartphone: Used to capture paper media as image data.

[0114] OCR technology: Used to extract text data from image data. An example is Tesseract OCR.

[0115] Database: Used to store electronic data. An example is MongoDB.

[0116] QR code generation library: Used to generate QR codes. A specific example is the Python qrcode library.

[0117] Data search engine: Used to search stored electronic data. An example is ElasticSearch (registered trademark).

[0118] Data analysis libraries: used to analyze stored data. Examples include Python's pandas and numpy.

[0119] Specific processing explanation

[0120] Data Extraction

[0121] The user captures paper documents as images using a scanner or smartphone. For example, the user takes a photo of an invoice image file "invoice_001.jpg" with their smartphone and uploads it to the system. The device receives the uploaded image file and temporarily saves it in secure storage. The server validates the image data and checks whether it is in the correct format. If it is not correct, it sends a notification prompting the user to re-upload. The server uses OCR technology to analyze the image data and extract text data such as "invoice number, date, amount."

[0122] Electronic Data Storage

[0123] The device converts the extracted text data into JSON format, producing data like this:

[0124] json

[0125] {

[0126] "Invoice Number": "001",

[0127] "Date": "2023-09-20",

[0128] "Amount": "10000"

[0129] }

[0130] The terminal stores this data in a storage directory and saves it in a database.

[0131] QR code generation and notification

[0132] The device generates a QR code based on the saved JSON data. The Python qrcode library is used to generate the code. The generated QR code image is saved as "invoice_001_qr.png" and a download link is sent to the user.

[0133] Searching for Data

[0134] When a user enters a search keyword on the search screen, for example, "May 2022," the device scans the stored database for the relevant JSON file. The Elasticsearch engine is used for the search. The search results are provided to the user, allowing them to quickly view the relevant invoice information.

[0135] Analyzing the data

[0136] When a user wants to analyze data, they specify the specific analysis target and conditions and send a request to the server. The server analyzes the stored data and extracts specific patterns and trends. For example, it uses Python's pandas library to build a data frame and aggregate specific field information (such as "amount"). The analysis results are provided to the user and displayed as a visual report.

[0137] Specific examples

[0138] For example, a user uploads an invoice like this:

[0139] Invoice file name: invoice_001.jpg

[0140] Included information: Invoice number 001, date 2023-09-20, amount 10,000 yen

[0141] The device does the following:

[0142] 1. Text data extraction using OCR technology

[0143] 2. Convert to JSON format and save to storage

[0144] 3. Generate a QR code from the data

[0145] The generated QR code is saved as "invoice_001_qr.png", and by scanning this QR code, users can quickly access the relevant data.

[0146] Prompt Sentence Examples

[0147] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[0148] By following the above steps, users can efficiently digitize paper-based data and centralize information management through QR codes.

[0149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0150] Step 1: Import and upload image data

[0151] The user takes a photo of a paper document (e.g., an invoice) with a scanner or smartphone and uploads it to the device as image data (e.g., "invoice_001.jpg"). The device receives this image data and temporarily stores it in secure storage.

[0152] Input: Image data of paper media (e.g. "invoice_001.jpg")

[0153] Output: Image data temporarily stored in secure storage

[0154] Step 2: Validate the image data

[0155] The server validates the image data to ensure it is in the correct format, resolution, etc. If it is in an inappropriate format or resolution, it sends a notification to the user urging them to re-upload.

[0156] Input: Temporarily saved image data

[0157] Output: Validated for proper format and resolution, and notifies user if necessary

[0158] Step 3: Extract text data using OCR analysis

[0159] The server uses Tesseract OCR technology to extract text information from image data, for example, extracting field information such as "invoice number, date, amount" from "invoice_001.jpg".

[0160] Input: Validated image data

[0161] Output: Extracted text data (e.g., "Invoice number: 001, Date: 2023-09-20, Amount: 10000")

[0162] Specific operation: Obtain text data using Tesseract OCR's image_to_string method

[0163] Step 4: Converting text data to JSON format

[0164] The device converts the extracted text data into JSON format, for example:

[0165] json

[0166] {

[0167] "Invoice Number": "001",

[0168] "Date": "2023-09-20",

[0169] "Amount": "10000"

[0170] }

[0171] Input: Extracted text data

[0172] Output: Data converted to JSON format

[0173] Step 5: Saving JSON Data

[0174] The device saves the converted JSON data in secure storage or a database (e.g., MongoDB), and notifies the user when the data has been saved.

[0175] Input: JSON format data

[0176] Output: JSON data saved in the database, save completion notification

[0177] Step 6: Generate a QR code

[0178] The device generates a QR code based on the stored JSON data. It uses the Python qrcode library to create an encoded QR code image.

[0179] Input: JSON format data

[0180] Output: Generated QR code image (e.g. "invoice_001_qr.png")

[0181] Step 7: Save and notify the QR code

[0182] Save the generated QR code image and send a notification to the user providing a download link.

[0183] Input: Generated QR code image

[0184] Output: QR code image saved in secure storage, notification of download link

[0185] Step 8: Search for data

[0186] The user enters a search keyword (e.g., "May 2022") into the system. The device uses the Elasticsearch engine to search for JSON data in the database.

[0187] Input: User-entered search keywords

[0188] Output: Search results for relevant JSON data

[0189] Step 9: Viewing search results

[0190] The search results are provided to the user by the terminal, allowing the user to quickly access the desired information.

[0191] Input: Searched JSON data

[0192] Output: Search results displayed to the user

[0193] Step 10: Analyze the data

[0194] A user submits a specific data analysis request to the system, and the server uses a data analysis library (e.g., pandas) to analyze the stored data and extract specific patterns or trends.

[0195] Input: User analysis request, data stored in the database

[0196] Output: Analysis results, visual reports

[0197] As a concrete example of operation, the following prompt sentence can be used:

[0198] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[0199] (Application example 1)

[0200] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0201] In logistics centers, manually managing paper-based inbound and outbound shipping slips and inspection reports causes many problems, including reduced work efficiency and the possibility of human error. This reduces overall business productivity and complicates information management. Furthermore, the task of searching and analyzing past data is cumbersome, making it difficult to quickly obtain information in real time. Therefore, there is a demand for a system that digitizes paper-based document management and provides efficient, centralized management.

[0202] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0203] In this invention, the server includes: means for acquiring image data from paper media and analyzing the image data to extract text data; means for converting the text data into electronic data and saving it in JSON format; means for generating a QR code based on the JSON-formatted electronic data; means for searching the JSON-formatted electronic data based on user input; means for analyzing the electronic data to extract specific patterns and trends; and means for photographing paper-based receipt / shipment slips and inspection reports at a logistics center using a smartphone or a camera-equipped robot, analyzing them using OCR technology to extract field information such as item name, quantity, and inspection results, saving the field information in JSON format, generating a QR code, and having an operator scan the QR code with a smartphone or robot to confirm the information. This digitizes paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis.

[0204] "Paper media" refers to media on which information is physically printed, such as documents and slips printed on paper.

[0205] "Image data" refers to image data acquired using a scanner or camera, and is information written on paper that is stored electronically.

[0206] "Text data" refers to character string information extracted from image data, and is character data recognized by OCR technology.

[0207] "Electronic data" refers to data in a digital format that is handled within a computer system and stored in JSON or other structured data formats.

[0208] "JSON format" stands for JavaScript Object Notation, a text-based data format that makes it easy to describe data structures.

[0209] A "QR code" is a square, two-dimensional barcode that digitally encodes information and can be scanned to quickly retrieve that information.

[0210] A "logistics center" is a facility where logistics operations are carried out, and where goods are received, shipped, stored, and managed.

[0211] A "shipping / receiving slip" is a document that records information about the receipt and dispatch of goods at a logistics center.

[0212] An "inspection report" is a document that records the results of a product's quality inspection at a logistics center.

[0213] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that automatically recognizes characters from image data and extracts them as text data.

[0214] "Mobile device" refers to a smartphone, tablet, or other portable electronic device, often equipped with a camera and communication capabilities.

[0215] A "camera-equipped robot" is a robot equipped with a camera that can move and take pictures automatically, and is used to improve work efficiency in logistics centers and other places.

[0216] The present invention provides a system for digitalizing and centrally managing paper-based documents in a logistics center.

[0217] System Configuration

[0218] The present invention uses the following main hardware and software:

[0219] Hardware: scanners, smartphones, robots with cameras.

[0220] Software: OCR technology (Tesseract OCR), Python library (qrcode), database (MySQL, PostgreSQL).

[0221] Hardware and Software Use

[0222] 1. Acquiring image data from paper media:

[0223] The server allows logistics center workers to acquire image data of paper-based shipping and receiving slips and inspection reports using smartphones or camera-equipped robots.

[0224] 2. Image data analysis and text data extraction:

[0225] The server analyzes the acquired image data using OCR technology and extracts field information such as product name, quantity, and inspection results as text data.

[0226] Specifically, Tesseract OCR is used to read text data from images.

[0227] 3. Conversion and storage of text data into electronic data:

[0228] The server converts the extracted text data into electronic data in JSON format and stores it in a database.

[0229] This makes the data structured and easier to search and analyze.

[0230] 4. Generate and save the QR code:

[0231] The server generates a QR code based on the electronic data in JSON format.

[0232] QR codes are used by workers to scan them with their smartphones or camera-equipped robots to check the information.

[0233] 5. Data retrieval and analysis:

[0234] The server searches for electronic data in JSON format based on user input and quickly provides the required information.

[0235] We also provide a data analysis function that extracts specific patterns and trends, and the analysis results can be used to improve business operations.

[0236] Example

[0237] Use within a distribution center:

[0238] A worker uses a smartphone to take a photo of the delivery slip for the incoming goods.

[0239] The server uses OCR technology to extract the product name, quantity, and inspection results from the image of the invoice and saves them in JSON format.

[0240] QR codes are generated from JSON format data, and workers can scan them with their smartphones to access the necessary information in real time.

[0241] Prompt Sentence Examples

[0242] We are considering digitizing inbound and outbound delivery slips at our logistics center. How can we take a photo of a paper-based slip, extract the data using OCR processing, save it in JSON format, and generate a QR code?

[0243] This system will streamline paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis. It is expected to improve the overall productivity of logistics operations, reduce human error, and improve operational efficiency.

[0244] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0245] Step 1:

[0246] A user takes a photo of a paper document (e.g., receipt / shipping slip, inspection report) using a smartphone or a camera-equipped robot. Image data (e.g., JPEG, PNG format) is generated as input. This image data is then uploaded to the system as output.

[0247] Step 2:

[0248] The server receives the uploaded image data and analyzes it using OCR technology (Tesseract OCR). Image data is given as input, and extracted text data is generated as output. Specifically, the character information in the image is converted into text data.

[0249] Step 3:

[0250] The server parses the extracted text data into field information. Text data is given as input, and structured electronic data (e.g., JSON format) is generated as output. Specifically, field information such as product name, quantity, and inspection results is parsed and structured.

[0251] Step 4:

[0252] The server stores structured electronic data in JSON format. JSON format data is given as input and saved in a database as output. Specifically, a storage directory is specified in the database (e.g., MySQL, PostgreSQL) and the data is stored.

[0253] Step 5:

[0254] The server generates a QR code based on the stored JSON format digital data. JSON data is given as input, and a QR code image is generated as output. Specifically, the QR code is generated using the Python qrcode library.

[0255] Step 6:

[0256] The server saves the generated QR code. The QR code image is given as input and stored in a directory as output. Specifically, the QR code image is saved in a specified directory and provided to the worker.

[0257] Step 7:

[0258] The user enters keywords to search for the information they need. The search keywords are given as input, and related JSON data is returned as output. Specifically, the JSON data in the database is searched and the relevant entries are extracted.

[0259] Step 8:

[0260] The server analyzes the relevant JSON data and extracts specific patterns and trends. The JSON data of the search results is given as input, and the analysis results are provided as output. Specifically, data analysis algorithms are used to visualize trends and help improve business operations.

[0261] The processing flow of this program digitizes paper document management at logistics centers, enabling efficient information search and analysis.

[0262] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0263] The embodiments of the present invention will be specifically described below.

[0264] System Configuration

[0265] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[0266] 1. Data extraction from paper documents

[0267] 2. Conversion and structuring of electronic data

[0268] 3. Generate and save a QR code

[0269] 4. Data retrieval and analysis

[0270] 5. User Emotion Recognition by Emotion Engine

[0271] Data extraction examples

[0272] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[0273] Data digitization and storage

[0274] The device converts the text data extracted from the image into electronic data and saves it in JSON format. This structured the data, making it easier to process and search later. For example, the following JSON format data is generated:

[0275] {

[0276] "Invoice Number": "001",

[0277] "Date": "2023-09-20",

[0278] "Amount": "10000"

[0279] }

[0280] The device stores this data in a storage directory and simultaneously generates a QR code.

[0281] QR code generation and output

[0282] The device generates a QR code based on the JSON data. This QR code is an encoded form of electronic data that the user can print or save digitally, for example, as "invoice_001_qr.png."

[0283] Searching for Data

[0284] The user enters specific keywords or conditions into the system to perform a data search. The device searches the JSON data in the storage directory and extracts entries that match the keywords. The search results are provided to the user, allowing them to quickly access the desired information.

[0285] Analyzing the data

[0286] If a user requests data analysis, the server analyzes the stored data. This analysis may include extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their business.

[0287] Recognizing user emotions with an emotion engine

[0288] An emotion engine is built into the system, which analyzes the user's voice and text inputs to recognize their emotions. This emotion data is used to adjust the system's response. For example, if the user is expressing dissatisfaction, the system will adjust to provide a more friendly response.

[0289] Examples of emotion engines

[0290] If a user types something into the system like "Work was tough today," the emotion engine will analyze this text and recognize that the user is tired. Based on this emotion data, the server will generate a response to the user such as "Thank you for your hard work. Maybe you should take a break."

[0291] This will improve the user experience and increase satisfaction when using the system. Emotion recognition technology can also be effectively used to improve user interfaces and customer support.

[0292] As described above, this system works in cooperation with each user, device, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis. Furthermore, it has an emotion engine that recognizes user emotions and adjusts the system's response.

[0293] The processing flow will be explained below.

[0294] Step 1: Importing image data

[0295] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[0296] Step 2: Extract text using OCR

[0297] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[0298] Step 3: Structuring the electronic data

[0299] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[0300] Step 4: Generate a QR code

[0301] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[0302] Step 5: Save your data

[0303] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[0304] Step 6: Emotion Recognition with the Emotion Engine

[0305] The user inputs text into the system. The device receives this input and uses the emotion engine to analyze the user's emotions. For example, if the user inputs "I'm tired today," the emotion engine analyzes this text and recognizes that the user is tired.

[0306] Step 7: Generate a response based on emotion

[0307] The server receives the analysis results from the emotion engine and adjusts the system's response accordingly. For example, if it determines that the user is tired, it will generate a friendly message such as, "Thank you for your hard work. We recommend that you take a break."

[0308] Step 8: Search for data

[0309] The user enters specific keywords or conditions into the system to perform a data search, and the device searches the JSON files in the storage directory and extracts entries that match the keywords.

[0310] Step 9: Viewing search results

[0311] The device displays the search results to the user, who can then access the information they need and use it in their work.

[0312] Step 10: Analyze the data

[0313] If the user requests that the data be analyzed, the server will analyze the stored data, which may involve extracting specific patterns or trends.

[0314] Step 11: Provide analysis results

[0315] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[0316] Through the above processing steps, users, terminals, and servers work together to operate the system efficiently, and business efficiency and user satisfaction can be improved through the digitization of paper-based data and emotion recognition functions.

[0317] Example 2

[0318] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0319] Conventional systems have had the problem that the process of digitizing and managing paper-based data is complicated, and data search and analysis take a long time. Furthermore, there is a lack of technology to recognize user emotions and reflect them in the system's responses, which has resulted in a lack of improvement in the user experience. It is necessary to solve these problems and provide an efficient and user-friendly data management system.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0321] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the extracted text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data, means for analyzing the electronic data to extract specific patterns or trends, means for analyzing a user's voice input or text input to recognize emotions, and means for adjusting the system response based on the recognized emotion data. This allows for efficient electronic conversion of paper medium data, facilitating search and analysis, and enabling responses according to the user's emotions.

[0322] "Image data" is data that expresses information acquired from paper media in an image format.

[0323] "Text data" is data that includes character information extracted from image data.

[0324] "Electronic data" refers to text data that has been converted into an electronic format and stored.

[0325] The "JSON format" is a lightweight data interchange format used to store electronic data.

[0326] A "QR code" is a square-shaped two-dimensional code that encodes and visually represents information.

[0327] "User voice input" is voice data provided by a user to the system through a microphone or other voice capturing device.

[0328] "Text input" is string information that a user provides to a system using a keyboard or other input device.

[0329] "Emotion recognition" is the process of analyzing a user's voice or text input to identify the user's emotional state.

[0330] "Search method" is a function that searches stored electronic data in JSON format based on specific conditions.

[0331] "Extracting specific patterns and trends" is the process of analyzing electronic data to find significant patterns and trends.

[0332] The "means for adjusting response" is a function for changing the way the system responds based on the recognized user emotion.

[0333] System Configuration

[0334] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[0335] Hardware and Software Used

[0336] Scanner or smartphone: Used to capture paper data as an image.

[0337] OCR engine (e.g. Tesseract OCR): Extracts text data from image data.

[0338] Terminal: A device that accepts user operations and processes data.

[0339] Server: A device used to store, retrieve, and analyze data.

[0340] QR code generation software (e.g., Python's qrcode library): Generates QR codes from JSON-formatted data.

[0341] Emotion recognition engines (e.g., Python's TextBlob library): Analyze emotions from user voice or text input.

[0342] Data processing and calculation flow

[0343] The user captures paper documents as images using a scanner or smartphone. Specifically, they upload the invoice image file "invoice_001.jpg" to the system. The device then analyzes this image data using OCR technology and extracts text data. The extracted text data contains field information such as "invoice number, date, amount." At this stage, JSON-formatted data like the one below is generated.

[0344] json

[0345] {

[0346] "Invoice Number": "001",

[0347] "Date": "2023-09-20",

[0348] "Amount": "10000"

[0349] }

[0350] The device converts this JSON data into a QR code using QR code generation software. The generated QR code is saved as "invoice_001_qr.png" and the user can print it or save it digitally.

[0351] Examples of concrete examples and prompt sentence usage

[0352] For example, if a user takes a picture of an invoice with their smartphone and uploads it to the system as "invoice_001.jpg," the image data will be analyzed using an OCR engine, and the following text data will be extracted:

[0353] Invoice number: 001

[0354] Date: 2023-09-20

[0355] Amount: 10,000

[0356] This text data is converted to JSON format,

[0357] {

[0358] "Invoice Number": "001",

[0359] "Date": "2023-09-20",

[0360] "Amount": "10000"

[0361] }

[0362] The device generates a QR code from this JSON data and saves it as "invoice_001_qr.png".

[0363] Furthermore, if a user inputs text such as "Work was tough today," the emotion recognition engine analyzes the text and recognizes that the user is tired. Based on this recognition result, the server generates a response message such as "Thank you for your hard work. Maybe it would be good to take a short break."

[0364] As a result, this system not only efficiently digitizes paper data and facilitates subsequent search and analysis, but also recognizes the user's emotions and provides appropriate feedback.

[0365] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0366] Explain the program's processing flow in detail

[0367] Step 1:

[0368] The user captures paper documents as images using a scanner or smartphone. Specifically, the user uploads the invoice image file "invoice_001.jpg" to the system. The input is the image data "invoice_001.jpg," and the output is that this image data is imported into the system. At this stage, the terminal receives the image data and prepares it for subsequent processing.

[0369] Step 2:

[0370] The terminal uses OCR technology (e.g., Tesseract OCR) to analyze the input image data and extract text data. The input is the image data "invoice_001.jpg" captured in step 1, and the output is the extracted text data. This text data includes field information such as "invoice number, date, and amount." Specifically, the OCR engine is called to perform image analysis and obtain text information.

[0371] Step 3:

[0372] The terminal converts the extracted text data into electronic data and saves it in JSON format. The input is the text data extracted in step 2, and the output is JSON format data. Specifically, the following JSON data is generated:

[0373] json

[0374] {

[0375] "Invoice Number": "001",

[0376] "Date": "2023-09-20",

[0377] "Amount": "10000"

[0378] }

[0379] The device stores this JSON data in the specified save directory.

[0380] Step 4:

[0381] The device generates a QR code based on the saved JSON data. The input is the JSON data generated in step 3, and the output is an image file of the QR code. Specifically, the QR code is generated using the Python qrcode library and saved as "invoice_001_qr.png." The device provides this file to the user.

[0382] Step 5:

[0383] The user enters specific keywords or conditions into the system, and the device searches for JSON data in the storage directory. The input is the search conditions entered by the user (e.g., "Invoice number is 001"), and the output is the search results. The device searches the stored JSON files and extracts the corresponding entries. Specifically, it reads the matching files from the file system and displays their contents to the user.

[0384] Step 6:

[0385] When a user requests data analysis, the server analyzes the stored data. The input is the user's analysis request (e.g., "analyze trends in billing data for the past year"), and the output is the analysis results. The server uses Python's pandas library to read the data and extract patterns and trends. For example, it can graph fluctuations in the number and amount of bills by month and provide this to the user.

[0386] Step 7:

[0387] An emotion engine is used to analyze a user's voice or text input and recognize the user's emotion. The input is the user's voice or text input (e.g., "Work was tough today") and the output is the recognized emotion data. An emotion engine (e.g., TextBlob) is used to parse the input data and identify the user's emotion.

[0388] Step 8:

[0389] The server adjusts the system's response based on the recognized emotion data. The input is the emotion data recognized in step 7, and the output is the adjusted response message. For example, if the user expresses the emotion "I'm very tired," the server generates a message such as "Thank you for your hard work. It might be a good idea to take a short break," and presents it to the user.

[0390] Through this series of processing steps, paper-based data can be efficiently digitized, facilitating subsequent search and analysis, and providing responses that reflect the user's emotions.

[0391] (Application example 2)

[0392] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0393] The purpose of this invention is to provide a system that facilitates information search and analysis by efficiently digitizing and centrally managing paper-based data. Another purpose is to improve the user experience by recognizing the user's emotions and providing feedback based on those emotions.

[0394] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0395] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data based on user input, means for analyzing the electronic data to extract specific patterns or trends, and means for recognizing user emotions and providing feedback based on the emotions, thereby enabling efficient information management and improving the user experience.

[0396] "Paper media" refers to information that is printed on physical paper.

[0397] "Image data" refers to digital image information obtained from paper media using a device such as a camera or scanner.

[0398] "Text data" refers to character information extracted from image data using OCR technology.

[0399] "Electronic data" refers to text data converted into a format that is easy to manage electronically.

[0400] "JSON format" refers to electronic data that has a data structure in JavaScript Object Notation format.

[0401] A "QR code" is a type of two-dimensional barcode that stores electronic data and is designed to be read by a machine.

[0402] "Means of storage" refers to methods and mechanisms for safely and efficiently storing QR codes and electronic data in JSON format.

[0403] "User input" refers to instructions or information provided by a user to a system in the form of text or voice.

[0404] "Search means" refers to a method or mechanism for locating electronic data based on specific conditions or keywords.

[0405] "Analytical means" refers to methods or mechanisms for examining electronic data in detail and identifying specific patterns or trends.

[0406] "Means for recognizing emotions" refers to a method or mechanism for determining a user's emotional state based on the user's input.

[0407] "Means for providing feedback" refers to a method or mechanism for returning appropriate messages or instructions to the user based on the results of emotion recognition.

[0408] System Configuration

[0409] The following is a detailed description of an embodiment of the present invention. The system efficiently digitizes paper-based data, centralizes management using QR codes, and recognizes the user's emotions and provides feedback based on those emotions.

[0410] Hardware and software used

[0411] 1. Smartphone - Use the camera function to capture image data of paper media. Specifically, iPhone (registered trademark) and Android (registered trademark) smartphones can be used.

[0412] 2. OCR technology library (pytesseract) - used to extract text data from captured image data.

[0413] 3. Image Processing Library (cv2) - Used to read and preprocess image data.

[0414] 4. Data Formatting Library (json) - Used to save extracted text data in JSON format.

[0415] 5. QR Code Generation Library (qrcode) - Used to generate QR codes based on electronic data in JSON format.

[0416] 6. Emotion Engine - Used to recognize emotions from user input and provide feedback based on the results.

[0417] Specific example explanation

[0418] 1. Acquiring image data and extracting text data

[0419] The user uses the smartphone camera to take an image of a paper document, such as a receipt, and saves it with a file name such as "receipt_20230920.jpg."

[0420] Image data acquired by the device is analyzed using pytesseract to extract text data. At this time, image preprocessing is performed using cv2 to improve OCR accuracy.

[0421] 2. Digitizing text data and saving it in JSON format

[0422] The device converts the extracted text data into electronic data and stores it in a structured format, making it easier to search and analyze later.

[0423] For example, this may include information such as: "date," "store name," "product," and "amount."

[0424] Finally, the data is stored in JSON format.

[0425] 3. Generate a QR code

[0426] The device generates a QR code based on the JSON formatted electronic data. For example, this JSON data is saved as "receipt_qr.png".

[0427] Users can easily share or reuse the data by displaying or printing this QR code.

[0428] 4. Recognizing emotions and providing feedback

[0429] The user inputs text to the system, such as "Today's shopping was great."

[0430] The emotion recognition engine (EmotionEngine) analyzes this text and recognizes the user's emotion as "happy."

[0431] Based on the results of emotion recognition, the device provides feedback to the user, such as "You made a good purchase!"

[0432] Prompt Sentence Examples

[0433] Below are some examples of specific prompt sentences.

[0434] Example input

[0435] Image file: "receipt_20230920.jpg"

[0436] Input text: "Today's shopping was amazing!"

[0437] Execution flow

[0438] The user takes a photo of the receipt using their smartphone and enters the image into the system. OCR technology extracts the text data and saves it in JSON format. A QR code is then generated and provided to the user. Furthermore, an emotion recognition engine analyzes the user's input text and provides emotion-based feedback, improving the user experience.

[0439] The above is an embodiment of the invention.

[0440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0441] Step 1:

[0442] The user captures image data of the paper medium using the smartphone camera and saves it as an image file. For example, the file name is "receipt_20230920.jpg." Based on this, image data is obtained.

[0443] Step 2:

[0444] The image data acquired by the device is read and preprocessed using the image processing library (cv2). This includes noise removal and grayscale conversion. This improves the quality of the image data and prepares it for efficient text extraction using OCR technology. The input is image data, and the output is preprocessed image data.

[0445] Step 3:

[0446] The terminal uses an OCR technology library (pytesseract) to extract text data from preprocessed image data. This text data includes information such as the date, store name, product name, and price. The input is the preprocessed image data, and the output is the extracted text data.

[0447] Step 4:

[0448] The terminal converts the extracted text data into electronic data and saves it in JSON format using the data format library (json). For example, the format is "{"Date": "2023-09-20", "Store Name": "XYZStore", "Amount": "10000"}". The input is the extracted text data, and the output is electronic data in JSON format.

[0449] Step 5:

[0450] The terminal generates a QR code using the QR code generation library (qrcode) based on the JSON format electronic data. For example, it is saved with a file name such as "receipt_qr.png." The input is JSON format electronic data, and the output is the generated QR code image.

[0451] Step 6:

[0452] The user provides text input to the system (e.g., "Shopping today was great"). The input is text data, and no actual emotion recognition processing is performed at this stage.

[0453] Step 7:

[0454] The device uses an emotion recognition engine (EmotionEngine) to recognize emotions from the user's text input. This engine analyzes the input text data and classifies emotions into categories such as "happy" and "sad." The input is text input, and the output is recognized emotion data.

[0455] Step 8:

[0456] The device provides feedback to the user based on the emotion recognition results. For example, if the emotion is "happy," a positive message such as "Good shopping!" is displayed. The input is the recognized emotion data, and the output is the feedback message.

[0457] In this way, users can easily digitize paper-based data using their smartphones and manage it with QR codes, as well as receive feedback based on emotion recognition.

[0458] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0459] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0460] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0461] [Second embodiment]

[0462] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0463] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0464] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0465] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0466] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0467] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0468] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0469] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0470] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0471] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0472] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0473] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0474] The embodiments of the present invention will be specifically described below.

[0475] System Configuration

[0476] The present invention is a system that efficiently digitizes paper-based data and centrally manages it using QR codes. This system mainly includes the following main processing steps.

[0477] 1. Data extraction from paper documents

[0478] 2. Conversion and structuring of electronic data

[0479] 3. Generate and save a QR code

[0480] 4. Data retrieval and analysis

[0481] Data extraction examples

[0482] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[0483] Data digitization and storage

[0484] The device converts the text data extracted from the image into electronic data and stores it in JSON format. This structured data makes it easier to manage, search, and analyze. For example, the following JSON format data is generated:

[0485] {

[0486] "Invoice Number": "001",

[0487] "Date": "2023-09-20",

[0488] "Amount": "10000"

[0489] }

[0490] The device stores this data in a storage directory and simultaneously generates a QR code.

[0491] QR code generation and output

[0492] The terminal generates a QR code based on the JSON-formatted digital data. This QR code is an encoded form of the digital data, and the user can print it or save it digitally. For example, it can be saved as "invoice_001_qr.png."

[0493] Searching for Data

[0494] When a user enters a search keyword into the system, the device searches the saved JSON data. For example, if you search for data for "May 2022," the device will scan all JSON files in the specified directory and extract the relevant entries. The search results are then provided to the user, allowing them to quickly access the desired information.

[0495] Analyzing the data

[0496] If a user requests data analysis, the server analyzes the stored data. This analysis may involve extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their operations.

[0497] As described above, the system of the present invention efficiently digitizes paper-based data and centrally manages it, making it easy to search and analyze information. Users can use the system with simple operations, which can significantly improve business efficiency in companies.

[0498] The processing flow will be explained below.

[0499] Step 1: Importing image data

[0500] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[0501] Step 2: Extract text using OCR

[0502] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[0503] Step 3: Structuring the electronic data

[0504] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[0505] Step 4: Generate a QR code

[0506] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[0507] Step 5: Save your data

[0508] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[0509] Step 6: Search for data

[0510] The user enters specific keywords or conditions into the system to perform a data search, and the device searches for JSON files in the storage directory and extracts data that matches the keywords.

[0511] Step 7: Viewing search results

[0512] The device displays the search results to the user, who can then access the information they need and use it in their work.

[0513] Step 8: Analyze the data

[0514] When a user requests that their data be analyzed, the server receives the stored data and performs the analysis, which includes extracting specific patterns or trends.

[0515] Step 9: Provide analysis results

[0516] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[0517] In this way, the processing steps of this system work in cooperation with each user, terminal, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis.

[0518] Example 1

[0519] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0520] Traditional systems that extract information from paper media, digitize it, and then manage and search it are inefficient because they require a lot of manual work and time. Furthermore, there are many issues, such as incorrect recognition of extracted data, low search accuracy, and difficulty in data analysis. This reduces the efficiency of information management and makes it difficult to respond quickly to business requests.

[0521] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0522] In this invention, the server includes means for acquiring image data from paper media, analyzing the image data, and extracting text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON-formatted electronic data, means for saving the QR code and the JSON-formatted electronic data, means for searching the JSON-formatted electronic data based on user input, means for analyzing the electronic data and extracting specific patterns or trends, means for extracting text data using OCR technology, means for providing the saved QR code to a user, means for saving the electronic data in a database and making it accessible, means for notifying the user of the generated data, and means for encoding the generated QR code and visually displaying it, thereby enabling efficient digitization of information from paper media, centralized management, and rapid search and analysis.

[0523] "Paper media" refers to physically printed documents and materials.

[0524] "Image data" refers to information captured from paper media and expressed visually, such as in bitmap format.

[0525] "Analysis" refers to the general process of extracting useful information from acquired image data.

[0526] "Text data" refers to character information extracted from analyzed image data.

[0527] "Electronic data" means information stored in digital form.

[0528] "JSON format" is an abbreviation for JavaScript Object Notation and is a lightweight data exchange format.

[0529] A "QR code" is a type of two-dimensional barcode that is used to read information quickly.

[0530] "Storage" means storing data in a certain location or storage device.

[0531] "User input" refers to instructions or commands from anyone using the system.

[0532] "Searching" is the act of finding specific information in a database or stored files.

[0533] An "analytical tool" is a method or device that reads data and finds specific patterns or trends within it.

[0534] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that reads character information from image data.

[0535] "Output means" refers to a mechanism for outputting processed data or generated information by displaying, printing, or the like.

[0536] A "database" is a system for systematically organizing data and efficiently storing and searching it.

[0537] "Notification" is the act of informing a user of certain information.

[0538] "Encoding" is the process of converting information into a particular format.

[0539] "Visual display" means graphically expressing the generated data and information and providing it in a form that is easy for the user to understand.

[0540] The following is a detailed description of an embodiment of the present invention. The present invention is a system that efficiently digitizes data on paper media and centrally manages it using QR codes. This system is operated mainly by three entities: a server, a terminal, and a user.

[0541] System Configuration

[0542] The system of the present invention comprises the following main processing steps:

[0543] 1. Data extraction from paper documents

[0544] 2. Conversion and structuring of electronic data

[0545] 3. Generate and save a QR code

[0546] 4. Data retrieval and analysis

[0547] Hardware and Software Use

[0548] The implementation of the present invention uses the following hardware and software:

[0549] Scanner or smartphone: Used to capture paper media as image data.

[0550] OCR technology: Used to extract text data from image data. An example is Tesseract OCR.

[0551] Database: Used to store electronic data. An example is MongoDB.

[0552] QR code generation library: Used to generate QR codes. A specific example is the Python qrcode library.

[0553] Data search engines: used to search stored electronic data. An example is Elasticsearch.

[0554] Data analysis libraries: used to analyze stored data. Examples include Python's pandas and numpy.

[0555] Specific processing explanation

[0556] Data Extraction

[0557] The user captures paper documents as images using a scanner or smartphone. For example, the user takes a photo of an invoice image file "invoice_001.jpg" with their smartphone and uploads it to the system. The device receives the uploaded image file and temporarily saves it in secure storage. The server validates the image data and checks whether it is in the correct format. If it is not correct, it sends a notification prompting the user to re-upload. The server uses OCR technology to analyze the image data and extract text data such as "invoice number, date, amount."

[0558] Electronic Data Storage

[0559] The device converts the extracted text data into JSON format, producing data like this:

[0560] json

[0561] {

[0562] "Invoice Number": "001",

[0563] "Date": "2023-09-20",

[0564] "Amount": "10000"

[0565] }

[0566] The terminal stores this data in a storage directory and saves it in a database.

[0567] QR code generation and notification

[0568] The device generates a QR code based on the saved JSON data. The Python qrcode library is used to generate the code. The generated QR code image is saved as "invoice_001_qr.png" and a download link is sent to the user.

[0569] Searching for Data

[0570] When a user enters a search keyword on the search screen, for example, "May 2022," the device scans the stored database for the relevant JSON file. The Elasticsearch engine is used for the search. The search results are provided to the user, allowing them to quickly view the relevant invoice information.

[0571] Analyzing the data

[0572] When a user wants to analyze data, they specify the specific analysis target and conditions and send a request to the server. The server analyzes the stored data and extracts specific patterns and trends. For example, it uses Python's pandas library to build a data frame and aggregate specific field information (such as "amount"). The analysis results are provided to the user and displayed as a visual report.

[0573] Specific examples

[0574] For example, a user uploads an invoice like this:

[0575] Invoice file name: invoice_001.jpg

[0576] Included information: Invoice number 001, date 2023-09-20, amount 10,000 yen

[0577] The device does the following:

[0578] 1. Text data extraction using OCR technology

[0579] 2. Convert to JSON format and save to storage

[0580] 3. Generate a QR code from the data

[0581] The generated QR code is saved as "invoice_001_qr.png", and by scanning this QR code, users can quickly access the relevant data.

[0582] Prompt Sentence Examples

[0583] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[0584] By following the above steps, users can efficiently digitize paper-based data and centralize information management through QR codes.

[0585] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0586] Step 1: Import and upload image data

[0587] The user takes a photo of a paper document (e.g., an invoice) with a scanner or smartphone and uploads it to the device as image data (e.g., "invoice_001.jpg"). The device receives this image data and temporarily stores it in secure storage.

[0588] Input: Image data of paper media (e.g. "invoice_001.jpg")

[0589] Output: Image data temporarily stored in secure storage

[0590] Step 2: Validate the image data

[0591] The server validates the image data to ensure it is in the correct format, resolution, etc. If it is in an inappropriate format or resolution, it sends a notification to the user urging them to re-upload.

[0592] Input: Temporarily saved image data

[0593] Output: Validated for proper format and resolution, and notifies user if necessary

[0594] Step 3: Extract text data using OCR analysis

[0595] The server uses Tesseract OCR technology to extract text information from image data, for example, extracting field information such as "invoice number, date, amount" from "invoice_001.jpg".

[0596] Input: Validated image data

[0597] Output: Extracted text data (e.g., "Invoice number: 001, Date: 2023-09-20, Amount: 10000")

[0598] Specific operation: Obtain text data using Tesseract OCR's image_to_string method

[0599] Step 4: Converting text data to JSON format

[0600] The device converts the extracted text data into JSON format, for example:

[0601] json

[0602] {

[0603] "Invoice Number": "001",

[0604] "Date": "2023-09-20",

[0605] "Amount": "10000"

[0606] }

[0607] Input: Extracted text data

[0608] Output: Data converted to JSON format

[0609] Step 5: Saving JSON Data

[0610] The device saves the converted JSON data in secure storage or a database (e.g., MongoDB), and notifies the user when the data has been saved.

[0611] Input: JSON format data

[0612] Output: JSON data saved in the database, save completion notification

[0613] Step 6: Generate a QR code

[0614] The device generates a QR code based on the stored JSON data. It uses the Python qrcode library to create an encoded QR code image.

[0615] Input: JSON format data

[0616] Output: Generated QR code image (e.g. "invoice_001_qr.png")

[0617] Step 7: Save and notify the QR code

[0618] Save the generated QR code image and send a notification to the user providing a download link.

[0619] Input: Generated QR code image

[0620] Output: QR code image saved in secure storage, notification of download link

[0621] Step 8: Search for data

[0622] The user enters a search keyword (e.g., "May 2022") into the system. The device uses the Elasticsearch engine to search for JSON data in the database.

[0623] Input: User-entered search keywords

[0624] Output: Search results for relevant JSON data

[0625] Step 9: Viewing search results

[0626] The search results are provided to the user by the terminal, allowing the user to quickly access the desired information.

[0627] Input: Searched JSON data

[0628] Output: Search results displayed to the user

[0629] Step 10: Analyze the data

[0630] A user submits a specific data analysis request to the system, and the server uses a data analysis library (e.g., pandas) to analyze the stored data and extract specific patterns or trends.

[0631] Input: User analysis request, data stored in the database

[0632] Output: Analysis results, visual reports

[0633] As a concrete example of operation, the following prompt sentence can be used:

[0634] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[0635] (Application example 1)

[0636] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0637] In logistics centers, manually managing paper-based inbound and outbound shipping slips and inspection reports causes many problems, including reduced work efficiency and the possibility of human error. This reduces overall business productivity and complicates information management. Furthermore, the task of searching and analyzing past data is cumbersome, making it difficult to quickly obtain information in real time. Therefore, there is a demand for a system that digitizes paper-based document management and provides efficient, centralized management.

[0638] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0639] In this invention, the server includes: means for acquiring image data from paper media and analyzing the image data to extract text data; means for converting the text data into electronic data and saving it in JSON format; means for generating a QR code based on the JSON-formatted electronic data; means for searching the JSON-formatted electronic data based on user input; means for analyzing the electronic data to extract specific patterns and trends; and means for photographing paper-based receipt / shipment slips and inspection reports at a logistics center using a smartphone or a camera-equipped robot, analyzing them using OCR technology to extract field information such as item name, quantity, and inspection results, saving the field information in JSON format, generating a QR code, and having an operator scan the QR code with a smartphone or robot to confirm the information. This digitizes paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis.

[0640] "Paper media" refers to media on which information is physically printed, such as documents and slips printed on paper.

[0641] "Image data" refers to image data acquired using a scanner or camera, and is information written on paper that is stored electronically.

[0642] "Text data" refers to character string information extracted from image data, and is character data recognized by OCR technology.

[0643] "Electronic data" refers to data in a digital format that is handled within a computer system and stored in JSON or other structured data formats.

[0644] "JSON format" stands for JavaScript Object Notation, a text-based data format that makes it easy to describe data structures.

[0645] A "QR code" is a square, two-dimensional barcode that digitally encodes information and can be scanned to quickly retrieve that information.

[0646] A "logistics center" is a facility where logistics operations are carried out, and where goods are received, shipped, stored, and managed.

[0647] A "shipping / receiving slip" is a document that records information about the receipt and dispatch of goods at a logistics center.

[0648] An "inspection report" is a document that records the results of a product's quality inspection at a logistics center.

[0649] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that automatically recognizes characters from image data and extracts them as text data.

[0650] "Mobile device" refers to a smartphone, tablet, or other portable electronic device, often equipped with a camera and communication capabilities.

[0651] A "camera-equipped robot" is a robot equipped with a camera that can move and take pictures automatically, and is used to improve work efficiency in logistics centers and other places.

[0652] The present invention provides a system for digitalizing and centrally managing paper-based documents in a logistics center.

[0653] System Configuration

[0654] The present invention uses the following main hardware and software:

[0655] Hardware: scanners, smartphones, robots with cameras.

[0656] Software: OCR technology (Tesseract OCR), Python library (qrcode), database (MySQL, PostgreSQL).

[0657] Hardware and Software Use

[0658] 1. Acquiring image data from paper media:

[0659] The server allows logistics center workers to acquire image data of paper-based shipping and receiving slips and inspection reports using smartphones or camera-equipped robots.

[0660] 2. Image data analysis and text data extraction:

[0661] The server analyzes the acquired image data using OCR technology and extracts field information such as product name, quantity, and inspection results as text data.

[0662] Specifically, Tesseract OCR is used to read text data from images.

[0663] 3. Conversion and storage of text data into electronic data:

[0664] The server converts the extracted text data into electronic data in JSON format and stores it in a database.

[0665] This makes the data structured and easier to search and analyze.

[0666] 4. Generate and save the QR code:

[0667] The server generates a QR code based on the electronic data in JSON format.

[0668] QR codes are used by workers to scan them with their smartphones or camera-equipped robots to check the information.

[0669] 5. Data retrieval and analysis:

[0670] The server searches for electronic data in JSON format based on user input and quickly provides the required information.

[0671] We also provide a data analysis function that extracts specific patterns and trends, and the analysis results can be used to improve business operations.

[0672] Example

[0673] Use within a distribution center:

[0674] A worker uses a smartphone to take a photo of the delivery slip for the incoming goods.

[0675] The server uses OCR technology to extract the product name, quantity, and inspection results from the image of the invoice and saves them in JSON format.

[0676] QR codes are generated from JSON format data, and workers can scan them with their smartphones to access the necessary information in real time.

[0677] Prompt Sentence Examples

[0678] We are considering digitizing inbound and outbound delivery slips at our logistics center. How can we take a photo of a paper-based slip, extract the data using OCR processing, save it in JSON format, and generate a QR code?

[0679] This system will streamline paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis. It is expected to improve the overall productivity of logistics operations, reduce human error, and improve operational efficiency.

[0680] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0681] Step 1:

[0682] A user takes a photo of a paper document (e.g., receipt / shipping slip, inspection report) using a smartphone or a camera-equipped robot. Image data (e.g., JPEG, PNG format) is generated as input. This image data is then uploaded to the system as output.

[0683] Step 2:

[0684] The server receives the uploaded image data and analyzes it using OCR technology (Tesseract OCR). Image data is given as input, and extracted text data is generated as output. Specifically, the character information in the image is converted into text data.

[0685] Step 3:

[0686] The server parses the extracted text data into field information. Text data is given as input, and structured electronic data (e.g., JSON format) is generated as output. Specifically, field information such as product name, quantity, and inspection results is parsed and structured.

[0687] Step 4:

[0688] The server stores structured electronic data in JSON format. JSON format data is given as input and saved in a database as output. Specifically, a storage directory is specified in the database (e.g., MySQL, PostgreSQL) and the data is stored.

[0689] Step 5:

[0690] The server generates a QR code based on the stored JSON format digital data. JSON data is given as input, and a QR code image is generated as output. Specifically, the QR code is generated using the Python qrcode library.

[0691] Step 6:

[0692] The server saves the generated QR code. The QR code image is given as input and stored in a directory as output. Specifically, the QR code image is saved in a specified directory and provided to the worker.

[0693] Step 7:

[0694] The user enters keywords to search for the information they need. The search keywords are given as input, and related JSON data is returned as output. Specifically, the JSON data in the database is searched and the relevant entries are extracted.

[0695] Step 8:

[0696] The server analyzes the relevant JSON data and extracts specific patterns and trends. The JSON data of the search results is given as input, and the analysis results are provided as output. Specifically, data analysis algorithms are used to visualize trends and help improve business operations.

[0697] The processing flow of this program digitizes paper document management at logistics centers, enabling efficient information search and analysis.

[0698] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0699] The embodiments of the present invention will be specifically described below.

[0700] System Configuration

[0701] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[0702] 1. Data extraction from paper documents

[0703] 2. Conversion and structuring of electronic data

[0704] 3. Generate and save a QR code

[0705] 4. Data retrieval and analysis

[0706] 5. User Emotion Recognition by Emotion Engine

[0707] Data extraction examples

[0708] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[0709] Data digitization and storage

[0710] The device converts the text data extracted from the image into electronic data and saves it in JSON format. This structured the data, making it easier to process and search later. For example, the following JSON format data is generated:

[0711] {

[0712] "Invoice Number": "001",

[0713] "Date": "2023-09-20",

[0714] "Amount": "10000"

[0715] }

[0716] The device stores this data in a storage directory and simultaneously generates a QR code.

[0717] QR code generation and output

[0718] The device generates a QR code based on the JSON data. This QR code is an encoded form of electronic data that the user can print or save digitally, for example, as "invoice_001_qr.png."

[0719] Searching for Data

[0720] The user enters specific keywords or conditions into the system to perform a data search. The device searches the JSON data in the storage directory and extracts entries that match the keywords. The search results are provided to the user, allowing them to quickly access the desired information.

[0721] Analyzing the data

[0722] If a user requests data analysis, the server analyzes the stored data. This analysis may include extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their business.

[0723] Recognizing user emotions with an emotion engine

[0724] An emotion engine is built into the system, which analyzes the user's voice and text inputs to recognize their emotions. This emotion data is used to adjust the system's response. For example, if the user is expressing dissatisfaction, the system will adjust to provide a more friendly response.

[0725] Examples of emotion engines

[0726] If a user types something into the system like "Work was tough today," the emotion engine will analyze this text and recognize that the user is tired. Based on this emotion data, the server will generate a response to the user such as "Thank you for your hard work. Maybe you should take a break."

[0727] This will improve the user experience and increase satisfaction when using the system. Emotion recognition technology can also be effectively used to improve user interfaces and customer support.

[0728] As described above, this system works in cooperation with each user, device, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis. Furthermore, it has an emotion engine that recognizes user emotions and adjusts the system's response.

[0729] The processing flow will be explained below.

[0730] Step 1: Importing image data

[0731] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[0732] Step 2: Extract text using OCR

[0733] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[0734] Step 3: Structuring the electronic data

[0735] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[0736] Step 4: Generate a QR code

[0737] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[0738] Step 5: Save your data

[0739] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[0740] Step 6: Emotion Recognition with the Emotion Engine

[0741] The user inputs text into the system. The device receives this input and uses the emotion engine to analyze the user's emotions. For example, if the user inputs "I'm tired today," the emotion engine analyzes this text and recognizes that the user is tired.

[0742] Step 7: Generate a response based on emotion

[0743] The server receives the analysis results from the emotion engine and adjusts the system's response accordingly. For example, if it determines that the user is tired, it will generate a friendly message such as, "Thank you for your hard work. We recommend that you take a break."

[0744] Step 8: Search for data

[0745] The user enters specific keywords or conditions into the system to perform a data search, and the device searches the JSON files in the storage directory and extracts entries that match the keywords.

[0746] Step 9: Viewing search results

[0747] The device displays the search results to the user, who can then access the information they need and use it in their work.

[0748] Step 10: Analyze the data

[0749] If the user requests that the data be analyzed, the server will analyze the stored data, which may involve extracting specific patterns or trends.

[0750] Step 11: Provide analysis results

[0751] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[0752] Through the above processing steps, users, terminals, and servers work together to operate the system efficiently, and business efficiency and user satisfaction can be improved through the digitization of paper-based data and emotion recognition functions.

[0753] Example 2

[0754] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0755] Conventional systems have had the problem that the process of digitizing and managing paper-based data is complicated, and data search and analysis take a long time. Furthermore, there is a lack of technology to recognize user emotions and reflect them in the system's responses, which has resulted in a lack of improvement in the user experience. It is necessary to solve these problems and provide an efficient and user-friendly data management system.

[0756] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0757] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the extracted text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data, means for analyzing the electronic data to extract specific patterns or trends, means for analyzing a user's voice input or text input to recognize emotions, and means for adjusting the system response based on the recognized emotion data. This allows for efficient electronic conversion of paper medium data, facilitating search and analysis, and enabling responses according to the user's emotions.

[0758] "Image data" is data that expresses information acquired from paper media in an image format.

[0759] "Text data" is data that includes character information extracted from image data.

[0760] "Electronic data" refers to text data that has been converted into an electronic format and stored.

[0761] The "JSON format" is a lightweight data interchange format used to store electronic data.

[0762] A "QR code" is a square-shaped two-dimensional code that encodes and visually represents information.

[0763] "User voice input" is voice data provided by a user to the system through a microphone or other voice capturing device.

[0764] "Text input" is string information that a user provides to a system using a keyboard or other input device.

[0765] "Emotion recognition" is the process of analyzing a user's voice or text input to identify the user's emotional state.

[0766] "Search method" is a function that searches stored electronic data in JSON format based on specific conditions.

[0767] "Extracting specific patterns and trends" is the process of analyzing electronic data to find significant patterns and trends.

[0768] The "means for adjusting response" is a function for changing the way the system responds based on the recognized user emotion.

[0769] System Configuration

[0770] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[0771] Hardware and Software Used

[0772] Scanner or smartphone: Used to capture paper data as an image.

[0773] OCR engine (e.g. Tesseract OCR): Extracts text data from image data.

[0774] Terminal: A device that accepts user operations and processes data.

[0775] Server: A device used to store, retrieve, and analyze data.

[0776] QR code generation software (e.g., Python's qrcode library): Generates QR codes from JSON-formatted data.

[0777] Emotion recognition engines (e.g., Python's TextBlob library): Analyze emotions from user voice or text input.

[0778] Data processing and calculation flow

[0779] The user captures paper documents as images using a scanner or smartphone. Specifically, they upload the invoice image file "invoice_001.jpg" to the system. The device then analyzes this image data using OCR technology and extracts text data. The extracted text data contains field information such as "invoice number, date, amount." At this stage, JSON-formatted data like the one below is generated.

[0780] json

[0781] {

[0782] "Invoice Number": "001",

[0783] "Date": "2023-09-20",

[0784] "Amount": "10000"

[0785] }

[0786] The device converts this JSON data into a QR code using QR code generation software. The generated QR code is saved as "invoice_001_qr.png" and the user can print it or save it digitally.

[0787] Examples of concrete examples and prompt sentence usage

[0788] For example, if a user takes a picture of an invoice with their smartphone and uploads it to the system as "invoice_001.jpg," the image data will be analyzed using an OCR engine, and the following text data will be extracted:

[0789] Invoice number: 001

[0790] Date: 2023-09-20

[0791] Amount: 10,000

[0792] This text data is converted to JSON format,

[0793] {

[0794] "Invoice Number": "001",

[0795] "Date": "2023-09-20",

[0796] "Amount": "10000"

[0797] }

[0798] The device generates a QR code from this JSON data and saves it as "invoice_001_qr.png".

[0799] Furthermore, if a user inputs text such as "Work was tough today," the emotion recognition engine analyzes the text and recognizes that the user is tired. Based on this recognition result, the server generates a response message such as "Thank you for your hard work. Maybe it would be good to take a short break."

[0800] As a result, this system not only efficiently digitizes paper data and facilitates subsequent search and analysis, but also recognizes the user's emotions and provides appropriate feedback.

[0801] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0802] Explain the program's processing flow in detail

[0803] Step 1:

[0804] The user captures paper documents as images using a scanner or smartphone. Specifically, the user uploads the invoice image file "invoice_001.jpg" to the system. The input is the image data "invoice_001.jpg," and the output is that this image data is imported into the system. At this stage, the terminal receives the image data and prepares it for subsequent processing.

[0805] Step 2:

[0806] The terminal uses OCR technology (e.g., Tesseract OCR) to analyze the input image data and extract text data. The input is the image data "invoice_001.jpg" captured in step 1, and the output is the extracted text data. This text data includes field information such as "invoice number, date, and amount." Specifically, the OCR engine is called to perform image analysis and obtain text information.

[0807] Step 3:

[0808] The terminal converts the extracted text data into electronic data and saves it in JSON format. The input is the text data extracted in step 2, and the output is JSON format data. Specifically, the following JSON data is generated:

[0809] json

[0810] {

[0811] "Invoice Number": "001",

[0812] "Date": "2023-09-20",

[0813] "Amount": "10000"

[0814] }

[0815] The device stores this JSON data in the specified save directory.

[0816] Step 4:

[0817] The device generates a QR code based on the saved JSON data. The input is the JSON data generated in step 3, and the output is an image file of the QR code. Specifically, the QR code is generated using the Python qrcode library and saved as "invoice_001_qr.png." The device provides this file to the user.

[0818] Step 5:

[0819] The user enters specific keywords or conditions into the system, and the device searches for JSON data in the storage directory. The input is the search conditions entered by the user (e.g., "Invoice number is 001"), and the output is the search results. The device searches the stored JSON files and extracts the corresponding entries. Specifically, it reads the matching files from the file system and displays their contents to the user.

[0820] Step 6:

[0821] When a user requests data analysis, the server analyzes the stored data. The input is the user's analysis request (e.g., "analyze trends in billing data for the past year"), and the output is the analysis results. The server uses Python's pandas library to read the data and extract patterns and trends. For example, it can graph fluctuations in the number and amount of bills by month and provide this to the user.

[0822] Step 7:

[0823] An emotion engine is used to analyze a user's voice or text input and recognize the user's emotion. The input is the user's voice or text input (e.g., "Work was tough today") and the output is the recognized emotion data. An emotion engine (e.g., TextBlob) is used to parse the input data and identify the user's emotion.

[0824] Step 8:

[0825] The server adjusts the system's response based on the recognized emotion data. The input is the emotion data recognized in step 7, and the output is the adjusted response message. For example, if the user expresses the emotion "I'm very tired," the server generates a message such as "Thank you for your hard work. It might be a good idea to take a short break," and presents it to the user.

[0826] Through this series of processing steps, paper-based data can be efficiently digitized, facilitating subsequent search and analysis, and providing responses that reflect the user's emotions.

[0827] (Application example 2)

[0828] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0829] The purpose of this invention is to provide a system that facilitates information search and analysis by efficiently digitizing and centrally managing paper-based data. Another purpose is to improve the user experience by recognizing the user's emotions and providing feedback based on those emotions.

[0830] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0831] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data based on user input, means for analyzing the electronic data to extract specific patterns or trends, and means for recognizing user emotions and providing feedback based on the emotions, thereby enabling efficient information management and improving the user experience.

[0832] "Paper media" refers to information that is printed on physical paper.

[0833] "Image data" refers to digital image information obtained from paper media using a device such as a camera or scanner.

[0834] "Text data" refers to character information extracted from image data using OCR technology.

[0835] "Electronic data" refers to text data converted into a format that is easy to manage electronically.

[0836] "JSON format" refers to electronic data that has a data structure in JavaScript Object Notation format.

[0837] A "QR code" is a type of two-dimensional barcode that stores electronic data and is designed to be read by a machine.

[0838] "Means of storage" refers to methods and mechanisms for safely and efficiently storing QR codes and electronic data in JSON format.

[0839] "User input" refers to instructions or information provided by a user to a system in the form of text or voice.

[0840] "Search means" refers to a method or mechanism for locating electronic data based on specific conditions or keywords.

[0841] "Analytical means" refers to methods or mechanisms for examining electronic data in detail and identifying specific patterns or trends.

[0842] "Means for recognizing emotions" refers to a method or mechanism for determining a user's emotional state based on the user's input.

[0843] "Means for providing feedback" refers to a method or mechanism for returning appropriate messages or instructions to the user based on the results of emotion recognition.

[0844] System Configuration

[0845] The following is a detailed description of an embodiment of the present invention. The system efficiently digitizes paper-based data, centralizes management using QR codes, and recognizes the user's emotions and provides feedback based on those emotions.

[0846] Hardware and software used

[0847] 1. Smartphone - Use the camera function to capture image data of paper media. Specifically, iPhones and Android smartphones can be used.

[0848] 2. OCR technology library (pytesseract) - used to extract text data from captured image data.

[0849] 3. Image Processing Library (cv2) - Used to read and preprocess image data.

[0850] 4. Data Formatting Library (json) - Used to save extracted text data in JSON format.

[0851] 5. QR Code Generation Library (qrcode) - Used to generate QR codes based on electronic data in JSON format.

[0852] 6. Emotion Engine - Used to recognize emotions from user input and provide feedback based on the results.

[0853] Specific example explanation

[0854] 1. Acquiring image data and extracting text data

[0855] The user uses the smartphone camera to take an image of a paper document, such as a receipt, and saves it with a file name such as "receipt_20230920.jpg."

[0856] Image data acquired by the device is analyzed using pytesseract to extract text data. At this time, image preprocessing is performed using cv2 to improve OCR accuracy.

[0857] 2. Digitizing text data and saving it in JSON format

[0858] The device converts the extracted text data into electronic data and stores it in a structured format, making it easier to search and analyze later.

[0859] For example, this may include information such as: "date," "store name," "product," and "amount."

[0860] Finally, the data is stored in JSON format.

[0861] 3. Generate a QR code

[0862] The device generates a QR code based on the JSON formatted electronic data. For example, this JSON data is saved as "receipt_qr.png".

[0863] Users can easily share or reuse the data by displaying or printing this QR code.

[0864] 4. Recognizing emotions and providing feedback

[0865] The user inputs text to the system, such as "Today's shopping was great."

[0866] The emotion recognition engine (EmotionEngine) analyzes this text and recognizes the user's emotion as "happy."

[0867] Based on the results of emotion recognition, the device provides feedback to the user, such as "You made a good purchase!"

[0868] Prompt Sentence Examples

[0869] Below are some examples of specific prompt sentences.

[0870] Example input

[0871] Image file: "receipt_20230920.jpg"

[0872] Input text: "Today's shopping was amazing!"

[0873] Execution flow

[0874] The user takes a photo of the receipt using their smartphone and enters the image into the system. OCR technology extracts the text data and saves it in JSON format. A QR code is then generated and provided to the user. Furthermore, an emotion recognition engine analyzes the user's input text and provides emotion-based feedback, improving the user experience.

[0875] The above is an embodiment of the invention.

[0876] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0877] Step 1:

[0878] The user captures image data of the paper medium using the smartphone camera and saves it as an image file. For example, the file name is "receipt_20230920.jpg." Based on this, image data is obtained.

[0879] Step 2:

[0880] The image data acquired by the device is read and preprocessed using the image processing library (cv2). This includes noise removal and grayscale conversion. This improves the quality of the image data and prepares it for efficient text extraction using OCR technology. The input is image data, and the output is preprocessed image data.

[0881] Step 3:

[0882] The terminal uses an OCR technology library (pytesseract) to extract text data from preprocessed image data. This text data includes information such as the date, store name, product name, and price. The input is the preprocessed image data, and the output is the extracted text data.

[0883] Step 4:

[0884] The terminal converts the extracted text data into electronic data and saves it in JSON format using the data format library (json). For example, the format is "{"Date": "2023-09-20", "Store Name": "XYZStore", "Amount": "10000"}". The input is the extracted text data, and the output is electronic data in JSON format.

[0885] Step 5:

[0886] The terminal generates a QR code using the QR code generation library (qrcode) based on the JSON format electronic data. For example, it is saved with a file name such as "receipt_qr.png." The input is JSON format electronic data, and the output is the generated QR code image.

[0887] Step 6:

[0888] The user provides text input to the system (e.g., "Shopping today was great"). The input is text data, and no actual emotion recognition processing is performed at this stage.

[0889] Step 7:

[0890] The device uses an emotion recognition engine (EmotionEngine) to recognize emotions from the user's text input. This engine analyzes the input text data and classifies emotions into categories such as "happy" and "sad." The input is text input, and the output is recognized emotion data.

[0891] Step 8:

[0892] The device provides feedback to the user based on the emotion recognition results. For example, if the emotion is "happy," a positive message such as "Good shopping!" is displayed. The input is the recognized emotion data, and the output is the feedback message.

[0893] In this way, users can easily digitize paper-based data using their smartphones and manage it with QR codes, as well as receive feedback based on emotion recognition.

[0894] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0895] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0896] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0897] [Third embodiment]

[0898] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0899] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0900] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0901] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0902] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0903] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0904] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0905] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0906] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0907] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0908] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0909] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0910] The embodiments of the present invention will be specifically described below.

[0911] System Configuration

[0912] The present invention is a system that efficiently digitizes paper-based data and centrally manages it using QR codes. This system mainly includes the following main processing steps.

[0913] 1. Data extraction from paper documents

[0914] 2. Conversion and structuring of electronic data

[0915] 3. Generate and save a QR code

[0916] 4. Data retrieval and analysis

[0917] Data extraction examples

[0918] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[0919] Data digitization and storage

[0920] The device converts the text data extracted from the image into electronic data and stores it in JSON format. This structured data makes it easier to manage, search, and analyze. For example, the following JSON format data is generated:

[0921] {

[0922] "Invoice Number": "001",

[0923] "Date": "2023-09-20",

[0924] "Amount": "10000"

[0925] }

[0926] The device stores this data in a storage directory and simultaneously generates a QR code.

[0927] QR code generation and output

[0928] The terminal generates a QR code based on the JSON-formatted digital data. This QR code is an encoded form of the digital data, and the user can print it or save it digitally. For example, it can be saved as "invoice_001_qr.png."

[0929] Searching for Data

[0930] When a user enters a search keyword into the system, the device searches the saved JSON data. For example, if you search for data for "May 2022," the device will scan all JSON files in the specified directory and extract the relevant entries. The search results are then provided to the user, allowing them to quickly access the desired information.

[0931] Analyzing the data

[0932] If a user requests data analysis, the server analyzes the stored data. This analysis may involve extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their operations.

[0933] As described above, the system of the present invention efficiently digitizes paper-based data and centrally manages it, making it easy to search and analyze information. Users can use the system with simple operations, which can significantly improve business efficiency in companies.

[0934] The processing flow will be explained below.

[0935] Step 1: Importing image data

[0936] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[0937] Step 2: Extract text using OCR

[0938] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[0939] Step 3: Structuring the electronic data

[0940] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[0941] Step 4: Generate a QR code

[0942] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[0943] Step 5: Save your data

[0944] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[0945] Step 6: Search for data

[0946] The user enters specific keywords or conditions into the system to perform a data search, and the device searches for JSON files in the storage directory and extracts data that matches the keywords.

[0947] Step 7: Viewing search results

[0948] The device displays the search results to the user, who can then access the information they need and use it in their work.

[0949] Step 8: Analyze the data

[0950] When a user requests that their data be analyzed, the server receives the stored data and performs the analysis, which includes extracting specific patterns or trends.

[0951] Step 9: Provide analysis results

[0952] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[0953] In this way, the processing steps of this system work in cooperation with each user, terminal, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis.

[0954] Example 1

[0955] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0956] Traditional systems that extract information from paper media, digitize it, and then manage and search it are inefficient because they require a lot of manual work and time. Furthermore, there are many issues, such as incorrect recognition of extracted data, low search accuracy, and difficulty in data analysis. This reduces the efficiency of information management and makes it difficult to respond quickly to business requests.

[0957] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0958] In this invention, the server includes means for acquiring image data from paper media, analyzing the image data, and extracting text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON-formatted electronic data, means for saving the QR code and the JSON-formatted electronic data, means for searching the JSON-formatted electronic data based on user input, means for analyzing the electronic data and extracting specific patterns or trends, means for extracting text data using OCR technology, means for providing the saved QR code to a user, means for saving the electronic data in a database and making it accessible, means for notifying the user of the generated data, and means for encoding the generated QR code and visually displaying it, thereby enabling efficient digitization of information from paper media, centralized management, and rapid search and analysis.

[0959] "Paper media" refers to physically printed documents and materials.

[0960] "Image data" refers to information captured from paper media and expressed visually, such as in bitmap format.

[0961] "Analysis" refers to the general process of extracting useful information from acquired image data.

[0962] "Text data" refers to character information extracted from analyzed image data.

[0963] "Electronic data" means information stored in digital form.

[0964] "JSON format" is an abbreviation for JavaScript Object Notation and is a lightweight data exchange format.

[0965] A "QR code" is a type of two-dimensional barcode that is used to read information quickly.

[0966] "Storage" means storing data in a certain location or storage device.

[0967] "User input" refers to instructions or commands from anyone using the system.

[0968] "Searching" is the act of finding specific information in a database or stored files.

[0969] An "analytical tool" is a method or device that reads data and finds specific patterns or trends within it.

[0970] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that reads character information from image data.

[0971] "Output means" refers to a mechanism for outputting processed data or generated information by displaying, printing, or the like.

[0972] A "database" is a system for systematically organizing data and efficiently storing and searching it.

[0973] "Notification" is the act of informing a user of certain information.

[0974] "Encoding" is the process of converting information into a particular format.

[0975] "Visual display" means graphically expressing the generated data and information and providing it in a form that is easy for the user to understand.

[0976] The following is a detailed description of an embodiment of the present invention. The present invention is a system that efficiently digitizes data on paper media and centrally manages it using QR codes. This system is operated mainly by three entities: a server, a terminal, and a user.

[0977] System Configuration

[0978] The system of the present invention comprises the following main processing steps:

[0979] 1. Data extraction from paper documents

[0980] 2. Conversion and structuring of electronic data

[0981] 3. Generate and save a QR code

[0982] 4. Data retrieval and analysis

[0983] Hardware and Software Use

[0984] The implementation of the present invention uses the following hardware and software:

[0985] Scanner or smartphone: Used to capture paper media as image data.

[0986] OCR technology: Used to extract text data from image data. An example is Tesseract OCR.

[0987] Database: Used to store electronic data. An example is MongoDB.

[0988] QR code generation library: Used to generate QR codes. A specific example is the Python qrcode library.

[0989] Data search engines: used to search stored electronic data. An example is Elasticsearch.

[0990] Data analysis libraries: used to analyze stored data. Examples include Python's pandas and numpy.

[0991] Specific processing explanation

[0992] Data Extraction

[0993] The user captures paper documents as images using a scanner or smartphone. For example, the user takes a photo of an invoice image file "invoice_001.jpg" with their smartphone and uploads it to the system. The device receives the uploaded image file and temporarily saves it in secure storage. The server validates the image data and checks whether it is in the correct format. If it is not correct, it sends a notification prompting the user to re-upload. The server uses OCR technology to analyze the image data and extract text data such as "invoice number, date, amount."

[0994] Electronic Data Storage

[0995] The device converts the extracted text data into JSON format, producing data like this:

[0996] json

[0997] {

[0998] "Invoice Number": "001",

[0999] "Date": "2023-09-20",

[1000] "Amount": "10000"

[1001] }

[1002] The terminal stores this data in a storage directory and saves it in a database.

[1003] QR code generation and notification

[1004] The device generates a QR code based on the saved JSON data. The Python qrcode library is used to generate the code. The generated QR code image is saved as "invoice_001_qr.png" and a download link is sent to the user.

[1005] Searching for Data

[1006] When a user enters a search keyword on the search screen, for example, "May 2022," the device scans the stored database for the relevant JSON file. The Elasticsearch engine is used for the search. The search results are provided to the user, allowing them to quickly view the relevant invoice information.

[1007] Analyzing the data

[1008] When a user wants to analyze data, they specify the specific analysis target and conditions and send a request to the server. The server analyzes the stored data and extracts specific patterns and trends. For example, it uses Python's pandas library to build a data frame and aggregate specific field information (such as "amount"). The analysis results are provided to the user and displayed as a visual report.

[1009] Specific examples

[1010] For example, a user uploads an invoice like this:

[1011] Invoice file name: invoice_001.jpg

[1012] Included information: Invoice number 001, date 2023-09-20, amount 10,000 yen

[1013] The device does the following:

[1014] 1. Text data extraction using OCR technology

[1015] 2. Convert to JSON format and save to storage

[1016] 3. Generate a QR code from the data

[1017] The generated QR code is saved as "invoice_001_qr.png", and by scanning this QR code, users can quickly access the relevant data.

[1018] Prompt Sentence Examples

[1019] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[1020] By following the above steps, users can efficiently digitize paper-based data and centralize information management through QR codes.

[1021] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1022] Step 1: Import and upload image data

[1023] The user takes a photo of a paper document (e.g., an invoice) with a scanner or smartphone and uploads it to the device as image data (e.g., "invoice_001.jpg"). The device receives this image data and temporarily stores it in secure storage.

[1024] Input: Image data of paper media (e.g. "invoice_001.jpg")

[1025] Output: Image data temporarily stored in secure storage

[1026] Step 2: Validate the image data

[1027] The server validates the image data to ensure it is in the correct format, resolution, etc. If it is in an inappropriate format or resolution, it sends a notification to the user urging them to re-upload.

[1028] Input: Temporarily saved image data

[1029] Output: Validated for proper format and resolution, and notifies user if necessary

[1030] Step 3: Extract text data using OCR analysis

[1031] The server uses Tesseract OCR technology to extract text information from image data, for example, extracting field information such as "invoice number, date, amount" from "invoice_001.jpg".

[1032] Input: Validated image data

[1033] Output: Extracted text data (e.g., "Invoice number: 001, Date: 2023-09-20, Amount: 10000")

[1034] Specific operation: Obtain text data using Tesseract OCR's image_to_string method

[1035] Step 4: Converting text data to JSON format

[1036] The device converts the extracted text data into JSON format, for example:

[1037] json

[1038] {

[1039] "Invoice Number": "001",

[1040] "Date": "2023-09-20",

[1041] "Amount": "10000"

[1042] }

[1043] Input: Extracted text data

[1044] Output: Data converted to JSON format

[1045] Step 5: Saving JSON Data

[1046] The device saves the converted JSON data in secure storage or a database (e.g., MongoDB), and notifies the user when the data has been saved.

[1047] Input: JSON format data

[1048] Output: JSON data saved in the database, save completion notification

[1049] Step 6: Generate a QR code

[1050] The device generates a QR code based on the stored JSON data. It uses the Python qrcode library to create an encoded QR code image.

[1051] Input: JSON format data

[1052] Output: Generated QR code image (e.g. "invoice_001_qr.png")

[1053] Step 7: Save and notify the QR code

[1054] Save the generated QR code image and send a notification to the user providing a download link.

[1055] Input: Generated QR code image

[1056] Output: QR code image saved in secure storage, notification of download link

[1057] Step 8: Search for data

[1058] The user enters a search keyword (e.g., "May 2022") into the system. The device uses the Elasticsearch engine to search for JSON data in the database.

[1059] Input: User-entered search keywords

[1060] Output: Search results for relevant JSON data

[1061] Step 9: Viewing search results

[1062] The search results are provided to the user by the terminal, allowing the user to quickly access the desired information.

[1063] Input: Searched JSON data

[1064] Output: Search results displayed to the user

[1065] Step 10: Analyze the data

[1066] A user submits a specific data analysis request to the system, and the server uses a data analysis library (e.g., pandas) to analyze the stored data and extract specific patterns or trends.

[1067] Input: User analysis request, data stored in the database

[1068] Output: Analysis results, visual reports

[1069] As a concrete example of operation, the following prompt sentence can be used:

[1070] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[1071] (Application example 1)

[1072] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1073] In logistics centers, manually managing paper-based inbound and outbound shipping slips and inspection reports causes many problems, including reduced work efficiency and the possibility of human error. This reduces overall business productivity and complicates information management. Furthermore, the task of searching and analyzing past data is cumbersome, making it difficult to quickly obtain information in real time. Therefore, there is a demand for a system that digitizes paper-based document management and provides efficient, centralized management.

[1074] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1075] In this invention, the server includes: means for acquiring image data from paper media and analyzing the image data to extract text data; means for converting the text data into electronic data and saving it in JSON format; means for generating a QR code based on the JSON-formatted electronic data; means for searching the JSON-formatted electronic data based on user input; means for analyzing the electronic data to extract specific patterns and trends; and means for photographing paper-based receipt / shipment slips and inspection reports at a logistics center using a smartphone or a camera-equipped robot, analyzing them using OCR technology to extract field information such as item name, quantity, and inspection results, saving the field information in JSON format, generating a QR code, and having an operator scan the QR code with a smartphone or robot to confirm the information. This digitizes paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis.

[1076] "Paper media" refers to media on which information is physically printed, such as documents and slips printed on paper.

[1077] "Image data" refers to image data acquired using a scanner or camera, and is information written on paper that is stored electronically.

[1078] "Text data" refers to character string information extracted from image data, and is character data recognized by OCR technology.

[1079] "Electronic data" refers to data in a digital format that is handled within a computer system and stored in JSON or other structured data formats.

[1080] "JSON format" stands for JavaScript Object Notation, a text-based data format that makes it easy to describe data structures.

[1081] A "QR code" is a square, two-dimensional barcode that digitally encodes information and can be scanned to quickly retrieve that information.

[1082] A "logistics center" is a facility where logistics operations are carried out, and where goods are received, shipped, stored, and managed.

[1083] A "shipping / receiving slip" is a document that records information about the receipt and dispatch of goods at a logistics center.

[1084] An "inspection report" is a document that records the results of a product's quality inspection at a logistics center.

[1085] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that automatically recognizes characters from image data and extracts them as text data.

[1086] "Mobile device" refers to a smartphone, tablet, or other portable electronic device, often equipped with a camera and communication capabilities.

[1087] A "camera-equipped robot" is a robot equipped with a camera that can move and take pictures automatically, and is used to improve work efficiency in logistics centers and other places.

[1088] The present invention provides a system for digitalizing and centrally managing paper-based documents in a logistics center.

[1089] System Configuration

[1090] The present invention uses the following main hardware and software:

[1091] Hardware: scanners, smartphones, robots with cameras.

[1092] Software: OCR technology (Tesseract OCR), Python library (qrcode), database (MySQL, PostgreSQL).

[1093] Hardware and Software Use

[1094] 1. Acquiring image data from paper media:

[1095] The server allows logistics center workers to acquire image data of paper-based shipping and receiving slips and inspection reports using smartphones or camera-equipped robots.

[1096] 2. Image data analysis and text data extraction:

[1097] The server analyzes the acquired image data using OCR technology and extracts field information such as product name, quantity, and inspection results as text data.

[1098] Specifically, Tesseract OCR is used to read text data from images.

[1099] 3. Conversion and storage of text data into electronic data:

[1100] The server converts the extracted text data into electronic data in JSON format and stores it in a database.

[1101] This makes the data structured and easier to search and analyze.

[1102] 4. Generate and save the QR code:

[1103] The server generates a QR code based on the electronic data in JSON format.

[1104] QR codes are used by workers to scan them with their smartphones or camera-equipped robots to check the information.

[1105] 5. Data retrieval and analysis:

[1106] The server searches for electronic data in JSON format based on user input and quickly provides the required information.

[1107] We also provide a data analysis function that extracts specific patterns and trends, and the analysis results can be used to improve business operations.

[1108] Example

[1109] Use within a distribution center:

[1110] A worker uses a smartphone to take a photo of the delivery slip for the incoming goods.

[1111] The server uses OCR technology to extract the product name, quantity, and inspection results from the image of the invoice and saves them in JSON format.

[1112] QR codes are generated from JSON format data, and workers can scan them with their smartphones to access the necessary information in real time.

[1113] Prompt Sentence Examples

[1114] We are considering digitizing inbound and outbound delivery slips at our logistics center. How can we take a photo of a paper-based slip, extract the data using OCR processing, save it in JSON format, and generate a QR code?

[1115] This system will streamline paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis. It is expected to improve the overall productivity of logistics operations, reduce human error, and improve operational efficiency.

[1116] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1117] Step 1:

[1118] A user takes a photo of a paper document (e.g., receipt / shipping slip, inspection report) using a smartphone or a camera-equipped robot. Image data (e.g., JPEG, PNG format) is generated as input. This image data is then uploaded to the system as output.

[1119] Step 2:

[1120] The server receives the uploaded image data and analyzes it using OCR technology (Tesseract OCR). Image data is given as input, and extracted text data is generated as output. Specifically, the character information in the image is converted into text data.

[1121] Step 3:

[1122] The server parses the extracted text data into field information. Text data is given as input, and structured electronic data (e.g., JSON format) is generated as output. Specifically, field information such as product name, quantity, and inspection results is parsed and structured.

[1123] Step 4:

[1124] The server stores structured electronic data in JSON format. JSON format data is given as input and saved in a database as output. Specifically, a storage directory is specified in the database (e.g., MySQL, PostgreSQL) and the data is stored.

[1125] Step 5:

[1126] The server generates a QR code based on the stored JSON format digital data. JSON data is given as input, and a QR code image is generated as output. Specifically, the QR code is generated using the Python qrcode library.

[1127] Step 6:

[1128] The server saves the generated QR code. The QR code image is given as input and stored in a directory as output. Specifically, the QR code image is saved in a specified directory and provided to the worker.

[1129] Step 7:

[1130] The user enters keywords to search for the information they need. The search keywords are given as input, and related JSON data is returned as output. Specifically, the JSON data in the database is searched and the relevant entries are extracted.

[1131] Step 8:

[1132] The server analyzes the relevant JSON data and extracts specific patterns and trends. The JSON data of the search results is given as input, and the analysis results are provided as output. Specifically, data analysis algorithms are used to visualize trends and help improve business operations.

[1133] The processing flow of this program digitizes paper document management at logistics centers, enabling efficient information search and analysis.

[1134] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1135] The embodiments of the present invention will be specifically described below.

[1136] System Configuration

[1137] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[1138] 1. Data extraction from paper documents

[1139] 2. Conversion and structuring of electronic data

[1140] 3. Generate and save a QR code

[1141] 4. Data retrieval and analysis

[1142] 5. User Emotion Recognition by Emotion Engine

[1143] Data extraction examples

[1144] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[1145] Data digitization and storage

[1146] The device converts the text data extracted from the image into electronic data and saves it in JSON format. This structured the data, making it easier to process and search later. For example, the following JSON format data is generated:

[1147] {

[1148] "Invoice Number": "001",

[1149] "Date": "2023-09-20",

[1150] "Amount": "10000"

[1151] }

[1152] The device stores this data in a storage directory and simultaneously generates a QR code.

[1153] QR code generation and output

[1154] The device generates a QR code based on the JSON data. This QR code is an encoded form of electronic data that the user can print or save digitally, for example, as "invoice_001_qr.png."

[1155] Searching for Data

[1156] The user enters specific keywords or conditions into the system to perform a data search. The device searches the JSON data in the storage directory and extracts entries that match the keywords. The search results are provided to the user, allowing them to quickly access the desired information.

[1157] Analyzing the data

[1158] If a user requests data analysis, the server analyzes the stored data. This analysis may include extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their business.

[1159] Recognizing user emotions with an emotion engine

[1160] An emotion engine is built into the system, which analyzes the user's voice and text inputs to recognize their emotions. This emotion data is used to adjust the system's response. For example, if the user is expressing dissatisfaction, the system will adjust to provide a more friendly response.

[1161] Examples of emotion engines

[1162] If a user types something into the system like "Work was tough today," the emotion engine will analyze this text and recognize that the user is tired. Based on this emotion data, the server will generate a response to the user such as "Thank you for your hard work. Maybe you should take a break."

[1163] This will improve the user experience and increase satisfaction when using the system. Emotion recognition technology can also be effectively used to improve user interfaces and customer support.

[1164] As described above, this system works in cooperation with each user, device, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis. Furthermore, it has an emotion engine that recognizes user emotions and adjusts the system's response.

[1165] The processing flow will be explained below.

[1166] Step 1: Importing image data

[1167] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[1168] Step 2: Extract text using OCR

[1169] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[1170] Step 3: Structuring the electronic data

[1171] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[1172] Step 4: Generate a QR code

[1173] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[1174] Step 5: Save your data

[1175] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[1176] Step 6: Emotion Recognition with the Emotion Engine

[1177] The user inputs text into the system. The device receives this input and uses the emotion engine to analyze the user's emotions. For example, if the user inputs "I'm tired today," the emotion engine analyzes this text and recognizes that the user is tired.

[1178] Step 7: Generate a response based on emotion

[1179] The server receives the analysis results from the emotion engine and adjusts the system's response accordingly. For example, if it determines that the user is tired, it will generate a friendly message such as, "Thank you for your hard work. We recommend that you take a break."

[1180] Step 8: Search for data

[1181] The user enters specific keywords or conditions into the system to perform a data search, and the device searches the JSON files in the storage directory and extracts entries that match the keywords.

[1182] Step 9: Viewing search results

[1183] The device displays the search results to the user, who can then access the information they need and use it in their work.

[1184] Step 10: Analyze the data

[1185] If the user requests that the data be analyzed, the server will analyze the stored data, which may involve extracting specific patterns or trends.

[1186] Step 11: Provide analysis results

[1187] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[1188] Through the above processing steps, users, terminals, and servers work together to operate the system efficiently, and business efficiency and user satisfaction can be improved through the digitization of paper-based data and emotion recognition functions.

[1189] Example 2

[1190] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1191] Conventional systems have had the problem that the process of digitizing and managing paper-based data is complicated, and data search and analysis take a long time. Furthermore, there is a lack of technology to recognize user emotions and reflect them in the system's responses, which has resulted in a lack of improvement in the user experience. It is necessary to solve these problems and provide an efficient and user-friendly data management system.

[1192] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1193] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the extracted text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data, means for analyzing the electronic data to extract specific patterns or trends, means for analyzing a user's voice input or text input to recognize emotions, and means for adjusting the system response based on the recognized emotion data. This allows for efficient electronic conversion of paper medium data, facilitating search and analysis, and enabling responses according to the user's emotions.

[1194] "Image data" is data that expresses information acquired from paper media in an image format.

[1195] "Text data" is data that includes character information extracted from image data.

[1196] "Electronic data" refers to text data that has been converted into an electronic format and stored.

[1197] The "JSON format" is a lightweight data interchange format used to store electronic data.

[1198] A "QR code" is a square-shaped two-dimensional code that encodes and visually represents information.

[1199] "User voice input" is voice data provided by a user to the system through a microphone or other voice capturing device.

[1200] "Text input" is string information that a user provides to a system using a keyboard or other input device.

[1201] "Emotion recognition" is the process of analyzing a user's voice or text input to identify the user's emotional state.

[1202] "Search method" is a function that searches stored electronic data in JSON format based on specific conditions.

[1203] "Extracting specific patterns and trends" is the process of analyzing electronic data to find significant patterns and trends.

[1204] The "means for adjusting response" is a function for changing the way the system responds based on the recognized user emotion.

[1205] System Configuration

[1206] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[1207] Hardware and Software Used

[1208] Scanner or smartphone: Used to capture paper data as an image.

[1209] OCR engine (e.g. Tesseract OCR): Extracts text data from image data.

[1210] Terminal: A device that accepts user operations and processes data.

[1211] Server: A device used to store, retrieve, and analyze data.

[1212] QR code generation software (e.g., Python's qrcode library): Generates QR codes from JSON-formatted data.

[1213] Emotion recognition engines (e.g., Python's TextBlob library): Analyze emotions from user voice or text input.

[1214] Data processing and calculation flow

[1215] The user captures paper documents as images using a scanner or smartphone. Specifically, they upload the invoice image file "invoice_001.jpg" to the system. The device then analyzes this image data using OCR technology and extracts text data. The extracted text data contains field information such as "invoice number, date, amount." At this stage, JSON-formatted data like the one below is generated.

[1216] json

[1217] {

[1218] "Invoice Number": "001",

[1219] "Date": "2023-09-20",

[1220] "Amount": "10000"

[1221] }

[1222] The device converts this JSON data into a QR code using QR code generation software. The generated QR code is saved as "invoice_001_qr.png" and the user can print it or save it digitally.

[1223] Examples of concrete examples and prompt sentence usage

[1224] For example, if a user takes a picture of an invoice with their smartphone and uploads it to the system as "invoice_001.jpg," the image data will be analyzed using an OCR engine, and the following text data will be extracted:

[1225] Invoice number: 001

[1226] Date: 2023-09-20

[1227] Amount: 10,000

[1228] This text data is converted to JSON format,

[1229] {

[1230] "Invoice Number": "001",

[1231] "Date": "2023-09-20",

[1232] "Amount": "10000"

[1233] }

[1234] The device generates a QR code from this JSON data and saves it as "invoice_001_qr.png".

[1235] Furthermore, if a user inputs text such as "Work was tough today," the emotion recognition engine analyzes the text and recognizes that the user is tired. Based on this recognition result, the server generates a response message such as "Thank you for your hard work. Maybe it would be good to take a short break."

[1236] As a result, this system not only efficiently digitizes paper data and facilitates subsequent search and analysis, but also recognizes the user's emotions and provides appropriate feedback.

[1237] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1238] Explain the program's processing flow in detail

[1239] Step 1:

[1240] The user captures paper documents as images using a scanner or smartphone. Specifically, the user uploads the invoice image file "invoice_001.jpg" to the system. The input is the image data "invoice_001.jpg," and the output is that this image data is imported into the system. At this stage, the terminal receives the image data and prepares it for subsequent processing.

[1241] Step 2:

[1242] The terminal uses OCR technology (e.g., Tesseract OCR) to analyze the input image data and extract text data. The input is the image data "invoice_001.jpg" captured in step 1, and the output is the extracted text data. This text data includes field information such as "invoice number, date, and amount." Specifically, the OCR engine is called to perform image analysis and obtain text information.

[1243] Step 3:

[1244] The terminal converts the extracted text data into electronic data and saves it in JSON format. The input is the text data extracted in step 2, and the output is JSON format data. Specifically, the following JSON data is generated:

[1245] json

[1246] {

[1247] "Invoice Number": "001",

[1248] "Date": "2023-09-20",

[1249] "Amount": "10000"

[1250] }

[1251] The device stores this JSON data in the specified save directory.

[1252] Step 4:

[1253] The device generates a QR code based on the saved JSON data. The input is the JSON data generated in step 3, and the output is an image file of the QR code. Specifically, the QR code is generated using the Python qrcode library and saved as "invoice_001_qr.png." The device provides this file to the user.

[1254] Step 5:

[1255] The user enters specific keywords or conditions into the system, and the device searches for JSON data in the storage directory. The input is the search conditions entered by the user (e.g., "Invoice number is 001"), and the output is the search results. The device searches the stored JSON files and extracts the corresponding entries. Specifically, it reads the matching files from the file system and displays their contents to the user.

[1256] Step 6:

[1257] When a user requests data analysis, the server analyzes the stored data. The input is the user's analysis request (e.g., "analyze trends in billing data for the past year"), and the output is the analysis results. The server uses Python's pandas library to read the data and extract patterns and trends. For example, it can graph fluctuations in the number and amount of bills by month and provide this to the user.

[1258] Step 7:

[1259] An emotion engine is used to analyze a user's voice or text input and recognize the user's emotion. The input is the user's voice or text input (e.g., "Work was tough today") and the output is the recognized emotion data. An emotion engine (e.g., TextBlob) is used to parse the input data and identify the user's emotion.

[1260] Step 8:

[1261] The server adjusts the system's response based on the recognized emotion data. The input is the emotion data recognized in step 7, and the output is the adjusted response message. For example, if the user expresses the emotion "I'm very tired," the server generates a message such as "Thank you for your hard work. It might be a good idea to take a short break," and presents it to the user.

[1262] Through this series of processing steps, paper-based data can be efficiently digitized, facilitating subsequent search and analysis, and providing responses that reflect the user's emotions.

[1263] (Application example 2)

[1264] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1265] The purpose of this invention is to provide a system that facilitates information search and analysis by efficiently digitizing and centrally managing paper-based data. Another purpose is to improve the user experience by recognizing the user's emotions and providing feedback based on those emotions.

[1266] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1267] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data based on user input, means for analyzing the electronic data to extract specific patterns or trends, and means for recognizing user emotions and providing feedback based on the emotions, thereby enabling efficient information management and improving the user experience.

[1268] "Paper media" refers to information that is printed on physical paper.

[1269] "Image data" refers to digital image information obtained from paper media using a device such as a camera or scanner.

[1270] "Text data" refers to character information extracted from image data using OCR technology.

[1271] "Electronic data" refers to text data converted into a format that is easy to manage electronically.

[1272] "JSON format" refers to electronic data that has a data structure in JavaScript Object Notation format.

[1273] A "QR code" is a type of two-dimensional barcode that stores electronic data and is designed to be read by a machine.

[1274] "Means of storage" refers to methods and mechanisms for safely and efficiently storing QR codes and electronic data in JSON format.

[1275] "User input" refers to instructions or information provided by a user to a system in the form of text or voice.

[1276] "Search means" refers to a method or mechanism for locating electronic data based on specific conditions or keywords.

[1277] "Analytical means" refers to methods or mechanisms for examining electronic data in detail and identifying specific patterns or trends.

[1278] "Means for recognizing emotions" refers to a method or mechanism for determining a user's emotional state based on the user's input.

[1279] "Means for providing feedback" refers to a method or mechanism for returning appropriate messages or instructions to the user based on the results of emotion recognition.

[1280] System Configuration

[1281] The following is a detailed description of an embodiment of the present invention. The system efficiently digitizes paper-based data, centralizes management using QR codes, and recognizes the user's emotions and provides feedback based on those emotions.

[1282] Hardware and software used

[1283] 1. Smartphone - Use the camera function to capture image data of paper media. Specifically, iPhones and Android smartphones can be used.

[1284] 2. OCR technology library (pytesseract) - used to extract text data from captured image data.

[1285] 3. Image Processing Library (cv2) - Used to read and preprocess image data.

[1286] 4. Data Formatting Library (json) - Used to save extracted text data in JSON format.

[1287] 5. QR Code Generation Library (qrcode) - Used to generate QR codes based on electronic data in JSON format.

[1288] 6. Emotion Engine - Used to recognize emotions from user input and provide feedback based on the results.

[1289] Specific example explanation

[1290] 1. Acquiring image data and extracting text data

[1291] The user uses the smartphone camera to take an image of a paper document, such as a receipt, and saves it with a file name such as "receipt_20230920.jpg."

[1292] Image data acquired by the device is analyzed using pytesseract to extract text data. At this time, image preprocessing is performed using cv2 to improve OCR accuracy.

[1293] 2. Digitizing text data and saving it in JSON format

[1294] The device converts the extracted text data into electronic data and stores it in a structured format, making it easier to search and analyze later.

[1295] For example, this may include information such as: "date," "store name," "product," and "amount."

[1296] Finally, the data is stored in JSON format.

[1297] 3. Generate a QR code

[1298] The device generates a QR code based on the JSON formatted electronic data. For example, this JSON data is saved as "receipt_qr.png".

[1299] Users can easily share or reuse the data by displaying or printing this QR code.

[1300] 4. Recognizing emotions and providing feedback

[1301] The user inputs text to the system, such as "Today's shopping was great."

[1302] The emotion recognition engine (EmotionEngine) analyzes this text and recognizes the user's emotion as "happy."

[1303] Based on the results of emotion recognition, the device provides feedback to the user, such as "You made a good purchase!"

[1304] Prompt Sentence Examples

[1305] Below are some examples of specific prompt sentences.

[1306] Example input

[1307] Image file: "receipt_20230920.jpg"

[1308] Input text: "Today's shopping was amazing!"

[1309] Execution flow

[1310] The user takes a photo of the receipt using their smartphone and enters the image into the system. OCR technology extracts the text data and saves it in JSON format. A QR code is then generated and provided to the user. Furthermore, an emotion recognition engine analyzes the user's input text and provides emotion-based feedback, improving the user experience.

[1311] The above is an embodiment of the invention.

[1312] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1313] Step 1:

[1314] The user captures image data of the paper medium using the smartphone camera and saves it as an image file. For example, the file name is "receipt_20230920.jpg." Based on this, image data is obtained.

[1315] Step 2:

[1316] The image data acquired by the device is read and preprocessed using the image processing library (cv2). This includes noise removal and grayscale conversion. This improves the quality of the image data and prepares it for efficient text extraction using OCR technology. The input is image data, and the output is preprocessed image data.

[1317] Step 3:

[1318] The terminal uses an OCR technology library (pytesseract) to extract text data from preprocessed image data. This text data includes information such as the date, store name, product name, and price. The input is the preprocessed image data, and the output is the extracted text data.

[1319] Step 4:

[1320] The terminal converts the extracted text data into electronic data and saves it in JSON format using the data format library (json). For example, the format is "{"Date": "2023-09-20", "Store Name": "XYZStore", "Amount": "10000"}". The input is the extracted text data, and the output is electronic data in JSON format.

[1321] Step 5:

[1322] The terminal generates a QR code using the QR code generation library (qrcode) based on the JSON format electronic data. For example, it is saved with a file name such as "receipt_qr.png." The input is JSON format electronic data, and the output is the generated QR code image.

[1323] Step 6:

[1324] The user provides text input to the system (e.g., "Shopping today was great"). The input is text data, and no actual emotion recognition processing is performed at this stage.

[1325] Step 7:

[1326] The device uses an emotion recognition engine (EmotionEngine) to recognize emotions from the user's text input. This engine analyzes the input text data and classifies emotions into categories such as "happy" and "sad." The input is text input, and the output is recognized emotion data.

[1327] Step 8:

[1328] The device provides feedback to the user based on the emotion recognition results. For example, if the emotion is "happy," a positive message such as "Good shopping!" is displayed. The input is the recognized emotion data, and the output is the feedback message.

[1329] In this way, users can easily digitize paper-based data using their smartphones and manage it with QR codes, as well as receive feedback based on emotion recognition.

[1330] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1331] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1332] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1333] [Fourth embodiment]

[1334] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1335] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1336] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1337] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1338] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1339] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1340] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1341] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1342] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1343] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1344] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1345] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1346] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1347] The embodiments of the present invention will be specifically described below.

[1348] System Configuration

[1349] The present invention is a system that efficiently digitizes paper-based data and centrally manages it using QR codes. This system mainly includes the following main processing steps.

[1350] 1. Data extraction from paper documents

[1351] 2. Conversion and structuring of electronic data

[1352] 3. Generate and save a QR code

[1353] 4. Data retrieval and analysis

[1354] Data extraction examples

[1355] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[1356] Data digitization and storage

[1357] The device converts the text data extracted from the image into electronic data and stores it in JSON format. This structured data makes it easier to manage, search, and analyze. For example, the following JSON format data is generated:

[1358] {

[1359] "Invoice Number": "001",

[1360] "Date": "2023-09-20",

[1361] "Amount": "10000"

[1362] }

[1363] The device stores this data in a storage directory and simultaneously generates a QR code.

[1364] QR code generation and output

[1365] The terminal generates a QR code based on the JSON-formatted digital data. This QR code is an encoded form of the digital data, and the user can print it or save it digitally. For example, it can be saved as "invoice_001_qr.png."

[1366] Searching for Data

[1367] When a user enters a search keyword into the system, the device searches the saved JSON data. For example, if you search for data for "May 2022," the device will scan all JSON files in the specified directory and extract the relevant entries. The search results are then provided to the user, allowing them to quickly access the desired information.

[1368] Analyzing the data

[1369] If a user requests data analysis, the server analyzes the stored data. This analysis may involve extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their operations.

[1370] As described above, the system of the present invention efficiently digitizes paper-based data and centrally manages it, making it easy to search and analyze information. Users can use the system with simple operations, which can significantly improve business efficiency in companies.

[1371] The processing flow will be explained below.

[1372] Step 1: Importing image data

[1373] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[1374] Step 2: Extract text using OCR

[1375] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[1376] Step 3: Structuring the electronic data

[1377] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[1378] Step 4: Generate a QR code

[1379] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[1380] Step 5: Save your data

[1381] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[1382] Step 6: Search for data

[1383] The user enters specific keywords or conditions into the system to perform a data search, and the device searches for JSON files in the storage directory and extracts data that matches the keywords.

[1384] Step 7: Viewing search results

[1385] The device displays the search results to the user, who can then access the information they need and use it in their work.

[1386] Step 8: Analyze the data

[1387] When a user requests that their data be analyzed, the server receives the stored data and performs the analysis, which includes extracting specific patterns or trends.

[1388] Step 9: Provide analysis results

[1389] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[1390] In this way, the processing steps of this system work in cooperation with each user, terminal, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis.

[1391] Example 1

[1392] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1393] Traditional systems that extract information from paper media, digitize it, and then manage and search it are inefficient because they require a lot of manual work and time. Furthermore, there are many issues, such as incorrect recognition of extracted data, low search accuracy, and difficulty in data analysis. This reduces the efficiency of information management and makes it difficult to respond quickly to business requests.

[1394] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1395] In this invention, the server includes means for acquiring image data from paper media, analyzing the image data, and extracting text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON-formatted electronic data, means for saving the QR code and the JSON-formatted electronic data, means for searching the JSON-formatted electronic data based on user input, means for analyzing the electronic data and extracting specific patterns or trends, means for extracting text data using OCR technology, means for providing the saved QR code to a user, means for saving the electronic data in a database and making it accessible, means for notifying the user of the generated data, and means for encoding the generated QR code and visually displaying it, thereby enabling efficient digitization of information from paper media, centralized management, and rapid search and analysis.

[1396] "Paper media" refers to physically printed documents and materials.

[1397] "Image data" refers to information captured from paper media and expressed visually, such as in bitmap format.

[1398] "Analysis" refers to the general process of extracting useful information from acquired image data.

[1399] "Text data" refers to character information extracted from analyzed image data.

[1400] "Electronic data" means information stored in digital form.

[1401] "JSON format" is an abbreviation for JavaScript Object Notation and is a lightweight data exchange format.

[1402] A "QR code" is a type of two-dimensional barcode that is used to read information quickly.

[1403] "Storage" means storing data in a certain location or storage device.

[1404] "User input" refers to instructions or commands from anyone using the system.

[1405] "Searching" is the act of finding specific information in a database or stored files.

[1406] An "analytical tool" is a method or device that reads data and finds specific patterns or trends within it.

[1407] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that reads character information from image data.

[1408] "Output means" refers to a mechanism for outputting processed data or generated information by displaying, printing, or the like.

[1409] A "database" is a system for systematically organizing data and efficiently storing and searching it.

[1410] "Notification" is the act of informing a user of certain information.

[1411] "Encoding" is the process of converting information into a particular format.

[1412] "Visual display" means graphically expressing the generated data and information and providing it in a form that is easy for the user to understand.

[1413] The following is a detailed description of an embodiment of the present invention. The present invention is a system that efficiently digitizes data on paper media and centrally manages it using QR codes. This system is operated mainly by three entities: a server, a terminal, and a user.

[1414] System Configuration

[1415] The system of the present invention comprises the following main processing steps:

[1416] 1. Data extraction from paper documents

[1417] 2. Conversion and structuring of electronic data

[1418] 3. Generate and save a QR code

[1419] 4. Data retrieval and analysis

[1420] Hardware and Software Use

[1421] The implementation of the present invention uses the following hardware and software:

[1422] Scanner or smartphone: Used to capture paper media as image data.

[1423] OCR technology: Used to extract text data from image data. An example is Tesseract OCR.

[1424] Database: Used to store electronic data. An example is MongoDB.

[1425] QR code generation library: Used to generate QR codes. A specific example is the Python qrcode library.

[1426] Data search engines: used to search stored electronic data. An example is Elasticsearch.

[1427] Data analysis libraries: used to analyze stored data. Examples include Python's pandas and numpy.

[1428] Specific processing explanation

[1429] Data Extraction

[1430] The user captures paper documents as images using a scanner or smartphone. For example, the user takes a photo of an invoice image file "invoice_001.jpg" with their smartphone and uploads it to the system. The device receives the uploaded image file and temporarily saves it in secure storage. The server validates the image data and checks whether it is in the correct format. If it is not correct, it sends a notification prompting the user to re-upload. The server uses OCR technology to analyze the image data and extract text data such as "invoice number, date, amount."

[1431] Electronic Data Storage

[1432] The device converts the extracted text data into JSON format, producing data like this:

[1433] json

[1434] {

[1435] "Invoice Number": "001",

[1436] "Date": "2023-09-20",

[1437] "Amount": "10000"

[1438] }

[1439] The terminal stores this data in a storage directory and saves it in a database.

[1440] QR code generation and notification

[1441] The device generates a QR code based on the saved JSON data. The Python qrcode library is used to generate the code. The generated QR code image is saved as "invoice_001_qr.png" and a download link is sent to the user.

[1442] Searching for Data

[1443] When a user enters a search keyword on the search screen, for example, "May 2022," the device scans the stored database for the relevant JSON file. The Elasticsearch engine is used for the search. The search results are provided to the user, allowing them to quickly view the relevant invoice information.

[1444] Analyzing the data

[1445] When a user wants to analyze data, they specify the specific analysis target and conditions and send a request to the server. The server analyzes the stored data and extracts specific patterns and trends. For example, it uses Python's pandas library to build a data frame and aggregate specific field information (such as "amount"). The analysis results are provided to the user and displayed as a visual report.

[1446] Specific examples

[1447] For example, a user uploads an invoice like this:

[1448] Invoice file name: invoice_001.jpg

[1449] Included information: Invoice number 001, date 2023-09-20, amount 10,000 yen

[1450] The device does the following:

[1451] 1. Text data extraction using OCR technology

[1452] 2. Convert to JSON format and save to storage

[1453] 3. Generate a QR code from the data

[1454] The generated QR code is saved as "invoice_001_qr.png", and by scanning this QR code, users can quickly access the relevant data.

[1455] Prompt Sentence Examples

[1456] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[1457] By following the above steps, users can efficiently digitize paper-based data and centralize information management through QR codes.

[1458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1459] Step 1: Import and upload image data

[1460] The user takes a photo of a paper document (e.g., an invoice) with a scanner or smartphone and uploads it to the device as image data (e.g., "invoice_001.jpg"). The device receives this image data and temporarily stores it in secure storage.

[1461] Input: Image data of paper media (e.g. "invoice_001.jpg")

[1462] Output: Image data temporarily stored in secure storage

[1463] Step 2: Validate the image data

[1464] The server validates the image data to ensure it is in the correct format, resolution, etc. If it is in an inappropriate format or resolution, it sends a notification to the user urging them to re-upload.

[1465] Input: Temporarily saved image data

[1466] Output: Validated for proper format and resolution, and notifies user if necessary

[1467] Step 3: Extract text data using OCR analysis

[1468] The server uses Tesseract OCR technology to extract text information from image data, for example, extracting field information such as "invoice number, date, amount" from "invoice_001.jpg".

[1469] Input: Validated image data

[1470] Output: Extracted text data (e.g., "Invoice number: 001, Date: 2023-09-20, Amount: 10000")

[1471] Specific operation: Obtain text data using Tesseract OCR's image_to_string method

[1472] Step 4: Converting text data to JSON format

[1473] The device converts the extracted text data into JSON format, for example:

[1474] json

[1475] {

[1476] "Invoice Number": "001",

[1477] "Date": "2023-09-20",

[1478] "Amount": "10000"

[1479] }

[1480] Input: Extracted text data

[1481] Output: Data converted to JSON format

[1482] Step 5: Saving JSON Data

[1483] The device saves the converted JSON data in secure storage or a database (e.g., MongoDB), and notifies the user when the data has been saved.

[1484] Input: JSON format data

[1485] Output: JSON data saved in the database, save completion notification

[1486] Step 6: Generate a QR code

[1487] The device generates a QR code based on the stored JSON data. It uses the Python qrcode library to create an encoded QR code image.

[1488] Input: JSON format data

[1489] Output: Generated QR code image (e.g. "invoice_001_qr.png")

[1490] Step 7: Save and notify the QR code

[1491] Save the generated QR code image and send a notification to the user providing a download link.

[1492] Input: Generated QR code image

[1493] Output: QR code image saved in secure storage, notification of download link

[1494] Step 8: Search for data

[1495] The user enters a search keyword (e.g., "May 2022") into the system. The device uses the Elasticsearch engine to search for JSON data in the database.

[1496] Input: User-entered search keywords

[1497] Output: Search results for relevant JSON data

[1498] Step 9: Viewing search results

[1499] The search results are provided to the user by the terminal, allowing the user to quickly access the desired information.

[1500] Input: Searched JSON data

[1501] Output: Search results displayed to the user

[1502] Step 10: Analyze the data

[1503] A user submits a specific data analysis request to the system, and the server uses a data analysis library (e.g., pandas) to analyze the stored data and extract specific patterns or trends.

[1504] Input: User analysis request, data stored in the database

[1505] Output: Analysis results, visual reports

[1506] As a concrete example of operation, the following prompt sentence can be used:

[1507] "Upload an invoice image, extract the invoice number, date, and amount, and generate a QR code along with the data saved in JSON format."

[1508] (Application example 1)

[1509] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1510] In logistics centers, manually managing paper-based inbound and outbound shipping slips and inspection reports causes many problems, including reduced work efficiency and the possibility of human error. This reduces overall business productivity and complicates information management. Furthermore, the task of searching and analyzing past data is cumbersome, making it difficult to quickly obtain information in real time. Therefore, there is a demand for a system that digitizes paper-based document management and provides efficient, centralized management.

[1511] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1512] In this invention, the server includes: means for acquiring image data from paper media and analyzing the image data to extract text data; means for converting the text data into electronic data and saving it in JSON format; means for generating a QR code based on the JSON-formatted electronic data; means for searching the JSON-formatted electronic data based on user input; means for analyzing the electronic data to extract specific patterns and trends; and means for photographing paper-based receipt / shipment slips and inspection reports at a logistics center using a smartphone or a camera-equipped robot, analyzing them using OCR technology to extract field information such as item name, quantity, and inspection results, saving the field information in JSON format, generating a QR code, and having an operator scan the QR code with a smartphone or robot to confirm the information. This digitizes paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis.

[1513] "Paper media" refers to media on which information is physically printed, such as documents and slips printed on paper.

[1514] "Image data" refers to image data acquired using a scanner or camera, and is information written on paper that is stored electronically.

[1515] "Text data" refers to character string information extracted from image data, and is character data recognized by OCR technology.

[1516] "Electronic data" refers to data in a digital format that is handled within a computer system and stored in JSON or other structured data formats.

[1517] "JSON format" stands for JavaScript Object Notation, a text-based data format that makes it easy to describe data structures.

[1518] A "QR code" is a square, two-dimensional barcode that digitally encodes information and can be scanned to quickly retrieve that information.

[1519] A "logistics center" is a facility where logistics operations are carried out, and where goods are received, shipped, stored, and managed.

[1520] A "shipping / receiving slip" is a document that records information about the receipt and dispatch of goods at a logistics center.

[1521] An "inspection report" is a document that records the results of a product's quality inspection at a logistics center.

[1522] "OCR technology" is an abbreviation for Optical Character Recognition, and is a technology that automatically recognizes characters from image data and extracts them as text data.

[1523] "Mobile device" refers to a smartphone, tablet, or other portable electronic device, often equipped with a camera and communication capabilities.

[1524] A "camera-equipped robot" is a robot equipped with a camera that can move and take pictures automatically, and is used to improve work efficiency in logistics centers and other places.

[1525] The present invention provides a system for digitalizing and centrally managing paper-based documents in a logistics center.

[1526] System Configuration

[1527] The present invention uses the following main hardware and software:

[1528] Hardware: scanners, smartphones, robots with cameras.

[1529] Software: OCR technology (Tesseract OCR), Python library (qrcode), database (MySQL, PostgreSQL).

[1530] Hardware and Software Use

[1531] 1. Acquiring image data from paper media:

[1532] The server allows logistics center workers to acquire image data of paper-based shipping and receiving slips and inspection reports using smartphones or camera-equipped robots.

[1533] 2. Image data analysis and text data extraction:

[1534] The server analyzes the acquired image data using OCR technology and extracts field information such as product name, quantity, and inspection results as text data.

[1535] Specifically, Tesseract OCR is used to read text data from images.

[1536] 3. Conversion and storage of text data into electronic data:

[1537] The server converts the extracted text data into electronic data in JSON format and stores it in a database.

[1538] This makes the data structured and easier to search and analyze.

[1539] 4. Generate and save the QR code:

[1540] The server generates a QR code based on the electronic data in JSON format.

[1541] QR codes are used by workers to scan them with their smartphones or camera-equipped robots to check the information.

[1542] 5. Data retrieval and analysis:

[1543] The server searches for electronic data in JSON format based on user input and quickly provides the required information.

[1544] We also provide a data analysis function that extracts specific patterns and trends, and the analysis results can be used to improve business operations.

[1545] Example

[1546] Use within a distribution center:

[1547] A worker uses a smartphone to take a photo of the delivery slip for the incoming goods.

[1548] The server uses OCR technology to extract the product name, quantity, and inspection results from the image of the invoice and saves them in JSON format.

[1549] QR codes are generated from JSON format data, and workers can scan them with their smartphones to access the necessary information in real time.

[1550] Prompt Sentence Examples

[1551] We are considering digitizing inbound and outbound delivery slips at our logistics center. How can we take a photo of a paper-based slip, extract the data using OCR processing, save it in JSON format, and generate a QR code?

[1552] This system will streamline paper-based document management at logistics centers, enabling centralized management of information and rapid search and analysis. It is expected to improve the overall productivity of logistics operations, reduce human error, and improve operational efficiency.

[1553] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1554] Step 1:

[1555] A user takes a photo of a paper document (e.g., receipt / shipping slip, inspection report) using a smartphone or a camera-equipped robot. Image data (e.g., JPEG, PNG format) is generated as input. This image data is then uploaded to the system as output.

[1556] Step 2:

[1557] The server receives the uploaded image data and analyzes it using OCR technology (Tesseract OCR). Image data is given as input, and extracted text data is generated as output. Specifically, the character information in the image is converted into text data.

[1558] Step 3:

[1559] The server parses the extracted text data into field information. Text data is given as input, and structured electronic data (e.g., JSON format) is generated as output. Specifically, field information such as product name, quantity, and inspection results is parsed and structured.

[1560] Step 4:

[1561] The server stores structured electronic data in JSON format. JSON format data is given as input and saved in a database as output. Specifically, a storage directory is specified in the database (e.g., MySQL, PostgreSQL) and the data is stored.

[1562] Step 5:

[1563] The server generates a QR code based on the stored JSON format digital data. JSON data is given as input, and a QR code image is generated as output. Specifically, the QR code is generated using the Python qrcode library.

[1564] Step 6:

[1565] The server saves the generated QR code. The QR code image is given as input and stored in a directory as output. Specifically, the QR code image is saved in a specified directory and provided to the worker.

[1566] Step 7:

[1567] The user enters keywords to search for the information they need. The search keywords are given as input, and related JSON data is returned as output. Specifically, the JSON data in the database is searched and the relevant entries are extracted.

[1568] Step 8:

[1569] The server analyzes the relevant JSON data and extracts specific patterns and trends. The JSON data of the search results is given as input, and the analysis results are provided as output. Specifically, data analysis algorithms are used to visualize trends and help improve business operations.

[1570] The processing flow of this program digitizes paper document management at logistics centers, enabling efficient information search and analysis.

[1571] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1572] The embodiments of the present invention will be specifically described below.

[1573] System Configuration

[1574] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[1575] 1. Data extraction from paper documents

[1576] 2. Conversion and structuring of electronic data

[1577] 3. Generate and save a QR code

[1578] 4. Data retrieval and analysis

[1579] 5. User Emotion Recognition by Emotion Engine

[1580] Data extraction examples

[1581] A user captures paper documents as images using a scanner or smartphone. For example, an invoice image file, "invoice_001.jpg," is uploaded to the system. The device analyzes this image data using OCR (optical character recognition) technology and extracts text data from the image. This text data includes field information such as "invoice number, date, and amount."

[1582] Data digitization and storage

[1583] The device converts the text data extracted from the image into electronic data and saves it in JSON format. This structured the data, making it easier to process and search later. For example, the following JSON format data is generated:

[1584] {

[1585] "Invoice Number": "001",

[1586] "Date": "2023-09-20",

[1587] "Amount": "10000"

[1588] }

[1589] The device stores this data in a storage directory and simultaneously generates a QR code.

[1590] QR code generation and output

[1591] The device generates a QR code based on the JSON data. This QR code is an encoded form of electronic data that the user can print or save digitally, for example, as "invoice_001_qr.png."

[1592] Searching for Data

[1593] The user enters specific keywords or conditions into the system to perform a data search. The device searches the JSON data in the storage directory and extracts entries that match the keywords. The search results are provided to the user, allowing them to quickly access the desired information.

[1594] Analyzing the data

[1595] If a user requests data analysis, the server analyzes the stored data. This analysis may include extracting specific patterns or trends. For example, the server may perform word frequency analysis to determine how frequently certain keywords appear. This allows companies to extract useful information from past data and use it to improve their business.

[1596] Recognizing user emotions with an emotion engine

[1597] An emotion engine is built into the system, which analyzes the user's voice and text inputs to recognize their emotions. This emotion data is used to adjust the system's response. For example, if the user is expressing dissatisfaction, the system will adjust to provide a more friendly response.

[1598] Examples of emotion engines

[1599] If a user types something into the system like "Work was tough today," the emotion engine will analyze this text and recognize that the user is tired. Based on this emotion data, the server will generate a response to the user such as "Thank you for your hard work. Maybe you should take a break."

[1600] This will improve the user experience and increase satisfaction when using the system. Emotion recognition technology can also be effectively used to improve user interfaces and customer support.

[1601] As described above, this system works in cooperation with each user, device, and server, efficiently digitizing paper-based data and facilitating subsequent search and analysis. Furthermore, it has an emotion engine that recognizes user emotions and adjusts the system's response.

[1602] The processing flow will be explained below.

[1603] Step 1: Importing image data

[1604] A user takes a photo of a paper document (such as a bill) using a scanner or a smartphone camera to create an image file, which is then uploaded to the system.

[1605] Step 2: Extract text using OCR

[1606] The device receives the uploaded image file and uses OCR technology to extract text data from the image, such as invoice number, date, amount, etc.

[1607] Step 3: Structuring the electronic data

[1608] The device organizes the extracted text data and structures it into electronic data, storing it in JSON format for easier subsequent processing and retrieval.

[1609] Step 4: Generate a QR code

[1610] The device generates a QR code from the structured JSON data, which encodes electronic data and can be used on a physical tag or in digital form.

[1611] Step 5: Save your data

[1612] The device saves the QR code and JSON data to the specified directory, creating a data infrastructure for subsequent searches and analysis.

[1613] Step 6: Emotion Recognition with the Emotion Engine

[1614] The user inputs text into the system. The device receives this input and uses the emotion engine to analyze the user's emotions. For example, if the user inputs "I'm tired today," the emotion engine analyzes this text and recognizes that the user is tired.

[1615] Step 7: Generate a response based on emotion

[1616] The server receives the analysis results from the emotion engine and adjusts the system's response accordingly. For example, if it determines that the user is tired, it will generate a friendly message such as, "Thank you for your hard work. We recommend that you take a break."

[1617] Step 8: Search for data

[1618] The user enters specific keywords or conditions into the system to perform a data search, and the device searches the JSON files in the storage directory and extracts entries that match the keywords.

[1619] Step 9: Viewing search results

[1620] The device displays the search results to the user, who can then access the information they need and use it in their work.

[1621] Step 10: Analyze the data

[1622] If the user requests that the data be analyzed, the server will analyze the stored data, which may involve extracting specific patterns or trends.

[1623] Step 11: Provide analysis results

[1624] The server provides the analysis results to the user, who can then make decisions to improve their business based on the reports and graphs provided.

[1625] Through the above processing steps, users, terminals, and servers work together to operate the system efficiently, and business efficiency and user satisfaction can be improved through the digitization of paper-based data and emotion recognition functions.

[1626] Example 2

[1627] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1628] Conventional systems have had the problem that the process of digitizing and managing paper-based data is complicated, and data search and analysis take a long time. Furthermore, there is a lack of technology to recognize user emotions and reflect them in the system's responses, which has resulted in a lack of improvement in the user experience. It is necessary to solve these problems and provide an efficient and user-friendly data management system.

[1629] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1630] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the extracted text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data, means for analyzing the electronic data to extract specific patterns or trends, means for analyzing a user's voice input or text input to recognize emotions, and means for adjusting the system response based on the recognized emotion data. This allows for efficient electronic conversion of paper medium data, facilitating search and analysis, and enabling responses according to the user's emotions.

[1631] "Image data" is data that expresses information acquired from paper media in an image format.

[1632] "Text data" is data that includes character information extracted from image data.

[1633] "Electronic data" refers to text data that has been converted into an electronic format and stored.

[1634] The "JSON format" is a lightweight data interchange format used to store electronic data.

[1635] A "QR code" is a square-shaped two-dimensional code that encodes and visually represents information.

[1636] "User voice input" is voice data provided by a user to the system through a microphone or other voice capturing device.

[1637] "Text input" is string information that a user provides to a system using a keyboard or other input device.

[1638] "Emotion recognition" is the process of analyzing a user's voice or text input to identify the user's emotional state.

[1639] "Search method" is a function that searches stored electronic data in JSON format based on specific conditions.

[1640] "Extracting specific patterns and trends" is the process of analyzing electronic data to find significant patterns and trends.

[1641] The "means for adjusting response" is a function for changing the way the system responds based on the recognized user emotion.

[1642] System Configuration

[1643] This invention combines a system that efficiently digitizes paper-based data and centrally manages it using QR codes with an emotion engine that recognizes user emotions. This system includes the following main processing steps:

[1644] Hardware and Software Used

[1645] Scanner or smartphone: Used to capture paper data as an image.

[1646] OCR engine (e.g. Tesseract OCR): Extracts text data from image data.

[1647] Terminal: A device that accepts user operations and processes data.

[1648] Server: A device used to store, retrieve, and analyze data.

[1649] QR code generation software (e.g., Python's qrcode library): Generates QR codes from JSON-formatted data.

[1650] Emotion recognition engines (e.g., Python's TextBlob library): Analyze emotions from user voice or text input.

[1651] Data processing and calculation flow

[1652] The user captures paper documents as images using a scanner or smartphone. Specifically, they upload the invoice image file "invoice_001.jpg" to the system. The device then analyzes this image data using OCR technology and extracts text data. The extracted text data contains field information such as "invoice number, date, amount." At this stage, JSON-formatted data like the one below is generated.

[1653] json

[1654] {

[1655] "Invoice Number": "001",

[1656] "Date": "2023-09-20",

[1657] "Amount": "10000"

[1658] }

[1659] The device converts this JSON data into a QR code using QR code generation software. The generated QR code is saved as "invoice_001_qr.png" and the user can print it or save it digitally.

[1660] Examples of concrete examples and prompt sentence usage

[1661] For example, if a user takes a picture of an invoice with their smartphone and uploads it to the system as "invoice_001.jpg," the image data will be analyzed using an OCR engine, and the following text data will be extracted:

[1662] Invoice number: 001

[1663] Date: 2023-09-20

[1664] Amount: 10,000

[1665] This text data is converted to JSON format,

[1666] {

[1667] "Invoice Number": "001",

[1668] "Date": "2023-09-20",

[1669] "Amount": "10000"

[1670] }

[1671] The device generates a QR code from this JSON data and saves it as "invoice_001_qr.png".

[1672] Furthermore, if a user inputs text such as "Work was tough today," the emotion recognition engine analyzes the text and recognizes that the user is tired. Based on this recognition result, the server generates a response message such as "Thank you for your hard work. Maybe it would be good to take a short break."

[1673] As a result, this system not only efficiently digitizes paper data and facilitates subsequent search and analysis, but also recognizes the user's emotions and provides appropriate feedback.

[1674] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1675] Explain the program's processing flow in detail

[1676] Step 1:

[1677] The user captures paper documents as images using a scanner or smartphone. Specifically, the user uploads the invoice image file "invoice_001.jpg" to the system. The input is the image data "invoice_001.jpg," and the output is that this image data is imported into the system. At this stage, the terminal receives the image data and prepares it for subsequent processing.

[1678] Step 2:

[1679] The terminal uses OCR technology (e.g., Tesseract OCR) to analyze the input image data and extract text data. The input is the image data "invoice_001.jpg" captured in step 1, and the output is the extracted text data. This text data includes field information such as "invoice number, date, and amount." Specifically, the OCR engine is called to perform image analysis and obtain text information.

[1680] Step 3:

[1681] The terminal converts the extracted text data into electronic data and saves it in JSON format. The input is the text data extracted in step 2, and the output is JSON format data. Specifically, the following JSON data is generated:

[1682] json

[1683] {

[1684] "Invoice Number": "001",

[1685] "Date": "2023-09-20",

[1686] "Amount": "10000"

[1687] }

[1688] The device stores this JSON data in the specified save directory.

[1689] Step 4:

[1690] The device generates a QR code based on the saved JSON data. The input is the JSON data generated in step 3, and the output is an image file of the QR code. Specifically, the QR code is generated using the Python qrcode library and saved as "invoice_001_qr.png." The device provides this file to the user.

[1691] Step 5:

[1692] The user enters specific keywords or conditions into the system, and the device searches for JSON data in the storage directory. The input is the search conditions entered by the user (e.g., "Invoice number is 001"), and the output is the search results. The device searches the stored JSON files and extracts the corresponding entries. Specifically, it reads the matching files from the file system and displays their contents to the user.

[1693] Step 6:

[1694] When a user requests data analysis, the server analyzes the stored data. The input is the user's analysis request (e.g., "analyze trends in billing data for the past year"), and the output is the analysis results. The server uses Python's pandas library to read the data and extract patterns and trends. For example, it can graph fluctuations in the number and amount of bills by month and provide this to the user.

[1695] Step 7:

[1696] An emotion engine is used to analyze a user's voice or text input and recognize the user's emotion. The input is the user's voice or text input (e.g., "Work was tough today") and the output is the recognized emotion data. An emotion engine (e.g., TextBlob) is used to parse the input data and identify the user's emotion.

[1697] Step 8:

[1698] The server adjusts the system's response based on the recognized emotion data. The input is the emotion data recognized in step 7, and the output is the adjusted response message. For example, if the user expresses the emotion "I'm very tired," the server generates a message such as "Thank you for your hard work. It might be a good idea to take a short break," and presents it to the user.

[1699] Through this series of processing steps, paper-based data can be efficiently digitized, facilitating subsequent search and analysis, and providing responses that reflect the user's emotions.

[1700] (Application example 2)

[1701] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1702] The purpose of this invention is to provide a system that facilitates information search and analysis by efficiently digitizing and centrally managing paper-based data. Another purpose is to improve the user experience by recognizing the user's emotions and providing feedback based on those emotions.

[1703] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1704] In this invention, the server includes means for acquiring image data from a paper medium and analyzing the image data to extract text data, means for converting the text data into electronic data and saving it in JSON format, means for generating a QR code based on the JSON format electronic data, means for saving the QR code and the JSON format electronic data, means for searching the JSON format electronic data based on user input, means for analyzing the electronic data to extract specific patterns or trends, and means for recognizing user emotions and providing feedback based on the emotions, thereby enabling efficient information management and improving the user experience.

[1705] "Paper media" refers to information that is printed on physical paper.

[1706] "Image data" refers to digital image information obtained from paper media using a device such as a camera or scanner.

[1707] "Text data" refers to character information extracted from image data using OCR technology.

[1708] "Electronic data" refers to text data converted into a format that is easy to manage electronically.

[1709] "JSON format" refers to electronic data that has a data structure in JavaScript Object Notation format.

[1710] A "QR code" is a type of two-dimensional barcode that stores electronic data and is designed to be read by a machine.

[1711] "Means of storage" refers to methods and mechanisms for safely and efficiently storing QR codes and electronic data in JSON format.

[1712] "User input" refers to instructions or information provided by a user to a system in the form of text or voice.

[1713] "Search means" refers to a method or mechanism for locating electronic data based on specific conditions or keywords.

[1714] "Analytical means" refers to methods or mechanisms for examining electronic data in detail and identifying specific patterns or trends.

[1715] "Means for recognizing emotions" refers to a method or mechanism for determining a user's emotional state based on the user's input.

[1716] "Means for providing feedback" refers to a method or mechanism for returning appropriate messages or instructions to the user based on the results of emotion recognition.

[1717] System Configuration

[1718] The following is a detailed description of an embodiment of the present invention. The system efficiently digitizes paper-based data, centralizes management using QR codes, and recognizes the user's emotions and provides feedback based on those emotions.

[1719] Hardware and software used

[1720] 1. Smartphone - Use the camera function to capture image data of paper media. Specifically, iPhones and Android smartphones can be used.

[1721] 2. OCR technology library (pytesseract) - used to extract text data from captured image data.

[1722] 3. Image Processing Library (cv2) - Used to read and preprocess image data.

[1723] 4. Data Formatting Library (json) - Used to save extracted text data in JSON format.

[1724] 5. QR Code Generation Library (qrcode) - Used to generate QR codes based on electronic data in JSON format.

[1725] 6. Emotion Engine - Used to recognize emotions from user input and provide feedback based on the results.

[1726] Specific example explanation

[1727] 1. Acquiring image data and extracting text data

[1728] The user uses the smartphone camera to take an image of a paper document, such as a receipt, and saves it with a file name such as "receipt_20230920.jpg."

[1729] Image data acquired by the device is analyzed using pytesseract to extract text data. At this time, image preprocessing is performed using cv2 to improve OCR accuracy.

[1730] 2. Digitizing text data and saving it in JSON format

[1731] The device converts the extracted text data into electronic data and stores it in a structured format, making it easier to search and analyze later.

[1732] For example, this may include information such as: "date," "store name," "product," and "amount."

[1733] Finally, the data is stored in JSON format.

[1734] 3. Generate a QR code

[1735] The device generates a QR code based on the JSON formatted electronic data. For example, this JSON data is saved as "receipt_qr.png".

[1736] Users can easily share or reuse the data by displaying or printing this QR code.

[1737] 4. Recognizing emotions and providing feedback

[1738] The user inputs text to the system, such as "Today's shopping was great."

[1739] The emotion recognition engine (EmotionEngine) analyzes this text and recognizes the user's emotion as "happy."

[1740] Based on the results of emotion recognition, the device provides feedback to the user, such as "You made a good purchase!"

[1741] Prompt Sentence Examples

[1742] Below are some examples of specific prompt sentences.

[1743] Example input

[1744] Image file: "receipt_20230920.jpg"

[1745] Input text: "Today's shopping was amazing!"

[1746] Execution flow

[1747] The user takes a photo of the receipt using their smartphone and enters the image into the system. OCR technology extracts the text data and saves it in JSON format. A QR code is then generated and provided to the user. Furthermore, an emotion recognition engine analyzes the user's input text and provides emotion-based feedback, improving the user experience.

[1748] The above is an embodiment of the invention.

[1749] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1750] Step 1:

[1751] The user captures image data of the paper medium using the smartphone camera and saves it as an image file. For example, the file name is "receipt_20230920.jpg." Based on this, image data is obtained.

[1752] Step 2:

[1753] The image data acquired by the device is read and preprocessed using the image processing library (cv2). This includes noise removal and grayscale conversion. This improves the quality of the image data and prepares it for efficient text extraction using OCR technology. The input is image data, and the output is preprocessed image data.

[1754] Step 3:

[1755] The terminal uses an OCR technology library (pytesseract) to extract text data from preprocessed image data. This text data includes information such as the date, store name, product name, and price. The input is the preprocessed image data, and the output is the extracted text data.

[1756] Step 4:

[1757] The terminal converts the extracted text data into electronic data and saves it in JSON format using the data format library (json). For example, the format is "{"Date": "2023-09-20", "Store Name": "XYZStore", "Amount": "10000"}". The input is the extracted text data, and the output is electronic data in JSON format.

[1758] Step 5:

[1759] The terminal generates a QR code using the QR code generation library (qrcode) based on the JSON format electronic data. For example, it is saved with a file name such as "receipt_qr.png." The input is JSON format electronic data, and the output is the generated QR code image.

[1760] Step 6:

[1761] The user provides text input to the system (e.g., "Shopping today was great"). The input is text data, and no actual emotion recognition processing is performed at this stage.

[1762] Step 7:

[1763] The device uses an emotion recognition engine (EmotionEngine) to recognize emotions from the user's text input. This engine analyzes the input text data and classifies emotions into categories such as "happy" and "sad." The input is text input, and the output is recognized emotion data.

[1764] Step 8:

[1765] The device provides feedback to the user based on the emotion recognition results. For example, if the emotion is "happy," a positive message such as "Good shopping!" is displayed. The input is the recognized emotion data, and the output is the feedback message.

[1766] In this way, users can easily digitize paper-based data using their smartphones and manage it with QR codes, as well as receive feedback based on emotion recognition.

[1767] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1768] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1769] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1770] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1771] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1772] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1773] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1774] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1775] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1776] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1777] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1778] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1779] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1780] 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.

[1781] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1782] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1783] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1784] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1785] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1786] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1787] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1788] The following is further disclosed regarding the above embodiment.

[1789] (Claim 1)

[1790] means for acquiring image data from a paper medium and analyzing the image data to extract text data;

[1791] means for converting the text data into electronic data and storing it in a JSON format;

[1792] means for generating a QR code based on the electronic data in JSON format;

[1793] A means for storing the QR code and electronic data in JSON format;

[1794] means for retrieving the JSON formatted electronic data based on user input;

[1795] A system including means for analyzing said electronic data to extract specific patterns or trends.

[1796] (Claim 2)

[1797] The system of claim 1 , further comprising: extracting text data from the image data using OCR technology.

[1798] (Claim 3)

[1799] 10. The system of claim 1, further comprising an output means for generating the QR code and providing the QR code to a user.

[1800] "Example 1"

[1801] (Claim 1)

[1802] means for acquiring image data from a paper medium and analyzing the image data to extract text data;

[1803] means for converting the text data into electronic data and storing it in a JSON format;

[1804] means for generating a QR code based on the electronic data in JSON format;

[1805] A means for storing the QR code and electronic data in JSON format;

[1806] means for retrieving the JSON formatted electronic data based on user input;

[1807] means for analyzing the electronic data to extract specific patterns or trends;

[1808] A means for extracting text data using OCR technology;

[1809] means for providing the stored QR code to a user;

[1810] A means for storing and making accessible electronic data in a database;

[1811] means for notifying the generated data;

[1812] The system includes a means for encoding and visually displaying the generated QR code.

[1813] (Claim 2)

[1814] 10. The system of claim 1, further comprising an output means for generating a QR code and providing the QR code to a user.

[1815] (Claim 3)

[1816] The system of claim 1 , further comprising: extracting text data from the image data using OCR technology.

[1817] "Application Example 1"

[1818] (Claim 1)

[1819] means for acquiring image data from a paper medium and analyzing the image data to extract text data;

[1820] means for converting the text data into electronic data and storing it in a JSON format;

[1821] means for generating a QR code based on the electronic data in JSON format;

[1822] A means for storing the QR code and electronic data in JSON format;

[1823] means for retrieving the JSON formatted electronic data based on user input;

[1824] means for analyzing the electronic data to extract specific patterns or trends;

[1825] A system that uses a smartphone or a camera-equipped robot to photograph paper-based inbound and outbound shipping slips and inspection reports at a logistics center, analyzes them using OCR technology to extract field information such as product name, quantity, and inspection results, saves the field information in JSON format, generates a QR code, and allows workers to scan the QR code with their smartphone or robot to confirm the information.

[1826] (Claim 2)

[1827] The system of claim 1 , further comprising: extracting text data from the image data using OCR technology.

[1828] (Claim 3)

[1829] 10. The system of claim 1, further comprising an output means for generating the QR code and providing the QR code to a worker.

[1830] "Example 2: Combining Emotion Engines"

[1831] (Claim 1)

[1832] means for acquiring image data from a paper medium and analyzing the image data to extract text data;

[1833] means for converting the text data into electronic data and storing it in a JSON format;

[1834] means for generating a QR code based on the electronic data in JSON format;

[1835] A means for storing the QR code and electronic data in JSON format;

[1836] A means for searching the electronic data in JSON format;

[1837] means for analyzing the electronic data to extract specific patterns or trends;

[1838] means for analyzing a user's voice or text input to recognize emotions;

[1839] and means for adjusting a response of the system based on said recognized emotion data.

[1840] (Claim 2)

[1841] The system of claim 1 , further comprising: extracting text data from the image data using OCR technology.

[1842] (Claim 3)

[1843] 10. The system of claim 1, further comprising an output means for generating the QR code and providing the QR code to a user.

[1844] "Application example 2 when combining emotion engines"

[1845] (Claim 1)

[1846] means for acquiring image data from a paper medium and analyzing the image data to extract text data;

[1847] means for converting the text data into electronic data and storing it in a JSON format;

[1848] means for generating a QR code based on the electronic data in JSON format;

[1849] A means for storing the QR code and electronic data in JSON format;

[1850] means for retrieving the JSON formatted electronic data based on user input;

[1851] means for analyzing the electronic data to extract specific patterns or trends;

[1852] A system including means for recognizing a user's emotions and providing feedback based on those emotions.

[1853] (Claim 2)

[1854] The system of claim 1 , further comprising: extracting text data from the image data using OCR technology.

[1855] (Claim 3)

[1856] 10. The system of claim 1, further comprising an output means for generating the QR code and providing the QR code to a user. [Explanation of symbols]

[1857] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for acquiring image data from a paper medium and analyzing the image data to extract text data; means for converting the text data into electronic data and storing it in a JSON format; means for generating a QR code based on the electronic data in JSON format; A means for storing the QR code and electronic data in JSON format; means for retrieving the JSON formatted electronic data based on user input; A system including means for analyzing said electronic data to extract specific patterns or trends.

2. The system of claim 1 , wherein the system extracts text data from the image data using OCR technology.

3. The system of claim 1 further comprising an output means for generating the QR code and providing the QR code to a user.

Images