system

Abstract

We provide a system that automatically analyzes and evaluates request information, and accurately determines the likelihood of acceptance based on established criteria. [Solution] A system comprising: input means for inputting request information; transmission means for sending the request information to a server; receiving means for receiving the request information; reference information reading means for reading pre-set reference information; analysis means for analyzing the request information and extracting important keywords; matching means for comparing the extracted keywords with the reference information; determination means for determining the possibility of accepting the request based on the matching results; notification means for notifying the user of the determination results; and log storage means for saving logs for all processing steps of the means.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] It is very important to quickly and accurately evaluate a request from an investigative agency and automatically determine whether it is acceptable. However, in the conventional method, since the evaluation of request information relies on manual work, it takes time and there is a possibility of subjectivity creeping in. In addition, the evaluation process based on criteria is not consistent, and there is also a risk of overlooking important information. An object of the present invention is to provide a system that can automatically analyze and evaluate request information and accurately determine the acceptability based on criteria.

Means for Solving the Problems

[0005] The present invention solves the above problems with a system that includes an input means for inputting request information, a transmission means for sending the request information to a server, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the feasibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, and a log storage means for saving logs for all processing steps of the means. This system may further include a text conversion means for converting the request information into text data and a display means for displaying the determination result to the user. This makes it possible to perform the process from receiving request information to evaluation and notification of the result quickly and accurately.

[0006] "Requested information" refers to information provided by investigative agencies that includes specific details and requirements related to an investigation.

[0007] "Input means" refers to the interface or device that allows the user to input request information into the system.

[0008] "Transmission means" refers to the function or device used to send the input request information to the server.

[0009] "Receiving means" refers to the functions or devices that allow a server to receive the request information that has been sent.

[0010] "Reference information" refers to information that includes pre-defined keywords and phrases used to evaluate the requested information.

[0011] "Reference information reading means" refers to the function or process that the server uses to read reference information.

[0012] "Analysis means" refers to functions and algorithms for analyzing received request information and extracting important keywords and phrases.

[0013] A "matching method" refers to a function or process for comparing extracted keywords or phrases with reference information to confirm whether or not they match.

[0014] "Determination means" refers to the logic or algorithm used to determine the likelihood of accepting a request based on the results of the matching means.

[0015] A "notification means" refers to a function or process for informing the user of the results of a determination means.

[0016] A "log storage means" refers to a function or device for recording and storing data related to all processing steps.

[0017] "Text conversion means" refers to functions or algorithms for converting request information into text data.

[0018] "Display means" refers to an interface or device for displaying the judgment result to the user. [Brief explanation of the drawing]

[0019] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0020] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described according to the attached drawings.

[0021] First, the language used in the following description will be explained.

[0022] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0023] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0024] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0025] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0032] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0039] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0040] This invention relates to a system for efficiently and accurately evaluating request information provided by investigative agencies and determining its feasibility. This system consists of the following components:

[0041] 1. User (Representative of the investigative agency)

[0042] The user is an officer of an investigative agency and uses a terminal to input request information. This information includes details about a specific investigation case. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[0043] 2. Terminal

[0044] The terminal provides a user interface and is a device for inputting and sending request information. Specifically, it has the following functions:

[0045] Input method: Provides forms or fields for users to enter request information.

[0046] Transmission method: The entered request information is sent to the server as text data.

[0047] 3. Server

[0048] The server is the central hub of the system and processes request information using multiple methods. Specifically, it uses the following methods:

[0049] Reference information reading means

[0050] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation.

[0051] Receiving means

[0052] The server receives request information sent from the terminal. This receiving mechanism has the functionality to receive request information in text data format.

[0053] Analysis means

[0054] The received request information is analyzed using a text analysis algorithm to extract important keywords and phrases. This analysis is performed using natural language processing technology.

[0055] Verification means

[0056] The extracted keywords are compared with the reference information. During this process, it is checked whether the keywords match the reference information, and the results are recorded.

[0057] Judgment means

[0058] The likelihood of accepting the request is determined based on the matching results. Specifically, if it perfectly matches the standard information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable."

[0059] Notification means

[0060] The user is notified of the judgment result. This notification sends the result back to the device so that the user can check the result.

[0061] Log storage method

[0062] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[0063] Specific example

[0064] Case 1: Acceptable Request

[0065] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0066] User: Enter the request information and click the submit button.

[0067] Terminal: Sends request information to the server as text data.

[0068] server:

[0069] Load the reference information.

[0070] The request information is received, and the analysis tool extracts "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[0071] The reference information is compared using a matching method and found to be a perfect match.

[0072] The evaluation method determined that it was "acceptable."

[0073] The system notifies the user that the request is "acceptable" via a notification method.

[0074] All processes are recorded using a logging system.

[0075] Case 2: Unacceptable Request

[0076] Request details: "Only a written note was found."

[0077] User: Enter the request information and click the submit button.

[0078] Terminal: Sends request information to the server as text data.

[0079] server:

[0080] Load the reference information.

[0081] Request information is received, and only "written notes" are extracted using an analysis tool.

[0082] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[0083] The evaluation method determined that it was "not acceptable."

[0084] The notification system will inform the user that the request "cannot be accepted".

[0085] All processes are recorded using a logging system.

[0086] In this way, the system of the present invention efficiently and accurately performs all processes of receiving request information, analyzing it, comparing it to a standard, determining whether it is accepted, and notifying the result.

[0087] The following describes the processing flow.

[0088] Step 1:

[0089] The user enters and submits the request information from their device.

[0090] User: Enter the request details into the input form on the screen and click the "Submit" button.

[0091] Step 2:

[0092] The terminal sends the request information to the server.

[0093] Terminal: Converts the entered request information into text data and sends it to the server.

[0094] Step 3:

[0095] The server receives the request information.

[0096] Server: Receives request information in text data format sent from the terminal.

[0097] Step 4:

[0098] The server reads the reference information.

[0099] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[0100] Step 5:

[0101] The server analyzes the request information and extracts keywords.

[0102] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[0103] Step 6:

[0104] The server compares the extracted keywords with the reference information.

[0105] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[0106] Step 7:

[0107] The server determines whether the request can be accepted.

[0108] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not.

[0109] Step 8:

[0110] The server notifies the user of the result of the determination.

[0111] Server: Sends the judgment result to the terminal.

[0112] Step 9:

[0113] The device displays the result to the user.

[0114] Terminal: Displays the received judgment results on the screen for the user to confirm.

[0115] Step 10:

[0116] The server saves logs for all processing steps.

[0117] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[0118] (Example 1)

[0119] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0120] Traditional systems for receiving investigation requests were inefficient in processing request information, making it difficult to respond quickly. Furthermore, the process of cross-referencing with standard information and extracting important keywords was often done manually, increasing the risk of human error. As a result, requests that should be accepted were sometimes not accurately identified, leading to decreased operational efficiency for investigative agencies.

[0121] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0122] In this invention, the server includes an input means for inputting request information, a transmission means for transmitting the request information to an information processing system, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, and a log storage means for saving logs for all processing steps of the means. This makes it possible to perform all processes from receiving request information to analysis, matching, determination, and notification efficiently and accurately.

[0123] "Requested information" refers to detailed information provided by investigative agencies regarding a specific case.

[0124] An "input method" is an interface that allows a user to input request information into the system.

[0125] "Transmission means" refers to a method or device for sending the input request information to the server.

[0126] "Receiving means" refers to a method or device for a server to receive request information transmitted from a terminal.

[0127] "Reference information reading means" refers to a method or device for reading pre-configured reference information from a configuration file or database.

[0128] "Analysis means" refers to a method or apparatus for analyzing received request information and extracting important keywords.

[0129] "Verification means" refers to a method or apparatus for verifying extracted keywords against reference information.

[0130] "Determination means" refers to a method or apparatus for determining the feasibility of accepting a request based on the results of the verification.

[0131] "Notification means" refers to a method or device for notifying the user of the judgment result.

[0132] "Log storage means" refers to a method or apparatus for recording and storing logs for all processing steps.

[0133] "Text conversion means" refers to a method or apparatus for converting request information into text data.

[0134] "Display means" refers to a method or device for displaying the judgment result to the user.

[0135] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. This system improves the efficiency and accuracy of operations by automating a series of processes from inputting request information to analysis, determination, and notification of results.

[0136] Overall system configuration

[0137] 1. User

[0138] The user is an officer of an investigative agency and uses a terminal to input the request information. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[0139] 2. Terminal

[0140] The terminal is a device used by users to input and submit request information. Specifically, it has the following functions:

[0141] Input method: A form or field is provided, allowing the user to enter the request information.

[0142] Transmission method: The entered request information is sent to the server as text data. For example, an HTTP POST request is used for this transmission.

[0143] 3. Server

[0144] The server is the central hub of the system and has multiple means of processing request information.

[0145] Reference information reading means

[0146] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation. Specifically, it uses an SQLite database or a JSON file.

[0147] Receiving means

[0148] The server receives request information sent from the terminal. For example, it can receive HTTP requests using a web framework such as Flask.

[0149] Analysis means

[0150] The received request information is analyzed using natural language processing techniques to extract important keywords and phrases. Specifically, text data is analyzed using Python's NLTK and SpaCy.

[0151] Verification means

[0152] The extracted keywords are compared with the reference information. Specifically, it is checked whether the extracted keywords are included in the reference information.

[0153] Judgment means

[0154] The likelihood of accepting the request is determined based on the matching results. If it perfectly matches the standard information, it is determined as "acceptable"; otherwise, it is determined as "unacceptable".

[0155] Notification means

[0156] The server notifies the user of the judgment result. Specifically, it returns an HTTP response and displays the judgment result on the terminal.

[0157] Log storage method

[0158] Logs are recorded and saved for all processing steps. Specifically, logs are saved to Elasticsearch® to manage the processing history.

[0159] Specific example

[0160] Case 1: Acceptable Request

[0161] 1. Request details: "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[0162] 2. User: Enter the request information and click the submit button.

[0163] 3. Terminal: Sends the request information to the server as text data.

[0164] 4. Server:

[0165] Load the reference information.

[0166] Request information received.

[0167] The analysis method extracted the terms "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[0168] The reference information is compared using a matching method and found to be a perfect match.

[0169] The evaluation method determined that it was "acceptable."

[0170] The system notifies the user that the request is "acceptable" via a notification method.

[0171] All processes are recorded using a logging system.

[0172] Case 2: Unacceptable Request

[0173] 1. Request details: "Only a written note was found."

[0174] 2. User: Enter the request information and click the submit button.

[0175] 3. Terminal: Sends the request information to the server as text data.

[0176] 4. Server:

[0177] Load the reference information.

[0178] Request information received.

[0179] The analysis method extracts only the "written notes."

[0180] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[0181] The evaluation method determined that it was "not acceptable."

[0182] The notification system will inform the user that the request "cannot be accepted".

[0183] All processes are recorded using a logging system.

[0184] Example of a prompt

[0185] "Please evaluate the following request information: 'A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected.'"

[0186] As a result, the system of the present invention can efficiently and accurately perform all processes of receiving request information, analyzing it, matching it to a standard, determining whether it is accepted, and notifying the result.

[0187] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0188] Step 1: User enters request information

[0189] Users enter details about the investigation into a dedicated input form. For example, "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[0190] Input: Details of the investigation

[0191] Output: Text data entered in the form

[0192] Step 2: Submitting the request information

[0193] When the user clicks the "Submit" button, the device sends the entered request information to the server in text data format. An HTTP POST request is used for submission.

[0194] Input: Text data entered in the form

[0195] Output: HTTP POST request data to the server

[0196] Step 3: Receiving the request information

[0197] The server receives an HTTP POST request sent from the terminal and extracts the text data of the request information. A web framework such as Flask is used here.

[0198] Input: HTTP POST request data

[0199] Output: Request information in text format

[0200] Step 4: Loading reference information

[0201] The server reads pre-configured reference information from a configuration file or database (e.g., SQLite or JSON file).

[0202] Input: File path or database query for reference information

[0203] Output: Reference information (keywords and phrases)

[0204] Step 5: Analysis of the request information

[0205] The server uses natural language processing libraries (such as NLTK or SpaCy) to analyze the received request information and extract important keywords and phrases.

[0206] Input: Request information in text format

[0207] Output: Extracted keywords and phrases (e.g., "note left," "under 13 years old," "kidnapping, abduction, and confinement")

[0208] Step 6: Verification against reference information

[0209] The server compares the keywords extracted by the analysis tool with reference information. The comparison then verifies whether the keywords match the reference information.

[0210] Input: Extracted keywords or phrases, reference information

[0211] Output: Matching result (match or mismatch)

[0212] Step 7: Determining the likelihood of acceptance

[0213] The server determines whether the request can be accepted based on the matching results. If it perfectly matches the reference information, it is determined to be "acceptable"; otherwise, it is determined to be "unacceptable".

[0214] Input: Matching result

[0215] Output: Judgment result (acceptable or unacceptable)

[0216] Step 8: Notification of the result

[0217] The server notifies the user of the judgment result. The judgment result is sent back to the terminal via an HTTP response, and the terminal displays the result to the user.

[0218] Input: Judgment Result

[0219] Output: Judgment result displayed to the user

[0220] Step 9: Save the log

[0221] The server logs and stores all processing steps. Specifically, it uses Elasticsearch to store the logs. The logs include all processes from receiving the request information to notifying the decision result.

[0222] Input: Data for each processing step

[0223] Output: Saved log data

[0224] (Application Example 1)

[0225] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0226] Traditional emergency reporting systems required users to manually evaluate the content of their reports and forward them to the appropriate law enforcement or security agency, which could lead to delays in response. Furthermore, incomplete reports could prevent appropriate action from being taken. As a result, there were problems with the rapid and accurate handling of emergencies.

[0227] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0228] In this invention, the server includes data reading means, natural language processing means, matching means, determination means, notification means, log management means, and user interface means. This makes it possible to quickly and accurately evaluate emergency notification information, automatically determine its acceptanceability, and promptly notify law enforcement agencies or security agencies.

[0229] "Request information" refers to information that users input and submit, requiring confirmation and evaluation.

[0230] A "device means" is a device used by a user to input request information.

[0231] "Communication means" refers to the methods or systems used to send request information to a server.

[0232] "Collection method" refers to the method or system used by the server to receive request information.

[0233] A "data loading method" refers to a method or system for reading pre-configured reference information from a database or configuration file.

[0234] "Natural language processing means" refers to computer processing methods for analyzing request information and extracting important keywords.

[0235] A "matching method" refers to a method or system for comparing extracted keywords with reference information to determine whether they match.

[0236] "Determination means" refers to a method or system for determining the feasibility of accepting the requested information based on the matching results.

[0237] "Notification means" refers to methods or systems for communicating the judgment results to the user.

[0238] A "log management system" refers to a method or system for saving and managing records of all processing steps.

[0239] A "user interface means" is an interface for a user to input and transmit emergency call information.

[0240] Modes for carrying out the invention

[0241] This invention relates to a system for efficiently and accurately evaluating request information and determining its feasibility of acceptance. Specific embodiments thereof are described below.

[0242] System Configuration

[0243] This system consists of the following main components:

[0244] 1. User's device (e.g., smartphone)

[0245] 2. Means of communication

[0246] 3. Server (data reading means, natural language processing means, matching means, determination means, notification means, and log management means)

[0247] 4. User Interface Means

[0248] Hardware and software

[0249] User device means:

[0250] The user uses a smartphone. This smartphone has an emergency call application installed. Using the application, the user enters and sends emergency call information.

[0251] Means of communication:

[0252] The communication method utilizes an internet connection. Emergency call information entered on a smartphone is transmitted to a server via the internet.

[0253] server:

[0254] The server performs the following roles:

[0255] Data loading method: Reads pre-configured reference information from a database or configuration file.

[0256] Natural language processing tools: Analyze the request information and extract important keywords. For natural language processing, libraries such as Spacy and NLTK are used.

[0257] Matching method: The extracted keywords are compared with reference information.

[0258] Determination method: The possibility of accepting the request information is determined based on the matching result.

[0259] Notification method: The user is notified of the judgment result.

[0260] Log management method: Logs of all processing steps are recorded and saved.

[0261] Specific examples and prompt statements

[0262] Specific example:

[0263] Let's consider a scenario where a user reports that "a suspicious person is loitering in the neighborhood."

[0264] 1. The user opens the emergency call application on their smartphone.

[0265] 2. Enter "A suspicious person has been loitering in the neighborhood. They have been standing in front of my house for a while" into the text field and press the send button.

[0266] 3. The application sends the entered text to the server.

[0267] 4. On the server side, natural language processing tools analyze the text and extract keywords such as "suspicious" and "wandering around."

[0268] 5. Compare the information with the standard criteria and determine if it is acceptable.

[0269] 6. The determination result will be sent back to the user via notification means, and the appropriate investigative agency will be notified as necessary.

[0270] Example of a prompt:

[0271] "There's a suspicious person loitering around the neighborhood. They've been standing in front of my house for a while."

[0272] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0273] Step 1:

[0274] The user opens the emergency call application on their smartphone, enters a prompt message describing the situation specifically, such as "A suspicious person is loitering in the neighborhood. They have been standing in front of my house for a while," and presses the send button. This input is received by the device's input method.

[0275] Step 2:

[0276] The terminal's communication method transmits the entered request information to the server via the internet.

[0277] Step 3:

[0278] The server's data collection mechanism receives the request information sent from the terminal. At this time, the request information is treated as text data.

[0279] Step 4:

[0280] The data reading means of the server reads the pre-set reference information (data including important keywords and phrases) from the database.

[0281] Step 5:

[0282] The natural language processing means of the server analyzes the received request information and extracts important keywords. Specifically, a natural language processing library using a generative AI model (such as Spacy or NLTK) is used to extract keywords such as "suspicious" and "loitering" from the text. The input is the text data of the request information, and the output is the list of extracted keywords.

[0283] Step 6:

[0284] The matching means of the server matches the extracted keywords with the reference information. The list of extracted keywords is compared with the reference information to check if there are matching keywords. The input is the list of extracted keywords and the reference information, and the output is the matching result.

[0285] Step 7:

[0286] The determination means of the server determines the acceptability of the request information based on the matching result. For example, if there are many matching keywords, it is determined as "acceptable", and if there are few or no matching keywords, it is determined as "unacceptable". The input is the matching result, and the output is the determination result of the acceptability.

[0287] Step 8:

[0288] The notification means of the server notifies the user of the determination result. Specifically, the determination result is returned to the terminal and displayed on the user's smartphone. The input is the determination result, and the output is the notification to the user terminal.

[0289] Step 9:

[0290] The server's log management system saves logs for all processing steps. Specifically, it records information for each step of request information reception, analysis, matching, determination, and notification, and stores it in a database. The input is data from each processing step, and the output is a log file.

[0291] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0292] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method based on those emotions.

[0293] 1. User (Representative of the investigative agency)

[0294] The user is an officer of an investigative agency and uses a terminal to input request information. The input form contains detailed information related to the investigation case, and the information is sent to the system by clicking the "Submit" button. In addition, an emotion engine analyzes the user's facial expressions and voice in real time while they are typing.

[0295] 2. Terminal

[0296] The device has the following functions:

[0297] Input methods: Provide forms and fields for the user to enter request information. Also, capture the user's facial expressions and voice through a camera and microphone for the emotion engine.

[0298] Transmission method: The input information and acquired emotion data are sent to the server.

[0299] 3. Server

[0300] The server is the center of the system and has the following functions.

[0301] Reference information reading means

[0302] The server reads the pre-set reference information from a configuration file or a database and stores it as an internal data structure.

[0303] Receiving means

[0304] The server receives the request information and emotion data sent from the terminal.

[0305] Analysis means

[0306] The received request information is analyzed by a text analysis algorithm to extract important keywords and phrases. At the same time, the emotion data is analyzed using an emotion engine to grasp the user's emotional state.

[0307] Matching means

[0308] The extracted keywords are matched with the reference information to confirm whether there is a match or not.

[0309] Judgment means

[0310] Based on the result of the match, the acceptance possibility of the request is judged. Specifically, if it completely matches the reference information, it is judged as "acceptable", and if it does not match, it is judged as "unacceptable". Also, the emotion data is considered to assist in the judgment of the result.

[0311] Notification means

[0312] The judgment result is notified to the user. The content and method of the notification are adjusted based on the emotion data. For example, if the user is judged to be tired, a simple and clear notification is made.

[0313] Log storage means

[0314] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[0315] Specific example

[0316] Case 1: Acceptable Request

[0317] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0318] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[0319] Terminal: Sends request information and sentiment data to the server as text data.

[0320] server:

[0321] Load the reference information.

[0322] The request information is received, and analysis is used to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, emotional data is analyzed.

[0323] The reference information is compared using a matching method and found to be a perfect match.

[0324] The system determines that the message is "acceptable" based on the evaluation criteria, and then adjusts the notification content considering the emotional data.

[0325] The system notifies the user that the request is "acceptable" via a notification method.

[0326] All processes are recorded using a logging system.

[0327] Case 2: Unacceptable Request

[0328] Request details: "Only a written note was found."

[0329] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[0330] Terminal: Sends request information and sentiment data to the server as text data.

[0331] server:

[0332] Load the reference information.

[0333] The request information is received, and only the "written note" is extracted using an analysis tool. At the same time, emotional data is analyzed.

[0334] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[0335] The system determines that the application is "unacceptable" and adjusts the notification content based on emotional data.

[0336] The notification system will inform the user that the request "cannot be accepted".

[0337] All processes are recorded using a logging system.

[0338] In this way, the system of the present invention efficiently and accurately performs the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[0339] The following describes the processing flow.

[0340] Step 1:

[0341] The user enters and submits the request information from their device.

[0342] User: Enter the request details into the input form on the screen and click the "Submit" button. The device's camera and microphone also collect the user's facial expressions and voice in real time.

[0343] Step 2:

[0344] The device sends request information and emotion data to the server.

[0345] Terminal: Converts the entered request information into text data and sends it to the server along with sentiment data.

[0346] Step 3:

[0347] The server receives the request information and sentiment data.

[0348] Server: Receives request information and sentiment data in text format sent from the terminal.

[0349] Step 4:

[0350] The server reads the reference information.

[0351] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[0352] Step 5:

[0353] The server analyzes the request information and extracts keywords.

[0354] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[0355] Step 6:

[0356] The server analyzes the emotional data.

[0357] Server: Uses an emotion engine to analyze received emotion data and recognize the user's emotional state (e.g., tension, joy, fatigue).

[0358] Step 7:

[0359] The server compares the extracted keywords with the reference information.

[0360] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[0361] Step 8:

[0362] The server determines whether the request can be accepted.

[0363] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not. It also considers emotional data to set up feedback appropriate to the user's emotional state.

[0364] Step 9:

[0365] The server notifies the user of the result of the determination.

[0366] Server: Sends the judgment result to the terminal and creates a notification with content and tone that matches the user's emotional state.

[0367] Step 10:

[0368] The device displays the result to the user.

[0369] Terminal: Displays the received judgment results on the screen and notifies the user in a format that can be reviewed. Displays messages based on sentiment feedback.

[0370] Step 11:

[0371] The server saves logs for all processing steps.

[0372] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[0373] (Example 2)

[0374] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0375] Conventional request information systems have faced challenges in accurately evaluating and quickly determining the input information, and furthermore, they cannot respond in a way that takes into account the user's emotional state, resulting in a poor user experience. In particular, law enforcement agencies are required to accurately grasp the content and urgency of request information and respond quickly and appropriately, but conventional systems have not been able to adequately achieve this.

[0376] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a receiving means for receiving request information, an analysis means for analyzing the request information and extracting important keywords, and an emotion analysis means for analyzing the user's emotion data. This enables accurate evaluation and rapid determination of the request information, as well as adjustment of an appropriate notification method based on the user's emotional state.

[0377] "Request information" refers to detailed information related to the investigation case entered by the user.

[0378] "Input means" refers to a device or mechanism for a user to input request information into the system.

[0379] "Transmission means" refers to a device or mechanism that transmits the input request information to the server.

[0380] "Receiving means" refers to the device or mechanism by which a server receives request information transmitted from a terminal.

[0381] "Reference information" refers to pre-configured information used to evaluate the requested information.

[0382] "Reference information reading means" refers to a device or mechanism for the server to read reference information.

[0383] "Analysis means" refers to a device or mechanism that analyzes the received request information and extracts important keywords.

[0384] "Verification means" refers to a device or mechanism that verifies extracted keywords against reference information.

[0385] "Determination means" refers to a device or mechanism that determines the likelihood of accepting a request based on the results of the verification.

[0386] "Notification means" refers to a device or mechanism that notifies the user of the judgment result.

[0387] "Emotional analysis means" refers to a device or system that analyzes a user's emotional data.

[0388] "Notification method adjustment means" refers to a device or mechanism that adjusts the notification method based on emotional data.

[0389] "Log storage means" refers to a device or mechanism that stores logs for all processing steps.

[0390] "Text conversion means" refers to a device or mechanism that converts request information into text data.

[0391] "Display means" refers to a device or mechanism that displays the judgment result to the user.

[0392] This invention relates to a system that quickly and accurately determines the likelihood of accepting a request through evaluation of the request information and consideration of the user's emotional state. The following describes how this system can be specifically implemented.

[0393] First, this system consists of a terminal, a server, and a user. The terminal includes a form for entering request information, a camera, and a microphone, which the user uses to input and submit the request information. The camera and microphone are responsible for capturing the user's facial expressions and voice as emotional data in real time. Specifically, commercially available webcams and microphones can be used as hardware.

[0394] Next, the terminal sends this request information and emotion data to the server. The server is equipped with modules that have the following various functions:

[0395] 1. Receiving method: Receives request information and sentiment data transmitted from the terminal.

[0396] 2. Means for reading reference information: Reads pre-configured reference information from a database or configuration file.

[0397] 3. Analysis Methods: The received request information is analyzed using text analysis, for example, the Google® Cloud Natural Language API, to extract important keywords and phrases. Simultaneously, emotional data is analyzed using the Microsoft® Azure® Emotion API, etc., to understand the user's emotional state.

[0398] 4. Matching method: The extracted keywords are compared with reference information to determine whether they match or not.

[0399] 5. Determination method: The likelihood of accepting the request is determined based on the matching results, and sentiment data is considered as necessary.

[0400] 6. Notification Method: Notify the user of the judgment result. Adjust the notification method and content based on sentiment data.

[0401] 7. Log storage method: Logs for all processing steps will be saved.

[0402] For example, if a user enters a request such as, "A child under 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected," the terminal sends this information along with the user's emotional data to the server. The server receives this and performs the necessary analysis and matching. If the request information perfectly matches the reference information, it is determined to be "acceptable." In this case, if the system determines that the user is tired, the notification is simplified to "The request is acceptable." In this way, the system can efficiently evaluate the request information and adjust the notification method based on the user's emotional state.

[0403] Examples of prompt messages are as follows:

[0404] "What data is required for this system's processing, what algorithms are used, and what role does each step play?"

[0405] In this way, this invention provides a system that can efficiently and accurately evaluate request information and determine its feasibility, while taking into account the user's feelings.

[0406] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0407] Step 1:

[0408] This is the step where the user enters and submits the request information. The user uses a web form on their device to enter detailed information related to the investigation case. For example, they might write, "A child under the age of 13 may have disappeared, leaving a note behind." The user then clicks the "Submit" button. The input at this point is the request information text, which will be the output for the next step.

[0409] Step 2:

[0410] This step involves the terminal collecting request information and emotion data and sending it to the server. The terminal receives the request information entered by the user as text data. Simultaneously, it uses the camera and microphone to capture the user's facial expressions and voice in real time and collect emotion data. For example, if the user has a worried expression, that facial expression data is also collected. This data (request information and emotion data) is sent to the server using an HTTP POST request. The input at this point is the request information text and emotion data, which will be the output for the next step.

[0411] Step 3:

[0412] This step involves the server reading baseline information and analyzing the received request information and sentiment data. First, the server reads pre-configured baseline information from a database or configuration file. This baseline information includes important keywords such as "under 13 years old," "note left behind," and "kidnapping, abduction, and confinement." Next, the server receives the request information and sentiment data sent from the terminal. It analyzes the received request information using a text analysis algorithm (e.g., Google Cloud Natural Language API) and extracts important keywords and phrases, such as "disappearance," "note left behind," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, it analyzes the sentiment data using a sentiment engine (e.g., Microsoft Azure Emotion API) to understand the user's emotional state. These analysis results are then output for the next step.

[0413] Step 4:

[0414] This step involves the server comparing the extracted keywords with reference information to determine the suitability of the request information. The server compares the keywords extracted by the analysis tool with the reference information. Specifically, the matching tool performs a match check and evaluates how many matching keywords or phrases exist. For example, if keywords such as "under 13 years old," "written note," and "kidnapping, abduction, and confinement" match, the server will determine that the request is "acceptable." At this point, the input consists of the analysis results and reference information, which will be the output for the next step.

[0415] Step 5:

[0416] This step involves the server notifying the user of the judgment result and saving a log of all processing steps. Based on the matching result, the server determines whether the request is "acceptable" or "unacceptable" and decides on the notification content considering sentiment data. If the server determines that the user is tired, the notification content will be summarized concisely. For example, it might notify the user, "Your request is acceptable." The server also saves data related to all processing steps as a log file. This includes all data from the input of the request information to the final judgment. This ensures traceability of the entire system. The input at this point is the judgment result and sentiment data, which become the final output.

[0417] (Application Example 2)

[0418] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0419] The problem that this invention aims to solve is to improve the user experience by efficiently and accurately evaluating the feasibility of accepting request information provided by investigative agencies, and by adjusting the notification method of the results while taking into account the user's emotional state. Furthermore, by linking with smart devices, it also aims to improve on-site operability and enable a rapid response.

[0420] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting request information, a transmission means for sending the request information to the server, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, a log storage means for saving logs for all processing steps of the means, an emotion data acquisition means for acquiring the user's emotion data, an emotion analysis means for analyzing the acquired emotion data, a notification method adjustment means for adjusting the notification method of the determination result based on the emotion data, and an interface means for coordinating with the interface of a smart device. This makes it possible to efficiently and accurately evaluate the possibility of accepting request information and to provide a notification method that takes into account the user's emotional state.

[0421] "Request information" refers to detailed information related to an investigation case, entered by an officer in charge at an investigative agency.

[0422] "Input method" refers to a function that provides forms or fields for entering request information.

[0423] "Transmission method" refers to the function that sends the entered request information to the server.

[0424] "Receiving means" refers to the function of a server to receive the request information that has been sent.

[0425] A "reference information loading mechanism" is a function that reads pre-configured reference information from a database or configuration file and stores it as an internal data structure.

[0426] The "analysis means" refers to a function that analyzes the received request information and extracts important keywords and phrases.

[0427] The "matching means" is a function that compares extracted keywords with reference information to confirm whether they match or not.

[0428] The "determination means" is a function that determines the likelihood of accepting a request based on the results of the verification.

[0429] "Notification method" refers to a function that notifies the user of the judgment result.

[0430] A "log storage method" is a function that records and saves logs for all processing steps.

[0431] "Method for acquiring emotional data" refers to a function that acquires emotional data from the user's facial expressions, voice, etc.

[0432] "Emotional analysis means" refers to a function that analyzes acquired emotional data to understand the user's emotional state.

[0433] The "notification method adjustment mechanism" is a function that adjusts the notification method and content of the judgment results based on emotion data.

[0434] "Interface means" refers to functions that work in conjunction with smart devices to support operability and information display.

[0435] "Smart devices" is a general term for devices used as interfaces, such as eyeglasses, personal digital assistants (PDAs), and wearable devices.

[0436] This invention is a system in which an investigator inputs request information, and then efficiently and accurately evaluates that information to determine its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method accordingly. This system is used in conjunction with smart glasses.

[0437] 1. User (Representative of the investigative agency)

[0438] The user wears smart glasses and uses the interface to input request information. The input form contains detailed information related to the investigation case, and the user clicks the submit button. Furthermore, the smart glasses' built-in camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[0439] 2. Device (smart glasses)

[0440] The device has the following functions:

[0441] Input methods: Provide forms and fields for users to input request information. Also, capture user facial expressions and voice via camera and microphone.

[0442] Transmission method: The entered request information and acquired emotion data are sent to the server.

[0443] Interface means: Assists user operation and displays information in conjunction with smart devices.

[0444] 3. Server

[0445] The server is the central hub of the system and has the following functions:

[0446] Reference information reading method: The server reads pre-configured reference information from the database and stores it internally.

[0447] Receiving method: The server receives request information and sentiment data sent from the terminal.

[0448] Analysis method: The received request information is analyzed and important keywords are extracted. Simultaneously, sentiment data is analyzed to understand the user's emotional state. For example, "Amazon Rekognition" is used.

[0449] Matching method: The extracted keywords are compared with reference information to confirm whether they match or not.

[0450] Determination method: The likelihood of accepting the request is determined based on the matching results. Specifically, if it matches the reference information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable." Sentiment data is also considered to assist in determining the result.

[0451] Notification method: The user is notified of the assessment result. The content and method of notification are adjusted based on sentiment data. For example, if it is determined that the user is feeling tired, a concise and clear notification is sent.

[0452] Log storage method: Logs are recorded and stored for all processing steps. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[0453] Specific operations and examples

[0454] Case 1: Acceptable Request

[0455] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0456] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[0457] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." A matching tool compares the information with the standard information to confirm a match. A judgment tool determines that the request is "acceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that the request is "acceptable." All processes are logged.

[0458] Case 2: Unacceptable Request

[0459] Request details: "Only a written note was found."

[0460] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[0461] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract only the "written message." A matching tool compares it with the reference information and determines that there is a mismatch. A judgment tool determines that it is "unacceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that it is "unacceptable." All processes are logged.

[0462] Example input prompts for a generative AI model

[0463] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[0464] In this way, the system of the present invention enables the efficient and accurate execution of the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[0465] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0466] Step 1:

[0467] The user enters request information through the smart glasses interface. The user enters detailed information related to the investigation case and clicks the submit button. The user's facial expressions and voice are captured in real time through the smart glasses' camera and microphone. Request information (text data) and facial / voice data are obtained as input data. This data is treated as input.

[0468] Step 2:

[0469] The terminal sends the acquired request information and emotion data together to the cloud server. The request information (text data) and emotion data (facial expression / voice data) are transmitted using the transmission method. The output at this time is the transmitted request information and emotion data.

[0470] Step 3:

[0471] The server receives the request information and sentiment data. Using the receiving means, it receives the request information and sentiment data sent from the terminal. The output of this step is the received request information and sentiment data.

[0472] Step 4:

[0473] The server's criteria information reading mechanism reads pre-configured criteria information from the database. This criteria information includes keywords and phrases for evaluating investigation cases. The criteria information is retrieved from the database and stored as an internal data structure. The output of this step is the read criteria information.

[0474] Step 5:

[0475] The server's analysis tool analyzes the received request information and extracts important keywords and phrases using a text analysis algorithm. It receives request information (text data) as input and performs keyword extraction. The output is a list of extracted keywords. Simultaneously, it analyzes emotional data using an emotion engine to understand the user's emotional state. It receives emotional data (facial expressions and voice data) as input and obtains the results of the emotional state analysis.

[0476] Step 6:

[0477] The server's matching mechanism compares the extracted keywords with the reference information. Using the matching mechanism, the extracted keyword list is compared with the reference information to determine whether they match or not. The output of this process is the keyword matching result.

[0478] Step 7:

[0479] The server's decision-making mechanism determines the likelihood of accepting the request based on the matching results. It uses the matching results and the analysis results of sentiment data as input to determine whether the request is acceptable or not. If it is acceptable, it displays "Acceptable"; otherwise, it displays "Not Acceptable." The output is the acceptance decision result.

[0480] Step 8:

[0481] The server's notification system informs the user of the acceptance judgment result. The content and method of the notification are adjusted based on the results of the emotional data analysis. For example, a concise notification is sent if the user is tired, while a detailed notification is sent if the user is calm. The acceptance judgment result and the emotional data analysis results are used as input to generate appropriate notification content and method, and then notify the user. The output is a notification message to the user.

[0482] Step 9:

[0483] The server's logging mechanism records and saves logs for all processing steps. It saves data and processes for each step, such as receiving, analyzing, matching, judging, and notifying, as logs. The input is the data and process information for each step, and the output is the saved log data.

[0484] Specific example

[0485] Case 1: Acceptable Request

[0486] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0487] Input: Request information (text data), emotion data (facial expressions, voice data)

[0488] Output: Acceptance determination, notification message to the user

[0489] Case 2: Unacceptable Request

[0490] Request details: "Only a written note was found."

[0491] Input: Request information (text data), emotion data (facial expressions, voice data)

[0492] Output: Rejection of submission, notification message to the user.

[0493] Example input prompts for a generative AI model

[0494] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[0495] Through the processing steps described above, the system of the present invention can efficiently evaluate, judge, and notify request information, thereby improving the user experience.

[0496] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0497] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0498] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0499] [Second Embodiment]

[0500] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0501] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0502] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0503] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0504] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0505] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0506] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0507] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0508] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0509] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0510] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0511] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0512] This invention relates to a system for efficiently and accurately evaluating request information provided by investigative agencies and determining its feasibility. This system consists of the following components:

[0513] 1. User (Representative of the investigative agency)

[0514] The user is an officer of an investigative agency and uses a terminal to input request information. This information includes details about a specific investigation case. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[0515] 2. Terminal

[0516] The terminal provides a user interface and is a device for inputting and sending request information. Specifically, it has the following functions:

[0517] Input method: Provides forms or fields for users to enter request information.

[0518] Transmission method: The entered request information is sent to the server as text data.

[0519] 3. Server

[0520] The server is the central hub of the system and processes request information using multiple methods. Specifically, it uses the following methods:

[0521] Reference information reading means

[0522] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation.

[0523] Receiving means

[0524] The server receives request information sent from the terminal. This receiving mechanism has the functionality to receive request information in text data format.

[0525] Analysis means

[0526] The received request information is analyzed using a text analysis algorithm to extract important keywords and phrases. This analysis is performed using natural language processing technology.

[0527] Verification means

[0528] The extracted keywords are compared with the reference information. During this process, it is checked whether the keywords match the reference information, and the results are recorded.

[0529] Judgment means

[0530] The likelihood of accepting the request is determined based on the matching results. Specifically, if it perfectly matches the standard information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable."

[0531] Notification means

[0532] The user is notified of the judgment result. This notification sends the result back to the device so that the user can check the result.

[0533] Log storage method

[0534] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[0535] Specific example

[0536] Case 1: Acceptable Request

[0537] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0538] User: Enter the request information and click the submit button.

[0539] Terminal: Sends request information to the server as text data.

[0540] server:

[0541] Load the reference information.

[0542] The request information is received, and the analysis tool extracts "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[0543] The reference information is compared using a matching method and found to be a perfect match.

[0544] The evaluation method determined that it was "acceptable."

[0545] The system notifies the user that the request is "acceptable" via a notification method.

[0546] All processes are recorded using a logging system.

[0547] Case 2: Unacceptable Request

[0548] Request details: "Only a written note was found."

[0549] User: Enter the request information and click the submit button.

[0550] Terminal: Sends request information to the server as text data.

[0551] server:

[0552] Load the reference information.

[0553] Request information is received, and only "written notes" are extracted using an analysis tool.

[0554] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[0555] The evaluation method determined that it was "not acceptable."

[0556] The notification system will inform the user that the request "cannot be accepted".

[0557] All processes are recorded using a logging system.

[0558] In this way, the system of the present invention efficiently and accurately performs all processes of receiving request information, analyzing it, comparing it to a standard, determining whether it is accepted, and notifying the result.

[0559] The following describes the processing flow.

[0560] Step 1:

[0561] The user enters and submits the request information from their device.

[0562] User: Enter the request details into the input form on the screen and click the "Submit" button.

[0563] Step 2:

[0564] The terminal sends the request information to the server.

[0565] Terminal: Converts the entered request information into text data and sends it to the server.

[0566] Step 3:

[0567] The server receives the request information.

[0568] Server: Receives request information in text data format sent from the terminal.

[0569] Step 4:

[0570] The server reads the reference information.

[0571] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[0572] Step 5:

[0573] The server analyzes the request information and extracts keywords.

[0574] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[0575] Step 6:

[0576] The server compares the extracted keywords with the reference information.

[0577] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[0578] Step 7:

[0579] The server determines whether the request can be accepted.

[0580] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not.

[0581] Step 8:

[0582] The server notifies the user of the result of the determination.

[0583] Server: Sends the judgment result to the terminal.

[0584] Step 9:

[0585] The device displays the result to the user.

[0586] Terminal: Displays the received judgment results on the screen for the user to confirm.

[0587] Step 10:

[0588] The server saves logs for all processing steps.

[0589] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[0590] (Example 1)

[0591] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0592] Traditional systems for receiving investigation requests were inefficient in processing request information, making it difficult to respond quickly. Furthermore, the process of cross-referencing with standard information and extracting important keywords was often done manually, increasing the risk of human error. As a result, requests that should be accepted were sometimes not accurately identified, leading to decreased operational efficiency for investigative agencies.

[0593] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0594] In this invention, the server includes an input means for inputting request information, a transmission means for transmitting the request information to an information processing system, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, and a log storage means for saving logs for all processing steps of the means. This makes it possible to perform all processes from receiving request information to analysis, matching, determination, and notification efficiently and accurately.

[0595] "Requested information" refers to detailed information provided by investigative agencies regarding a specific case.

[0596] An "input method" is an interface that allows a user to input request information into the system.

[0597] "Transmission means" refers to a method or device for sending the input request information to the server.

[0598] "Receiving means" refers to a method or device for a server to receive request information transmitted from a terminal.

[0599] "Reference information reading means" refers to a method or device for reading pre-configured reference information from a configuration file or database.

[0600] "Analysis means" refers to a method or apparatus for analyzing received request information and extracting important keywords.

[0601] "Verification means" refers to a method or apparatus for verifying extracted keywords against reference information.

[0602] "Determination means" refers to a method or apparatus for determining the feasibility of accepting a request based on the results of the verification.

[0603] "Notification means" refers to a method or device for notifying the user of the judgment result.

[0604] "Log storage means" refers to a method or apparatus for recording and storing logs for all processing steps.

[0605] "Text conversion means" refers to a method or apparatus for converting request information into text data.

[0606] "Display means" refers to a method or device for displaying the judgment result to the user.

[0607] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. This system improves the efficiency and accuracy of operations by automating a series of processes from inputting request information to analysis, determination, and notification of results.

[0608] Overall system configuration

[0609] 1. User

[0610] The user is an officer of an investigative agency and uses a terminal to input the request information. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[0611] 2. Terminal

[0612] The terminal is a device used by users to input and submit request information. Specifically, it has the following functions:

[0613] Input method: A form or field is provided, allowing the user to enter the request information.

[0614] Transmission method: The entered request information is sent to the server as text data. For example, an HTTP POST request is used for this transmission.

[0615] 3. Server

[0616] The server is the central hub of the system and has multiple means of processing request information.

[0617] Reference information reading means

[0618] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation. Specifically, it uses an SQLite database or a JSON file.

[0619] Receiving means

[0620] The server receives request information sent from the terminal. For example, it can receive HTTP requests using a web framework such as Flask.

[0621] Analysis means

[0622] The received request information is analyzed using natural language processing techniques to extract important keywords and phrases. Specifically, text data is analyzed using Python's NLTK and SpaCy.

[0623] Verification means

[0624] The extracted keywords are compared with the reference information. Specifically, it is checked whether the extracted keywords are included in the reference information.

[0625] Judgment means

[0626] The likelihood of accepting the request is determined based on the matching results. If it perfectly matches the standard information, it is determined as "acceptable"; otherwise, it is determined as "unacceptable".

[0627] Notification means

[0628] The server notifies the user of the judgment result. Specifically, it returns an HTTP response and displays the judgment result on the terminal.

[0629] Log storage method

[0630] Logs are recorded and saved for all processing steps. Specifically, logs are saved to Elasticsearch to manage the processing history.

[0631] Specific example

[0632] Case 1: Acceptable Request

[0633] 1. Request details: "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[0634] 2. User: Enter the request information and click the submit button.

[0635] 3. Terminal: Sends the request information to the server as text data.

[0636] 4. Server:

[0637] Load the reference information.

[0638] Request information received.

[0639] The analysis method extracted the terms "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[0640] The reference information is compared using a matching method and found to be a perfect match.

[0641] The evaluation method determined that it was "acceptable."

[0642] The system notifies the user that the request is "acceptable" via a notification method.

[0643] All processes are recorded using a logging system.

[0644] Case 2: Unacceptable Request

[0645] 1. Request details: "Only a written note was found."

[0646] 2. User: Enter the request information and click the submit button.

[0647] 3. Terminal: Sends the request information to the server as text data.

[0648] 4. Server:

[0649] Load the reference information.

[0650] Request information received.

[0651] The analysis method extracts only the "written notes."

[0652] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[0653] The evaluation method determined that it was "not acceptable."

[0654] The notification system will inform the user that the request "cannot be accepted".

[0655] All processes are recorded using a logging system.

[0656] Example of a prompt

[0657] "Please evaluate the following request information: 'A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected.'"

[0658] As a result, the system of the present invention can efficiently and accurately perform all processes of receiving request information, analyzing it, matching it to a standard, determining whether it is accepted, and notifying the result.

[0659] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0660] Step 1: User enters request information

[0661] Users enter details about the investigation into a dedicated input form. For example, "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[0662] Input: Details of the investigation

[0663] Output: Text data entered in the form

[0664] Step 2: Submitting the request information

[0665] When the user clicks the "Submit" button, the device sends the entered request information to the server in text data format. An HTTP POST request is used for submission.

[0666] Input: Text data entered in the form

[0667] Output: HTTP POST request data to the server

[0668] Step 3: Receiving the request information

[0669] The server receives an HTTP POST request sent from the terminal and extracts the text data of the request information. A web framework such as Flask is used here.

[0670] Input: HTTP POST request data

[0671] Output: Request information in text format

[0672] Step 4: Loading reference information

[0673] The server reads pre-configured reference information from a configuration file or database (e.g., SQLite or JSON file).

[0674] Input: File path or database query for reference information

[0675] Output: Reference information (keywords and phrases)

[0676] Step 5: Analysis of the request information

[0677] The server uses natural language processing libraries (such as NLTK or SpaCy) to analyze the received request information and extract important keywords and phrases.

[0678] Input: Request information in text format

[0679] Output: Extracted keywords and phrases (e.g., "note left," "under 13 years old," "kidnapping, abduction, and confinement")

[0680] Step 6: Verification against reference information

[0681] The server compares the keywords extracted by the analysis tool with reference information. The comparison then verifies whether the keywords match the reference information.

[0682] Input: Extracted keywords or phrases, reference information

[0683] Output: Matching result (match or mismatch)

[0684] Step 7: Determining the likelihood of acceptance

[0685] The server determines whether the request can be accepted based on the matching results. If it perfectly matches the reference information, it is determined to be "acceptable"; otherwise, it is determined to be "unacceptable".

[0686] Input: Matching result

[0687] Output: Judgment result (acceptable or unacceptable)

[0688] Step 8: Notification of the result

[0689] The server notifies the user of the judgment result. The judgment result is sent back to the terminal via an HTTP response, and the terminal displays the result to the user.

[0690] Input: Judgment Result

[0691] Output: Judgment result displayed to the user

[0692] Step 9: Save the log

[0693] The server logs and stores all processing steps. Specifically, it uses Elasticsearch to store the logs. The logs include all processes from receiving the request information to notifying the decision result.

[0694] Input: Data for each processing step

[0695] Output: Saved log data

[0696] (Application Example 1)

[0697] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0698] Traditional emergency reporting systems required users to manually evaluate the content of their reports and forward them to the appropriate law enforcement or security agency, which could lead to delays in response. Furthermore, incomplete reports could prevent appropriate action from being taken. As a result, there were problems with the rapid and accurate handling of emergencies.

[0699] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0700] In this invention, the server includes data reading means, natural language processing means, matching means, determination means, notification means, log management means, and user interface means. This makes it possible to quickly and accurately evaluate emergency notification information, automatically determine its acceptanceability, and promptly notify law enforcement agencies or security agencies.

[0701] "Request information" refers to information that users input and submit, requiring confirmation and evaluation.

[0702] A "device means" is a device used by a user to input request information.

[0703] "Communication means" refers to the methods or systems used to send request information to a server.

[0704] "Collection method" refers to the method or system used by the server to receive request information.

[0705] A "data loading method" refers to a method or system for reading pre-configured reference information from a database or configuration file.

[0706] "Natural language processing means" refers to computer processing methods for analyzing request information and extracting important keywords.

[0707] A "matching method" refers to a method or system for comparing extracted keywords with reference information to determine whether they match.

[0708] "Determination means" refers to a method or system for determining the feasibility of accepting the requested information based on the matching results.

[0709] "Notification means" refers to methods or systems for communicating the judgment results to the user.

[0710] A "log management system" refers to a method or system for saving and managing records of all processing steps.

[0711] A "user interface means" is an interface for a user to input and transmit emergency call information.

[0712] Modes for carrying out the invention

[0713] This invention relates to a system for efficiently and accurately evaluating request information and determining its feasibility of acceptance. Specific embodiments thereof are described below.

[0714] System Configuration

[0715] This system consists of the following main components:

[0716] 1. User's device (e.g., smartphone)

[0717] 2. Means of communication

[0718] 3. Server (data reading means, natural language processing means, matching means, determination means, notification means, and log management means)

[0719] 4. User Interface Means

[0720] Hardware and software

[0721] User device means:

[0722] The user uses a smartphone. This smartphone has an emergency call application installed. Using the application, the user enters and sends emergency call information.

[0723] Means of communication:

[0724] The communication method utilizes an internet connection. Emergency call information entered on a smartphone is transmitted to a server via the internet.

[0725] server:

[0726] The server performs the following roles:

[0727] Data loading method: Reads pre-configured reference information from a database or configuration file.

[0728] Natural language processing tools: Analyze the request information and extract important keywords. For natural language processing, libraries such as Spacy and NLTK are used.

[0729] Matching method: The extracted keywords are compared with reference information.

[0730] Determination method: The possibility of accepting the request information is determined based on the matching result.

[0731] Notification method: The user is notified of the judgment result.

[0732] Log management method: Logs of all processing steps are recorded and saved.

[0733] Specific examples and prompt statements

[0734] Specific example:

[0735] Let's consider a scenario where a user reports that "a suspicious person is loitering in the neighborhood."

[0736] 1. The user opens the emergency call application on their smartphone.

[0737] 2. Enter "A suspicious person has been loitering in the neighborhood. They have been standing in front of my house for a while" into the text field and press the send button.

[0738] 3. The application sends the entered text to the server.

[0739] 4. On the server side, natural language processing tools analyze the text and extract keywords such as "suspicious" and "wandering around."

[0740] 5. Compare the information with the standard criteria and determine if it is acceptable.

[0741] 6. The determination result will be sent back to the user via notification means, and the appropriate investigative agency will be notified as necessary.

[0742] Example of a prompt:

[0743] "There's a suspicious person loitering around the neighborhood. They've been standing in front of my house for a while."

[0744] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0745] Step 1:

[0746] The user opens the emergency call application on their smartphone, enters a prompt message describing the situation specifically, such as "A suspicious person is loitering in the neighborhood. They have been standing in front of my house for a while," and presses the send button. This input is received by the device's input method.

[0747] Step 2:

[0748] The terminal's communication method transmits the entered request information to the server via the internet.

[0749] Step 3:

[0750] The server's data collection mechanism receives the request information sent from the terminal. At this time, the request information is treated as text data.

[0751] Step 4:

[0752] The server's data reading mechanism reads pre-configured reference information (data containing important keywords and phrases) from the database.

[0753] Step 5:

[0754] The server's natural language processing system analyzes the received request information and extracts important keywords. Specifically, it uses a natural language processing library with a generative AI model (e.g., Spacy or NLTK) to extract keywords such as "suspicious" and "wandering" from the text. The input is the text data of the request information, and the output is a list of extracted keywords.

[0755] Step 6:

[0756] The server's matching mechanism compares the extracted keywords with the reference information. It compares the extracted keyword list with the reference information to check for any matching keywords. The input is the extracted keyword list and the reference information, and the output is the matching result.

[0757] Step 7:

[0758] The server's judgment mechanism determines the likelihood of accepting the request information based on the matching results. For example, if there are many matching keywords, it is determined to be "acceptable," and if there are few or no matching keywords, it is determined to be "unacceptable." The input is the matching results, and the output is the acceptance likelihood determination result.

[0759] Step 8:

[0760] The server's notification system informs the user of the judgment result. Specifically, it sends the judgment result back to the terminal and displays it on the user's smartphone. The input is the judgment result, and the output is the notification to the user's terminal.

[0761] Step 9:

[0762] The server's log management system saves logs for all processing steps. Specifically, it records information for each step of request information reception, analysis, matching, determination, and notification, and stores it in a database. The input is data from each processing step, and the output is a log file.

[0763] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0764] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method based on those emotions.

[0765] 1. User (Representative of the investigative agency)

[0766] The user is an officer of an investigative agency and uses a terminal to input request information. The input form contains detailed information related to the investigation case, and the information is sent to the system by clicking the "Submit" button. In addition, an emotion engine analyzes the user's facial expressions and voice in real time while they are typing.

[0767] 2. Terminal

[0768] The device has the following functions:

[0769] Input methods: Provide forms and fields for the user to enter request information. Also, capture the user's facial expressions and voice through a camera and microphone for the emotion engine.

[0770] Transmission method: The input information and acquired emotion data are sent to the server.

[0771] 3. Server

[0772] The server is the central hub of the system and has the following functions:

[0773] Reference information reading means

[0774] The server reads pre-configured reference information from a configuration file or database and stores it as an internal data structure.

[0775] Receiving means

[0776] The server receives request information and sentiment data sent from the terminal.

[0777] Analysis means

[0778] The received request information is analyzed using a text analysis algorithm to extract important keywords and phrases. Simultaneously, an emotion engine is used to analyze emotional data and understand the user's emotional state.

[0779] Verification means

[0780] The extracted keywords are compared with the reference information to check for matches or mismatches.

[0781] Judgment means

[0782] The likelihood of accepting the request is determined based on the matching results. Specifically, if it perfectly matches the reference information, it is determined as "acceptable"; if it does not match, it is determined as "unacceptable." Sentimental data is also considered to assist in determining the result.

[0783] Notification means

[0784] The user is notified of the assessment result. The content and method of the notification are adjusted based on the sentiment data. For example, if the user is determined to be tired, a concise and clear notification is sent.

[0785] Log storage method

[0786] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[0787] Specific example

[0788] Case 1: Acceptable Request

[0789] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0790] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[0791] Terminal: Sends request information and sentiment data to the server as text data.

[0792] server:

[0793] Load the reference information.

[0794] The request information is received, and analysis is used to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, emotional data is analyzed.

[0795] The reference information is compared using a matching method and found to be a perfect match.

[0796] The system determines that the message is "acceptable" based on the evaluation criteria, and then adjusts the notification content considering the emotional data.

[0797] The system notifies the user that the request is "acceptable" via a notification method.

[0798] All processes are recorded using a logging system.

[0799] Case 2: Unacceptable Request

[0800] Request details: "Only a written note was found."

[0801] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[0802] Terminal: Sends request information and sentiment data to the server as text data.

[0803] server:

[0804] Load the reference information.

[0805] The request information is received, and only the "written note" is extracted using an analysis tool. At the same time, emotional data is analyzed.

[0806] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[0807] The system determines that the application is "unacceptable" and adjusts the notification content based on emotional data.

[0808] The notification system will inform the user that the request "cannot be accepted".

[0809] All processes are recorded using a logging system.

[0810] In this way, the system of the present invention efficiently and accurately performs the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[0811] The following describes the processing flow.

[0812] Step 1:

[0813] The user enters and submits the request information from their device.

[0814] User: Enter the request details into the input form on the screen and click the "Submit" button. The device's camera and microphone also collect the user's facial expressions and voice in real time.

[0815] Step 2:

[0816] The device sends request information and emotion data to the server.

[0817] Terminal: Converts the entered request information into text data and sends it to the server along with sentiment data.

[0818] Step 3:

[0819] The server receives the request information and sentiment data.

[0820] Server: Receives request information and sentiment data in text format sent from the terminal.

[0821] Step 4:

[0822] The server reads the reference information.

[0823] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[0824] Step 5:

[0825] The server analyzes the request information and extracts keywords.

[0826] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[0827] Step 6:

[0828] The server analyzes the emotional data.

[0829] Server: Uses an emotion engine to analyze received emotion data and recognize the user's emotional state (e.g., tension, joy, fatigue).

[0830] Step 7:

[0831] The server compares the extracted keywords with the reference information.

[0832] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[0833] Step 8:

[0834] The server determines whether the request can be accepted.

[0835] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not. It also considers emotional data to set up feedback appropriate to the user's emotional state.

[0836] Step 9:

[0837] The server notifies the user of the result of the determination.

[0838] Server: Sends the judgment result to the terminal and creates a notification with content and tone that matches the user's emotional state.

[0839] Step 10:

[0840] The device displays the result to the user.

[0841] Terminal: Displays the received judgment results on the screen and notifies the user in a format that can be reviewed. Displays messages based on sentiment feedback.

[0842] Step 11:

[0843] The server saves logs for all processing steps.

[0844] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[0845] (Example 2)

[0846] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0847] Conventional request information systems have faced challenges in accurately evaluating and quickly determining the input information, and furthermore, they cannot respond in a way that takes into account the user's emotional state, resulting in a poor user experience. In particular, law enforcement agencies are required to accurately grasp the content and urgency of request information and respond quickly and appropriately, but conventional systems have not been able to adequately achieve this.

[0848] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a receiving means for receiving request information, an analysis means for analyzing the request information and extracting important keywords, and an emotion analysis means for analyzing the user's emotion data. This enables accurate evaluation and rapid determination of the request information, as well as adjustment of an appropriate notification method based on the user's emotional state.

[0849] "Request information" refers to detailed information related to the investigation case entered by the user.

[0850] "Input means" refers to a device or mechanism for a user to input request information into the system.

[0851] "Transmission means" refers to a device or mechanism that transmits the input request information to the server.

[0852] "Receiving means" refers to the device or mechanism by which a server receives request information transmitted from a terminal.

[0853] "Reference information" refers to pre-configured information used to evaluate the requested information.

[0854] "Reference information reading means" refers to a device or mechanism for the server to read reference information.

[0855] "Analysis means" refers to a device or mechanism that analyzes the received request information and extracts important keywords.

[0856] "Verification means" refers to a device or mechanism that verifies extracted keywords against reference information.

[0857] "Determination means" refers to a device or mechanism that determines the likelihood of accepting a request based on the results of the verification.

[0858] "Notification means" refers to a device or mechanism that notifies the user of the judgment result.

[0859] "Emotional analysis means" refers to a device or system that analyzes a user's emotional data.

[0860] "Notification method adjustment means" refers to a device or mechanism that adjusts the notification method based on emotional data.

[0861] "Log storage means" refers to a device or mechanism that stores logs for all processing steps.

[0862] "Text conversion means" refers to a device or mechanism that converts request information into text data.

[0863] "Display means" refers to a device or mechanism that displays the judgment result to the user.

[0864] This invention relates to a system that quickly and accurately determines the likelihood of accepting a request through evaluation of the request information and consideration of the user's emotional state. The following describes how this system can be specifically implemented.

[0865] First, this system consists of a terminal, a server, and a user. The terminal includes a form for entering request information, a camera, and a microphone, which the user uses to input and submit the request information. The camera and microphone are responsible for capturing the user's facial expressions and voice as emotional data in real time. Specifically, commercially available webcams and microphones can be used as hardware.

[0866] Next, the terminal sends this request information and emotion data to the server. The server is equipped with modules that have the following various functions:

[0867] 1. Receiving method: Receives request information and sentiment data transmitted from the terminal.

[0868] 2. Means for reading reference information: Reads pre-configured reference information from a database or configuration file.

[0869] 3. Analysis Methods: The received request information is analyzed using text analysis, for example, the Google Cloud Natural Language API, to extract important keywords and phrases. Simultaneously, emotional data is analyzed using the Microsoft Azure Emotion API, etc., to understand the user's emotional state.

[0870] 4. Matching method: The extracted keywords are compared with reference information to determine whether they match or not.

[0871] 5. Determination method: The likelihood of accepting the request is determined based on the matching results, and sentiment data is considered as necessary.

[0872] 6. Notification Method: Notify the user of the judgment result. Adjust the notification method and content based on sentiment data.

[0873] 7. Log storage method: Logs for all processing steps will be saved.

[0874] For example, if a user enters a request such as, "A child under 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected," the terminal sends this information along with the user's emotional data to the server. The server receives this and performs the necessary analysis and matching. If the request information perfectly matches the reference information, it is determined to be "acceptable." In this case, if the system determines that the user is tired, the notification is simplified to "The request is acceptable." In this way, the system can efficiently evaluate the request information and adjust the notification method based on the user's emotional state.

[0875] Examples of prompt messages are as follows:

[0876] "What data is required for this system's processing, what algorithms are used, and what role does each step play?"

[0877] In this way, this invention provides a system that can efficiently and accurately evaluate request information and determine its feasibility, while taking into account the user's feelings.

[0878] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0879] Step 1:

[0880] This is the step where the user enters and submits the request information. The user uses a web form on their device to enter detailed information related to the investigation case. For example, they might write, "A child under the age of 13 may have disappeared, leaving a note behind." The user then clicks the "Submit" button. The input at this point is the request information text, which will be the output for the next step.

[0881] Step 2:

[0882] This step involves the terminal collecting request information and emotion data and sending it to the server. The terminal receives the request information entered by the user as text data. Simultaneously, it uses the camera and microphone to capture the user's facial expressions and voice in real time and collect emotion data. For example, if the user has a worried expression, that facial expression data is also collected. This data (request information and emotion data) is sent to the server using an HTTP POST request. The input at this point is the request information text and emotion data, which will be the output for the next step.

[0883] Step 3:

[0884] This step involves the server reading baseline information and analyzing the received request information and sentiment data. First, the server reads pre-configured baseline information from a database or configuration file. This baseline information includes important keywords such as "under 13 years old," "note left behind," and "kidnapping, abduction, and confinement." Next, the server receives the request information and sentiment data sent from the terminal. It analyzes the received request information using a text analysis algorithm (e.g., Google Cloud Natural Language API) and extracts important keywords and phrases, such as "disappearance," "note left behind," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, it analyzes the sentiment data using a sentiment engine (e.g., Microsoft Azure Emotion API) to understand the user's emotional state. These analysis results are then output for the next step.

[0885] Step 4:

[0886] This step involves the server comparing the extracted keywords with reference information to determine the suitability of the request information. The server compares the keywords extracted by the analysis tool with the reference information. Specifically, the matching tool performs a match check and evaluates how many matching keywords or phrases exist. For example, if keywords such as "under 13 years old," "written note," and "kidnapping, abduction, and confinement" match, the server will determine that the request is "acceptable." At this point, the input consists of the analysis results and reference information, which will be the output for the next step.

[0887] Step 5:

[0888] This step involves the server notifying the user of the judgment result and saving a log of all processing steps. Based on the matching result, the server determines whether the request is "acceptable" or "unacceptable" and decides on the notification content considering sentiment data. If the server determines that the user is tired, the notification content will be summarized concisely. For example, it might notify the user, "Your request is acceptable." The server also saves data related to all processing steps as a log file. This includes all data from the input of the request information to the final judgment. This ensures traceability of the entire system. The input at this point is the judgment result and sentiment data, which become the final output.

[0889] (Application Example 2)

[0890] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0891] The problem that this invention aims to solve is to improve the user experience by efficiently and accurately evaluating the feasibility of accepting request information provided by investigative agencies, and by adjusting the notification method of the results while taking into account the user's emotional state. Furthermore, by linking with smart devices, it also aims to improve on-site operability and enable a rapid response.

[0892] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting request information, a transmission means for sending the request information to the server, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, a log storage means for saving logs for all processing steps of the means, an emotion data acquisition means for acquiring the user's emotion data, an emotion analysis means for analyzing the acquired emotion data, a notification method adjustment means for adjusting the notification method of the determination result based on the emotion data, and an interface means for coordinating with the interface of a smart device. This makes it possible to efficiently and accurately evaluate the possibility of accepting request information and to provide a notification method that takes into account the user's emotional state.

[0893] "Request information" refers to detailed information related to an investigation case, entered by an officer in charge at an investigative agency.

[0894] "Input method" refers to a function that provides forms or fields for entering request information.

[0895] "Transmission method" refers to the function that sends the entered request information to the server.

[0896] "Receiving means" refers to the function of a server to receive the request information that has been sent.

[0897] A "reference information loading mechanism" is a function that reads pre-configured reference information from a database or configuration file and stores it as an internal data structure.

[0898] The "analysis means" refers to a function that analyzes the received request information and extracts important keywords and phrases.

[0899] The "matching means" is a function that compares extracted keywords with reference information to confirm whether they match or not.

[0900] The "determination means" is a function that determines the likelihood of accepting a request based on the results of the verification.

[0901] "Notification method" refers to a function that notifies the user of the judgment result.

[0902] A "log storage method" is a function that records and saves logs for all processing steps.

[0903] "Method for acquiring emotional data" refers to a function that acquires emotional data from the user's facial expressions, voice, etc.

[0904] "Emotional analysis means" refers to a function that analyzes acquired emotional data to understand the user's emotional state.

[0905] The "notification method adjustment mechanism" is a function that adjusts the notification method and content of the judgment results based on emotion data.

[0906] "Interface means" refers to functions that work in conjunction with smart devices to support operability and information display.

[0907] "Smart devices" is a general term for devices used as interfaces, such as eyeglasses, personal digital assistants (PDAs), and wearable devices.

[0908] This invention is a system in which an investigator inputs request information, and then efficiently and accurately evaluates that information to determine its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method accordingly. This system is used in conjunction with smart glasses.

[0909] 1. User (Representative of the investigative agency)

[0910] The user wears smart glasses and uses the interface to input request information. The input form contains detailed information related to the investigation case, and the user clicks the submit button. Furthermore, the smart glasses' built-in camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[0911] 2. Device (smart glasses)

[0912] The device has the following functions:

[0913] Input methods: Provide forms and fields for users to input request information. Also, capture user facial expressions and voice via camera and microphone.

[0914] Transmission method: The entered request information and acquired emotion data are sent to the server.

[0915] Interface means: Assists user operation and displays information in conjunction with smart devices.

[0916] 3. Server

[0917] The server is the central hub of the system and has the following functions:

[0918] Reference information reading method: The server reads pre-configured reference information from the database and stores it internally.

[0919] Receiving method: The server receives request information and sentiment data sent from the terminal.

[0920] Analysis method: The received request information is analyzed and important keywords are extracted. Simultaneously, sentiment data is analyzed to understand the user's emotional state. For example, "Amazon Rekognition" is used.

[0921] Matching method: The extracted keywords are compared with reference information to confirm whether they match or not.

[0922] Determination method: The likelihood of accepting the request is determined based on the matching results. Specifically, if it matches the reference information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable." Sentiment data is also considered to assist in determining the result.

[0923] Notification method: The user is notified of the assessment result. The content and method of notification are adjusted based on sentiment data. For example, if it is determined that the user is feeling tired, a concise and clear notification is sent.

[0924] Log storage method: Logs are recorded and stored for all processing steps. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[0925] Specific operations and examples

[0926] Case 1: Acceptable Request

[0927] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0928] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[0929] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." A matching tool compares the information with the standard information to confirm a match. A judgment tool determines that the request is "acceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that the request is "acceptable." All processes are logged.

[0930] Case 2: Unacceptable Request

[0931] Request details: "Only a written note was found."

[0932] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[0933] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract only the "written message." A matching tool compares it with the reference information and determines that there is a mismatch. A judgment tool determines that it is "unacceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that it is "unacceptable." All processes are logged.

[0934] Example input prompts for a generative AI model

[0935] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[0936] In this way, the system of the present invention enables the efficient and accurate execution of the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[0937] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0938] Step 1:

[0939] The user enters request information through the smart glasses interface. The user enters detailed information related to the investigation case and clicks the submit button. The user's facial expressions and voice are captured in real time through the smart glasses' camera and microphone. Request information (text data) and facial / voice data are obtained as input data. This data is treated as input.

[0940] Step 2:

[0941] The terminal sends the acquired request information and emotion data together to the cloud server. The request information (text data) and emotion data (facial expression / voice data) are transmitted using the transmission method. The output at this time is the transmitted request information and emotion data.

[0942] Step 3:

[0943] The server receives the request information and sentiment data. Using the receiving means, it receives the request information and sentiment data sent from the terminal. The output of this step is the received request information and sentiment data.

[0944] Step 4:

[0945] The server's criteria information reading mechanism reads pre-configured criteria information from the database. This criteria information includes keywords and phrases for evaluating investigation cases. The criteria information is retrieved from the database and stored as an internal data structure. The output of this step is the read criteria information.

[0946] Step 5:

[0947] The server's analysis tool analyzes the received request information and extracts important keywords and phrases using a text analysis algorithm. It receives request information (text data) as input and performs keyword extraction. The output is a list of extracted keywords. Simultaneously, it analyzes emotional data using an emotion engine to understand the user's emotional state. It receives emotional data (facial expressions and voice data) as input and obtains the results of the emotional state analysis.

[0948] Step 6:

[0949] The server's matching mechanism compares the extracted keywords with the reference information. Using the matching mechanism, the extracted keyword list is compared with the reference information to determine whether they match or not. The output of this process is the keyword matching result.

[0950] Step 7:

[0951] The server's decision-making mechanism determines the likelihood of accepting the request based on the matching results. It uses the matching results and the analysis results of sentiment data as input to determine whether the request is acceptable or not. If it is acceptable, it displays "Acceptable"; otherwise, it displays "Not Acceptable." The output is the acceptance decision result.

[0952] Step 8:

[0953] The server's notification system informs the user of the acceptance judgment result. The content and method of the notification are adjusted based on the results of the emotional data analysis. For example, a concise notification is sent if the user is tired, while a detailed notification is sent if the user is calm. The acceptance judgment result and the emotional data analysis results are used as input to generate appropriate notification content and method, and then notify the user. The output is a notification message to the user.

[0954] Step 9:

[0955] The server's logging mechanism records and saves logs for all processing steps. It saves data and processes for each step, such as receiving, analyzing, matching, judging, and notifying, as logs. The input is the data and process information for each step, and the output is the saved log data.

[0956] Specific example

[0957] Case 1: Acceptable Request

[0958] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[0959] Input: Request information (text data), emotion data (facial expressions, voice data)

[0960] Output: Acceptance determination, notification message to the user

[0961] Case 2: Unacceptable Request

[0962] Request details: "Only a written note was found."

[0963] Input: Request information (text data), emotion data (facial expressions, voice data)

[0964] Output: Rejection of submission, notification message to the user.

[0965] Example input prompts for a generative AI model

[0966] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[0967] Through the processing steps described above, the system of the present invention can efficiently evaluate, judge, and notify request information, thereby improving the user experience.

[0968] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0969] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0970] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0971] [Third Embodiment]

[0972] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0973] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0974] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0975] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0976] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0977] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0978] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0979] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0980] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0981] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0982] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0983] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0984] This invention relates to a system for efficiently and accurately evaluating request information provided by investigative agencies and determining its feasibility. This system consists of the following components:

[0985] 1. User (Representative of the investigative agency)

[0986] The user is an officer of an investigative agency and uses a terminal to input request information. This information includes details about a specific investigation case. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[0987] 2. Terminal

[0988] The terminal provides a user interface and is a device for inputting and sending request information. Specifically, it has the following functions:

[0989] Input method: Provides forms or fields for users to enter request information.

[0990] Transmission method: The entered request information is sent to the server as text data.

[0991] 3. Server

[0992] The server is the central hub of the system and processes request information using multiple methods. Specifically, it uses the following methods:

[0993] Reference information reading means

[0994] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation.

[0995] Receiving means

[0996] The server receives request information sent from the terminal. This receiving mechanism has the functionality to receive request information in text data format.

[0997] Analysis means

[0998] The received request information is analyzed using a text analysis algorithm to extract important keywords and phrases. This analysis is performed using natural language processing technology.

[0999] Verification means

[1000] The extracted keywords are compared with the reference information. During this process, it is checked whether the keywords match the reference information, and the results are recorded.

[1001] Judgment means

[1002] The likelihood of accepting the request is determined based on the matching results. Specifically, if it perfectly matches the standard information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable."

[1003] Notification means

[1004] The user is notified of the judgment result. This notification sends the result back to the device so that the user can check the result.

[1005] Log storage method

[1006] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[1007] Specific example

[1008] Case 1: Acceptable Request

[1009] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1010] User: Enter the request information and click the submit button.

[1011] Terminal: Sends request information to the server as text data.

[1012] server:

[1013] Load the reference information.

[1014] The request information is received, and the analysis tool extracts "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[1015] The reference information is compared using a matching method and found to be a perfect match.

[1016] The evaluation method determined that it was "acceptable."

[1017] The system notifies the user that the request is "acceptable" via a notification method.

[1018] All processes are recorded using a logging system.

[1019] Case 2: Unacceptable Request

[1020] Request details: "Only a written note was found."

[1021] User: Enter the request information and click the submit button.

[1022] Terminal: Sends request information to the server as text data.

[1023] server:

[1024] Load the reference information.

[1025] Request information is received, and only "written notes" are extracted using an analysis tool.

[1026] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[1027] The evaluation method determined that it was "not acceptable."

[1028] The notification system will inform the user that the request "cannot be accepted".

[1029] All processes are recorded using a logging system.

[1030] In this way, the system of the present invention efficiently and accurately performs all processes of receiving request information, analyzing it, comparing it to a standard, determining whether it is accepted, and notifying the result.

[1031] The following describes the processing flow.

[1032] Step 1:

[1033] The user enters and submits the request information from their device.

[1034] User: Enter the request details into the input form on the screen and click the "Submit" button.

[1035] Step 2:

[1036] The terminal sends the request information to the server.

[1037] Terminal: Converts the entered request information into text data and sends it to the server.

[1038] Step 3:

[1039] The server receives the request information.

[1040] Server: Receives request information in text data format sent from the terminal.

[1041] Step 4:

[1042] The server reads the reference information.

[1043] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[1044] Step 5:

[1045] The server analyzes the request information and extracts keywords.

[1046] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[1047] Step 6:

[1048] The server compares the extracted keywords with the reference information.

[1049] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[1050] Step 7:

[1051] The server determines whether the request can be accepted.

[1052] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not.

[1053] Step 8:

[1054] The server notifies the user of the result of the determination.

[1055] Server: Sends the judgment result to the terminal.

[1056] Step 9:

[1057] The device displays the result to the user.

[1058] Terminal: Displays the received judgment results on the screen for the user to confirm.

[1059] Step 10:

[1060] The server saves logs for all processing steps.

[1061] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[1062] (Example 1)

[1063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1064] Traditional systems for receiving investigation requests were inefficient in processing request information, making it difficult to respond quickly. Furthermore, the process of cross-referencing with standard information and extracting important keywords was often done manually, increasing the risk of human error. As a result, requests that should be accepted were sometimes not accurately identified, leading to decreased operational efficiency for investigative agencies.

[1065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1066] In this invention, the server includes an input means for inputting request information, a transmission means for transmitting the request information to an information processing system, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, and a log storage means for saving logs for all processing steps of the means. This makes it possible to perform all processes from receiving request information to analysis, matching, determination, and notification efficiently and accurately.

[1067] "Requested information" refers to detailed information provided by investigative agencies regarding a specific case.

[1068] An "input method" is an interface that allows a user to input request information into the system.

[1069] "Transmission means" refers to a method or device for sending the input request information to the server.

[1070] "Receiving means" refers to a method or device for a server to receive request information transmitted from a terminal.

[1071] "Reference information reading means" refers to a method or device for reading pre-configured reference information from a configuration file or database.

[1072] "Analysis means" refers to a method or apparatus for analyzing received request information and extracting important keywords.

[1073] "Verification means" refers to a method or apparatus for verifying extracted keywords against reference information.

[1074] "Determination means" refers to a method or apparatus for determining the feasibility of accepting a request based on the results of the verification.

[1075] "Notification means" refers to a method or device for notifying the user of the judgment result.

[1076] "Log storage means" refers to a method or apparatus for recording and storing logs for all processing steps.

[1077] "Text conversion means" refers to a method or apparatus for converting request information into text data.

[1078] "Display means" refers to a method or device for displaying the judgment result to the user.

[1079] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. This system improves the efficiency and accuracy of operations by automating a series of processes from inputting request information to analysis, determination, and notification of results.

[1080] Overall system configuration

[1081] 1. User

[1082] The user is an officer of an investigative agency and uses a terminal to input the request information. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[1083] 2. Terminal

[1084] The terminal is a device used by users to input and submit request information. Specifically, it has the following functions:

[1085] Input method: A form or field is provided, allowing the user to enter the request information.

[1086] Transmission method: The entered request information is sent to the server as text data. For example, an HTTP POST request is used for this transmission.

[1087] 3. Server

[1088] The server is the central hub of the system and has multiple means of processing request information.

[1089] Reference information reading means

[1090] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation. Specifically, it uses an SQLite database or a JSON file.

[1091] Receiving means

[1092] The server receives request information sent from the terminal. For example, it can receive HTTP requests using a web framework such as Flask.

[1093] Analysis means

[1094] The received request information is analyzed using natural language processing techniques to extract important keywords and phrases. Specifically, text data is analyzed using Python's NLTK and SpaCy.

[1095] Verification means

[1096] The extracted keywords are compared with the reference information. Specifically, it is checked whether the extracted keywords are included in the reference information.

[1097] Judgment means

[1098] The likelihood of accepting the request is determined based on the matching results. If it perfectly matches the standard information, it is determined as "acceptable"; otherwise, it is determined as "unacceptable".

[1099] Notification means

[1100] The server notifies the user of the judgment result. Specifically, it returns an HTTP response and displays the judgment result on the terminal.

[1101] Log storage method

[1102] Logs are recorded and saved for all processing steps. Specifically, logs are saved to Elasticsearch to manage the processing history.

[1103] Specific example

[1104] Case 1: Acceptable Request

[1105] 1. Request details: "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[1106] 2. User: Enter the request information and click the submit button.

[1107] 3. Terminal: Sends the request information to the server as text data.

[1108] 4. Server:

[1109] Load the reference information.

[1110] Request information received.

[1111] The analysis method extracted the terms "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[1112] The reference information is compared using a matching method and found to be a perfect match.

[1113] The evaluation method determined that it was "acceptable."

[1114] The system notifies the user that the request is "acceptable" via a notification method.

[1115] All processes are recorded using a logging system.

[1116] Case 2: Unacceptable Request

[1117] 1. Request details: "Only a written note was found."

[1118] 2. User: Enter the request information and click the submit button.

[1119] 3. Terminal: Sends the request information to the server as text data.

[1120] 4. Server:

[1121] Load the reference information.

[1122] Request information received.

[1123] The analysis method extracts only the "written notes."

[1124] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[1125] The evaluation method determined that it was "not acceptable."

[1126] The notification system will inform the user that the request "cannot be accepted".

[1127] All processes are recorded using a logging system.

[1128] Example of a prompt

[1129] "Please evaluate the following request information: 'A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected.'"

[1130] As a result, the system of the present invention can efficiently and accurately perform all processes of receiving request information, analyzing it, matching it to a standard, determining whether it is accepted, and notifying the result.

[1131] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1132] Step 1: User enters request information

[1133] Users enter details about the investigation into a dedicated input form. For example, "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[1134] Input: Details of the investigation

[1135] Output: Text data entered in the form

[1136] Step 2: Submitting the request information

[1137] When the user clicks the "Submit" button, the device sends the entered request information to the server in text data format. An HTTP POST request is used for submission.

[1138] Input: Text data entered in the form

[1139] Output: HTTP POST request data to the server

[1140] Step 3: Receiving the request information

[1141] The server receives an HTTP POST request sent from the terminal and extracts the text data of the request information. A web framework such as Flask is used here.

[1142] Input: HTTP POST request data

[1143] Output: Request information in text format

[1144] Step 4: Loading reference information

[1145] The server reads pre-configured reference information from a configuration file or database (e.g., SQLite or JSON file).

[1146] Input: File path or database query for reference information

[1147] Output: Reference information (keywords and phrases)

[1148] Step 5: Analysis of the request information

[1149] The server uses natural language processing libraries (such as NLTK or SpaCy) to analyze the received request information and extract important keywords and phrases.

[1150] Input: Request information in text format

[1151] Output: Extracted keywords and phrases (e.g., "note left," "under 13 years old," "kidnapping, abduction, and confinement")

[1152] Step 6: Verification against reference information

[1153] The server compares the keywords extracted by the analysis tool with reference information. The comparison then verifies whether the keywords match the reference information.

[1154] Input: Extracted keywords or phrases, reference information

[1155] Output: Matching result (match or mismatch)

[1156] Step 7: Determining the likelihood of acceptance

[1157] The server determines whether the request can be accepted based on the matching results. If it perfectly matches the reference information, it is determined to be "acceptable"; otherwise, it is determined to be "unacceptable".

[1158] Input: Matching result

[1159] Output: Judgment result (acceptable or unacceptable)

[1160] Step 8: Notification of the result

[1161] The server notifies the user of the judgment result. The judgment result is sent back to the terminal via an HTTP response, and the terminal displays the result to the user.

[1162] Input: Judgment Result

[1163] Output: Judgment result displayed to the user

[1164] Step 9: Save the log

[1165] The server logs and stores all processing steps. Specifically, it uses Elasticsearch to store the logs. The logs include all processes from receiving the request information to notifying the decision result.

[1166] Input: Data for each processing step

[1167] Output: Saved log data

[1168] (Application Example 1)

[1169] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1170] Traditional emergency reporting systems required users to manually evaluate the content of their reports and forward them to the appropriate law enforcement or security agency, which could lead to delays in response. Furthermore, incomplete reports could prevent appropriate action from being taken. As a result, there were problems with the rapid and accurate handling of emergencies.

[1171] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1172] In this invention, the server includes data reading means, natural language processing means, matching means, determination means, notification means, log management means, and user interface means. This makes it possible to quickly and accurately evaluate emergency notification information, automatically determine its acceptanceability, and promptly notify law enforcement agencies or security agencies.

[1173] "Request information" refers to information that users input and submit, requiring confirmation and evaluation.

[1174] A "device means" is a device used by a user to input request information.

[1175] "Communication means" refers to the methods or systems used to send request information to a server.

[1176] "Collection method" refers to the method or system used by the server to receive request information.

[1177] A "data loading method" refers to a method or system for reading pre-configured reference information from a database or configuration file.

[1178] "Natural language processing means" refers to computer processing methods for analyzing request information and extracting important keywords.

[1179] A "matching method" refers to a method or system for comparing extracted keywords with reference information to determine whether they match.

[1180] "Determination means" refers to a method or system for determining the feasibility of accepting the requested information based on the matching results.

[1181] "Notification means" refers to methods or systems for communicating the judgment results to the user.

[1182] A "log management system" refers to a method or system for saving and managing records of all processing steps.

[1183] A "user interface means" is an interface for a user to input and transmit emergency call information.

[1184] Modes for carrying out the invention

[1185] This invention relates to a system for efficiently and accurately evaluating request information and determining its feasibility of acceptance. Specific embodiments thereof are described below.

[1186] System Configuration

[1187] This system consists of the following main components:

[1188] 1. User's device (e.g., smartphone)

[1189] 2. Means of communication

[1190] 3. Server (data reading means, natural language processing means, matching means, determination means, notification means, and log management means)

[1191] 4. User Interface Means

[1192] Hardware and software

[1193] User device means:

[1194] The user uses a smartphone. This smartphone has an emergency call application installed. Using the application, the user enters and sends emergency call information.

[1195] Means of communication:

[1196] The communication method utilizes an internet connection. Emergency call information entered on a smartphone is transmitted to a server via the internet.

[1197] server:

[1198] The server performs the following roles:

[1199] Data loading method: Reads pre-configured reference information from a database or configuration file.

[1200] Natural language processing tools: Analyze the request information and extract important keywords. For natural language processing, libraries such as Spacy and NLTK are used.

[1201] Matching method: The extracted keywords are compared with reference information.

[1202] Determination method: The possibility of accepting the request information is determined based on the matching result.

[1203] Notification method: The user is notified of the judgment result.

[1204] Log management method: Logs of all processing steps are recorded and saved.

[1205] Specific examples and prompt statements

[1206] Specific example:

[1207] Let's consider a scenario where a user reports that "a suspicious person is loitering in the neighborhood."

[1208] 1. The user opens the emergency call application on their smartphone.

[1209] 2. Enter "A suspicious person has been loitering in the neighborhood. They have been standing in front of my house for a while" into the text field and press the send button.

[1210] 3. The application sends the entered text to the server.

[1211] 4. On the server side, natural language processing tools analyze the text and extract keywords such as "suspicious" and "wandering around."

[1212] 5. Compare the information with the standard criteria and determine if it is acceptable.

[1213] 6. The determination result will be sent back to the user via notification means, and the appropriate investigative agency will be notified as necessary.

[1214] Example of a prompt:

[1215] "There's a suspicious person loitering around the neighborhood. They've been standing in front of my house for a while."

[1216] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1217] Step 1:

[1218] The user opens the emergency call application on their smartphone, enters a prompt message describing the situation specifically, such as "A suspicious person is loitering in the neighborhood. They have been standing in front of my house for a while," and presses the send button. This input is received by the device's input method.

[1219] Step 2:

[1220] The terminal's communication method transmits the entered request information to the server via the internet.

[1221] Step 3:

[1222] The server's data collection mechanism receives the request information sent from the terminal. At this time, the request information is treated as text data.

[1223] Step 4:

[1224] The server's data reading mechanism reads pre-configured reference information (data containing important keywords and phrases) from the database.

[1225] Step 5:

[1226] The server's natural language processing system analyzes the received request information and extracts important keywords. Specifically, it uses a natural language processing library with a generative AI model (e.g., Spacy or NLTK) to extract keywords such as "suspicious" and "wandering" from the text. The input is the text data of the request information, and the output is a list of extracted keywords.

[1227] Step 6:

[1228] The server's matching mechanism compares the extracted keywords with the reference information. It compares the extracted keyword list with the reference information to check for any matching keywords. The input is the extracted keyword list and the reference information, and the output is the matching result.

[1229] Step 7:

[1230] The server's judgment mechanism determines the likelihood of accepting the request information based on the matching results. For example, if there are many matching keywords, it is determined to be "acceptable," and if there are few or no matching keywords, it is determined to be "unacceptable." The input is the matching results, and the output is the acceptance likelihood determination result.

[1231] Step 8:

[1232] The server's notification system informs the user of the judgment result. Specifically, it sends the judgment result back to the terminal and displays it on the user's smartphone. The input is the judgment result, and the output is the notification to the user's terminal.

[1233] Step 9:

[1234] The server's log management system saves logs for all processing steps. Specifically, it records information for each step of request information reception, analysis, matching, determination, and notification, and stores it in a database. The input is data from each processing step, and the output is a log file.

[1235] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1236] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method based on those emotions.

[1237] 1. User (Representative of the investigative agency)

[1238] The user is an officer of an investigative agency and uses a terminal to input request information. The input form contains detailed information related to the investigation case, and the information is sent to the system by clicking the "Submit" button. In addition, an emotion engine analyzes the user's facial expressions and voice in real time while they are typing.

[1239] 2. Terminal

[1240] The device has the following functions:

[1241] Input methods: Provide forms and fields for the user to enter request information. Also, capture the user's facial expressions and voice through a camera and microphone for the emotion engine.

[1242] Transmission method: The input information and acquired emotion data are sent to the server.

[1243] 3. Server

[1244] The server is the central hub of the system and has the following functions:

[1245] Reference information reading means

[1246] The server reads pre-configured reference information from a configuration file or database and stores it as an internal data structure.

[1247] Receiving means

[1248] The server receives request information and sentiment data sent from the terminal.

[1249] Analysis means

[1250] The received request information is analyzed using a text analysis algorithm to extract important keywords and phrases. Simultaneously, an emotion engine is used to analyze emotional data and understand the user's emotional state.

[1251] Verification means

[1252] The extracted keywords are compared with the reference information to check for matches or mismatches.

[1253] Judgment means

[1254] The likelihood of accepting the request is determined based on the matching results. Specifically, if it perfectly matches the reference information, it is determined as "acceptable"; if it does not match, it is determined as "unacceptable." Sentimental data is also considered to assist in determining the result.

[1255] Notification means

[1256] The user is notified of the assessment result. The content and method of the notification are adjusted based on the sentiment data. For example, if the user is determined to be tired, a concise and clear notification is sent.

[1257] Log storage method

[1258] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[1259] Specific example

[1260] Case 1: Acceptable Request

[1261] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1262] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[1263] Terminal: Sends request information and sentiment data to the server as text data.

[1264] server:

[1265] Load the reference information.

[1266] The request information is received, and analysis is used to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, emotional data is analyzed.

[1267] The reference information is compared using a matching method and found to be a perfect match.

[1268] The system determines that the message is "acceptable" based on the evaluation criteria, and then adjusts the notification content considering the emotional data.

[1269] The system notifies the user that the request is "acceptable" via a notification method.

[1270] All processes are recorded using a logging system.

[1271] Case 2: Unacceptable Request

[1272] Request details: "Only a written note was found."

[1273] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[1274] Terminal: Sends request information and sentiment data to the server as text data.

[1275] server:

[1276] Load the reference information.

[1277] The request information is received, and only the "written note" is extracted using an analysis tool. At the same time, emotional data is analyzed.

[1278] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[1279] The system determines that the application is "unacceptable" and adjusts the notification content based on emotional data.

[1280] The notification system will inform the user that the request "cannot be accepted".

[1281] All processes are recorded using a logging system.

[1282] In this way, the system of the present invention efficiently and accurately performs the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[1283] The following describes the processing flow.

[1284] Step 1:

[1285] The user enters and submits the request information from their device.

[1286] User: Enter the request details into the input form on the screen and click the "Submit" button. The device's camera and microphone also collect the user's facial expressions and voice in real time.

[1287] Step 2:

[1288] The device sends request information and emotion data to the server.

[1289] Terminal: Converts the entered request information into text data and sends it to the server along with sentiment data.

[1290] Step 3:

[1291] The server receives the request information and sentiment data.

[1292] Server: Receives request information and sentiment data in text format sent from the terminal.

[1293] Step 4:

[1294] The server reads the reference information.

[1295] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[1296] Step 5:

[1297] The server analyzes the request information and extracts keywords.

[1298] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[1299] Step 6:

[1300] The server analyzes the emotional data.

[1301] Server: Uses an emotion engine to analyze received emotion data and recognize the user's emotional state (e.g., tension, joy, fatigue).

[1302] Step 7:

[1303] The server compares the extracted keywords with the reference information.

[1304] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[1305] Step 8:

[1306] The server determines whether the request can be accepted.

[1307] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not. It also considers emotional data to set up feedback appropriate to the user's emotional state.

[1308] Step 9:

[1309] The server notifies the user of the result of the determination.

[1310] Server: Sends the judgment result to the terminal and creates a notification with content and tone that matches the user's emotional state.

[1311] Step 10:

[1312] The device displays the result to the user.

[1313] Terminal: Displays the received judgment results on the screen and notifies the user in a format that can be reviewed. Displays messages based on sentiment feedback.

[1314] Step 11:

[1315] The server saves logs for all processing steps.

[1316] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[1317] (Example 2)

[1318] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1319] Conventional request information systems have faced challenges in accurately evaluating and quickly determining the input information, and furthermore, they cannot respond in a way that takes into account the user's emotional state, resulting in a poor user experience. In particular, law enforcement agencies are required to accurately grasp the content and urgency of request information and respond quickly and appropriately, but conventional systems have not been able to adequately achieve this.

[1320] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a receiving means for receiving request information, an analysis means for analyzing the request information and extracting important keywords, and an emotion analysis means for analyzing the user's emotion data. This enables accurate evaluation and rapid determination of the request information, as well as adjustment of an appropriate notification method based on the user's emotional state.

[1321] "Request information" refers to detailed information related to the investigation case entered by the user.

[1322] "Input means" refers to a device or mechanism for a user to input request information into the system.

[1323] "Transmission means" refers to a device or mechanism that transmits the input request information to the server.

[1324] "Receiving means" refers to the device or mechanism by which a server receives request information transmitted from a terminal.

[1325] "Reference information" refers to pre-configured information used to evaluate the requested information.

[1326] "Reference information reading means" refers to a device or mechanism for the server to read reference information.

[1327] "Analysis means" refers to a device or mechanism that analyzes the received request information and extracts important keywords.

[1328] "Verification means" refers to a device or mechanism that verifies extracted keywords against reference information.

[1329] "Determination means" refers to a device or mechanism that determines the likelihood of accepting a request based on the results of the verification.

[1330] "Notification means" refers to a device or mechanism that notifies the user of the judgment result.

[1331] "Emotional analysis means" refers to a device or system that analyzes a user's emotional data.

[1332] "Notification method adjustment means" refers to a device or mechanism that adjusts the notification method based on emotional data.

[1333] "Log storage means" refers to a device or mechanism that stores logs for all processing steps.

[1334] "Text conversion means" refers to a device or mechanism that converts request information into text data.

[1335] "Display means" refers to a device or mechanism that displays the judgment result to the user.

[1336] This invention relates to a system that quickly and accurately determines the likelihood of accepting a request through evaluation of the request information and consideration of the user's emotional state. The following describes how this system can be specifically implemented.

[1337] First, this system consists of a terminal, a server, and a user. The terminal includes a form for entering request information, a camera, and a microphone, which the user uses to input and submit the request information. The camera and microphone are responsible for capturing the user's facial expressions and voice as emotional data in real time. Specifically, commercially available webcams and microphones can be used as hardware.

[1338] Next, the terminal sends this request information and emotion data to the server. The server is equipped with modules that have the following various functions:

[1339] 1. Receiving method: Receives request information and sentiment data transmitted from the terminal.

[1340] 2. Means for reading reference information: Reads pre-configured reference information from a database or configuration file.

[1341] 3. Analysis Methods: The received request information is analyzed using text analysis, for example, the Google Cloud Natural Language API, to extract important keywords and phrases. Simultaneously, emotional data is analyzed using the Microsoft Azure Emotion API, etc., to understand the user's emotional state.

[1342] 4. Matching method: The extracted keywords are compared with reference information to determine whether they match or not.

[1343] 5. Determination method: The likelihood of accepting the request is determined based on the matching results, and sentiment data is considered as necessary.

[1344] 6. Notification Method: Notify the user of the judgment result. Adjust the notification method and content based on sentiment data.

[1345] 7. Log storage method: Logs for all processing steps will be saved.

[1346] For example, if a user enters a request such as, "A child under 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected," the terminal sends this information along with the user's emotional data to the server. The server receives this and performs the necessary analysis and matching. If the request information perfectly matches the reference information, it is determined to be "acceptable." In this case, if the system determines that the user is tired, the notification is simplified to "The request is acceptable." In this way, the system can efficiently evaluate the request information and adjust the notification method based on the user's emotional state.

[1347] Examples of prompt messages are as follows:

[1348] "What data is required for this system's processing, what algorithms are used, and what role does each step play?"

[1349] In this way, this invention provides a system that can efficiently and accurately evaluate request information and determine its feasibility, while taking into account the user's feelings.

[1350] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1351] Step 1:

[1352] This is the step where the user enters and submits the request information. The user uses a web form on their device to enter detailed information related to the investigation case. For example, they might write, "A child under the age of 13 may have disappeared, leaving a note behind." The user then clicks the "Submit" button. The input at this point is the request information text, which will be the output for the next step.

[1353] Step 2:

[1354] This step involves the terminal collecting request information and emotion data and sending it to the server. The terminal receives the request information entered by the user as text data. Simultaneously, it uses the camera and microphone to capture the user's facial expressions and voice in real time and collect emotion data. For example, if the user has a worried expression, that facial expression data is also collected. This data (request information and emotion data) is sent to the server using an HTTP POST request. The input at this point is the request information text and emotion data, which will be the output for the next step.

[1355] Step 3:

[1356] This step involves the server reading baseline information and analyzing the received request information and sentiment data. First, the server reads pre-configured baseline information from a database or configuration file. This baseline information includes important keywords such as "under 13 years old," "note left behind," and "kidnapping, abduction, and confinement." Next, the server receives the request information and sentiment data sent from the terminal. It analyzes the received request information using a text analysis algorithm (e.g., Google Cloud Natural Language API) and extracts important keywords and phrases, such as "disappearance," "note left behind," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, it analyzes the sentiment data using a sentiment engine (e.g., Microsoft Azure Emotion API) to understand the user's emotional state. These analysis results are then output for the next step.

[1357] Step 4:

[1358] This step involves the server comparing the extracted keywords with reference information to determine the suitability of the request information. The server compares the keywords extracted by the analysis tool with the reference information. Specifically, the matching tool performs a match check and evaluates how many matching keywords or phrases exist. For example, if keywords such as "under 13 years old," "written note," and "kidnapping, abduction, and confinement" match, the server will determine that the request is "acceptable." At this point, the input consists of the analysis results and reference information, which will be the output for the next step.

[1359] Step 5:

[1360] This step involves the server notifying the user of the judgment result and saving a log of all processing steps. Based on the matching result, the server determines whether the request is "acceptable" or "unacceptable" and decides on the notification content considering sentiment data. If the server determines that the user is tired, the notification content will be summarized concisely. For example, it might notify the user, "Your request is acceptable." The server also saves data related to all processing steps as a log file. This includes all data from the input of the request information to the final judgment. This ensures traceability of the entire system. The input at this point is the judgment result and sentiment data, which become the final output.

[1361] (Application Example 2)

[1362] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1363] The problem that this invention aims to solve is to improve the user experience by efficiently and accurately evaluating the feasibility of accepting request information provided by investigative agencies, and by adjusting the notification method of the results while taking into account the user's emotional state. Furthermore, by linking with smart devices, it also aims to improve on-site operability and enable a rapid response.

[1364] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting request information, a transmission means for sending the request information to the server, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, a log storage means for saving logs for all processing steps of the means, an emotion data acquisition means for acquiring the user's emotion data, an emotion analysis means for analyzing the acquired emotion data, a notification method adjustment means for adjusting the notification method of the determination result based on the emotion data, and an interface means for coordinating with the interface of a smart device. This makes it possible to efficiently and accurately evaluate the possibility of accepting request information and to provide a notification method that takes into account the user's emotional state.

[1365] "Request information" refers to detailed information related to an investigation case, entered by an officer in charge at an investigative agency.

[1366] "Input method" refers to a function that provides forms or fields for entering request information.

[1367] "Transmission method" refers to the function that sends the entered request information to the server.

[1368] "Receiving means" refers to the function of a server to receive the request information that has been sent.

[1369] A "reference information loading mechanism" is a function that reads pre-configured reference information from a database or configuration file and stores it as an internal data structure.

[1370] The "analysis means" refers to a function that analyzes the received request information and extracts important keywords and phrases.

[1371] The "matching means" is a function that compares extracted keywords with reference information to confirm whether they match or not.

[1372] The "determination means" is a function that determines the likelihood of accepting a request based on the results of the verification.

[1373] "Notification method" refers to a function that notifies the user of the judgment result.

[1374] A "log storage method" is a function that records and saves logs for all processing steps.

[1375] "Method for acquiring emotional data" refers to a function that acquires emotional data from the user's facial expressions, voice, etc.

[1376] "Emotional analysis means" refers to a function that analyzes acquired emotional data to understand the user's emotional state.

[1377] The "notification method adjustment mechanism" is a function that adjusts the notification method and content of the judgment results based on emotion data.

[1378] "Interface means" refers to functions that work in conjunction with smart devices to support operability and information display.

[1379] "Smart devices" is a general term for devices used as interfaces, such as eyeglasses, personal digital assistants (PDAs), and wearable devices.

[1380] This invention is a system in which an investigator inputs request information, and then efficiently and accurately evaluates that information to determine its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method accordingly. This system is used in conjunction with smart glasses.

[1381] 1. User (Representative of the investigative agency)

[1382] The user wears smart glasses and uses the interface to input request information. The input form contains detailed information related to the investigation case, and the user clicks the submit button. Furthermore, the smart glasses' built-in camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[1383] 2. Device (smart glasses)

[1384] The device has the following functions:

[1385] Input methods: Provide forms and fields for users to input request information. Also, capture user facial expressions and voice via camera and microphone.

[1386] Transmission method: The entered request information and acquired emotion data are sent to the server.

[1387] Interface means: Assists user operation and displays information in conjunction with smart devices.

[1388] 3. Server

[1389] The server is the central hub of the system and has the following functions:

[1390] Reference information reading method: The server reads pre-configured reference information from the database and stores it internally.

[1391] Receiving method: The server receives request information and sentiment data sent from the terminal.

[1392] Analysis method: The received request information is analyzed and important keywords are extracted. Simultaneously, sentiment data is analyzed to understand the user's emotional state. For example, "Amazon Rekognition" is used.

[1393] Matching method: The extracted keywords are compared with reference information to confirm whether they match or not.

[1394] Determination method: The likelihood of accepting the request is determined based on the matching results. Specifically, if it matches the reference information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable." Sentiment data is also considered to assist in determining the result.

[1395] Notification method: The user is notified of the assessment result. The content and method of notification are adjusted based on sentiment data. For example, if it is determined that the user is feeling tired, a concise and clear notification is sent.

[1396] Log storage method: Logs are recorded and stored for all processing steps. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[1397] Specific operations and examples

[1398] Case 1: Acceptable Request

[1399] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1400] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[1401] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." A matching tool compares the information with the standard information to confirm a match. A judgment tool determines that the request is "acceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that the request is "acceptable." All processes are logged.

[1402] Case 2: Unacceptable Request

[1403] Request details: "Only a written note was found."

[1404] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[1405] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract only the "written message." A matching tool compares it with the reference information and determines that there is a mismatch. A judgment tool determines that it is "unacceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that it is "unacceptable." All processes are logged.

[1406] Example input prompts for a generative AI model

[1407] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[1408] In this way, the system of the present invention enables the efficient and accurate execution of the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[1409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1410] Step 1:

[1411] The user enters request information through the smart glasses interface. The user enters detailed information related to the investigation case and clicks the submit button. The user's facial expressions and voice are captured in real time through the smart glasses' camera and microphone. Request information (text data) and facial / voice data are obtained as input data. This data is treated as input.

[1412] Step 2:

[1413] The terminal sends the acquired request information and emotion data together to the cloud server. The request information (text data) and emotion data (facial expression / voice data) are transmitted using the transmission method. The output at this time is the transmitted request information and emotion data.

[1414] Step 3:

[1415] The server receives the request information and sentiment data. Using the receiving means, it receives the request information and sentiment data sent from the terminal. The output of this step is the received request information and sentiment data.

[1416] Step 4:

[1417] The server's criteria information reading mechanism reads pre-configured criteria information from the database. This criteria information includes keywords and phrases for evaluating investigation cases. The criteria information is retrieved from the database and stored as an internal data structure. The output of this step is the read criteria information.

[1418] Step 5:

[1419] The server's analysis tool analyzes the received request information and extracts important keywords and phrases using a text analysis algorithm. It receives request information (text data) as input and performs keyword extraction. The output is a list of extracted keywords. Simultaneously, it analyzes emotional data using an emotion engine to understand the user's emotional state. It receives emotional data (facial expressions and voice data) as input and obtains the results of the emotional state analysis.

[1420] Step 6:

[1421] The server's matching mechanism compares the extracted keywords with the reference information. Using the matching mechanism, the extracted keyword list is compared with the reference information to determine whether they match or not. The output of this process is the keyword matching result.

[1422] Step 7:

[1423] The server's decision-making mechanism determines the likelihood of accepting the request based on the matching results. It uses the matching results and the analysis results of sentiment data as input to determine whether the request is acceptable or not. If it is acceptable, it displays "Acceptable"; otherwise, it displays "Not Acceptable." The output is the acceptance decision result.

[1424] Step 8:

[1425] The server's notification system informs the user of the acceptance judgment result. The content and method of the notification are adjusted based on the results of the emotional data analysis. For example, a concise notification is sent if the user is tired, while a detailed notification is sent if the user is calm. The acceptance judgment result and the emotional data analysis results are used as input to generate appropriate notification content and method, and then notify the user. The output is a notification message to the user.

[1426] Step 9:

[1427] The server's logging mechanism records and saves logs for all processing steps. It saves data and processes for each step, such as receiving, analyzing, matching, judging, and notifying, as logs. The input is the data and process information for each step, and the output is the saved log data.

[1428] Specific example

[1429] Case 1: Acceptable Request

[1430] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1431] Input: Request information (text data), emotion data (facial expressions, voice data)

[1432] Output: Acceptance determination, notification message to the user

[1433] Case 2: Unacceptable Request

[1434] Request details: "Only a written note was found."

[1435] Input: Request information (text data), emotion data (facial expressions, voice data)

[1436] Output: Rejection of submission, notification message to the user.

[1437] Example input prompts for a generative AI model

[1438] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[1439] Through the processing steps described above, the system of the present invention can efficiently evaluate, judge, and notify request information, thereby improving the user experience.

[1440] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1441] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1442] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1443] [Fourth Embodiment]

[1444] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1445] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1446] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1447] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1448] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1449] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1450] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1451] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1452] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1453] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1454] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1455] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1456] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1457] This invention relates to a system for efficiently and accurately evaluating request information provided by investigative agencies and determining its feasibility. This system consists of the following components:

[1458] 1. User (Representative of the investigative agency)

[1459] The user is an officer of an investigative agency and uses a terminal to input request information. This information includes details about a specific investigation case. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[1460] 2. Terminal

[1461] The terminal provides a user interface and is a device for inputting and sending request information. Specifically, it has the following functions:

[1462] Input method: Provides forms or fields for users to enter request information.

[1463] Transmission method: The entered request information is sent to the server as text data.

[1464] 3. Server

[1465] The server is the central hub of the system and processes request information using multiple methods. Specifically, it uses the following methods:

[1466] Reference information reading means

[1467] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation.

[1468] Receiving means

[1469] The server receives request information sent from the terminal. This receiving mechanism has the functionality to receive request information in text data format.

[1470] Analysis means

[1471] The received request information is analyzed using a text analysis algorithm to extract important keywords and phrases. This analysis is performed using natural language processing technology.

[1472] Verification means

[1473] The extracted keywords are compared with the reference information. During this process, it is checked whether the keywords match the reference information, and the results are recorded.

[1474] Judgment means

[1475] The likelihood of accepting the request is determined based on the matching results. Specifically, if it perfectly matches the standard information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable."

[1476] Notification means

[1477] The user is notified of the judgment result. This notification sends the result back to the device so that the user can check the result.

[1478] Log storage method

[1479] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[1480] Specific example

[1481] Case 1: Acceptable Request

[1482] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1483] User: Enter the request information and click the submit button.

[1484] Terminal: Sends request information to the server as text data.

[1485] server:

[1486] Load the reference information.

[1487] The request information is received, and the analysis tool extracts "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[1488] The reference information is compared using a matching method and found to be a perfect match.

[1489] The evaluation method determined that it was "acceptable."

[1490] The system notifies the user that the request is "acceptable" via a notification method.

[1491] All processes are recorded using a logging system.

[1492] Case 2: Unacceptable Request

[1493] Request details: "Only a written note was found."

[1494] User: Enter the request information and click the submit button.

[1495] Terminal: Sends request information to the server as text data.

[1496] server:

[1497] Load the reference information.

[1498] Request information is received, and only "written notes" are extracted using an analysis tool.

[1499] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[1500] The evaluation method determined that it was "not acceptable."

[1501] The notification system will inform the user that the request "cannot be accepted".

[1502] All processes are recorded using a logging system.

[1503] In this way, the system of the present invention efficiently and accurately performs all processes of receiving request information, analyzing it, comparing it to a standard, determining whether it is accepted, and notifying the result.

[1504] The following describes the processing flow.

[1505] Step 1:

[1506] The user enters and submits the request information from their device.

[1507] User: Enter the request details into the input form on the screen and click the "Submit" button.

[1508] Step 2:

[1509] The terminal sends the request information to the server.

[1510] Terminal: Converts the entered request information into text data and sends it to the server.

[1511] Step 3:

[1512] The server receives the request information.

[1513] Server: Receives request information in text data format sent from the terminal.

[1514] Step 4:

[1515] The server reads the reference information.

[1516] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[1517] Step 5:

[1518] The server analyzes the request information and extracts keywords.

[1519] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[1520] Step 6:

[1521] The server compares the extracted keywords with the reference information.

[1522] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[1523] Step 7:

[1524] The server determines whether the request can be accepted.

[1525] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not.

[1526] Step 8:

[1527] The server notifies the user of the result of the determination.

[1528] Server: Sends the judgment result to the terminal.

[1529] Step 9:

[1530] The device displays the result to the user.

[1531] Terminal: Displays the received judgment results on the screen for the user to confirm.

[1532] Step 10:

[1533] The server saves logs for all processing steps.

[1534] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[1535] (Example 1)

[1536] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1537] Traditional systems for receiving investigation requests were inefficient in processing request information, making it difficult to respond quickly. Furthermore, the process of cross-referencing with standard information and extracting important keywords was often done manually, increasing the risk of human error. As a result, requests that should be accepted were sometimes not accurately identified, leading to decreased operational efficiency for investigative agencies.

[1538] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1539] In this invention, the server includes an input means for inputting request information, a transmission means for transmitting the request information to an information processing system, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, and a log storage means for saving logs for all processing steps of the means. This makes it possible to perform all processes from receiving request information to analysis, matching, determination, and notification efficiently and accurately.

[1540] "Requested information" refers to detailed information provided by investigative agencies regarding a specific case.

[1541] An "input method" is an interface that allows a user to input request information into the system.

[1542] "Transmission means" refers to a method or device for sending the input request information to the server.

[1543] "Receiving means" refers to a method or device for a server to receive request information transmitted from a terminal.

[1544] "Reference information reading means" refers to a method or device for reading pre-configured reference information from a configuration file or database.

[1545] "Analysis means" refers to a method or apparatus for analyzing received request information and extracting important keywords.

[1546] "Verification means" refers to a method or apparatus for verifying extracted keywords against reference information.

[1547] "Determination means" refers to a method or apparatus for determining the feasibility of accepting a request based on the results of the verification.

[1548] "Notification means" refers to a method or device for notifying the user of the judgment result.

[1549] "Log storage means" refers to a method or apparatus for recording and storing logs for all processing steps.

[1550] "Text conversion means" refers to a method or apparatus for converting request information into text data.

[1551] "Display means" refers to a method or device for displaying the judgment result to the user.

[1552] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. This system improves the efficiency and accuracy of operations by automating a series of processes from inputting request information to analysis, determination, and notification of results.

[1553] Overall system configuration

[1554] 1. User

[1555] The user is an officer of an investigative agency and uses a terminal to input the request information. The user enters the necessary information into a dedicated input form and sends the request information to the system by clicking the "Submit" button.

[1556] 2. Terminal

[1557] The terminal is a device used by users to input and submit request information. Specifically, it has the following functions:

[1558] Input method: A form or field is provided, allowing the user to enter the request information.

[1559] Transmission method: The entered request information is sent to the server as text data. For example, an HTTP POST request is used for this transmission.

[1560] 3. Server

[1561] The server is the central hub of the system and has multiple means of processing request information.

[1562] Reference information reading means

[1563] The server reads pre-configured criteria information from a configuration file or database. This includes keywords and phrases that serve as criteria for matching and evaluation. Specifically, it uses an SQLite database or a JSON file.

[1564] Receiving means

[1565] The server receives request information sent from the terminal. For example, it can receive HTTP requests using a web framework such as Flask.

[1566] Analysis means

[1567] The received request information is analyzed using natural language processing techniques to extract important keywords and phrases. Specifically, text data is analyzed using Python's NLTK and SpaCy.

[1568] Verification means

[1569] The extracted keywords are compared with the reference information. Specifically, it is checked whether the extracted keywords are included in the reference information.

[1570] Judgment means

[1571] The likelihood of accepting the request is determined based on the matching results. If it perfectly matches the standard information, it is determined as "acceptable"; otherwise, it is determined as "unacceptable".

[1572] Notification means

[1573] The server notifies the user of the judgment result. Specifically, it returns an HTTP response and displays the judgment result on the terminal.

[1574] Log storage method

[1575] Logs are recorded and saved for all processing steps. Specifically, logs are saved to Elasticsearch to manage the processing history.

[1576] Specific example

[1577] Case 1: Acceptable Request

[1578] 1. Request details: "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[1579] 2. User: Enter the request information and click the submit button.

[1580] 3. Terminal: Sends the request information to the server as text data.

[1581] 4. Server:

[1582] Load the reference information.

[1583] Request information received.

[1584] The analysis method extracted the terms "written note," "under 13 years old," and "kidnapping, abduction, and confinement."

[1585] The reference information is compared using a matching method and found to be a perfect match.

[1586] The evaluation method determined that it was "acceptable."

[1587] The system notifies the user that the request is "acceptable" via a notification method.

[1588] All processes are recorded using a logging system.

[1589] Case 2: Unacceptable Request

[1590] 1. Request details: "Only a written note was found."

[1591] 2. User: Enter the request information and click the submit button.

[1592] 3. Terminal: Sends the request information to the server as text data.

[1593] 4. Server:

[1594] Load the reference information.

[1595] Request information received.

[1596] The analysis method extracts only the "written notes."

[1597] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[1598] The evaluation method determined that it was "not acceptable."

[1599] The notification system will inform the user that the request "cannot be accepted".

[1600] All processes are recorded using a logging system.

[1601] Example of a prompt

[1602] "Please evaluate the following request information: 'A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected.'"

[1603] As a result, the system of the present invention can efficiently and accurately perform all processes of receiving request information, analyzing it, matching it to a standard, determining whether it is accepted, and notifying the result.

[1604] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1605] Step 1: User enters request information

[1606] Users enter details about the investigation into a dedicated input form. For example, "A child under the age of 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected."

[1607] Input: Details of the investigation

[1608] Output: Text data entered in the form

[1609] Step 2: Submitting the request information

[1610] When the user clicks the "Submit" button, the device sends the entered request information to the server in text data format. An HTTP POST request is used for submission.

[1611] Input: Text data entered in the form

[1612] Output: HTTP POST request data to the server

[1613] Step 3: Receiving the request information

[1614] The server receives an HTTP POST request sent from the terminal and extracts the text data of the request information. A web framework such as Flask is used here.

[1615] Input: HTTP POST request data

[1616] Output: Request information in text format

[1617] Step 4: Loading reference information

[1618] The server reads pre-configured reference information from a configuration file or database (e.g., SQLite or JSON file).

[1619] Input: File path or database query for reference information

[1620] Output: Reference information (keywords and phrases)

[1621] Step 5: Analysis of the request information

[1622] The server uses natural language processing libraries (such as NLTK or SpaCy) to analyze the received request information and extract important keywords and phrases.

[1623] Input: Request information in text format

[1624] Output: Extracted keywords and phrases (e.g., "note left," "under 13 years old," "kidnapping, abduction, and confinement")

[1625] Step 6: Verification against reference information

[1626] The server compares the keywords extracted by the analysis tool with reference information. The comparison then verifies whether the keywords match the reference information.

[1627] Input: Extracted keywords or phrases, reference information

[1628] Output: Matching result (match or mismatch)

[1629] Step 7: Determining the likelihood of acceptance

[1630] The server determines whether the request can be accepted based on the matching results. If it perfectly matches the reference information, it is determined to be "acceptable"; otherwise, it is determined to be "unacceptable".

[1631] Input: Matching result

[1632] Output: Judgment result (acceptable or unacceptable)

[1633] Step 8: Notification of the result

[1634] The server notifies the user of the judgment result. The judgment result is sent back to the terminal via an HTTP response, and the terminal displays the result to the user.

[1635] Input: Judgment Result

[1636] Output: Judgment result displayed to the user

[1637] Step 9: Save the log

[1638] The server logs and stores all processing steps. Specifically, it uses Elasticsearch to store the logs. The logs include all processes from receiving the request information to notifying the decision result.

[1639] Input: Data for each processing step

[1640] Output: Saved log data

[1641] (Application Example 1)

[1642] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1643] Traditional emergency reporting systems required users to manually evaluate the content of their reports and forward them to the appropriate law enforcement or security agency, which could lead to delays in response. Furthermore, incomplete reports could prevent appropriate action from being taken. As a result, there were problems with the rapid and accurate handling of emergencies.

[1644] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1645] In this invention, the server includes data reading means, natural language processing means, matching means, determination means, notification means, log management means, and user interface means. This makes it possible to quickly and accurately evaluate emergency notification information, automatically determine its acceptanceability, and promptly notify law enforcement agencies or security agencies.

[1646] "Request information" refers to information that users input and submit, requiring confirmation and evaluation.

[1647] A "device means" is a device used by a user to input request information.

[1648] "Communication means" refers to the methods or systems used to send request information to a server.

[1649] "Collection method" refers to the method or system used by the server to receive request information.

[1650] A "data loading method" refers to a method or system for reading pre-configured reference information from a database or configuration file.

[1651] "Natural language processing means" refers to computer processing methods for analyzing request information and extracting important keywords.

[1652] A "matching method" refers to a method or system for comparing extracted keywords with reference information to determine whether they match.

[1653] "Determination means" refers to a method or system for determining the feasibility of accepting the requested information based on the matching results.

[1654] "Notification means" refers to methods or systems for communicating the judgment results to the user.

[1655] A "log management system" refers to a method or system for saving and managing records of all processing steps.

[1656] A "user interface means" is an interface for a user to input and transmit emergency call information.

[1657] Modes for carrying out the invention

[1658] This invention relates to a system for efficiently and accurately evaluating request information and determining its feasibility of acceptance. Specific embodiments thereof are described below.

[1659] System Configuration

[1660] This system consists of the following main components:

[1661] 1. User's device (e.g., smartphone)

[1662] 2. Means of communication

[1663] 3. Server (data reading means, natural language processing means, matching means, determination means, notification means, and log management means)

[1664] 4. User Interface Means

[1665] Hardware and software

[1666] User device means:

[1667] The user uses a smartphone. This smartphone has an emergency call application installed. Using the application, the user enters and sends emergency call information.

[1668] Means of communication:

[1669] The communication method utilizes an internet connection. Emergency call information entered on a smartphone is transmitted to a server via the internet.

[1670] server:

[1671] The server performs the following roles:

[1672] Data loading method: Reads pre-configured reference information from a database or configuration file.

[1673] Natural language processing tools: Analyze the request information and extract important keywords. For natural language processing, libraries such as Spacy and NLTK are used.

[1674] Matching method: The extracted keywords are compared with reference information.

[1675] Determination method: The possibility of accepting the request information is determined based on the matching result.

[1676] Notification method: The user is notified of the judgment result.

[1677] Log management method: Logs of all processing steps are recorded and saved.

[1678] Specific examples and prompt statements

[1679] Specific example:

[1680] Let's consider a scenario where a user reports that "a suspicious person is loitering in the neighborhood."

[1681] 1. The user opens the emergency call application on their smartphone.

[1682] 2. Enter "A suspicious person has been loitering in the neighborhood. They have been standing in front of my house for a while" into the text field and press the send button.

[1683] 3. The application sends the entered text to the server.

[1684] 4. On the server side, natural language processing tools analyze the text and extract keywords such as "suspicious" and "wandering around."

[1685] 5. Compare the information with the standard criteria and determine if it is acceptable.

[1686] 6. The determination result will be sent back to the user via notification means, and the appropriate investigative agency will be notified as necessary.

[1687] Example of a prompt:

[1688] "There's a suspicious person loitering around the neighborhood. They've been standing in front of my house for a while."

[1689] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1690] Step 1:

[1691] The user opens the emergency call application on their smartphone, enters a prompt message describing the situation specifically, such as "A suspicious person is loitering in the neighborhood. They have been standing in front of my house for a while," and presses the send button. This input is received by the device's input method.

[1692] Step 2:

[1693] The terminal's communication method transmits the entered request information to the server via the internet.

[1694] Step 3:

[1695] The server's data collection mechanism receives the request information sent from the terminal. At this time, the request information is treated as text data.

[1696] Step 4:

[1697] The server's data reading mechanism reads pre-configured reference information (data containing important keywords and phrases) from the database.

[1698] Step 5:

[1699] The server's natural language processing system analyzes the received request information and extracts important keywords. Specifically, it uses a natural language processing library with a generative AI model (e.g., Spacy or NLTK) to extract keywords such as "suspicious" and "wandering" from the text. The input is the text data of the request information, and the output is a list of extracted keywords.

[1700] Step 6:

[1701] The server's matching mechanism compares the extracted keywords with the reference information. It compares the extracted keyword list with the reference information to check for any matching keywords. The input is the extracted keyword list and the reference information, and the output is the matching result.

[1702] Step 7:

[1703] The server's judgment mechanism determines the likelihood of accepting the request information based on the matching results. For example, if there are many matching keywords, it is determined to be "acceptable," and if there are few or no matching keywords, it is determined to be "unacceptable." The input is the matching results, and the output is the acceptance likelihood determination result.

[1704] Step 8:

[1705] The server's notification system informs the user of the judgment result. Specifically, it sends the judgment result back to the terminal and displays it on the user's smartphone. The input is the judgment result, and the output is the notification to the user's terminal.

[1706] Step 9:

[1707] The server's log management system saves logs for all processing steps. Specifically, it records information for each step of request information reception, analysis, matching, determination, and notification, and stores it in a database. The input is data from each processing step, and the output is a log file.

[1708] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1709] This invention relates to a system for efficiently and accurately evaluating request information provided by law enforcement agencies and determining its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method based on those emotions.

[1710] 1. User (Representative of the investigative agency)

[1711] The user is an officer of an investigative agency and uses a terminal to input request information. The input form contains detailed information related to the investigation case, and the information is sent to the system by clicking the "Submit" button. In addition, an emotion engine analyzes the user's facial expressions and voice in real time while they are typing.

[1712] 2. Terminal

[1713] The device has the following functions:

[1714] Input methods: Provide forms and fields for the user to enter request information. Also, capture the user's facial expressions and voice through a camera and microphone for the emotion engine.

[1715] Transmission method: The input information and acquired emotion data are sent to the server.

[1716] 3. Server

[1717] The server is the central hub of the system and has the following functions:

[1718] Reference information reading means

[1719] The server reads pre-configured reference information from a configuration file or database and stores it as an internal data structure.

[1720] Receiving means

[1721] The server receives request information and sentiment data sent from the terminal.

[1722] Analysis means

[1723] The received request information is analyzed using a text analysis algorithm to extract important keywords and phrases. Simultaneously, an emotion engine is used to analyze emotional data and understand the user's emotional state.

[1724] Verification means

[1725] The extracted keywords are compared with the reference information to check for matches or mismatches.

[1726] Judgment means

[1727] The likelihood of accepting the request is determined based on the matching results. Specifically, if it perfectly matches the reference information, it is determined as "acceptable"; if it does not match, it is determined as "unacceptable." Sentimental data is also considered to assist in determining the result.

[1728] Notification means

[1729] The user is notified of the assessment result. The content and method of the notification are adjusted based on the sentiment data. For example, if the user is determined to be tired, a concise and clear notification is sent.

[1730] Log storage method

[1731] Logs are recorded and saved for every processing step. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[1732] Specific example

[1733] Case 1: Acceptable Request

[1734] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1735] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[1736] Terminal: Sends request information and sentiment data to the server as text data.

[1737] server:

[1738] Load the reference information.

[1739] The request information is received, and analysis is used to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, emotional data is analyzed.

[1740] The reference information is compared using a matching method and found to be a perfect match.

[1741] The system determines that the message is "acceptable" based on the evaluation criteria, and then adjusts the notification content considering the emotional data.

[1742] The system notifies the user that the request is "acceptable" via a notification method.

[1743] All processes are recorded using a logging system.

[1744] Case 2: Unacceptable Request

[1745] Request details: "Only a written note was found."

[1746] User: Enter the request information and click the submit button. The camera and microphone are used to collect the user's facial expressions and voice while they are entering the information.

[1747] Terminal: Sends request information and sentiment data to the server as text data.

[1748] server:

[1749] Load the reference information.

[1750] The request information is received, and only the "written note" is extracted using an analysis tool. At the same time, emotional data is analyzed.

[1751] The system compares the information with the reference information using a matching method and determines that there is a mismatch.

[1752] The system determines that the application is "unacceptable" and adjusts the notification content based on emotional data.

[1753] The notification system will inform the user that the request "cannot be accepted".

[1754] All processes are recorded using a logging system.

[1755] In this way, the system of the present invention efficiently and accurately performs the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[1756] The following describes the processing flow.

[1757] Step 1:

[1758] The user enters and submits the request information from their device.

[1759] User: Enter the request details into the input form on the screen and click the "Submit" button. The device's camera and microphone also collect the user's facial expressions and voice in real time.

[1760] Step 2:

[1761] The device sends request information and emotion data to the server.

[1762] Terminal: Converts the entered request information into text data and sends it to the server along with sentiment data.

[1763] Step 3:

[1764] The server receives the request information and sentiment data.

[1765] Server: Receives request information and sentiment data in text format sent from the terminal.

[1766] Step 4:

[1767] The server reads the reference information.

[1768] Server: At startup, it reads reference information from a configuration file or database and stores it as an internal data structure.

[1769] Step 5:

[1770] The server analyzes the request information and extracts keywords.

[1771] Server: Uses a text analysis algorithm to analyze the received request information and extract important keywords and phrases.

[1772] Step 6:

[1773] The server analyzes the emotional data.

[1774] Server: Uses an emotion engine to analyze received emotion data and recognize the user's emotional state (e.g., tension, joy, fatigue).

[1775] Step 7:

[1776] The server compares the extracted keywords with the reference information.

[1777] Server: Compares the extracted keywords with the reference information to check for matches or mismatches.

[1778] Step 8:

[1779] The server determines whether the request can be accepted.

[1780] Server: Based on the matching results, the server determines whether the request is "acceptable" if it meets the criteria, or "unacceptable" if it does not. It also considers emotional data to set up feedback appropriate to the user's emotional state.

[1781] Step 9:

[1782] The server notifies the user of the result of the determination.

[1783] Server: Sends the judgment result to the terminal and creates a notification with content and tone that matches the user's emotional state.

[1784] Step 10:

[1785] The device displays the result to the user.

[1786] Terminal: Displays the received judgment results on the screen and notifies the user in a format that can be reviewed. Displays messages based on sentiment feedback.

[1787] Step 11:

[1788] The server saves logs for all processing steps.

[1789] Server: Records event logs for each step of receiving, analyzing, matching, determining, and notifying request information, and saves them to a specified log file or database.

[1790] (Example 2)

[1791] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1792] Conventional request information systems have faced challenges in accurately evaluating and quickly determining the input information, and furthermore, they cannot respond in a way that takes into account the user's emotional state, resulting in a poor user experience. In particular, law enforcement agencies are required to accurately grasp the content and urgency of request information and respond quickly and appropriately, but conventional systems have not been able to adequately achieve this.

[1793] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a receiving means for receiving request information, an analysis means for analyzing the request information and extracting important keywords, and an emotion analysis means for analyzing the user's emotion data. This enables accurate evaluation and rapid determination of the request information, as well as adjustment of an appropriate notification method based on the user's emotional state.

[1794] "Request information" refers to detailed information related to the investigation case entered by the user.

[1795] "Input means" refers to a device or mechanism for a user to input request information into the system.

[1796] "Transmission means" refers to a device or mechanism that transmits the input request information to the server.

[1797] "Receiving means" refers to the device or mechanism by which a server receives request information transmitted from a terminal.

[1798] "Reference information" refers to pre-configured information used to evaluate the requested information.

[1799] "Reference information reading means" refers to a device or mechanism for the server to read reference information.

[1800] "Analysis means" refers to a device or mechanism that analyzes the received request information and extracts important keywords.

[1801] "Verification means" refers to a device or mechanism that verifies extracted keywords against reference information.

[1802] "Determination means" refers to a device or mechanism that determines the likelihood of accepting a request based on the results of the verification.

[1803] "Notification means" refers to a device or mechanism that notifies the user of the judgment result.

[1804] "Emotional analysis means" refers to a device or system that analyzes a user's emotional data.

[1805] "Notification method adjustment means" refers to a device or mechanism that adjusts the notification method based on emotional data.

[1806] "Log storage means" refers to a device or mechanism that stores logs for all processing steps.

[1807] "Text conversion means" refers to a device or mechanism that converts request information into text data.

[1808] "Display means" refers to a device or mechanism that displays the judgment result to the user.

[1809] This invention relates to a system that quickly and accurately determines the likelihood of accepting a request through evaluation of the request information and consideration of the user's emotional state. The following describes how this system can be specifically implemented.

[1810] First, this system consists of a terminal, a server, and a user. The terminal includes a form for entering request information, a camera, and a microphone, which the user uses to input and submit the request information. The camera and microphone are responsible for capturing the user's facial expressions and voice as emotional data in real time. Specifically, commercially available webcams and microphones can be used as hardware.

[1811] Next, the terminal sends this request information and emotion data to the server. The server is equipped with modules that have the following various functions:

[1812] 1. Receiving method: Receives request information and sentiment data transmitted from the terminal.

[1813] 2. Means for reading reference information: Reads pre-configured reference information from a database or configuration file.

[1814] 3. Analysis Methods: The received request information is analyzed using text analysis, for example, the Google Cloud Natural Language API, to extract important keywords and phrases. Simultaneously, emotional data is analyzed using the Microsoft Azure Emotion API, etc., to understand the user's emotional state.

[1815] 4. Matching method: The extracted keywords are compared with reference information to determine whether they match or not.

[1816] 5. Determination method: The likelihood of accepting the request is determined based on the matching results, and sentiment data is considered as necessary.

[1817] 6. Notification Method: Notify the user of the judgment result. Adjust the notification method and content based on sentiment data.

[1818] 7. Log storage method: Logs for all processing steps will be saved.

[1819] For example, if a user enters a request such as, "A child under 13 may have disappeared after leaving a note. Kidnapping, abduction, and unlawful confinement are suspected," the terminal sends this information along with the user's emotional data to the server. The server receives this and performs the necessary analysis and matching. If the request information perfectly matches the reference information, it is determined to be "acceptable." In this case, if the system determines that the user is tired, the notification is simplified to "The request is acceptable." In this way, the system can efficiently evaluate the request information and adjust the notification method based on the user's emotional state.

[1820] Examples of prompt messages are as follows:

[1821] "What data is required for this system's processing, what algorithms are used, and what role does each step play?"

[1822] In this way, this invention provides a system that can efficiently and accurately evaluate request information and determine its feasibility, while taking into account the user's feelings.

[1823] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1824] Step 1:

[1825] This is the step where the user enters and submits the request information. The user uses a web form on their device to enter detailed information related to the investigation case. For example, they might write, "A child under the age of 13 may have disappeared, leaving a note behind." The user then clicks the "Submit" button. The input at this point is the request information text, which will be the output for the next step.

[1826] Step 2:

[1827] This step involves the terminal collecting request information and emotion data and sending it to the server. The terminal receives the request information entered by the user as text data. Simultaneously, it uses the camera and microphone to capture the user's facial expressions and voice in real time and collect emotion data. For example, if the user has a worried expression, that facial expression data is also collected. This data (request information and emotion data) is sent to the server using an HTTP POST request. The input at this point is the request information text and emotion data, which will be the output for the next step.

[1828] Step 3:

[1829] This step involves the server reading baseline information and analyzing the received request information and sentiment data. First, the server reads pre-configured baseline information from a database or configuration file. This baseline information includes important keywords such as "under 13 years old," "note left behind," and "kidnapping, abduction, and confinement." Next, the server receives the request information and sentiment data sent from the terminal. It analyzes the received request information using a text analysis algorithm (e.g., Google Cloud Natural Language API) and extracts important keywords and phrases, such as "disappearance," "note left behind," "under 13 years old," and "kidnapping, abduction, and confinement." Simultaneously, it analyzes the sentiment data using a sentiment engine (e.g., Microsoft Azure Emotion API) to understand the user's emotional state. These analysis results are then output for the next step.

[1830] Step 4:

[1831] This step involves the server comparing the extracted keywords with reference information to determine the suitability of the request information. The server compares the keywords extracted by the analysis tool with the reference information. Specifically, the matching tool performs a match check and evaluates how many matching keywords or phrases exist. For example, if keywords such as "under 13 years old," "written note," and "kidnapping, abduction, and confinement" match, the server will determine that the request is "acceptable." At this point, the input consists of the analysis results and reference information, which will be the output for the next step.

[1832] Step 5:

[1833] This step involves the server notifying the user of the judgment result and saving a log of all processing steps. Based on the matching result, the server determines whether the request is "acceptable" or "unacceptable" and decides on the notification content considering sentiment data. If the server determines that the user is tired, the notification content will be summarized concisely. For example, it might notify the user, "Your request is acceptable." The server also saves data related to all processing steps as a log file. This includes all data from the input of the request information to the final judgment. This ensures traceability of the entire system. The input at this point is the judgment result and sentiment data, which become the final output.

[1834] (Application Example 2)

[1835] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1836] The problem that this invention aims to solve is to improve the user experience by efficiently and accurately evaluating the feasibility of accepting request information provided by investigative agencies, and by adjusting the notification method of the results while taking into account the user's emotional state. Furthermore, by linking with smart devices, it also aims to improve on-site operability and enable a rapid response.

[1837] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting request information, a transmission means for sending the request information to the server, a receiving means for receiving the request information, a reference information reading means for reading pre-set reference information, an analysis means for analyzing the request information and extracting important keywords, a matching means for comparing the extracted keywords with the reference information, a determination means for determining the possibility of accepting the request based on the matching results, a notification means for notifying the user of the determination result, a log storage means for saving logs for all processing steps of the means, an emotion data acquisition means for acquiring the user's emotion data, an emotion analysis means for analyzing the acquired emotion data, a notification method adjustment means for adjusting the notification method of the determination result based on the emotion data, and an interface means for coordinating with the interface of a smart device. This makes it possible to efficiently and accurately evaluate the possibility of accepting request information and to provide a notification method that takes into account the user's emotional state.

[1838] "Request information" refers to detailed information related to an investigation case, entered by an officer in charge at an investigative agency.

[1839] "Input method" refers to a function that provides forms or fields for entering request information.

[1840] "Transmission method" refers to the function that sends the entered request information to the server.

[1841] "Receiving means" refers to the function of a server to receive the request information that has been sent.

[1842] A "reference information loading mechanism" is a function that reads pre-configured reference information from a database or configuration file and stores it as an internal data structure.

[1843] The "analysis means" refers to a function that analyzes the received request information and extracts important keywords and phrases.

[1844] The "matching means" is a function that compares extracted keywords with reference information to confirm whether they match or not.

[1845] The "determination means" is a function that determines the likelihood of accepting a request based on the results of the verification.

[1846] "Notification method" refers to a function that notifies the user of the judgment result.

[1847] A "log storage method" is a function that records and saves logs for all processing steps.

[1848] "Method for acquiring emotional data" refers to a function that acquires emotional data from the user's facial expressions, voice, etc.

[1849] "Emotional analysis means" refers to a function that analyzes acquired emotional data to understand the user's emotional state.

[1850] The "notification method adjustment mechanism" is a function that adjusts the notification method and content of the judgment results based on emotion data.

[1851] "Interface means" refers to functions that work in conjunction with smart devices to support operability and information display.

[1852] "Smart devices" is a general term for devices used as interfaces, such as eyeglasses, personal digital assistants (PDAs), and wearable devices.

[1853] This invention is a system in which an investigator inputs request information, and then efficiently and accurately evaluates that information to determine its feasibility. Furthermore, it enhances the user experience by adding a function that recognizes the user's emotions and adjusts the notification method accordingly. This system is used in conjunction with smart glasses.

[1854] 1. User (Representative of the investigative agency)

[1855] The user wears smart glasses and uses the interface to input request information. The input form contains detailed information related to the investigation case, and the user clicks the submit button. Furthermore, the smart glasses' built-in camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[1856] 2. Device (smart glasses)

[1857] The device has the following functions:

[1858] Input methods: Provide forms and fields for users to input request information. Also, capture user facial expressions and voice via camera and microphone.

[1859] Transmission method: The entered request information and acquired emotion data are sent to the server.

[1860] Interface means: Assists user operation and displays information in conjunction with smart devices.

[1861] 3. Server

[1862] The server is the central hub of the system and has the following functions:

[1863] Reference information reading method: The server reads pre-configured reference information from the database and stores it internally.

[1864] Receiving method: The server receives request information and sentiment data sent from the terminal.

[1865] Analysis method: The received request information is analyzed and important keywords are extracted. Simultaneously, sentiment data is analyzed to understand the user's emotional state. For example, "Amazon Rekognition" is used.

[1866] Matching method: The extracted keywords are compared with reference information to confirm whether they match or not.

[1867] Determination method: The likelihood of accepting the request is determined based on the matching results. Specifically, if it matches the reference information, it is determined as "acceptable," and if it does not match, it is determined as "unacceptable." Sentiment data is also considered to assist in determining the result.

[1868] Notification method: The user is notified of the assessment result. The content and method of notification are adjusted based on sentiment data. For example, if it is determined that the user is feeling tired, a concise and clear notification is sent.

[1869] Log storage method: Logs are recorded and stored for all processing steps. These logs include information about the entire process, from receiving the request information to notifying the decision result.

[1870] Specific operations and examples

[1871] Case 1: Acceptable Request

[1872] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1873] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[1874] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract "written note," "under 13 years old," and "kidnapping, abduction, and confinement." A matching tool compares the information with the standard information to confirm a match. A judgment tool determines that the request is "acceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that the request is "acceptable." All processes are logged.

[1875] Case 2: Unacceptable Request

[1876] Request details: "Only a written note was found."

[1877] User Operation: The person wearing the smart glasses enters the request information through the interface and clicks the submit button. During input, the camera and microphone are used to collect facial expressions and voice.

[1878] System Processing: The server receives the request information and sentiment data, and uses an analysis tool to extract only the "written message." A matching tool compares it with the reference information and determines that there is a mismatch. A judgment tool determines that it is "unacceptable," and adjusts the notification content considering the sentiment data. A notification tool notifies the user that it is "unacceptable." All processes are logged.

[1879] Example input prompts for a generative AI model

[1880] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[1881] In this way, the system of the present invention enables the efficient and accurate execution of the entire process, including receiving request information, analyzing it, matching it to a standard, determining acceptance, notifying the result, and making adjustments that take into account the user's feelings.

[1882] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1883] Step 1:

[1884] The user enters request information through the smart glasses interface. The user enters detailed information related to the investigation case and clicks the submit button. The user's facial expressions and voice are captured in real time through the smart glasses' camera and microphone. Request information (text data) and facial / voice data are obtained as input data. This data is treated as input.

[1885] Step 2:

[1886] The terminal sends the acquired request information and emotion data together to the cloud server. The request information (text data) and emotion data (facial expression / voice data) are transmitted using the transmission method. The output at this time is the transmitted request information and emotion data.

[1887] Step 3:

[1888] The server receives the request information and sentiment data. Using the receiving means, it receives the request information and sentiment data sent from the terminal. The output of this step is the received request information and sentiment data.

[1889] Step 4:

[1890] The server's criteria information reading mechanism reads pre-configured criteria information from the database. This criteria information includes keywords and phrases for evaluating investigation cases. The criteria information is retrieved from the database and stored as an internal data structure. The output of this step is the read criteria information.

[1891] Step 5:

[1892] The server's analysis tool analyzes the received request information and extracts important keywords and phrases using a text analysis algorithm. It receives request information (text data) as input and performs keyword extraction. The output is a list of extracted keywords. Simultaneously, it analyzes emotional data using an emotion engine to understand the user's emotional state. It receives emotional data (facial expressions and voice data) as input and obtains the results of the emotional state analysis.

[1893] Step 6:

[1894] The server's matching mechanism compares the extracted keywords with the reference information. Using the matching mechanism, the extracted keyword list is compared with the reference information to determine whether they match or not. The output of this process is the keyword matching result.

[1895] Step 7:

[1896] The server's decision-making mechanism determines the likelihood of accepting the request based on the matching results. It uses the matching results and the analysis results of sentiment data as input to determine whether the request is acceptable or not. If it is acceptable, it displays "Acceptable"; otherwise, it displays "Not Acceptable." The output is the acceptance decision result.

[1897] Step 8:

[1898] The server's notification system informs the user of the acceptance judgment result. The content and method of the notification are adjusted based on the results of the emotional data analysis. For example, a concise notification is sent if the user is tired, while a detailed notification is sent if the user is calm. The acceptance judgment result and the emotional data analysis results are used as input to generate appropriate notification content and method, and then notify the user. The output is a notification message to the user.

[1899] Step 9:

[1900] The server's logging mechanism records and saves logs for all processing steps. It saves data and processes for each step, such as receiving, analyzing, matching, judging, and notifying, as logs. The input is the data and process information for each step, and the output is the saved log data.

[1901] Specific example

[1902] Case 1: Acceptable Request

[1903] Request details: "A child under the age of 13 may have disappeared, leaving a note behind. Kidnapping, abduction, and unlawful confinement are suspected."

[1904] Input: Request information (text data), emotion data (facial expressions, voice data)

[1905] Output: Acceptance determination, notification message to the user

[1906] Case 2: Unacceptable Request

[1907] Request details: "Only a written note was found."

[1908] Input: Request information (text data), emotion data (facial expressions, voice data)

[1909] Output: Rejection of submission, notification message to the user.

[1910] Example input prompts for a generative AI model

[1911] "A suspicious individual has been frequently spotted in a certain office, and there is a possibility that they are attempting to leak internal company information."

[1912] Through the processing steps described above, the system of the present invention can efficiently evaluate, judge, and notify request information, thereby improving the user experience.

[1913] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1914] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1915] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1916] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1917] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1918] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1919] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1920] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1921] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1922] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1923] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1924] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1925] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1926] 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.

[1927] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1928] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1929] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1930] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1931] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1932] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1933] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1934] The following is further disclosed regarding the embodiments described above.

[1935] (Claim 1)

[1936] Input method for entering request information,

[1937] A transmission means for sending the aforementioned request information to a server,

[1938] Receiving means for receiving the aforementioned request information,

[1939] A means for reading pre-set reference information,

[1940] An analysis means for analyzing the aforementioned request information and extracting important keywords,

[1941] A matching means for comparing extracted keywords with reference information,

[1942] A determination means for determining the likelihood of accepting the request based on the results of the verification,

[1943] A notification method for informing the user of the judgment result,

[1944] A log storage means that saves a log for all processing steps of the aforementioned means,

[1945] A system that includes this.

[1946] (Claim 2)

[1947] The system according to claim 1, further comprising a text conversion means for converting request information into text data.

[1948] (Claim 3)

[1949] The system according to claim 1, wherein the notification means includes a display means for displaying the determination result to the user.

[1950] "Example 1"

[1951] (Claim 1)

[1952] Input method for entering request information,

[1953] A transmission means for transmitting the aforementioned request information to an information processing system,

[1954] Receiving means for receiving the aforementioned request information,

[1955] A means for reading pre-set reference information,

[1956] An analysis means for analyzing the aforementioned request information and extracting important keywords,

[1957] A matching means for comparing extracted keywords with reference information,

[1958] A determination means for determining the likelihood of accepting the request based on the results of the verification,

[1959] A notification method for informing the user of the judgment result,

[1960] A log storage means that saves a log for all processing steps of the aforementioned means,

[1961] A system that includes this.

[1962] (Claim 2)

[1963] The system according to claim 1, further comprising a text conversion means for converting request information into text data.

[1964] (Claim 3)

[1965] The system according to claim 1, wherein the notification means includes a display means for displaying the determination result to the user.

[1966] "Application Example 1"

[1967] (Claim 1)

[1968] A device for entering request information,

[1969] A communication means for sending the aforementioned request information to the server,

[1970] A collection means for receiving the aforementioned request information,

[1971] A data reading means that reads pre-set reference information,

[1972] A natural language processing means for analyzing the aforementioned request information and extracting important keywords,

[1973] A matching means for comparing extracted keywords with reference information,

[1974] A determination means for determining the likelihood of accepting the request based on the results of the verification,

[1975] A notification method for informing the user of the judgment result,

[1976] A log management means that saves logs for all processing steps of the aforementioned means,

[1977] A user interface means for users to input and transmit emergency call information,

[1978] A system that includes this.

[1979] (Claim 2)

[1980] The system according to claim 1, further comprising a text conversion means for converting request information into text data.

[1981] (Claim 3)

[1982] The system according to claim 1, wherein the notification means includes a display means for displaying the determination result to the user.

[1983] "Example 2 of combining an emotion engine"

[1984] (Claim 1)

[1985] Input method for entering request information,

[1986] A transmission means for sending the aforementioned request information to a server,

[1987] Receiving means for receiving the aforementioned request information,

[1988] A means for reading pre-set reference information,

[1989] An analysis means for analyzing the aforementioned request information and extracting important keywords,

[1990] A matching means for comparing extracted keywords with reference information,

[1991] A determination means for determining the likelihood of accepting the request based on the results of the verification,

[1992] A notification method for informing the user of the judgment result,

[1993] A means of analyzing user emotional data,

[1994] A notification method adjustment means that adjusts the notification method based on emotional data,

[1995] A log storage means that saves a log for all processing steps of the aforementioned means,

[1996] A system that includes this.

[1997] (Claim 2)

[1998] The system according to claim 1, further comprising a text conversion means for converting request information into text data.

[1999] (Claim 3)

[2000] The system according to claim 1, wherein the notification means includes a display means for displaying the determination result to the user.

[2001] "Application example 2 when combining with an emotional engine"

[2002] (Claim 1)

[2003] Input method for entering request information,

[2004] A transmission means for sending the aforementioned request information to a server,

[2005] Receiving means for receiving the aforementioned request information,

[2006] A means for reading pre-set reference information,

[2007] An analysis means for analyzing the aforementioned request information and extracting important keywords,

[2008] A matching means for comparing extracted keywords with reference information,

[2009] A determination means for determining the likelihood of accepting the request based on the results of the verification,

[2010] A notification method for informing the user of the judgment result,

[2011] A log storage means that saves a log for all processing steps of the aforementioned means,

[2012] A means for acquiring emotional data to obtain user emotional data,

[2013] A means of analyzing acquired emotional data,

[2014] A notification method adjustment means that adjusts the method of notifying the judgment result based on emotional data,

[2015] Interface means that interact with the interface of a smart device,

[2016] A system that includes this.

[2017] (Claim 2)

[2018] The system according to claim 1, further comprising a text conversion means for converting request information into text data.

[2019] (Claim 3)

[2020] The system according to claim 1, wherein the notification means includes a display means for displaying the determination result to the user. [Explanation of symbols]

[2021] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Input method for entering request information, A transmission means for sending the aforementioned request information to a server, Receiving means for receiving the aforementioned request information, A means for reading pre-set reference information, An analysis means for analyzing the aforementioned request information and extracting important keywords, A matching means for comparing extracted keywords with reference information, A determination means for determining the likelihood of accepting the request based on the results of the verification, A notification method for informing the user of the judgment result, A log storage means that saves a log for all processing steps of the aforementioned means, A system that includes this.

2. The system according to claim 1, further comprising a text conversion means for converting request information into text data.

3. The system according to claim 1, wherein the notification means includes a display means for displaying the determination result to the user.

Images