system

Abstract

Provide a system. An input means for a user to input transfer information; A communication means for the terminal to transmit transfer information to a server; a fraud detection means for analyzing the reason for the transfer received by the server; analysis result return means for the server to return the analysis result to the terminal; A display means by which the terminal displays the analysis results to the user A system including:

Description

[Technical Field]

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

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

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

[0004] Today, police officers spend a lot of their time directing traffic and fighting fraud in front of ATMs. These tasks reduce the time they can devote to their primary duties of maintaining public order and investigating crimes, potentially undermining the safety and security of citizens. Furthermore, traffic enforcement is also plagued by manpower shortages and unfairness. The purpose of this invention is to solve these problems by utilizing automation and AI technology, thereby improving the efficiency of police work and ensuring the safety of citizens. [Means for solving the problem]

[0005] The present invention provides a system that solves the above problems by the following means.

[0006] First, we provide an input means for users to input transfer information, which allows users to input the amount to be transferred, recipient information, and reason for transfer using an ATM or bank app.

[0007] Next, a communication means is provided for the terminal to transmit the transfer information to the server, and by this means, the input information is transmitted to the server safely and in real time.

[0008] On the server side, we provide a fraud detection method that analyzes the received transfer reason, and then applies an AI algorithm to detect fraudulent activity to determine whether the transfer is safe.

[0009] Furthermore, an analysis result return means is provided for the server to return the analysis results to the terminal, which allows the user to be notified of the analysis results promptly.

[0010] Finally, the terminal provides a display means for displaying the analysis results to the user, allowing the transfer to be completed if it is safe, or to display a warning and cancel the transfer if there is a problem.

[0011] These measures ensure the safety of transfers and prevent fraud before it occurs. The present invention also provides a traffic monitoring system using AI. The server monitors traffic conditions in a designated area and notifies police officers if a violation is detected, making traffic enforcement more efficient.

[0012] "User" refers to an individual or corporation that makes a transfer using the system.

[0013] "Terminal" refers to a device operated by a user, such as an ATM or a smartphone with a banking app installed.

[0014] "Communication means" refers to the network protocol and communication technology used to transmit data from the terminal to the server.

[0015] "Input means" refers to an interface through which a user can input transfer information and the reason for the transfer.

[0016] "Server" refers to the computing system that receives the transfer information, analyzes it, and returns the results.

[0017] "Fraud detection means" refers to the function of using AI algorithms and machine learning models built into the server to analyze the reason for transfer and other information to detect fraud.

[0018] "Means for returning analysis results" refers to the technology by which the server encodes the analysis results and returns them to the terminal.

[0019] "Display means" refers to an interface that allows the terminal to visually display analysis results and other important information to the user.

[0020] The "monitoring means" for monitoring "traffic conditions" refers to sensors and cameras for monitoring traffic conditions in designated areas in real time, as well as AI technology for analyzing the data collected from them.

[0021] "Notification means" refers to the technology that allows the server to send a notification to police officers or automated control devices when it detects a traffic violation.

[0022] "Storage means" refers to the technology that enables the server to store evidentiary data related to traffic violations so that it can be reviewed later. [Brief explanation of the drawings]

[0023] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0024] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0025] First, the terms used in the following description will be explained.

[0026] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0027] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0028] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0029] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0030] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0034] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0035] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0036] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0037] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0038] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0041] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0042] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0043] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0044] The present invention provides a system for preventing fraud when users make bank transfers, and a system for monitoring traffic conditions to detect traffic violations, thereby improving the efficiency of police work and ensuring the safety of citizens. The system of the present invention is implemented by a series of programs, and its processing is as follows.

[0045] System for specifying the reason for transfer

[0046] Program processing explanation

[0047] 1. The user opens an ATM or banking app.

[0048] Users first open the ATM's main screen or their bank's app on their smartphone to begin accessing the system.

[0049] 2. The terminal will display the transfer menu.

[0050] The terminal presents the user with a menu of transfer options, from which the user selects "Transfer."

[0051] 3. The user enters the transfer information.

[0052] The user inputs the transfer amount, the recipient's information, and the reason for the transfer. For example, the user inputs information such as "100,000 yen to Ichiro Suzuki as the recipient, and the reason is the purchase price of a product."

[0053] 4. The terminal sends the entered information to the server.

[0054] The terminal transmits all entered information to the server using a secure communication protocol.

[0055] 5. The server receives and analyzes the transfer information.

[0056] The server applies fraud detection algorithms to analyze the reason for the transfer received, checking reasons such as "purchase of goods" or "repayment to a friend," and comparing them with historical data.

[0057] 6. The server determines whether the transfer is safe.

[0058] Based on the analysis, the server determines whether the transfer is safe or suspicious. If it is safe, the transfer proceeds, otherwise a warning is issued.

[0059] 7. The server sends the results back to the device.

[0060] The server returns the security result to the terminal, for example, a message saying "The transfer has been approved" or "The reason for the transfer is unclear. Please check again."

[0061] 8. The terminal displays the results to the user.

[0062] The terminal displays the result received from the server to the user, for example, displaying a message such as "Transfer completed" or "Warning: The reason for transfer is unclear" on the screen.

[0063] Specific examples

[0064] Suppose a user uses an ATM to transfer 50,000 yen to his friend, Tanaka Taro. When the user enters "50,000 yen," "Tanaka Taro," and "loan to friend" into the ATM, the terminal sends this information to the server. The server analyzes "loan to friend" and, if it determines that the transfer is not fraudulent, it sends a result back to the terminal. The terminal displays the message "Transfer completed," and the transfer is carried out.

[0065] Automatic AI Traffic Monitoring System

[0066] Program processing explanation

[0067] 1. The server performs a scan to monitor traffic conditions in a specified area.

[0068] The server synchronizes all cameras and sensors in the specified city or intersection and begins collecting data in real time.

[0069] 2. The device collects data from surveillance cameras and sensors and sends it to the server.

[0070] The device transmits video data from surveillance cameras and information obtained from sensors to a server in real time.

[0071] 3. The server analyzes the data and determines whether a traffic law violation has occurred.

[0072] The server uses AI and machine learning models to analyze video and sensor data to detect traffic violations, such as running red lights or speeding.

[0073] 4. If the server detects a violation, it notifies nearby police officers.

[0074] When a violation is detected, the server immediately notifies nearby police officers of the incident, including the location and details of the violation.

[0075] 5. The user (police officer) receives the notification and rushes to the scene.

[0076] Once police receive the notification, they will rush to the designated location and crack down on the offending vehicle.

[0077] 6. The server stores evidence data related to the breach.

[0078] The server stores footage and data of violations so that they can be viewed later.

[0079] Specific examples

[0080] While the server monitors traffic conditions at a specific intersection, it detects vehicles that run red lights. Data from sensors and cameras is sent to the server in real time, and the server uses AI to confirm that a red light has been run. The server then sends a notification to a nearby police officer that a red light has been run, and the officer rushes to the scene to crack down on the violating vehicle. At that time, the server stores the video data of the red light run.

[0081] Through these specific processes, the system of the present invention provides efficient fraud prevention and traffic monitoring.

[0082] The processing flow will be explained below.

[0083] System for specifying the reason for transfer

[0084] Program processing explanation

[0085] Step 1:

[0086] The user opens an ATM or banking app.

[0087] Users operate the ATM's touchscreen to access the main menu, or they launch their banking app on their smartphone and log in.

[0088] Step 2:

[0089] The terminal will display the transfer menu.

[0090] The terminal will display a "Transfer" option on the screen for the user to select.

[0091] Step 3:

[0092] The user selects the "Transfer" option.

[0093] The user taps the "Transfer" button to proceed to the transfer information input screen.

[0094] Step 4:

[0095] The terminal displays the transfer information input screen.

[0096] The terminal displays a screen with fields to enter the amount, recipient information, and reason for the transfer.

[0097] Step 5:

[0098] The user enters the necessary transfer information.

[0099] The user enters information such as "100,000 yen," "Suzuki Ichiro," and "purchase price of the product" into the form on the screen.

[0100] Step 6:

[0101] The terminal transmits the input information to the server.

[0102] The terminal encodes the input data and sends it to the server using a secure communication protocol.

[0103] Step 7:

[0104] The server receives the transfer information.

[0105] The server decodes the received data and prepares it for analysis.

[0106] Step 8:

[0107] The server analyzes the reason for the transfer.

[0108] The server applies fraud detection algorithms to analyze the input reason for the transfer and assess its safety.

[0109] Step 9:

[0110] The server determines the security of the transfer.

[0111] The server will then use the analysis results to determine whether the transfer is safe or not, and if it is determined to be fraudulent, it will also provide the reason for this.

[0112] Step 10:

[0113] The server returns the analysis results to the device.

[0114] The server encodes the safety judgment result and returns it to the terminal using a secure communication protocol.

[0115] Step 11:

[0116] The device displays the analysis results to the user.

[0117] The terminal will display a message to the user such as "Transfer completed" or "Warning: Reason for transfer unclear."

[0118] Automatic AI Traffic Monitoring System

[0119] Program processing explanation

[0120] Step 1:

[0121] The server performs a scan to monitor traffic conditions in the designated area.

[0122] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[0123] Step 2:

[0124] The device collects data from surveillance cameras and sensors.

[0125] The device acquires surveillance camera footage and sensor data in real time and sends it to the server.

[0126] Step 3:

[0127] The server receives the collected data and prepares it for analysis.

[0128] The server stores the received video data and sensor data in a temporary database and prepares it for analysis.

[0129] Step 4:

[0130] The server analyzes the data and determines whether any traffic laws have been violated.

[0131] The server uses AI algorithms to analyze the video data and detect traffic violations such as running red lights or speeding.

[0132] Step 5:

[0133] If the server detects a violation, it sends a notification to nearby police officers.

[0134] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[0135] Step 6:

[0136] The user (police officer) receives a notification and rushes to the scene.

[0137] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[0138] Step 7:

[0139] A server stores evidence data associated with the violation.

[0140] The server stores video and sensor data of violations and archives them for future reference.

[0141] By these steps, the system of the present invention realizes the user's bank transfer activity and traffic situation monitoring efficiently and safely.

[0142] Example 1

[0143] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0144] Conventional bank transfer systems and traffic monitoring systems are unable to efficiently detect bank transfer fraud and traffic law violations, resulting in insufficient safety for users and the general public. With the rise in bank transfer fraud, real-time fraud detection is required. Furthermore, when detecting traffic law violations, issues arise, such as delayed police response and inability to reliably preserve evidence of violations. To solve these problems, systems using more advanced technology are needed.

[0145] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0146] In this invention, the server includes fraud detection means for analyzing the received reason for transfer, safety determination means for determining the safety of the transfer based on the analysis results, and monitoring means for monitoring traffic conditions to detect violations. This makes it possible to detect transfer fraud in real time, ensure safe transfers, and quickly detect and notify violations of traffic laws.

[0147] "User" refers to an individual or corporation that uses the system to perform transfer operations or check traffic information.

[0148] "Terminal" refers to a device used by a user to input transfer information or display traffic information, such as an ATM or smartphone application.

[0149] A "server" is a computer system that receives and analyzes bank transfer information and traffic information.

[0150] "Input means" refers to the interface (keyboard, touch panel, etc.) through which the user inputs transfer information.

[0151] "Communication means" refers to the network communication protocol (e.g., HTTPS) used by the terminal to send transfer information to the server.

[0152] "Fraud detection means" refers to a function including algorithms and programs that allow the server to analyze the reason for the transfer and detect the possibility of fraud.

[0153] The "analysis result return means" refers to a function by which the server returns the analysis results to the terminal.

[0154] "Display means" refers to a screen or interface that the terminal uses to display the analysis results received from the server to the user.

[0155] "Safety determination means" refers to the function that the server uses to determine the safety of a transfer based on the analysis results.

[0156] "Means for issuing a warning" refers to a function for sending a warning to the user if the server determines that a transfer is suspicious.

[0157] "Monitoring means" refers to the function that enables the server to use AI to monitor traffic conditions in real time and detect violations.

[0158] "Notification means" refers to a function that notifies nearby police officers when the server detects a traffic law violation.

[0159] "Storage means" refers to the storage or database in which the server stores evidence data related to the violation.

[0160] The present invention provides a system for preventing fraud when users make transfers, and a system for monitoring traffic conditions to detect traffic violations. This system is implemented by a series of programs as follows:

[0161] First, a user initiates access to the system by opening an ATM or a banking app on their smartphone. Next, the terminal presents the user with a transfer option, and the user enters the transfer information (transfer amount, recipient information, and reason for the transfer) from the transfer menu. For example, a user might enter "50,000 yen," "Taro Tanaka," and "loan to a friend" at an ATM. The information entered is transmitted from the terminal to the server using a secure communication protocol (e.g., HTTPS).

[0162] The server analyzes the received transfer information in real time and applies a fraud detection algorithm. This algorithm compares the transfer reason, such as "loan to a friend," with past data to determine whether it is likely to be fraudulent. The server then returns the result of the safety assessment to the device. The device then displays the result to the user, displaying a message such as "Transfer completed" or "Warning: Transfer reason unclear."

[0163] Furthermore, in traffic monitoring systems, the server synchronizes surveillance cameras and sensors in designated cities and intersections and begins collecting data in real time. This allows devices to transmit video data from surveillance cameras and information from sensors to the server in real time. The server then uses AI and machine learning models to analyze the collected video data and sensor data and detect violations of traffic laws, such as running red lights or speeding. If a violation is detected, the server notifies nearby police officers, who then include the location and details of the violation. Police officers then rush to the scene and crack down on the offending vehicle.

[0164] As a specific example, a server may detect a vehicle running a red light while monitoring traffic conditions at a specific intersection. Data from surveillance cameras and sensors is sent to the server in real time, and the server uses AI to confirm the violation. This violation information is notified to police officers, who rush to the scene and crack down on the violating vehicle. At that time, the server stores the video data of the red light violation.

[0165] Examples of prompts for generative AI models include:

[0166] "Please tell me more about your fraud prevention system. If a user goes to an ATM to transfer 50,000 yen to his friend Taro Tanaka, how would fraud prevention work?"

[0167] "Please provide details about your automated AI traffic monitoring system. If a red light is detected at a particular intersection, how will the system respond?"

[0168] With these specific processing and prompt sentence examples, the system of the present invention provides effective fraud prevention and traffic monitoring, ensuring the safety of users and citizens.

[0169] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0170] Step 1:

[0171] The user opens an ATM or banking app.

[0172] Input: User action (accessing an ATM or launching a banking app)

[0173] Output: ATM main screen or initial screen of bank app

[0174] Specifically, the user accesses the nearest ATM or launches a banking app on their smartphone, for example, by tapping the app on their smartphone at home.

[0175] Step 2:

[0176] The terminal will display the transfer menu.

[0177] Input: User request (Display transfer screen on ATM or app)

[0178] Output: Display of transfer options

[0179] Specifically, buttons such as "Transfer" and "Remittance" will appear on the ATM screen or smartphone display, and the user will select one of them.

[0180] Step 3:

[0181] The user enters the transfer information.

[0182] Input: Transfer information entered by the user (transfer amount, recipient information, reason for transfer)

[0183] Output: Confirmation screen of input information

[0184] Specifically, the user uses a keypad or on-screen keyboard to enter information such as "50,000 yen," "Taro Tanaka," and "loan to a friend." Once the information is complete, it is displayed on a confirmation screen.

[0185] Step 4:

[0186] The terminal transmits the input information to the server.

[0187] Input: User's bank transfer information

[0188] Output: Send confirmation message

[0189] Specifically, the terminal sends the transfer information to the server using a secure communication protocol such as HTTPS. Once the transmission is complete, the terminal displays a confirmation message to the user.

[0190] Step 5:

[0191] The server receives and analyzes the transfer information.

[0192] Input: Transfer information sent from the terminal

[0193] Output: Analysis results

[0194] Specifically, the server uses a fraud detection algorithm to compare the reason for the transfer, such as "loan to a friend," with past data. Once the analysis is complete, the server determines whether the transaction is legitimate or suspicious.

[0195] Step 6:

[0196] The server determines the security of the transfer.

[0197] Input: Analysis result of transfer reason

[0198] Output: Safety judgment result (normal or suspicious)

[0199] Specifically, the server determines whether the transfer is safe based on the analysis results. For example, if the "loan to a friend" matches the usual transaction pattern in the past, it will be deemed normal.

[0200] Step 7:

[0201] The server sends the results back to the terminal.

[0202] Input: Safety judgment result

[0203] Output: Confirmation of sending result data

[0204] Specifically, the server sends a message to the terminal such as "The transfer has been approved" or "The reason for the transfer is unclear. Please check again." Once the transfer is complete, a log of the transfer confirmation is recorded.

[0205] Step 8:

[0206] The terminal displays the results to the user.

[0207] Input: Result data from the server

[0208] Output: Result display screen

[0209] Specifically, the terminal displays the result received from the server to the user, for example, "Transfer completed" or "Warning: Transfer reason unclear" on the screen.

[0210] The above are the specific processing steps of the bank transfer fraud prevention system of the present invention. Next, we will explain the specific processing steps of the automatic AI traffic monitoring system.

[0211] Step 1:

[0212] The server performs a scan to monitor traffic conditions in the designated area.

[0213] Input: Monitoring area settings

[0214] Output: Confirmation that monitoring has started

[0215] Specifically, the server synchronizes surveillance cameras and sensors installed in designated cities and intersections with the system and begins collecting data in real time.

[0216] Step 2:

[0217] The device collects data from surveillance cameras and sensors and sends it to a server.

[0218] Input: Data from surveillance cameras and sensors

[0219] Output: Data transmission confirmation message

[0220] Specifically, the device sends video data from surveillance cameras and information from speed sensors to the server in real time. Once the transmission is complete, a confirmation message is displayed.

[0221] Step 3:

[0222] The server analyzes the data and determines whether a traffic law violation has occurred.

[0223] Input: Data from surveillance cameras and sensors

[0224] Output: Violation judgment result

[0225] Specifically, the server uses AI and machine learning models to analyze the collected data and detect traffic violations, such as running red lights or speeding.

[0226] Step 4:

[0227] If the server detects a violation, it notifies nearby police officers.

[0228] Input: Violation judgment result

[0229] Output: Notification message to police officer

[0230] Specifically, if a violation is detected, the server immediately notifies nearby police officers of the information, including the driver's location and the details of the violation.

[0231] Step 5:

[0232] The user (police officer) receives a notification and rushes to the scene.

[0233] Input: Notification message from the server

[0234] Output: Officer response actions

[0235] Specifically, police officers receive notifications via smartphones or police radio, rush to the designated scene, and crack down on violating vehicles.

[0236] Step 6:

[0237] A server stores evidence data associated with the violation.

[0238] Input: Video and sensor data from the violation

[0239] Output: Confirmation of save completion

[0240] Specifically, the server stores the video and data of the violation in storage so that it can be viewed later. For example, it stores the video of the moment the red light was run and the speed sensor data.

[0241] The above are the specific processing steps of the automatic AI traffic monitoring system of the present invention, which realizes efficient fraud prevention and traffic monitoring.

[0242] (Application example 1)

[0243] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0244] In modern society, bank transfer fraud and traffic violations have become serious problems. Dealing with these problems often relies on manual monitoring, which is not very efficient. In particular, the number of victims of bank transfer fraud is increasing, especially among the elderly, and traffic violations also have a significant social impact as a cause of traffic accidents. To solve these problems, there is a need for a system that can prevent bank transfer fraud and detect traffic violations in real time and respond immediately.

[0245] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0246] In this invention, the server includes an input means for a user to input transfer information, a communication means by which the terminal transmits the transfer information to the server, a fraud detection means by which the server analyzes the reason for the transfer received, an analysis result return means by which the server returns the analysis result to the terminal, a display means by which the terminal displays the analysis result to the user, a monitoring means by which a police officer uses smart glasses to monitor traffic violations in real time, a data collection means by which the smart glasses collect data from surveillance cameras and sensors and transmit it to the server, and a notification means by which the server detects traffic violations using an AI model and notifies the police officer. This makes it possible to prevent transfer fraud and detect traffic violations in real time.

[0247] "Input means" refers to a device or method for a user to input data such as transfer information.

[0248] A "communication means" is a device or method for transmitting data from a terminal to a server.

[0249] "Fraud detection means" refers to a device or method that analyzes the transfer information received by the server and determines the possibility of fraud based on its contents.

[0250] The "analysis result return means" is a device or method for the server to return the analysis results to the terminal.

[0251] The "display means" is a device or method for displaying the analysis results received by the terminal from the server to the user.

[0252] "Monitoring means" means a device or method for officers to monitor traffic conditions in real time using smart glasses.

[0253] "Data collection means" refers to a device or method by which the smart glasses collect traffic data from surveillance cameras and sensors and transmit it to the server.

[0254] The "notification means" is a device or method for notifying police officers of traffic violations detected by the server.

[0255] An "AI model" is a model for data analysis that is trained using machine learning algorithms.

[0256] "Real-time" refers to processing and reacting simultaneously with real-world time.

[0257] "Bank transfer fraud" is a type of criminal activity that involves deceiving users and fraudulently withdrawing funds.

[0258] A "traffic violation" refers to any action or situation that violates a traffic law.

[0259] As an embodiment of the present invention, a fraud prevention and real-time traffic violation detection system is specifically configured. First, each component of the system is described, and then specific program processing is described.

[0260] Main components of the system

[0261] 1. Input method:

[0262] The user uses a device or method to input transfer information, such as an ATM or a smartphone app.

[0263] 2. Means of communication:

[0264] The terminal uses the internet or mobile network to send the transfer information to the server, using the HTTP protocol and secure communication via SSL / TLS.

[0265] 3. Fraud detection measures:

[0266] The server uses a machine learning model (e.g., a neural network trained with Keras) to analyze the reason for the incoming transfer. This model determines the likelihood of transfer fraud based on historical data.

[0267] 4. Method of returning analysis results:

[0268] The server has a means to return the analysis results to the device, and this process is also carried out via a secure communication protocol.

[0269] 5. Display means:

[0270] The terminal receives the analysis results from the server and displays them to the user, specifically on the smartphone screen or ATM display.

[0271] 6. Monitoring measures:

[0272] Police officers will monitor traffic conditions in real time using smart glasses, which are equipped with a built-in camera and display, through which AI models will detect traffic violations.

[0273] 7. Data Collection Methods:

[0274] The smart glasses collect traffic data from surveillance cameras and sensors and transmit it to a server in real time using wireless communication technologies such as Wi-Fi and Bluetooth.

[0275] 8. Means of notification:

[0276] The server notifies police officers of detected traffic violations using text displayed on the smart glasses' display and an audible alert.

[0277] Program processing explanation

[0278] In this invention, when a user transfers funds using an ATM or smartphone app, the input information is sent to a server via secure communications. The server uses an AI model to analyze the reason for the transfer and returns the results to the terminal. The user is informed of the security of the transfer on a display, and the transfer is canceled if there is a possibility of fraud.

[0279] Police officers can monitor traffic conditions in real time by wearing smart glasses. The glasses are equipped with a sophisticated camera that transmits video data of traffic conditions to a server. The server then uses an AI model to analyze the video data, and if a traffic violation is detected, a notification will appear on the smart glasses' display.

[0280] Specific examples

[0281] For example, suppose a police officer is using smart glasses at a busy intersection and a vehicle runs a red light. In this case, the camera in the smart glasses captures the vehicle running the red light, and the data is sent to the server in real time. The server uses an AI model to detect the traffic violation and displays a notification on the officer's smart glasses saying, "A red light has been detected!" The officer can then respond quickly and crack down on the violating vehicle.

[0282] Prompt Sentence Examples

[0283] For a wire transfer fraud detection model: "Is this wire transfer reason likely to be fraudulent?"

[0284] For traffic violation detection models: "Does this image contain a red light run?"

[0285] As a result, the present invention can efficiently prevent bank transfer fraud and detect traffic violations in real time.

[0286] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0287] Step 1:

[0288] The user enters transfer information. The user launches the ATM or smartphone app and enters information such as the transfer amount, recipient information, and reason for transfer. The entered information is obtained through the input means.

[0289] Input: User inputs transfer amount, recipient information, and reason for transfer.

[0290] Output: Transfer information data obtained via the input means.

[0291] Step 2:

[0292] The terminal sends the transfer information to the server. The terminal uses a secure communication protocol (e.g. HTTPS, SSL / TLS) to send the transfer information to the server in real time.

[0293] Input: Transfer information data.

[0294] Output: Transfer information data sent to the server.

[0295] Step 3:

[0296] The server analyzes the reason for the transfer received. The server analyzes the received transfer information using a generative AI model to check for possible fraud. This process includes data enrichment and text analysis to compare with historical data.

[0297] Input: Transfer information data received from the terminal.

[0298] Output: Fraud detection result (whether fraud is likely or not).

[0299] Step 4:

[0300] The server returns the analysis results to the terminal. The server generates the analysis results and returns them to the terminal via a secure communication means.

[0301] Input: Fraud detection results.

[0302] Output: Analysis result data returned to the device.

[0303] Step 5:

[0304] The terminal displays the analysis results to the user. The terminal displays the analysis results received from the server on the screen. The user checks them and, if deemed safe, completes the transfer. If there is a problem, a warning message is displayed.

[0305] Input: Analysis result data from the server.

[0306] Output: Analysis results and warning messages displayed on the screen.

[0307] Step 6:

[0308] Police officers monitor traffic conditions using smart glasses, which use built-in cameras to capture and collect data on traffic conditions in real time.

[0309] Input: Smart glasses camera footage.

[0310] Output: Collected real-time traffic data.

[0311] Step 7:

[0312] The smart glasses transmit the data obtained from the surveillance cameras and sensors to the server. The smart glasses use Wi-Fi or Bluetooth to transmit the collected data to the server.

[0313] Input: Collected real-time traffic data.

[0314] Output: Traffic data sent to the server.

[0315] Step 8:

[0316] The server uses an AI model to detect traffic violations. The server uses an AI model (e.g., computer vision algorithm) to analyze the transmitted video data and detect traffic violations.

[0317] Input: Traffic data sent from smart glasses.

[0318] Output: Detected traffic violation information.

[0319] Step 9:

[0320] The server notifies the police officer of the detected traffic violation information. The server generates the detected traffic violation information and displays the notification on the smart glasses display.

[0321] Input: Detected traffic violation information.

[0322] Output: Notifications shown on the smart glasses display.

[0323] By using these steps, the present invention can efficiently prevent bank transfer fraud and detect traffic violations in real time. This program process appropriately processes input data at each step and performs necessary data calculations, ultimately providing important information to users and police officers.

[0324] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0325] The present invention provides a system that combines a system for preventing fraud when users make bank transfers, a system for monitoring traffic conditions to detect traffic violations, and an emotion engine for recognizing user emotions. This not only improves the efficiency of police work and ensures the safety of citizens, but also improves convenience by taking the user's emotional state into consideration. The system of the present invention is realized by the following program, and its processing is performed as follows.

[0326] Transfer reason specification system and emotion engine

[0327] Program processing explanation

[0328] 1. The user opens an ATM or banking app.

[0329] Users can access the main menu by operating the ATM's touchscreen, or they can launch their banking app on their smartphone and log in.

[0330] 2. The terminal will display the transfer menu.

[0331] The terminal will display a "Transfer" option on the screen for the user to select.

[0332] 3. The user selects the "Transfer" option.

[0333] The user taps the "Transfer" button to proceed to the transfer information input screen.

[0334] 4. The terminal will display the transfer information input screen.

[0335] The terminal displays a screen with fields to enter the amount, recipient information, and reason for the transfer.

[0336] 5. The user enters the necessary bank transfer information.

[0337] The user enters information such as "100,000 yen," "Suzuki Ichiro," and "purchase price of the product" into the form on the screen.

[0338] 6. The terminal sends the entered information to the server.

[0339] The terminal encodes the input data and sends it to the server using a secure communication protocol.

[0340] 7. The device activates an emotion engine that recognizes the user's emotions.

[0341] The device uses sensors such as a camera and microphone to transmit the user's facial expressions and tone of voice to the emotion engine.

[0342] 8. The emotion engine analyzes the user's emotions.

[0343] The emotion engine analyzes facial and vocal data to identify the user's emotional state, such as whether they are tense, relaxed, or confused.

[0344] 9. The emotion engine sends the analysis results to the server.

[0345] The emotion engine encodes the analysis results and sends them to the server.

[0346] 10. The server analyzes the reason for the transfer and emotional data.

[0347] The server integrates and analyzes the received reason for the transfer and emotional data to assess the safety of the transfer and the possibility of fraud.

[0348] 11. The server determines the security of the transfer.

[0349] Based on the analysis results, the server determines whether the transfer is safe and sends the result to the terminal.

[0350] 12. The server returns the analysis results to the device.

[0351] The server encodes the safety judgment result and returns it to the terminal using a secure communication protocol.

[0352] 13. The device displays the analysis results to the user.

[0353] The terminal will display messages to the user such as "Transfer completed" or "Warning: Reason for transfer unclear," and will provide additional guidance and assistance as needed based on emotion data.

[0354] Specific examples

[0355] Suppose a user uses an ATM to transfer 50,000 yen to his friend, Tanaka Taro. When the user enters "50,000 yen," "Tanaka Taro," and "loan to friend" into the ATM, the terminal sends this information to the server. At the same time, the emotion engine analyzes the user's facial expression and tone of voice and determines that the user is relaxed. The server analyzes "loan to friend" and the relaxed emotional state, and if it determines that the transfer does not constitute fraud, it sends a result back to the terminal. The terminal displays the message "Transfer completed," and the transfer is carried out.

[0356] Automatic AI traffic monitoring system and emotion engine

[0357] Program processing explanation

[0358] 1. The server performs a scan to monitor traffic conditions in a specified area.

[0359] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[0360] 2. The device collects data from surveillance cameras and sensors.

[0361] The device acquires surveillance camera footage and sensor data in real time and sends it to the server.

[0362] 3. The server receives the collected data and prepares it for analysis.

[0363] The server stores the received video data and sensor data in a temporary database and prepares it for analysis.

[0364] 4. The server analyzes the data and determines whether a traffic law violation has occurred.

[0365] The server uses AI algorithms to analyze the video data and detect traffic violations such as running red lights or speeding.

[0366] 5. If the server detects a violation, it sends a notification to a nearby police officer.

[0367] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[0368] 6. The user (police officer) receives the notification and rushes to the scene.

[0369] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[0370] 7. The server stores evidence data related to the breach.

[0371] The server stores video and sensor data of violations and archives them for future reference.

[0372] 8. The server combines an emotion engine that recognizes the emotions of police officers.

[0373] The server uses an emotion engine to monitor the emotional state of officers as they conduct field enforcement.

[0374] 9. The emotion engine analyzes the emotions of police officers.

[0375] The emotion engine analyzes the officer's facial expressions and tone of voice to detect stress, fatigue, and other symptoms.

[0376] 10. The server stores the results of the emotion engine and monitors the health status of the officers.

[0377] The server records the analysis results of the emotion engine and continuously monitors the health status of the officers.

[0378] Specific examples

[0379] While the server monitors traffic conditions at a specific intersection, it detects a vehicle running a red light. Data from sensors and cameras is sent to the server in real time, and the server uses AI to confirm the red light has been run. The server then notifies nearby police officers that a red light has been run, and the officers rush to the scene to crack down on the violating vehicle. During this process, the emotion engine monitors the officer's stress level, and provides appropriate support if an abnormality is detected.

[0380] Through these specific processes, the system of the present invention realizes efficient fraud prevention and traffic monitoring, and also builds a safe and fair society that takes into account the emotional states of users and police officers.

[0381] The processing flow will be explained below.

[0382] Transfer reason specification system and emotion engine

[0383] Program processing explanation

[0384] Step 1:

[0385] The user opens an ATM or banking app.

[0386] Users interact with the ATM's touchscreen to access the main menu, or they open their banking app on their smartphone and log in to their account.

[0387] Step 2:

[0388] The terminal will display the transfer menu.

[0389] The terminal displays the transfer options on the screen and allows the user to select the "Transfer" button.

[0390] Step 3:

[0391] The user selects the "Transfer" option.

[0392] The user taps the "Transfer" button and proceeds to the next information input screen.

[0393] Step 4:

[0394] The terminal displays the transfer information input screen.

[0395] The terminal displays a screen containing input fields for entering the transfer amount, recipient information, and reason for the transfer.

[0396] Step 5:

[0397] The user enters the necessary transfer information.

[0398] The user enters "100,000 yen" in the amount field, "Suzuki Ichiro" in the recipient information field, and "purchase price of product" in the transfer reason field.

[0399] Step 6:

[0400] The terminal transmits the input information to the server.

[0401] The terminal transmits the input data to the server using a secure communication protocol.

[0402] Step 7:

[0403] The device activates an emotion engine that recognizes the user's emotions.

[0404] The device activates sensors such as a camera and microphone to transmit the user's facial expressions and tone of voice to the emotion engine.

[0405] Step 8:

[0406] The emotion engine analyzes the user's emotions.

[0407] The emotion engine analyzes the collected facial expression and voice data to determine the user's emotional state, such as whether they are nervous, relaxed, or confused.

[0408] Step 9:

[0409] The emotion engine sends the analysis results to the server.

[0410] The emotion engine encodes the analysis results and sends them to the server using a secure communication protocol.

[0411] Step 10:

[0412] The server receives and analyzes the transfer information and emotion data.

[0413] The server integrates and analyzes the individually received transfer information and emotional data to determine whether the transfer is suspected of being fraudulent.

[0414] Step 11:

[0415] The server determines the security of the transfer.

[0416] Based on the analysis results, the server evaluates whether the transfer is safe and sends the result back to the terminal.

[0417] Step 12:

[0418] The server returns the analysis results to the device.

[0419] The server encodes the result of the decision and returns it to the terminal using a secure communication protocol.

[0420] Step 13:

[0421] The device displays the analysis results to the user.

[0422] The terminal will display messages to the user such as "Transfer completed" or "Warning: Reason for transfer unclear" and will also display additional guidance and assistance messages as needed based on emotion data.

[0423] Automatic AI traffic monitoring system and emotion engine

[0424] Program processing explanation

[0425] Step 1:

[0426] The server performs a scan to monitor traffic conditions in the designated area.

[0427] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[0428] Step 2:

[0429] The device collects data from surveillance cameras and sensors.

[0430] The terminal acquires surveillance camera video data and sensor data in real time and sends it to the server.

[0431] Step 3:

[0432] The server receives the collected data and prepares it for analysis.

[0433] The server stores the received video data and sensor data in virtual memory and prepares it for analysis.

[0434] Step 4:

[0435] The server analyzes the data and determines whether any traffic laws have been violated.

[0436] The server uses AI algorithms to analyze the collected video data and detect traffic violations such as running red lights and speeding.

[0437] Step 5:

[0438] If the server detects a violation, it sends a notification to nearby police officers.

[0439] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[0440] Step 6:

[0441] The user (police officer) receives a notification and rushes to the scene.

[0442] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[0443] Step 7:

[0444] A server stores evidence data associated with the violation.

[0445] The server stores video and sensor data of violations and archives them for future evidence.

[0446] Step 8:

[0447] The server combines an emotion engine that recognizes the emotions of the police officers.

[0448] The server uses an emotion engine to monitor emotional data as police officers conduct enforcement in the field.

[0449] Step 9:

[0450] An emotion engine analyzes the emotions of police officers.

[0451] The emotion engine analyzes an officer's facial expressions and tone of voice to identify stress and fatigue.

[0452] Step 10:

[0453] The server stores the results of the emotion engine and monitors the health of the officers.

[0454] The server records the emotion engine's analysis results and continuously tracks the officers' health status.

[0455] Through these specific processing steps, the system of the present invention effectively realizes fraud prevention and traffic monitoring, and supports safe and fair operation taking into account the emotional states of users and police officers.

[0456] Example 2

[0457] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0458] Conventional bank transfer systems and traffic monitoring systems have difficulty in detecting fraud and traffic violations because it is difficult for users to clearly state the reason for a transfer and to monitor traffic conditions in real time. Furthermore, they are unable to take into account the emotional state of users and police officers, which has led to challenges in improving operational efficiency and safety.

[0459] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0460] In this invention, the server comprises means for a user to input transfer information and a reason for transfer using an information processing device, communication means for a terminal to transmit the input transfer information to the server, emotion recognition means for the terminal to acquire the user's facial expression and voice data, emotion analysis means for analyzing the facial expression and voice data acquired by the emotion recognition means, communication means for transmitting the user's emotion data analyzed by the emotion analysis means to the server, fraud detection means for the server to analyze the transfer reason and the emotion data by integrating them, analysis result return means for the server to return the analysis results to the terminal, display means for the terminal to display the analysis results to the user, and The system includes a means for inputting the information, a communication means for the terminal to transmit the input information to a server in real time, a monitoring means for the server to monitor traffic conditions using an AI algorithm, a notification means for the server to detect violations of traffic laws from the monitoring results and notify police officers, a storage means for the server to store evidential data related to traffic violations, a means for completing the transfer if it is determined to be safe based on the analysis results and displaying a warning and stopping the transfer if fraud is suspected, a means for the server to collect and analyze data obtained from surveillance cameras and sensors in real time, and a means for sending a notification to local police officers or remote control devices when a traffic violation is detected. This enables a safe and efficient system that ensures the safety of transfers, effectively monitors and detects violations of traffic laws, and takes into account the emotional states of users and police officers.

[0461] A "user" is an individual or organization that uses the system and is the entity that performs bank transfer operations and receives traffic monitoring data.

[0462] "Information processing device" refers to all hardware and software used for calculations and data processing, and specifically includes ATMs, smartphones, computers, etc.

[0463] A "terminal" is a device that is directly operated by a user, and is used to input and display information and communicate with a server.

[0464] "Communication means" refers to protocols and devices for transmitting and receiving data, including networks, modems, Wi-Fi, and related software.

[0465] "Emotion recognition means" refers to devices such as sensors, cameras, and microphones that acquire the user's facial expressions and voice data and analyze their emotions.

[0466] "Emotion analysis means" refers to algorithms and software for analyzing acquired facial and voice data to identify the user's emotional state.

[0467] A "server" is a high-performance computer system that collects, stores, analyzes, and communicates data, and includes a central processing unit.

[0468] "Fraud detection methods" refers to algorithms and software that analyze transfer reasons and emotional data to assess the likelihood of fraudulent activity.

[0469] "Means for returning analysis results" refers to a communication protocol and related devices for the server to return the analysis results to the user.

[0470] "Display means" refers to devices and software for visually displaying analysis results, warning messages, etc. to the user.

[0471] "Monitoring means" refers to cameras, sensors, and associated software used to monitor traffic conditions in real time and collect data.

[0472] "Means of notification" refers to communications protocols and related devices for notifying police officers when a traffic violation is detected.

[0473] "Storage means" refers to data storage and software for storing evidentiary data related to traffic violations and making it available for reference when necessary.

[0474] A "remote control device" is a device for dealing with traffic violations remotely, including traffic light control systems and automobile control systems.

[0475] The system of the present invention combines a traffic violation detection system that monitors traffic conditions and prevents fraud when making bank transfers with an emotion engine that recognizes the user's emotional state. This not only improves the efficiency of police work and ensures the safety of citizens, but also improves convenience by taking the user's emotional state into consideration.

[0476] The system includes the following main components:

[0477] 1. User: Enters data at an ATM or through a banking app.

[0478] 2. Terminal: A device operated by the user that inputs and displays transfer information and acquires emotional data. Examples include ATMs, smartphones, and computers.

[0479] 3. Server: A central computer system that collects, stores, analyzes, and communicates data.

[0480] Transfer reason specification system and emotion engine

[0481] Hardware and Software

[0482] The user uses an information processing device (an ATM or a smartphone or computer with a banking app running).

[0483] The terminal uses a touch screen and keyboard to input transfer information and the reason for the transfer.

[0484] The device collects the user's facial expressions using a camera and their tone of voice using a microphone, and sends these to emotion recognition software (e.g., Google® Cloud Vision API or Amazon Rekognition).

[0485] The server uses AI algorithms (TENSORFLOW (registered trademark) and PyTorch) to analyze the reason for transfer and emotional data in real time.

[0486] Specific examples

[0487] Suppose a user wants to use an ATM to transfer 50,000 yen to their friend, Taro Tanaka. The user enters "50,000 yen," "Taro Tanaka," and "loan to friend" in the ATM's "Transfer" menu. At the same time, the device's emotion recognition function analyzes the user's facial expressions and voice and determines that they are relaxed. This data is sent to a server, which uses AI to analyze the safety of the transfer. If it determines that the transfer is not fraudulent, a "Transfer Completed" notification is displayed on the device and the transfer is carried out.

[0488] Automatic AI traffic monitoring system and emotion engine

[0489] Hardware and Software

[0490] The device collects traffic data from surveillance cameras and sensors and sends it to a server.

[0491] The server uses a database (such as AWS (registered trademark) S3) and analysis software (such as OpenCV and YOLOv3 model) to store and analyze the data collected in real time.

[0492] A communication system in which a server detects violations of traffic laws and notifies police officers.

[0493] Specific examples

[0494] The server monitors traffic conditions at specific intersections and detects vehicles that run red lights. Data from sensors and cameras is sent to the server in real time, and AI confirms that the red light has been run. The server then sends a notification to nearby police officers that a red light has been run. The officers then rush to the scene and crack down on the violating vehicle. At this time, the emotion engine monitors the stress level of the officers, and if an abnormality is detected, appropriate support is provided.

[0495] Example prompts for generative AI models

[0496] "I would like to transfer 50,000 yen to Taro Tanaka using an ATM. However, please tell me the process to check whether this transfer is fraudulent."

[0497] "Please tell me in detail the specific processing steps of an AI system that detects traffic violations using surveillance cameras placed at specific intersections."

[0498] In this way, the system of the present invention realizes efficient fraud prevention and traffic monitoring, and builds a safe and fair society that takes into account the emotional states of users and police officers.

[0499] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0500] Transfer reason specification system and emotion engine

[0501] Processing flow and specific operations

[0502] Step 1:

[0503] The user opens an ATM or banking app.

[0504] Input: Authentication begins when you insert your card into an ATM or launch your banking app on your smartphone.

[0505] Output: After authentication, the main menu will be displayed.

[0506] Specific actions: The user operates the ATM's touch screen to access the main menu, or logs in using their banking app by entering their ID and password.

[0507] Step 2:

[0508] The terminal will display the transfer menu.

[0509] Input: The authenticated user's request.

[0510] Output: The transfer menu will appear on the screen.

[0511] What it does: The terminal displays the "Transfer" option on the screen for the user to select.

[0512] Step 3:

[0513] The user selects the "Transfer" option.

[0514] Input: Select Transfer menu.

[0515] Output: The transfer information input screen will be displayed.

[0516] Specific operation: The user taps the "Transfer" button and proceeds to the screen to enter transfer information.

[0517] Step 4:

[0518] The terminal displays the transfer information input screen.

[0519] Enter: Select a transfer option.

[0520] Output: Input fields for amount, recipient information, and transfer reason are displayed.

[0521] What it does: The terminal displays a screen with fields for entering the amount, recipient information, and reason for the transfer.

[0522] Step 5:

[0523] The user enters the necessary transfer information.

[0524] Input: Enter the transfer amount, recipient information, and reason for transfer.

[0525] Output: The input data is saved to the device.

[0526] Specific operation: The user enters information such as "50,000 yen," "Taro Tanaka," and "loan to a friend" into the form on the screen.

[0527] Step 6:

[0528] The terminal transmits the input information to the server.

[0529] Input: Transfer information entered by the user.

[0530] Output: The transfer information is sent to the server.

[0531] Specific operation: The terminal encrypts the input data using the SSL / TLS protocol and sends it to the server.

[0532] Step 7:

[0533] The device activates an emotion engine that recognizes the user's emotions.

[0534] Input: User's facial expression and voice data.

[0535] Output: Emotion recognition data is sent to the emotion engine.

[0536] Specific operation: The device's camera captures the user's facial expressions, and the microphone captures the user's voice. This data is then sent to the emotion engine.

[0537] Step 8:

[0538] The emotion engine analyzes the user's emotions.

[0539] Input: facial expression and voice data.

[0540] Output: Emotional state analysis result.

[0541] What it does: The emotion engine uses facial recognition and voice analysis to determine whether the user is relaxed or tense.

[0542] Step 9:

[0543] The emotion engine sends the analysis results to the server.

[0544] Input: Emotional state analysis results.

[0545] Output: Emotion data sent to the server.

[0546] Specific operation: The emotion engine encodes the analysis results and sends them to the server.

[0547] Step 10:

[0548] The server analyzes the reason for the transfer and emotional data.

[0549] Input: Reason for transfer, emotional data.

[0550] Output: A rating of the transfer's safety.

[0551] How it works: The server uses an AI model to comprehensively analyze the reason for the transfer and emotional data to assess the likelihood of fraud.

[0552] Step 11:

[0553] The server determines the security of the transfer.

[0554] Input: A rating of the transfer's safety.

[0555] Output: Safety-based decision result.

[0556] Specific operation: The server determines the safety of the transfer based on the evaluation results and prepares to send the results to the terminal.

[0557] Step 12:

[0558] The server returns the analysis results to the device.

[0559] Input: Safety decision result.

[0560] Output: The result data sent to the terminal.

[0561] Specific operation: The server encodes the security judgment result and sends it to the terminal.

[0562] Step 13:

[0563] The device displays the analysis results to the user.

[0564] Input: Analysis results received from the server.

[0565] Output: The resulting message displayed to the user.

[0566] What it does: The terminal will display a message such as "Transfer complete" or "Warning: Reason for transfer unclear" and provide additional guidance or assistance as needed.

[0567] Automatic AI traffic monitoring system and emotion engine

[0568] Processing flow and specific operations

[0569] Step 1:

[0570] The server performs a scan to monitor traffic conditions in the designated area.

[0571] Input: Specification of the monitoring area.

[0572] Output: Monitoring data collection begins.

[0573] Specific operation: The server activates the surveillance cameras and sensors placed in the designated area and starts collecting data in real time.

[0574] Step 2:

[0575] The device collects data from surveillance cameras and sensors.

[0576] Input: Data from surveillance cameras and sensors.

[0577] Output: Collected data sent to the server.

[0578] Specific operation: The device acquires video data from surveillance cameras and speed information from radar sensors, and sends this data to a server.

[0579] Step 3:

[0580] The server receives the collected data and prepares it for analysis.

[0581] Input: Collected monitoring data.

[0582] Output: Database updates required for analysis.

[0583] Specific operation: The server stores the collected data in temporary data storage (e.g., AWS S3) and prepares it for analysis.

[0584] Step 4:

[0585] The server analyzes the data and determines whether any traffic laws have been violated.

[0586] Input: Stored monitoring data.

[0587] Output: Traffic law violation detection results.

[0588] Specific operation: The server uses AI algorithms (e.g., OpenCV or YOLOv3 models) to analyze video data and detect traffic violations such as running red lights or speeding.

[0589] Step 5:

[0590] If the server detects a violation, it sends a notification to nearby police officers.

[0591] Input: Traffic violation detection results.

[0592] Output: Notification sent to the officer.

[0593] Specific operation: When a violation is detected, the server sends a notification containing the details of the violation and GPS information to the device of a nearby police officer.

[0594] Step 6:

[0595] The user (police officer) receives a notification and rushes to the scene.

[0596] Input: Notification from the server.

[0597] Output: Police arrive on scene and take action.

[0598] Specific operation: The police officer receives a notification from the server and rushes to the designated location to crack down on traffic violators.

[0599] Step 7:

[0600] A server stores evidence data associated with the violation.

[0601] Input: Evidence data related to traffic violations.

[0602] Output: Stored evidence data.

[0603] Specific operation: The server stores video data and sensor data related to violations for a long period of time, making it available for reference when needed.

[0604] Step 8:

[0605] The server combines an emotion engine that recognizes the emotions of the police officers.

[0606] Input: Officer facial and voice data.

[0607] Output: Recognized emotion data.

[0608] How it works: When police officers conduct a police operation, the server activates the emotion engine to monitor their facial expressions and tone of voice, and the collected data is sent to the emotion analysis engine.

[0609] Step 9:

[0610] An emotion engine analyzes the emotions of police officers.

[0611] Input: facial expression and voice data.

[0612] Output: Emotional state analysis result.

[0613] How it works: The emotion engine uses facial recognition technology and voice analysis algorithms to identify officer stress and fatigue.

[0614] Step 10:

[0615] The server stores the results of the emotion engine and monitors the health of the officers.

[0616] Input: Emotional state analysis results.

[0617] Output: Stored officer health data.

[0618] What it does: The server stores the analysis results in a database, continuously monitors the health status of officers, and issues an alert to provide appropriate support if an abnormality is detected.

[0619] (Application example 2)

[0620] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0621] In modern society, preventing fraud during bank transfers, monitoring and detecting traffic violations, and ensuring safety in self-driving vehicles are important challenges. However, existing systems address each problem individually and do not provide a consistent solution that takes into account the emotional state of the user or driver. Therefore, a more effective and comprehensive system is needed.

[0622] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes input means for the user to input bank transfer information, communication means by which the terminal transmits the bank transfer information to the server, fraud detection means for analyzing the reason for the bank transfer received by the server, analysis result return means by which the server transmits the analysis results to the terminal, display means by which the terminal displays the analysis results to the user, collection means by which the terminal collects image information and audio information from inside the vehicle, emotion analysis means by which the emotion engine analyzes the collected data to identify the emotional state, and vehicle control means for controlling the vehicle based on the emotion analysis results. This enables fraud prevention during bank transfers, detection of traffic violations, and comprehensive safety measures that take into account the emotional states of drivers and passengers in self-driving vehicles.

[0623] "User" means a person who uses the system to make bank transfers or operate self-driving vehicles.

[0624] "Transfer information" refers to detailed information required for a user to make a transfer, such as the account number of the transfer recipient, the transfer amount, and the reason for the transfer.

[0625] "Input means" refers to a device or interface through which a user inputs transfer information. Specifically, this includes ATMs and smartphone applications.

[0626] "Communication means" refers to the communication protocol and network functions that allow the terminal to send transfer information to the server.

[0627] "Fraud detection means" refers to algorithms or programs that analyze the reason for transfer received by the server and evaluate and detect the possibility of fraud.

[0628] "Means for returning analysis results" refers to the communication protocol and network functions that allow the server to return analysis results to the terminal.

[0629] The "display means" refers to a display or screen that the terminal uses to display the analysis results to the user.

[0630] "In-vehicle image information and audio information" refers to image and audio data of the driver and passengers collected by cameras and microphones installed inside the vehicle.

[0631] "Collection means" refers to cameras and microphones used to collect image and audio information inside the vehicle, as well as associated sensors and software.

[0632] "Emotion analysis means" refers to AI algorithms or programs for analyzing the emotional state of drivers and passengers from collected image and audio information.

[0633] "Vehicle control means" refers to a device or program for controlling the speed and behavior of a vehicle based on the emotion analysis results.

[0634] "Traffic condition data" refers to information such as traffic flow, traffic light conditions, and vehicle positions collected from surveillance cameras and sensors.

[0635] "Emergency services" refers to services such as police, fire, and ambulances that respond quickly in the event of an accident or dangerous situation.

[0636] An "emotion engine" refers to a program or algorithm for implementing emotion analysis means, which analyzes emotional states from collected image and audio data.

[0637] "Analysis means" refers to the systems and algorithms used to integrate emotion analysis results with traffic data and analyze them using an AI model.

[0638] This invention is a comprehensive system for preventing fraudulent bank transfers, monitoring traffic violations, and improving safety in self-driving vehicles. Each means and process of the system will be described below.

[0639] Bank transfer fraud prevention system

[0640] The user enters transfer information using an ATM or bank app. The entered information is sent to the server via the terminal. The server analyzes the reason for the transfer using fraud detection means. The analysis results are sent back from the server to the terminal, which displays them to the user. If the server detects the possibility of fraud in the transfer information entered by the user, the terminal displays a warning to the user and cancels the transfer.

[0641] Traffic Monitoring System

[0642] The server collects and analyzes traffic data from surveillance cameras and sensors in real time. The server is equipped with AI algorithms that detect traffic violations, such as running red lights and speeding, in real time. Detected violations are reported to police officers or automated control devices. Evidence data related to violations is stored on the server for future reference.

[0643] Safety management systems for autonomous vehicles

[0644] Emotion Monitoring

[0645] The device uses cameras and microphones installed inside the autonomous vehicle to collect image and audio information from the driver and passengers. The collected data is analyzed by an emotion engine to identify the emotional state of the driver and passengers. The behavior of the autonomous vehicle is controlled based on this emotional state. For example, if the emotion engine determines that the driver is fatigued or stressed, it may slow down the vehicle or suggest a break.

[0646] Emergency response

[0647] The server integrates and analyzes traffic data and emotion data to detect accidents and emergencies. If an emergency occurs, the server automatically notifies the police and emergency services. If necessary, an emergency assistance message is displayed to the user.

[0648] Hardware and software used

[0649] Camera and microphone: To monitor what's happening inside the car in real time.

[0650] OpenCV: A library for real-time image processing.

[0651] Emotion Analysis Engine (EmotionEngine): A software module for analyzing the emotional state of drivers and passengers.

[0652] Traffic Monitoring System (TrafficMonitor): A system for monitoring surrounding traffic conditions in real time.

[0653] Emergency Response System (EmergencyResponse): A software module for responding to accidents and emergency situations.

[0654] Specific examples

[0655] A concrete example would be a scenario where an autonomous vehicle is traveling on a highway and the driver is fatigued, and the vehicle detects this emotional state and slows down, encouraging the driver to take a break.

[0656] Prompt Sentence Examples

[0657] "A self-driving vehicle is driving down the highway and the driver's face looks fatigued. What should the self-driving vehicle do next?"

[0658] By implementing this invention, it will be possible to prevent fraud during bank transfers, detect traffic violations, and implement comprehensive safety measures in autonomous vehicles that take into account the emotional state of drivers and passengers.

[0659] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0660] Step 1:

[0661] A user opens an ATM or banking app. They either interact with the ATM's touchscreen to access the main menu or launch the banking app on their smartphone and log in. Inputs include the user's login information and interface interactions. Outputs include the ATM or app's main menu screen.

[0662] Step 2:

[0663] The terminal displays a transfer menu. The terminal displays a "Transfer" option on the screen for the user to select. Input includes the user's selection on the main menu. Output includes a screen where transfer information can be entered.

[0664] Step 3:

[0665] The user selects the "Transfer" option. The user taps the "Transfer" button to proceed to the transfer information input screen. The input includes the user's selection. The output displays the transfer information input screen.

[0666] Step 4:

[0667] The terminal displays a screen for inputting transfer information. The terminal displays a screen containing input fields for the amount, recipient information, and reason for transfer. The input contains the transfer information format held by the system. The output is the screen for inputting transfer information.

[0668] Step 5:

[0669] The user enters the necessary transfer information. The user enters information such as "100,000 yen," "recipient's name," and "purchase price of the product" into the form on the screen. The input includes the transfer information provided by the user. The output is generated as transfer information data.

[0670] Step 6:

[0671] The terminal sends the input information to the server. The terminal encodes the input data and sends it to the server using a secure communication protocol. The input is the encoded transfer information. The output is the transfer information data to be sent to the server.

[0672] Step 7:

[0673] The terminal collects image and audio information from inside the vehicle. Using cameras and microphones installed inside the vehicle, the terminal collects image and audio information from the driver and passengers. The input is real-time data from the cameras and microphones. The output is the collected image and audio data.

[0674] Step 8:

[0675] The emotion engine analyzes the collected data to identify the emotional state. The emotion engine analyzes image and audio information to identify the emotional state, for example, whether the driver is relaxed or tense. The input is the collected image and audio data. The output is the identified emotional state data.

[0676] Step 9:

[0677] The server analyzes the received reason for the transfer. The server uses fraud detection means to analyze the reason for the transfer and evaluate the likelihood of fraud. The inputs are the reason for the transfer and emotional state data. The output is an analysis result regarding the likelihood of fraud.

[0678] Step 10:

[0679] The server returns the analysis results to the device. The server encodes the analysis results and returns them to the device using a secure communication protocol. The input is the analysis results. The output is the returned analysis result data.

[0680] Step 11:

[0681] The terminal displays the analysis results to the user. The terminal displays messages such as "Transfer completed" or "Warning: The reason for transfer is unclear" to the user. It also displays additional guidance or assistance as needed based on the emotion data. The input is the returned analysis result data. The output is the message or guidance to be displayed.

[0682] Step 12:

[0683] The system controls the vehicle based on the emotion analysis results. If the emotional state is recognized as abnormal, it controls the vehicle speed or suggests a break. The input is the identified emotional state data. The output is the vehicle speed control or a suggested message.

[0684] Step 13:

[0685] The server collects and analyzes traffic condition data in real time. The server collects traffic condition data from surveillance cameras and sensors and analyzes it using an AI algorithm. The input is data from surveillance cameras and sensors. The output is data on traffic violation detection results.

[0686] Step 14:

[0687] Detects traffic violations and sends notifications to police officers or automated control devices. When the server detects a traffic violation, it sends a notification to a nearby police officer or automated control device. As input, it has the detection result data. As output, it has the notification data to be sent.

[0688] Step 15:

[0689] Stores evidence data related to violations. The server stores video data and sensor information related to traffic violations and archives it for future reference. The input is the collected and analyzed evidence data. The output is the stored archive data.

[0690] Step 16:

[0691] Automatically notify police and emergency services when an accident or emergency situation occurs. The server sends a notification to police and emergency services when an accident is detected, and appropriate assistance is provided. The input is the accident detection data. The output is the sent emergency notification data.

[0692] Step 17:

[0693] The user follows the messages and suggestions they receive from the system. The user receives suggestions and notifications from the device and takes action based on them. The input is the message or suggestion from the device. The output is the user's actions.

[0694] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0695] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0696] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0697] [Second embodiment]

[0698] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0699] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0700] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0701] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0702] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0703] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0704] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0705] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0706] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0707] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0708] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0709] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0710] The present invention provides a system for preventing fraud when users make bank transfers, and a system for monitoring traffic conditions to detect traffic violations, thereby improving the efficiency of police work and ensuring the safety of citizens. The system of the present invention is implemented by a series of programs, and its processing is as follows.

[0711] System for specifying the reason for transfer

[0712] Program processing explanation

[0713] 1. The user opens an ATM or banking app.

[0714] Users first open the ATM's main screen or their bank's app on their smartphone to begin accessing the system.

[0715] 2. The terminal will display the transfer menu.

[0716] The terminal presents the user with a menu of transfer options, from which the user selects "Transfer."

[0717] 3. The user enters the transfer information.

[0718] The user inputs the transfer amount, the recipient's information, and the reason for the transfer. For example, the user inputs information such as "100,000 yen to Ichiro Suzuki as the recipient, and the reason is the purchase price of a product."

[0719] 4. The terminal sends the entered information to the server.

[0720] The terminal transmits all entered information to the server using a secure communication protocol.

[0721] 5. The server receives and analyzes the transfer information.

[0722] The server applies fraud detection algorithms to analyze the reason for the transfer received, checking reasons such as "purchase of goods" or "repayment to a friend," and compares them with historical data.

[0723] 6. The server determines whether the transfer is safe.

[0724] Based on the analysis, the server determines whether the transfer is safe or suspicious. If it is safe, the transfer proceeds, otherwise a warning is issued.

[0725] 7. The server sends the results back to the device.

[0726] The server returns the security result to the terminal, for example, a message saying "The transfer has been approved" or "The reason for the transfer is unclear. Please check again."

[0727] 8. The terminal displays the results to the user.

[0728] The terminal displays the result received from the server to the user, for example, displaying a message such as "Transfer completed" or "Warning: The reason for transfer is unclear" on the screen.

[0729] Specific examples

[0730] Suppose a user uses an ATM to transfer 50,000 yen to his friend, Tanaka Taro. When the user enters "50,000 yen," "Tanaka Taro," and "loan to friend" into the ATM, the terminal sends this information to the server. The server analyzes "loan to friend" and, if it determines that the transfer is not fraudulent, it sends a result back to the terminal. The terminal displays the message "Transfer completed," and the transfer is carried out.

[0731] Automatic AI Traffic Monitoring System

[0732] Program processing explanation

[0733] 1. The server performs a scan to monitor traffic conditions in a specified area.

[0734] The server synchronizes all cameras and sensors in the specified city or intersection and begins collecting data in real time.

[0735] 2. The device collects data from surveillance cameras and sensors and sends it to the server.

[0736] The device transmits video data from surveillance cameras and information obtained from sensors to a server in real time.

[0737] 3. The server analyzes the data and determines whether a traffic law violation has occurred.

[0738] The server uses AI and machine learning models to analyze video and sensor data to detect traffic violations, such as running red lights or speeding.

[0739] 4. If the server detects a violation, it notifies nearby police officers.

[0740] When a violation is detected, the server immediately notifies nearby police officers of the incident, including the location and details of the violation.

[0741] 5. The user (police officer) receives the notification and rushes to the scene.

[0742] Once police receive the notification, they will rush to the designated location and crack down on the offending vehicle.

[0743] 6. The server stores evidence data related to the breach.

[0744] The server stores footage and data of violations so that they can be viewed later.

[0745] Specific examples

[0746] While the server monitors traffic conditions at a specific intersection, it detects vehicles that run red lights. Data from sensors and cameras is sent to the server in real time, and the server uses AI to confirm that a red light has been run. The server then sends a notification to a nearby police officer that a red light has been run, and the officer rushes to the scene to crack down on the violating vehicle. At that time, the server stores the video data of the red light run.

[0747] Through these specific processes, the system of the present invention provides efficient fraud prevention and traffic monitoring.

[0748] The processing flow will be explained below.

[0749] System for specifying the reason for transfer

[0750] Program processing explanation

[0751] Step 1:

[0752] The user opens an ATM or banking app.

[0753] Users operate the ATM's touchscreen to access the main menu, or they launch their banking app on their smartphone and log in.

[0754] Step 2:

[0755] The terminal will display the transfer menu.

[0756] The terminal will display a "Transfer" option on the screen for the user to select.

[0757] Step 3:

[0758] The user selects the "Transfer" option.

[0759] The user taps the "Transfer" button to proceed to the transfer information input screen.

[0760] Step 4:

[0761] The terminal displays the transfer information input screen.

[0762] The terminal displays a screen with fields to enter the amount, recipient information, and reason for the transfer.

[0763] Step 5:

[0764] The user enters the necessary transfer information.

[0765] The user enters information such as "100,000 yen," "Suzuki Ichiro," and "purchase price of the product" into the form on the screen.

[0766] Step 6:

[0767] The terminal transmits the input information to the server.

[0768] The terminal encodes the input data and sends it to the server using a secure communication protocol.

[0769] Step 7:

[0770] The server receives the transfer information.

[0771] The server decodes the received data and prepares it for analysis.

[0772] Step 8:

[0773] The server analyzes the reason for the transfer.

[0774] The server applies fraud detection algorithms to analyze the input reason for the transfer and assess its safety.

[0775] Step 9:

[0776] The server determines the security of the transfer.

[0777] The server will then use the analysis results to determine whether the transfer is safe or not, and if it is determined to be fraudulent, it will also provide the reason for this.

[0778] Step 10:

[0779] The server returns the analysis results to the device.

[0780] The server encodes the safety judgment result and returns it to the terminal using a secure communication protocol.

[0781] Step 11:

[0782] The device displays the analysis results to the user.

[0783] The terminal will display a message to the user such as "Transfer completed" or "Warning: Reason for transfer unclear."

[0784] Automatic AI Traffic Monitoring System

[0785] Program processing explanation

[0786] Step 1:

[0787] The server performs a scan to monitor traffic conditions in the designated area.

[0788] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[0789] Step 2:

[0790] The device collects data from surveillance cameras and sensors.

[0791] The device acquires surveillance camera footage and sensor data in real time and sends it to the server.

[0792] Step 3:

[0793] The server receives the collected data and prepares it for analysis.

[0794] The server stores the received video data and sensor data in a temporary database and prepares it for analysis.

[0795] Step 4:

[0796] The server analyzes the data and determines whether any traffic laws have been violated.

[0797] The server uses AI algorithms to analyze the video data and detect traffic violations such as running red lights or speeding.

[0798] Step 5:

[0799] If the server detects a violation, it sends a notification to nearby police officers.

[0800] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[0801] Step 6:

[0802] The user (police officer) receives a notification and rushes to the scene.

[0803] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[0804] Step 7:

[0805] A server stores evidence data associated with the violation.

[0806] The server stores video and sensor data of violations and archives them for future reference.

[0807] By these steps, the system of the present invention realizes the user's bank transfer activity and traffic situation monitoring efficiently and safely.

[0808] Example 1

[0809] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0810] Conventional bank transfer systems and traffic monitoring systems are unable to efficiently detect bank transfer fraud and traffic law violations, resulting in insufficient safety for users and the general public. With the rise in bank transfer fraud, real-time fraud detection is required. Furthermore, when detecting traffic law violations, issues arise, such as delayed police response and inability to reliably preserve evidence of violations. To solve these problems, systems using more advanced technology are needed.

[0811] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0812] In this invention, the server includes fraud detection means for analyzing the received reason for transfer, safety determination means for determining the safety of the transfer based on the analysis results, and monitoring means for monitoring traffic conditions to detect violations. This makes it possible to detect transfer fraud in real time, ensure safe transfers, and quickly detect and notify violations of traffic laws.

[0813] "User" refers to an individual or corporation that uses the system to perform transfer operations or check traffic information.

[0814] "Terminal" refers to a device used by a user to input transfer information or display traffic information, such as an ATM or smartphone application.

[0815] A "server" is a computer system that receives and analyzes bank transfer information and traffic information.

[0816] "Input means" refers to the interface (keyboard, touch panel, etc.) through which the user inputs transfer information.

[0817] "Communication means" refers to the network communication protocol (e.g., HTTPS) used by the terminal to send transfer information to the server.

[0818] "Fraud detection means" refers to a function including algorithms and programs that allow the server to analyze the reason for the transfer and detect the possibility of fraud.

[0819] The "analysis result return means" refers to a function by which the server returns the analysis results to the terminal.

[0820] "Display means" refers to a screen or interface that the terminal uses to display the analysis results received from the server to the user.

[0821] "Safety determination means" refers to the function that the server uses to determine the safety of a transfer based on the analysis results.

[0822] "Means for issuing a warning" refers to a function for sending a warning to the user if the server determines that a transfer is suspicious.

[0823] "Monitoring means" refers to the function that enables the server to use AI to monitor traffic conditions in real time and detect violations.

[0824] "Notification means" refers to a function that notifies nearby police officers when the server detects a traffic law violation.

[0825] "Storage means" refers to the storage or database in which the server stores evidence data related to the violation.

[0826] The present invention provides a system for preventing fraud when users make transfers, and a system for monitoring traffic conditions to detect traffic violations. This system is implemented by a series of programs as follows:

[0827] First, a user initiates access to the system by opening an ATM or a banking app on their smartphone. Next, the terminal presents the user with a transfer option, and the user enters the transfer information (transfer amount, recipient information, and reason for the transfer) from the transfer menu. For example, a user might enter "50,000 yen," "Taro Tanaka," and "loan to a friend" at an ATM. The information entered is transmitted from the terminal to the server using a secure communication protocol (e.g., HTTPS).

[0828] The server analyzes the received transfer information in real time and applies a fraud detection algorithm. This algorithm compares the transfer reason, such as "loan to a friend," with past data to determine whether it is likely to be fraudulent. The server then returns the result of the safety assessment to the device. The device then displays the result to the user, displaying a message such as "Transfer completed" or "Warning: Transfer reason unclear."

[0829] Furthermore, in traffic monitoring systems, the server synchronizes surveillance cameras and sensors in designated cities and intersections and begins collecting data in real time. This allows devices to transmit video data from surveillance cameras and information from sensors to the server in real time. The server then uses AI and machine learning models to analyze the collected video data and sensor data and detect violations of traffic laws, such as running red lights or speeding. If a violation is detected, the server notifies nearby police officers, who then include the location and details of the violation. Police officers then rush to the scene and crack down on the offending vehicle.

[0830] As a specific example, a server may detect a vehicle running a red light while monitoring traffic conditions at a specific intersection. Data from surveillance cameras and sensors is sent to the server in real time, and the server uses AI to confirm the violation. This violation information is notified to police officers, who rush to the scene and crack down on the violating vehicle. At that time, the server stores the video data of the red light violation.

[0831] Examples of prompts for generative AI models include:

[0832] "Please tell me more about your fraud prevention system. If a user goes to an ATM to transfer 50,000 yen to his friend Taro Tanaka, how would fraud prevention work?"

[0833] "Please provide details about your automated AI traffic monitoring system. If a red light is detected at a particular intersection, how will the system respond?"

[0834] With these specific processing and prompt sentence examples, the system of the present invention provides efficient fraud prevention and traffic monitoring, ensuring the safety of users and citizens.

[0835] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0836] Step 1:

[0837] The user opens an ATM or banking app.

[0838] Input: User action (accessing an ATM or launching a banking app)

[0839] Output: ATM main screen or initial screen of bank app

[0840] Specifically, the user accesses the nearest ATM or launches a banking app on their smartphone, for example, by tapping the app on their smartphone at home.

[0841] Step 2:

[0842] The terminal will display the transfer menu.

[0843] Input: User request (Display transfer screen on ATM or app)

[0844] Output: Display of transfer options

[0845] Specifically, buttons such as "Transfer" and "Remittance" will appear on the ATM screen or smartphone display, and the user will select one of them.

[0846] Step 3:

[0847] The user enters the transfer information.

[0848] Input: Transfer information entered by the user (transfer amount, recipient information, reason for transfer)

[0849] Output: Confirmation screen of input information

[0850] Specifically, the user uses a keypad or on-screen keyboard to enter information such as "50,000 yen," "Taro Tanaka," and "loan to a friend." Once the information is complete, it is displayed on a confirmation screen.

[0851] Step 4:

[0852] The terminal transmits the input information to the server.

[0853] Input: User's bank transfer information

[0854] Output: Send confirmation message

[0855] Specifically, the terminal sends the transfer information to the server using a secure communication protocol such as HTTPS. Once the transmission is complete, the terminal displays a confirmation message to the user.

[0856] Step 5:

[0857] The server receives and analyzes the transfer information.

[0858] Input: Transfer information sent from the terminal

[0859] Output: Analysis results

[0860] Specifically, the server uses a fraud detection algorithm to compare the reason for the transfer, such as "loan to a friend," with past data. Once the analysis is complete, the server determines whether the transaction is legitimate or suspicious.

[0861] Step 6:

[0862] The server determines the security of the transfer.

[0863] Input: Analysis result of transfer reason

[0864] Output: Safety judgment result (normal or suspicious)

[0865] Specifically, the server determines whether the transfer is safe based on the analysis results. For example, if the "loan to a friend" matches the usual transaction pattern in the past, it will be deemed normal.

[0866] Step 7:

[0867] The server sends the results back to the terminal.

[0868] Input: Safety judgment result

[0869] Output: Confirmation of sending result data

[0870] Specifically, the server sends a message to the terminal such as "The transfer has been approved" or "The reason for the transfer is unclear. Please check again." Once the transfer is complete, a log of the transfer confirmation is recorded.

[0871] Step 8:

[0872] The terminal displays the results to the user.

[0873] Input: Result data from the server

[0874] Output: Result display screen

[0875] Specifically, the terminal displays the result received from the server to the user, for example, "Transfer completed" or "Warning: Transfer reason unclear" on the screen.

[0876] The above are the specific processing steps of the bank transfer fraud prevention system of the present invention. Next, we will explain the specific processing steps of the automatic AI traffic monitoring system.

[0877] Step 1:

[0878] The server performs a scan to monitor traffic conditions in the designated area.

[0879] Input: Monitoring area settings

[0880] Output: Confirmation that monitoring has started

[0881] Specifically, the server synchronizes surveillance cameras and sensors installed in designated cities and intersections with the system and begins collecting data in real time.

[0882] Step 2:

[0883] The device collects data from surveillance cameras and sensors and sends it to a server.

[0884] Input: Data from surveillance cameras and sensors

[0885] Output: Data transmission confirmation message

[0886] Specifically, the device sends video data from surveillance cameras and information from speed sensors to the server in real time. Once the transmission is complete, a confirmation message is displayed.

[0887] Step 3:

[0888] The server analyzes the data and determines whether a traffic law violation has occurred.

[0889] Input: Data from surveillance cameras and sensors

[0890] Output: Violation judgment result

[0891] Specifically, the server uses AI and machine learning models to analyze the collected data and detect traffic violations, such as running red lights or speeding.

[0892] Step 4:

[0893] If the server detects a violation, it notifies nearby police officers.

[0894] Input: Violation judgment result

[0895] Output: Notification message to police officer

[0896] Specifically, if a violation is detected, the server immediately notifies nearby police officers of the information, including the driver's location and the details of the violation.

[0897] Step 5:

[0898] The user (police officer) receives a notification and rushes to the scene.

[0899] Input: Notification message from the server

[0900] Output: Officer response actions

[0901] Specifically, police officers receive notifications via smartphones or police radio, rush to the designated scene, and crack down on violating vehicles.

[0902] Step 6:

[0903] A server stores evidence data associated with the violation.

[0904] Input: Video and sensor data from the violation

[0905] Output: Confirmation of save completion

[0906] Specifically, the server stores the video and data of the violation in storage so that it can be viewed later. For example, it stores the video of the moment the red light was run and the speed sensor measurement data.

[0907] The above are the specific processing steps of the automatic AI traffic monitoring system of the present invention, which realizes efficient fraud prevention and traffic monitoring.

[0908] (Application example 1)

[0909] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0910] In modern society, bank transfer fraud and traffic violations have become serious problems. Dealing with these problems often relies on manual monitoring, which is not very efficient. In particular, the number of victims of bank transfer fraud is increasing, especially among the elderly, and traffic violations also have a significant social impact as a cause of traffic accidents. To solve these problems, there is a need for a system that can prevent bank transfer fraud and detect traffic violations in real time and respond immediately.

[0911] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0912] In this invention, the server includes an input means for a user to input transfer information, a communication means by which the terminal transmits the transfer information to the server, a fraud detection means by which the server analyzes the reason for the transfer received, an analysis result return means by which the server returns the analysis result to the terminal, a display means by which the terminal displays the analysis result to the user, a monitoring means by which a police officer uses smart glasses to monitor traffic violations in real time, a data collection means by which the smart glasses collect data from surveillance cameras and sensors and transmit it to the server, and a notification means by which the server detects traffic violations using an AI model and notifies the police officer. This makes it possible to prevent transfer fraud and detect traffic violations in real time.

[0913] "Input means" refers to a device or method for a user to input data such as transfer information.

[0914] A "communication means" is a device or method for transmitting data from a terminal to a server.

[0915] "Fraud detection means" refers to a device or method that analyzes the transfer information received by the server and determines the possibility of fraud based on its contents.

[0916] The "analysis result return means" is a device or method for the server to return the analysis results to the terminal.

[0917] The "display means" is a device or method for displaying the analysis results received by the terminal from the server to the user.

[0918] "Monitoring means" means a device or method for officers to monitor traffic conditions in real time using smart glasses.

[0919] "Data collection means" refers to a device or method by which the smart glasses collect traffic data from surveillance cameras and sensors and transmit it to the server.

[0920] The "notification means" is a device or method for notifying police officers of traffic violations detected by the server.

[0921] An "AI model" is a model for data analysis that is trained using machine learning algorithms.

[0922] "Real-time" refers to processing and reacting simultaneously with real-world time.

[0923] "Bank transfer fraud" is a type of criminal activity that involves deceiving users and fraudulently withdrawing funds.

[0924] A "traffic violation" refers to any action or situation that violates a traffic law.

[0925] As an embodiment of the present invention, a fraud prevention and real-time traffic violation detection system is specifically configured. First, each component of the system is described, and then specific program processing is described.

[0926] Main components of the system

[0927] 1. Input method:

[0928] The user uses a device or method to input transfer information, such as an ATM or a smartphone app.

[0929] 2. Means of communication:

[0930] The terminal uses the internet or mobile network to send the transfer information to the server, using the HTTP protocol and secure communication via SSL / TLS.

[0931] 3. Fraud detection measures:

[0932] The server uses a machine learning model (e.g., a neural network trained with Keras) to analyze the reason for the incoming transfer. This model determines the likelihood of transfer fraud based on past data.

[0933] 4. Method of returning analysis results:

[0934] The server has a means to return the analysis results to the device, and this process is also carried out via a secure communication protocol.

[0935] 5. Display means:

[0936] The terminal receives the analysis results from the server and displays them to the user, specifically on the smartphone screen or ATM display.

[0937] 6. Monitoring measures:

[0938] Police officers will monitor traffic conditions in real time using smart glasses, which are equipped with a built-in camera and display, through which AI models can detect traffic violations.

[0939] 7. Data Collection Methods:

[0940] The smart glasses collect traffic data from surveillance cameras and sensors and transmit it to a server in real time using wireless communication technologies such as Wi-Fi and Bluetooth.

[0941] 8. Means of notification:

[0942] The server notifies police officers of detected traffic violations using text displayed on the smart glasses' display and an audible alert.

[0943] Program processing explanation

[0944] In this invention, when a user transfers funds using an ATM or smartphone app, the input information is sent to a server via secure communications. The server uses an AI model to analyze the reason for the transfer and returns the results to the terminal. The user is informed of the security of the transfer on a display, and the transfer is canceled if there is a possibility of fraud.

[0945] Police officers can monitor traffic conditions in real time by wearing smart glasses. The glasses are equipped with a sophisticated camera that transmits video data of traffic conditions to a server. The server then uses an AI model to analyze the video data, and if a traffic violation is detected, a notification will appear on the smart glasses' display.

[0946] Specific examples

[0947] For example, suppose a police officer is using smart glasses at a busy intersection and a vehicle runs a red light. In this case, the camera in the smart glasses captures the vehicle running the red light, and the data is sent to the server in real time. The server uses an AI model to detect the traffic violation and displays a notification on the officer's smart glasses saying, "A red light has been detected!" The officer can then respond quickly and crack down on the violating vehicle.

[0948] Prompt Sentence Examples

[0949] For a wire transfer fraud detection model: "Is this wire transfer reason likely to be fraudulent?"

[0950] For traffic violation detection models: "Does this image contain a red light run?"

[0951] As a result, the present invention can efficiently prevent bank transfer fraud and detect traffic violations in real time.

[0952] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0953] Step 1:

[0954] The user enters transfer information. The user launches the ATM or smartphone app and enters information such as the transfer amount, recipient information, and reason for transfer. The entered information is obtained through the input means.

[0955] Input: User inputs transfer amount, recipient information, and reason for transfer.

[0956] Output: Transfer information data obtained via the input means.

[0957] Step 2:

[0958] The terminal sends the transfer information to the server. The terminal uses a secure communication protocol (e.g. HTTPS, SSL / TLS) to send the transfer information to the server in real time.

[0959] Input: Transfer information data.

[0960] Output: Transfer information data sent to the server.

[0961] Step 3:

[0962] The server analyzes the reason for the transfer received. The server analyzes the received transfer information using a generative AI model to check for possible fraud. This process includes data enrichment and text analysis to compare with historical data.

[0963] Input: Transfer information data received from the terminal.

[0964] Output: Fraud detection result (whether fraud is likely or not).

[0965] Step 4:

[0966] The server returns the analysis results to the terminal. The server generates the analysis results and returns them to the terminal via a secure communication means.

[0967] Input: Fraud detection results.

[0968] Output: Analysis result data returned to the device.

[0969] Step 5:

[0970] The terminal displays the analysis results to the user. The terminal displays the analysis results received from the server on the screen. The user checks them and completes the transfer if it is deemed safe. If there is a problem, a warning message is displayed.

[0971] Input: Analysis result data from the server.

[0972] Output: Analysis results and warning messages displayed on the screen.

[0973] Step 6:

[0974] Police officers monitor traffic conditions using smart glasses, which use built-in cameras to capture and collect data on traffic conditions in real time.

[0975] Input: Smart glasses camera footage.

[0976] Output: Collected real-time traffic data.

[0977] Step 7:

[0978] The smart glasses transmit the data obtained from the surveillance cameras and sensors to the server. The smart glasses use Wi-Fi or Bluetooth to transmit the collected data to the server.

[0979] Input: Collected real-time traffic data.

[0980] Output: Traffic data sent to the server.

[0981] Step 8:

[0982] The server uses an AI model to detect traffic violations. The server uses an AI model (e.g., computer vision algorithm) to analyze the transmitted video data and detect traffic violations.

[0983] Input: Traffic data sent from smart glasses.

[0984] Output: Detected traffic violation information.

[0985] Step 9:

[0986] The server notifies the police officer of the detected traffic violation information. The server generates the detected traffic violation information and displays the notification on the smart glasses display.

[0987] Input: Detected traffic violation information.

[0988] Output: Notifications shown on the smart glasses display.

[0989] By using these steps, the present invention can efficiently prevent bank transfer fraud and detect traffic violations in real time. This program process appropriately processes input data at each step and performs necessary data calculations, ultimately providing important information to users and police officers.

[0990] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0991] The present invention provides a system that combines a system for preventing fraud when users make bank transfers, a system for monitoring traffic conditions to detect traffic violations, and an emotion engine for recognizing user emotions. This not only improves the efficiency of police work and ensures the safety of citizens, but also improves convenience by taking the user's emotional state into consideration. The system of the present invention is realized by the following program, and its processing is performed as follows.

[0992] Transfer reason specification system and emotion engine

[0993] Program processing explanation

[0994] 1. The user opens an ATM or banking app.

[0995] Users can access the main menu by operating the ATM's touchscreen, or they can launch their banking app on their smartphone and log in.

[0996] 2. The terminal will display the transfer menu.

[0997] The terminal will display a "Transfer" option on the screen for the user to select.

[0998] 3. The user selects the "Transfer" option.

[0999] The user taps the "Transfer" button to proceed to the transfer information input screen.

[1000] 4. The terminal will display the transfer information input screen.

[1001] The terminal displays a screen with fields to enter the amount, recipient information, and reason for the transfer.

[1002] 5. The user enters the necessary bank transfer information.

[1003] The user enters information such as "100,000 yen," "Suzuki Ichiro," and "purchase price of the product" into the form on the screen.

[1004] 6. The terminal sends the entered information to the server.

[1005] The terminal encodes the input data and sends it to the server using a secure communication protocol.

[1006] 7. The device activates an emotion engine that recognizes the user's emotions.

[1007] The device uses sensors such as a camera and microphone to transmit the user's facial expressions and tone of voice to the emotion engine.

[1008] 8. The emotion engine analyzes the user's emotions.

[1009] The emotion engine analyzes facial and vocal data to identify the user's emotional state, such as whether they are tense, relaxed, or confused.

[1010] 9. The emotion engine sends the analysis results to the server.

[1011] The emotion engine encodes the analysis results and sends them to the server.

[1012] 10. The server analyzes the reason for the transfer and emotional data.

[1013] The server integrates and analyzes the received reason for the transfer and emotional data to assess the safety of the transfer and the possibility of fraud.

[1014] 11. The server determines the security of the transfer.

[1015] Based on the analysis results, the server determines whether the transfer is safe and sends the result to the terminal.

[1016] 12. The server returns the analysis results to the device.

[1017] The server encodes the safety judgment result and returns it to the terminal using a secure communication protocol.

[1018] 13. The device displays the analysis results to the user.

[1019] The terminal will display messages to the user such as "Transfer completed" or "Warning: Reason for transfer unclear," and will provide additional guidance and assistance as needed based on emotion data.

[1020] Specific examples

[1021] Suppose a user uses an ATM to transfer 50,000 yen to his friend, Tanaka Taro. When the user enters "50,000 yen," "Tanaka Taro," and "loan to friend" into the ATM, the terminal sends this information to the server. At the same time, the emotion engine analyzes the user's facial expression and tone of voice and determines that the user is relaxed. The server analyzes "loan to friend" and the relaxed emotional state, and if it determines that the transfer does not constitute fraud, it sends a result back to the terminal. The terminal displays the message "Transfer completed," and the transfer is carried out.

[1022] Automatic AI traffic monitoring system and emotion engine

[1023] Program processing explanation

[1024] 1. The server performs a scan to monitor traffic conditions in a specified area.

[1025] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[1026] 2. The device collects data from surveillance cameras and sensors.

[1027] The device acquires surveillance camera footage and sensor data in real time and sends it to the server.

[1028] 3. The server receives the collected data and prepares it for analysis.

[1029] The server stores the received video data and sensor data in a temporary database and prepares it for analysis.

[1030] 4. The server analyzes the data and determines whether a traffic law violation has occurred.

[1031] The server uses AI algorithms to analyze the video data and detect traffic violations such as running red lights or speeding.

[1032] 5. If the server detects a violation, it sends a notification to a nearby police officer.

[1033] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[1034] 6. The user (police officer) receives the notification and rushes to the scene.

[1035] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[1036] 7. The server stores evidence data related to the breach.

[1037] The server stores video and sensor data of violations and archives them for future reference.

[1038] 8. The server combines an emotion engine that recognizes the emotions of police officers.

[1039] The server uses an emotion engine to monitor the emotional state of officers as they conduct field enforcement.

[1040] 9. The emotion engine analyzes the emotions of police officers.

[1041] The emotion engine analyzes the officer's facial expressions and tone of voice to detect stress, fatigue, and other symptoms.

[1042] 10. The server stores the results of the emotion engine and monitors the health status of the officers.

[1043] The server records the analysis results of the emotion engine and continuously monitors the health status of the officers.

[1044] Specific examples

[1045] While the server monitors traffic conditions at a specific intersection, it detects a vehicle running a red light. Data from sensors and cameras is sent to the server in real time, and the server uses AI to confirm the red light has been run. The server then notifies nearby police officers that a red light has been run, and the officers rush to the scene to crack down on the violating vehicle. During this process, the emotion engine monitors the officer's stress level, and provides appropriate support if an abnormality is detected.

[1046] Through these specific processes, the system of the present invention realizes efficient fraud prevention and traffic monitoring, and also builds a safe and fair society that takes into account the emotional states of users and police officers.

[1047] The processing flow will be explained below.

[1048] Transfer reason specification system and emotion engine

[1049] Program processing explanation

[1050] Step 1:

[1051] The user opens an ATM or banking app.

[1052] Users interact with the ATM's touchscreen to access the main menu, or they open their banking app on their smartphone and log in to their account.

[1053] Step 2:

[1054] The terminal will display the transfer menu.

[1055] The terminal displays the transfer options on the screen and allows the user to select the "Transfer" button.

[1056] Step 3:

[1057] The user selects the "Transfer" option.

[1058] The user taps the "Transfer" button and proceeds to the next information input screen.

[1059] Step 4:

[1060] The terminal displays the transfer information input screen.

[1061] The terminal displays a screen containing input fields for entering the transfer amount, recipient information, and reason for the transfer.

[1062] Step 5:

[1063] The user enters the necessary transfer information.

[1064] The user enters "100,000 yen" in the amount field, "Suzuki Ichiro" in the recipient information field, and "purchase price of product" in the transfer reason field.

[1065] Step 6:

[1066] The terminal transmits the input information to the server.

[1067] The terminal transmits the input data to the server using a secure communication protocol.

[1068] Step 7:

[1069] The device activates an emotion engine that recognizes the user's emotions.

[1070] The device activates sensors such as a camera and microphone to transmit the user's facial expressions and tone of voice to the emotion engine.

[1071] Step 8:

[1072] The emotion engine analyzes the user's emotions.

[1073] The emotion engine analyzes the collected facial expression and voice data to determine the user's emotional state, such as whether they are nervous, relaxed, or confused.

[1074] Step 9:

[1075] The emotion engine sends the analysis results to the server.

[1076] The emotion engine encodes the analysis results and sends them to the server using a secure communication protocol.

[1077] Step 10:

[1078] The server receives and analyzes the transfer information and emotion data.

[1079] The server integrates and analyzes the individually received transfer information and emotional data to determine whether the transfer is suspected of being fraudulent.

[1080] Step 11:

[1081] The server determines the security of the transfer.

[1082] Based on the analysis results, the server evaluates whether the transfer is safe and sends the result back to the terminal.

[1083] Step 12:

[1084] The server returns the analysis results to the device.

[1085] The server encodes the result of the decision and returns it to the terminal using a secure communication protocol.

[1086] Step 13:

[1087] The device displays the analysis results to the user.

[1088] The terminal will display messages to the user such as "Transfer completed" or "Warning: Reason for transfer unclear" and will also display additional guidance and assistance messages as needed based on emotion data.

[1089] Automatic AI traffic monitoring system and emotion engine

[1090] Program processing explanation

[1091] Step 1:

[1092] The server performs a scan to monitor traffic conditions in the designated area.

[1093] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[1094] Step 2:

[1095] The device collects data from surveillance cameras and sensors.

[1096] The terminal acquires surveillance camera video data and sensor data in real time and sends it to the server.

[1097] Step 3:

[1098] The server receives the collected data and prepares it for analysis.

[1099] The server stores the received video data and sensor data in virtual memory and prepares it for analysis.

[1100] Step 4:

[1101] The server analyzes the data and determines whether any traffic laws have been violated.

[1102] The server uses AI algorithms to analyze the collected video data and detect traffic violations such as running red lights and speeding.

[1103] Step 5:

[1104] If the server detects a violation, it sends a notification to nearby police officers.

[1105] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[1106] Step 6:

[1107] The user (police officer) receives a notification and rushes to the scene.

[1108] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[1109] Step 7:

[1110] A server stores evidence data associated with the violation.

[1111] The server stores video and sensor data of violations and archives them for future evidence.

[1112] Step 8:

[1113] The server combines an emotion engine that recognizes the emotions of the police officers.

[1114] The server uses an emotion engine to monitor emotional data as police officers conduct enforcement in the field.

[1115] Step 9:

[1116] An emotion engine analyzes the emotions of police officers.

[1117] The emotion engine analyzes an officer's facial expressions and tone of voice to identify stress and fatigue.

[1118] Step 10:

[1119] The server stores the results of the emotion engine and monitors the health of the officers.

[1120] The server records the emotion engine's analysis results and continuously tracks the officers' health status.

[1121] Through these specific processing steps, the system of the present invention effectively realizes fraud prevention and traffic monitoring, and supports safe and fair operation taking into account the emotional states of users and police officers.

[1122] Example 2

[1123] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1124] Conventional bank transfer systems and traffic monitoring systems have difficulty in detecting fraud and traffic violations because it is difficult for users to clearly state the reason for a transfer and to monitor traffic conditions in real time. Furthermore, they are unable to take into account the emotional state of users and police officers, which has led to challenges in improving operational efficiency and safety.

[1125] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1126] In this invention, the server comprises means for a user to input transfer information and a reason for transfer using an information processing device, communication means for a terminal to transmit the input transfer information to the server, emotion recognition means for the terminal to acquire the user's facial expression and voice data, emotion analysis means for analyzing the facial expression and voice data acquired by the emotion recognition means, communication means for transmitting the user's emotion data analyzed by the emotion analysis means to the server, fraud detection means for the server to analyze the transfer reason and the emotion data by integrating them, analysis result return means for the server to return the analysis results to the terminal, display means for the terminal to display the analysis results to the user, and The system includes a means for inputting the information, a communication means for the terminal to transmit the input information to a server in real time, a monitoring means for the server to monitor traffic conditions using an AI algorithm, a notification means for the server to detect violations of traffic laws from the monitoring results and notify police officers, a storage means for the server to store evidential data related to traffic violations, a means for completing the transfer if it is determined to be safe based on the analysis results and displaying a warning and stopping the transfer if fraud is suspected, a means for the server to collect and analyze data obtained from surveillance cameras and sensors in real time, and a means for sending a notification to local police officers or remote control devices when a traffic violation is detected. This enables a safe and efficient system that ensures the safety of transfers, effectively monitors and detects violations of traffic laws, and takes into account the emotional states of users and police officers.

[1127] A "user" is an individual or organization that uses the system and is the entity that performs bank transfer operations and receives traffic monitoring data.

[1128] "Information processing device" refers to all hardware and software used for calculations and data processing, and specifically includes ATMs, smartphones, computers, etc.

[1129] A "terminal" is a device that is directly operated by a user, and is used to input and display information and communicate with a server.

[1130] "Communication means" refers to protocols and devices for transmitting and receiving data, including networks, modems, Wi-Fi, and related software.

[1131] "Emotion recognition means" refers to devices such as sensors, cameras, and microphones that acquire the user's facial expressions and voice data and analyze their emotions.

[1132] "Emotion analysis means" refers to algorithms and software for analyzing acquired facial and voice data to identify the user's emotional state.

[1133] A "server" is a high-performance computer system that collects, stores, analyzes, and communicates data, and includes a central processing unit.

[1134] "Fraud detection methods" refers to algorithms and software that analyze transfer reasons and emotional data to assess the likelihood of fraudulent activity.

[1135] "Means for returning analysis results" refers to a communication protocol and related devices for the server to return the analysis results to the user.

[1136] "Display means" refers to devices and software for visually displaying analysis results, warning messages, etc. to the user.

[1137] "Monitoring means" refers to cameras, sensors, and associated software used to monitor traffic conditions in real time and collect data.

[1138] "Means of notification" refers to communications protocols and related devices for notifying police officers when a traffic violation is detected.

[1139] "Storage means" refers to data storage and software for storing evidentiary data related to traffic violations and making it available for reference when necessary.

[1140] A "remote control device" is a device for dealing with traffic violations remotely, including traffic light control systems and automobile control systems.

[1141] The system of the present invention combines a traffic violation detection system that monitors traffic conditions and prevents fraud when making bank transfers with an emotion engine that recognizes the user's emotional state. This not only improves the efficiency of police work and ensures the safety of citizens, but also improves convenience by taking the user's emotional state into consideration.

[1142] The system includes the following main components:

[1143] 1. User: Enters data at an ATM or through a banking app.

[1144] 2. Terminal: A device operated by the user that inputs and displays transfer information and acquires emotional data. Examples include ATMs, smartphones, and computers.

[1145] 3. Server: A central computer system that collects, stores, analyzes, and communicates data.

[1146] Transfer reason specification system and emotion engine

[1147] Hardware and Software

[1148] The user uses an information processing device (an ATM or a smartphone or computer with a banking app running).

[1149] The terminal uses a touch screen and keyboard to input transfer information and the reason for the transfer.

[1150] The device collects the user's facial expressions using a camera and their tone of voice using a microphone, and sends these to emotion recognition software (e.g., Google Cloud Vision API or Amazon Rekognition).

[1151] The server uses AI algorithms (TensorFlow and PyTorch) to analyze the reason for transfer and emotional data in real time.

[1152] Specific examples

[1153] Suppose a user wants to use an ATM to transfer 50,000 yen to their friend, Taro Tanaka. The user enters "50,000 yen," "Taro Tanaka," and "loan to friend" in the ATM's "Transfer" menu. At the same time, the device's emotion recognition function analyzes the user's facial expressions and voice and determines that they are relaxed. This data is sent to a server, which uses AI to analyze the safety of the transfer. If it determines that the transfer is not fraudulent, a "Transfer Completed" notification is displayed on the device and the transfer is carried out.

[1154] Automatic AI traffic monitoring system and emotion engine

[1155] Hardware and Software

[1156] The device collects traffic data from surveillance cameras and sensors and sends it to a server.

[1157] The server uses a database (e.g., AWS S3) and analysis software (e.g., OpenCV, YOLOv3 model) to store and analyze the data collected in real time.

[1158] A communication system in which a server detects violations of traffic laws and notifies police officers.

[1159] Specific examples

[1160] The server monitors traffic conditions at specific intersections and detects vehicles that run red lights. Data from sensors and cameras is sent to the server in real time, and AI confirms that the red light has been run. The server then sends a notification to nearby police officers that a red light has been run. The officers then rush to the scene and crack down on the violating vehicle. At this time, the emotion engine monitors the stress level of the officers, and if an abnormality is detected, appropriate support is provided.

[1161] Example prompts for generative AI models

[1162] "I would like to transfer 50,000 yen to Taro Tanaka using an ATM. However, please tell me the process to check whether this transfer is fraudulent."

[1163] "Please tell me in detail the specific processing steps of an AI system that detects traffic violations using surveillance cameras placed at specific intersections."

[1164] In this way, the system of the present invention realizes efficient fraud prevention and traffic monitoring, and builds a safe and fair society that takes into account the emotional states of users and police officers.

[1165] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1166] Transfer reason specification system and emotion engine

[1167] Processing flow and specific operations

[1168] Step 1:

[1169] The user opens an ATM or banking app.

[1170] Input: Authentication begins when you insert your card into an ATM or launch your banking app on your smartphone.

[1171] Output: After authentication, the main menu will be displayed.

[1172] Specific actions: The user operates the ATM's touch screen to access the main menu, or logs in using their ID and password in the banking app.

[1173] Step 2:

[1174] The terminal will display the transfer menu.

[1175] Input: The authenticated user's request.

[1176] Output: The transfer menu will appear on the screen.

[1177] What it does: The terminal displays the "Transfer" option on the screen for the user to select.

[1178] Step 3:

[1179] The user selects the "Transfer" option.

[1180] Input: Select Transfer menu.

[1181] Output: The transfer information input screen will be displayed.

[1182] Specific operation: The user taps the "Transfer" button and proceeds to the screen to enter transfer information.

[1183] Step 4:

[1184] The terminal displays the transfer information input screen.

[1185] Enter: Select a transfer option.

[1186] Output: Input fields for amount, recipient information, and transfer reason are displayed.

[1187] What it does: The terminal displays a screen with fields for entering the amount, recipient information, and reason for the transfer.

[1188] Step 5:

[1189] The user enters the necessary transfer information.

[1190] Input: Enter the transfer amount, recipient information, and reason for transfer.

[1191] Output: The input data is saved to the device.

[1192] Specific operation: The user enters information such as "50,000 yen," "Taro Tanaka," and "loan to a friend" into the form on the screen.

[1193] Step 6:

[1194] The terminal transmits the input information to the server.

[1195] Input: Transfer information entered by the user.

[1196] Output: The transfer information is sent to the server.

[1197] Specific operation: The terminal encrypts the input data using the SSL / TLS protocol and sends it to the server.

[1198] Step 7:

[1199] The device activates an emotion engine that recognizes the user's emotions.

[1200] Input: User's facial expression and voice data.

[1201] Output: Emotion recognition data is sent to the emotion engine.

[1202] Specific operation: The device's camera captures the user's facial expressions, and the microphone captures the user's voice. This data is then sent to the emotion engine.

[1203] Step 8:

[1204] The emotion engine analyzes the user's emotions.

[1205] Input: facial expression and voice data.

[1206] Output: Emotional state analysis result.

[1207] What it does: The emotion engine uses facial recognition and voice analysis to determine whether the user is relaxed or tense.

[1208] Step 9:

[1209] The emotion engine sends the analysis results to the server.

[1210] Input: Emotional state analysis results.

[1211] Output: Emotion data sent to the server.

[1212] Specific operation: The emotion engine encodes the analysis results and sends them to the server.

[1213] Step 10:

[1214] The server analyzes the reason for the transfer and emotional data.

[1215] Input: Reason for transfer, emotional data.

[1216] Output: A rating of the transfer's safety.

[1217] How it works: The server uses an AI model to comprehensively analyze the reason for the transfer and emotional data to assess the likelihood of fraud.

[1218] Step 11:

[1219] The server determines the security of the transfer.

[1220] Input: A rating of the transfer's safety.

[1221] Output: Safety-based decision result.

[1222] Specific operation: The server determines the safety of the transfer based on the evaluation results and prepares to send the results to the terminal.

[1223] Step 12:

[1224] The server returns the analysis results to the device.

[1225] Input: Safety decision result.

[1226] Output: The result data sent to the terminal.

[1227] Specific operation: The server encodes the security judgment result and sends it to the terminal.

[1228] Step 13:

[1229] The device displays the analysis results to the user.

[1230] Input: Analysis results received from the server.

[1231] Output: The resulting message displayed to the user.

[1232] What it does: The terminal will display a message such as "Transfer complete" or "Warning: Reason for transfer unclear" and provide additional guidance or assistance as needed.

[1233] Automatic AI traffic monitoring system and emotion engine

[1234] Processing flow and specific operations

[1235] Step 1:

[1236] The server performs a scan to monitor traffic conditions in the designated area.

[1237] Input: Specification of the monitoring area.

[1238] Output: Monitoring data collection begins.

[1239] Specific operation: The server activates the surveillance cameras and sensors placed in the designated area and starts collecting data in real time.

[1240] Step 2:

[1241] The device collects data from surveillance cameras and sensors.

[1242] Input: Data from surveillance cameras and sensors.

[1243] Output: Collected data sent to the server.

[1244] Specific operation: The device acquires video data from surveillance cameras and speed information from radar sensors, and sends this data to a server.

[1245] Step 3:

[1246] The server receives the collected data and prepares it for analysis.

[1247] Input: Collected monitoring data.

[1248] Output: Database updates required for analysis.

[1249] Specific operation: The server stores the collected data in temporary data storage (e.g., AWS S3) and prepares it for analysis.

[1250] Step 4:

[1251] The server analyzes the data and determines whether any traffic laws have been violated.

[1252] Input: Stored monitoring data.

[1253] Output: Traffic law violation detection results.

[1254] Specific operation: The server uses AI algorithms (e.g., OpenCV or YOLOv3 models) to analyze video data and detect traffic violations such as running red lights or speeding.

[1255] Step 5:

[1256] If the server detects a violation, it sends a notification to nearby police officers.

[1257] Input: Traffic violation detection results.

[1258] Output: Notification sent to the officer.

[1259] Specific operation: When a violation is detected, the server sends a notification containing the details of the violation and GPS information to the device of a nearby police officer.

[1260] Step 6:

[1261] The user (police officer) receives a notification and rushes to the scene.

[1262] Input: Notification from the server.

[1263] Output: Police arrive on scene and take action.

[1264] Specific operation: The police officer receives a notification from the server and rushes to the designated location to crack down on traffic violators.

[1265] Step 7:

[1266] A server stores evidence data associated with the violation.

[1267] Input: Evidence data related to traffic violations.

[1268] Output: Stored evidence data.

[1269] Specific operation: The server stores video data and sensor data related to violations for a long period of time, making it available for reference when needed.

[1270] Step 8:

[1271] The server combines an emotion engine that recognizes the emotions of the police officers.

[1272] Input: Officer facial and voice data.

[1273] Output: Recognized emotion data.

[1274] How it works: When police officers conduct a police operation, the server activates the emotion engine to monitor their facial expressions and tone of voice, and the collected data is sent to the emotion analysis engine.

[1275] Step 9:

[1276] An emotion engine analyzes the emotions of police officers.

[1277] Input: facial expression and voice data.

[1278] Output: Emotional state analysis result.

[1279] How it works: The emotion engine uses facial recognition technology and voice analysis algorithms to identify officer stress and fatigue.

[1280] Step 10:

[1281] The server stores the results of the emotion engine and monitors the health of the officers.

[1282] Input: Emotional state analysis results.

[1283] Output: Stored officer health data.

[1284] What it does: The server stores the analysis results in a database, continuously monitors the health status of officers, and issues an alert to provide appropriate support if an abnormality is detected.

[1285] (Application example 2)

[1286] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1287] In modern society, preventing fraud during bank transfers, monitoring and detecting traffic violations, and ensuring safety in self-driving vehicles are important challenges. However, existing systems address each problem individually and do not provide a consistent solution that takes into account the emotional state of the user or driver. Therefore, a more effective and comprehensive system is needed.

[1288] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes input means for the user to input bank transfer information, communication means by which the terminal transmits the bank transfer information to the server, fraud detection means for analyzing the reason for the bank transfer received by the server, analysis result return means by which the server transmits the analysis results to the terminal, display means by which the terminal displays the analysis results to the user, collection means by which the terminal collects image information and audio information from inside the vehicle, emotion analysis means by which the emotion engine analyzes the collected data to identify the emotional state, and vehicle control means for controlling the vehicle based on the emotion analysis results. This enables fraud prevention during bank transfers, detection of traffic violations, and comprehensive safety measures that take into account the emotional states of drivers and passengers in self-driving vehicles.

[1289] "User" means a person who uses the system to make bank transfers or operate self-driving vehicles.

[1290] "Transfer information" refers to detailed information required for a user to make a transfer, such as the account number of the transfer recipient, the transfer amount, and the reason for the transfer.

[1291] "Input means" refers to a device or interface through which a user inputs transfer information. Specifically, this includes ATMs and smartphone applications.

[1292] "Communication means" refers to the communication protocol and network functions that allow the terminal to send transfer information to the server.

[1293] "Fraud detection means" refers to algorithms or programs that analyze the reason for transfer received by the server and evaluate and detect the possibility of fraud.

[1294] "Means for returning analysis results" refers to the communication protocol and network functions that allow the server to return analysis results to the terminal.

[1295] The "display means" refers to a display or screen that the terminal uses to display the analysis results to the user.

[1296] "In-vehicle image information and audio information" refers to image and audio data of the driver and passengers collected by cameras and microphones installed inside the vehicle.

[1297] "Collection means" refers to cameras and microphones used to collect image and audio information inside the vehicle, as well as associated sensors and software.

[1298] "Emotion analysis means" refers to AI algorithms or programs for analyzing the emotional state of drivers and passengers from collected image and audio information.

[1299] "Vehicle control means" refers to a device or program for controlling the speed and behavior of a vehicle based on the emotion analysis results.

[1300] "Traffic condition data" refers to information such as traffic flow, traffic light conditions, and vehicle positions collected from surveillance cameras and sensors.

[1301] "Emergency services" refers to services such as police, fire, and ambulances that respond quickly in the event of an accident or dangerous situation.

[1302] An "emotion engine" refers to a program or algorithm for implementing emotion analysis means, which analyzes emotional states from collected image and audio data.

[1303] "Analysis means" refers to the systems and algorithms used to integrate emotion analysis results with traffic data and analyze them using an AI model.

[1304] This invention is a comprehensive system for preventing fraudulent bank transfers, monitoring traffic violations, and improving safety in self-driving vehicles. Each means and process of the system will be described below.

[1305] Bank transfer fraud prevention system

[1306] The user enters transfer information using an ATM or bank app. The entered information is sent to the server via the terminal. The server analyzes the reason for the transfer using fraud detection means. The analysis results are sent back from the server to the terminal, which displays them to the user. If the server detects the possibility of fraud in the transfer information entered by the user, the terminal displays a warning to the user and cancels the transfer.

[1307] Traffic Monitoring System

[1308] The server collects and analyzes traffic data from surveillance cameras and sensors in real time. The server is equipped with AI algorithms that detect traffic violations, such as running red lights and speeding, in real time. Detected violations are reported to police officers or automated control devices. Evidence data related to violations is stored on the server for future reference.

[1309] Safety management systems for autonomous vehicles

[1310] Emotion Monitoring

[1311] The device uses cameras and microphones installed inside the autonomous vehicle to collect image and audio information from the driver and passengers. The collected data is analyzed by an emotion engine to identify the emotional state of the driver and passengers. The behavior of the autonomous vehicle is controlled based on this emotional state. For example, if the emotion engine determines that the driver is fatigued or stressed, it may slow down the vehicle or suggest a break.

[1312] Emergency response

[1313] The server integrates and analyzes traffic data and emotion data to detect accidents and emergencies. If an emergency occurs, the server automatically notifies the police and emergency services. If necessary, an emergency assistance message is displayed to the user.

[1314] Hardware and software used

[1315] Camera and microphone: To monitor what's happening inside the car in real time.

[1316] OpenCV: A library for real-time image processing.

[1317] Emotion Analysis Engine (EmotionEngine): A software module for analyzing the emotional state of drivers and passengers.

[1318] Traffic Monitoring System (TrafficMonitor): A system for monitoring surrounding traffic conditions in real time.

[1319] Emergency Response System (EmergencyResponse): A software module for responding to accidents and emergency situations.

[1320] Specific examples

[1321] A concrete example would be a scenario where an autonomous vehicle is traveling on a highway and the driver is fatigued, and the vehicle detects this emotional state and slows down, encouraging the driver to take a break.

[1322] Prompt Sentence Examples

[1323] "A self-driving vehicle is driving down the highway and the driver's face looks fatigued. What should the self-driving vehicle do next?"

[1324] By implementing this invention, it will be possible to prevent fraud during bank transfers, detect traffic violations, and implement comprehensive safety measures in autonomous vehicles that take into account the emotional state of drivers and passengers.

[1325] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1326] Step 1:

[1327] A user opens an ATM or banking app. They either interact with the ATM's touchscreen to access the main menu or launch the banking app on their smartphone and log in. Inputs include the user's login information and interface interactions. Outputs include the ATM or app's main menu screen.

[1328] Step 2:

[1329] The terminal displays a transfer menu. The terminal displays a "Transfer" option on the screen for the user to select. Input includes the user's selection on the main menu. Output includes a screen where transfer information can be entered.

[1330] Step 3:

[1331] The user selects the "Transfer" option. The user taps the "Transfer" button to proceed to the transfer information input screen. The input includes the user's selection. The output displays the transfer information input screen.

[1332] Step 4:

[1333] The terminal displays a screen for inputting transfer information. The terminal displays a screen containing input fields for the amount, recipient information, and reason for transfer. The input contains the transfer information format held by the system. The output is the screen for inputting transfer information.

[1334] Step 5:

[1335] The user enters the necessary transfer information. The user enters information such as "100,000 yen," "recipient's name," and "purchase price of the product" into the form on the screen. The input includes the transfer information provided by the user. The output is generated as transfer information data.

[1336] Step 6:

[1337] The terminal sends the input information to the server. The terminal encodes the input data and sends it to the server using a secure communication protocol. The input is the encoded transfer information. The output is the transfer information data to be sent to the server.

[1338] Step 7:

[1339] The terminal collects image and audio information from inside the vehicle. Using cameras and microphones installed inside the vehicle, the terminal collects image and audio information from the driver and passengers. The input is real-time data from the cameras and microphones. The output is the collected image and audio data.

[1340] Step 8:

[1341] The emotion engine analyzes the collected data to identify the emotional state. The emotion engine analyzes image and audio information to identify the emotional state, for example, whether the driver is relaxed or tense. The input is the collected image and audio data. The output is the identified emotional state data.

[1342] Step 9:

[1343] The server analyzes the received reason for the transfer. The server uses fraud detection means to analyze the reason for the transfer and evaluate the likelihood of fraud. The inputs are the reason for the transfer and emotional state data. The output is an analysis result regarding the likelihood of fraud.

[1344] Step 10:

[1345] The server returns the analysis results to the device. The server encodes the analysis results and returns them to the device using a secure communication protocol. The input is the analysis results. The output is the returned analysis result data.

[1346] Step 11:

[1347] The terminal displays the analysis results to the user. The terminal displays messages such as "Transfer completed" or "Warning: The reason for transfer is unclear" to the user. It also displays additional guidance or assistance as needed based on the emotion data. The input is the returned analysis result data. The output is the message or guidance to be displayed.

[1348] Step 12:

[1349] The system controls the vehicle based on the emotion analysis results. If the emotional state is recognized as abnormal, it controls the vehicle speed or suggests a break. The input is the identified emotional state data. The output is the vehicle speed control or a suggested message.

[1350] Step 13:

[1351] The server collects and analyzes traffic condition data in real time. The server collects traffic condition data from surveillance cameras and sensors and analyzes it using an AI algorithm. The input is data from surveillance cameras and sensors. The output is data on traffic violation detection results.

[1352] Step 14:

[1353] Detects traffic violations and sends notifications to police officers or automated control devices. When the server detects a traffic violation, it sends a notification to a nearby police officer or automated control device. As input, it has the detection result data. As output, it has the notification data to be sent.

[1354] Step 15:

[1355] Stores evidence data related to violations. The server stores video data and sensor information related to traffic violations and archives it for future reference. The input is the collected and analyzed evidence data. The output is the stored archive data.

[1356] Step 16:

[1357] Automatically notify police and emergency services when an accident or emergency situation occurs. The server sends a notification to police and emergency services when an accident is detected, and appropriate assistance is provided. The input is the accident detection data. The output is the sent emergency notification data.

[1358] Step 17:

[1359] The user follows the messages and suggestions they receive from the system. The user receives suggestions and notifications from the device and takes action based on them. The input is the message or suggestion from the device. The output is the user's actions.

[1360] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1361] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1362] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1363] [Third embodiment]

[1364] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1365] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1366] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1367] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1368] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1369] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1370] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1371] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1372] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1373] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1374] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1375] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1376] The present invention provides a system for preventing fraud when users make bank transfers, and a system for monitoring traffic conditions to detect traffic violations, thereby improving the efficiency of police work and ensuring the safety of citizens. The system of the present invention is implemented by a series of programs, and its processing is as follows.

[1377] System for specifying the reason for transfer

[1378] Program processing explanation

[1379] 1. The user opens an ATM or banking app.

[1380] Users first open the ATM's main screen or their bank's app on their smartphone to begin accessing the system.

[1381] 2. The terminal will display the transfer menu.

[1382] The terminal presents the user with a menu of transfer options, from which the user selects "Transfer."

[1383] 3. The user enters the transfer information.

[1384] The user inputs the transfer amount, the recipient's information, and the reason for the transfer. For example, the user inputs information such as "100,000 yen to Ichiro Suzuki as the recipient, and the reason is the purchase price of a product."

[1385] 4. The terminal sends the entered information to the server.

[1386] The terminal transmits all entered information to the server using a secure communication protocol.

[1387] 5. The server receives and analyzes the transfer information.

[1388] The server applies fraud detection algorithms to analyze the reason for the transfer received, checking reasons such as "purchase of goods" or "repayment to a friend," and compares them with historical data.

[1389] 6. The server determines whether the transfer is safe.

[1390] Based on the analysis, the server determines whether the transfer is safe or suspicious. If it is safe, the transfer proceeds, otherwise a warning is issued.

[1391] 7. The server sends the results back to the device.

[1392] The server returns the security result to the terminal, for example, a message saying "The transfer has been approved" or "The reason for the transfer is unclear. Please check again."

[1393] 8. The terminal displays the results to the user.

[1394] The terminal displays the result received from the server to the user, for example, displaying a message such as "Transfer completed" or "Warning: The reason for transfer is unclear" on the screen.

[1395] Specific examples

[1396] Suppose a user uses an ATM to transfer 50,000 yen to his friend, Tanaka Taro. When the user enters "50,000 yen," "Tanaka Taro," and "loan to friend" into the ATM, the terminal sends this information to the server. The server analyzes "loan to friend" and, if it determines that the transfer is not fraudulent, it sends a result back to the terminal. The terminal displays the message "Transfer completed," and the transfer is carried out.

[1397] Automatic AI Traffic Monitoring System

[1398] Program processing explanation

[1399] 1. The server performs a scan to monitor traffic conditions in a specified area.

[1400] The server synchronizes all cameras and sensors in the specified city or intersection and begins collecting data in real time.

[1401] 2. The device collects data from surveillance cameras and sensors and sends it to the server.

[1402] The device transmits video data from surveillance cameras and information obtained from sensors to a server in real time.

[1403] 3. The server analyzes the data and determines whether a traffic law violation has occurred.

[1404] The server uses AI and machine learning models to analyze video and sensor data to detect traffic violations, such as running red lights or speeding.

[1405] 4. If the server detects a violation, it notifies nearby police officers.

[1406] When a violation is detected, the server immediately notifies nearby police officers of the incident, including the location and details of the violation.

[1407] 5. The user (police officer) receives the notification and rushes to the scene.

[1408] Once police receive the notification, they will rush to the designated location and crack down on the offending vehicle.

[1409] 6. The server stores evidence data related to the breach.

[1410] The server stores footage and data of violations so that they can be viewed later.

[1411] Specific examples

[1412] While the server monitors traffic conditions at a specific intersection, it detects vehicles that run red lights. Data from sensors and cameras is sent to the server in real time, and the server uses AI to confirm that a red light has been run. The server then sends a notification to a nearby police officer that a red light has been run, and the officer rushes to the scene to crack down on the violating vehicle. At that time, the server stores the video data of the red light run.

[1413] Through these specific processes, the system of the present invention provides efficient fraud prevention and traffic monitoring.

[1414] The processing flow will be explained below.

[1415] System for specifying the reason for transfer

[1416] Program processing explanation

[1417] Step 1:

[1418] The user opens an ATM or banking app.

[1419] Users operate the ATM's touchscreen to access the main menu, or they launch their banking app on their smartphone and log in.

[1420] Step 2:

[1421] The terminal will display the transfer menu.

[1422] The terminal will display a "Transfer" option on the screen for the user to select.

[1423] Step 3:

[1424] The user selects the "Transfer" option.

[1425] The user taps the "Transfer" button to proceed to the transfer information input screen.

[1426] Step 4:

[1427] The terminal displays the transfer information input screen.

[1428] The terminal displays a screen with fields to enter the amount, recipient information, and reason for the transfer.

[1429] Step 5:

[1430] The user enters the necessary transfer information.

[1431] The user enters information such as "100,000 yen," "Suzuki Ichiro," and "purchase price of the product" into the form on the screen.

[1432] Step 6:

[1433] The terminal transmits the input information to the server.

[1434] The terminal encodes the input data and sends it to the server using a secure communication protocol.

[1435] Step 7:

[1436] The server receives the transfer information.

[1437] The server decodes the received data and prepares it for analysis.

[1438] Step 8:

[1439] The server analyzes the reason for the transfer.

[1440] The server applies fraud detection algorithms to analyze the input reason for the transfer and assess its safety.

[1441] Step 9:

[1442] The server determines the security of the transfer.

[1443] The server will then use the analysis results to determine whether the transfer is safe or not, and if it is determined to be fraudulent, it will also provide the reason for this.

[1444] Step 10:

[1445] The server returns the analysis results to the device.

[1446] The server encodes the safety judgment result and returns it to the terminal using a secure communication protocol.

[1447] Step 11:

[1448] The device displays the analysis results to the user.

[1449] The terminal will display a message to the user such as "Transfer completed" or "Warning: Reason for transfer unclear."

[1450] Automatic AI Traffic Monitoring System

[1451] Program processing explanation

[1452] Step 1:

[1453] The server performs a scan to monitor traffic conditions in the designated area.

[1454] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[1455] Step 2:

[1456] The device collects data from surveillance cameras and sensors.

[1457] The device acquires surveillance camera footage and sensor data in real time and sends it to the server.

[1458] Step 3:

[1459] The server receives the collected data and prepares it for analysis.

[1460] The server stores the received video data and sensor data in a temporary database and prepares it for analysis.

[1461] Step 4:

[1462] The server analyzes the data and determines whether any traffic laws have been violated.

[1463] The server uses AI algorithms to analyze the video data and detect traffic violations such as running red lights or speeding.

[1464] Step 5:

[1465] If the server detects a violation, it sends a notification to nearby police officers.

[1466] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[1467] Step 6:

[1468] The user (police officer) receives a notification and rushes to the scene.

[1469] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[1470] Step 7:

[1471] A server stores evidence data associated with the violation.

[1472] The server stores video and sensor data of violations and archives them for future reference.

[1473] By these steps, the system of the present invention realizes the user's bank transfer activity and traffic situation monitoring efficiently and safely.

[1474] Example 1

[1475] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1476] Conventional bank transfer systems and traffic monitoring systems are unable to efficiently detect bank transfer fraud and traffic law violations, resulting in insufficient safety for users and the general public. With the rise in bank transfer fraud, real-time fraud detection is required. Furthermore, when detecting traffic law violations, issues arise, such as delayed police response and inability to reliably preserve evidence of violations. To solve these problems, systems using more advanced technology are needed.

[1477] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1478] In this invention, the server includes fraud detection means for analyzing the received reason for transfer, safety determination means for determining the safety of the transfer based on the analysis results, and monitoring means for monitoring traffic conditions to detect violations. This makes it possible to detect transfer fraud in real time, ensure safe transfers, and quickly detect and notify violations of traffic laws.

[1479] "User" refers to an individual or corporation that uses the system to perform transfer operations or check traffic information.

[1480] "Terminal" refers to a device used by a user to input transfer information or display traffic information, such as an ATM or smartphone application.

[1481] A "server" is a computer system that receives and analyzes bank transfer information and traffic information.

[1482] "Input means" refers to the interface (keyboard, touch panel, etc.) through which the user inputs transfer information.

[1483] "Communication means" refers to the network communication protocol (e.g., HTTPS) used by the terminal to send transfer information to the server.

[1484] "Fraud detection means" refers to a function including algorithms and programs that allow the server to analyze the reason for the transfer and detect the possibility of fraud.

[1485] The "analysis result return means" refers to a function by which the server returns the analysis results to the terminal.

[1486] "Display means" refers to a screen or interface that the terminal uses to display the analysis results received from the server to the user.

[1487] "Safety determination means" refers to the function that the server uses to determine the safety of a transfer based on the analysis results.

[1488] "Means for issuing a warning" refers to a function for sending a warning to the user if the server determines that a transfer is suspicious.

[1489] "Monitoring means" refers to the function that enables the server to use AI to monitor traffic conditions in real time and detect violations.

[1490] "Notification means" refers to a function that notifies nearby police officers when the server detects a traffic law violation.

[1491] "Storage means" refers to the storage or database in which the server stores evidence data related to the violation.

[1492] The present invention provides a system for preventing fraud when users make transfers, and a system for monitoring traffic conditions to detect traffic violations. This system is implemented by a series of programs as follows:

[1493] First, a user initiates access to the system by opening an ATM or a banking app on their smartphone. Next, the terminal presents the user with a transfer option, and the user enters the transfer information (transfer amount, recipient information, and reason for the transfer) from the transfer menu. For example, a user might enter "50,000 yen," "Taro Tanaka," and "loan to a friend" at an ATM. The information entered is transmitted from the terminal to the server using a secure communication protocol (e.g., HTTPS).

[1494] The server analyzes the received transfer information in real time and applies a fraud detection algorithm. This algorithm compares the transfer reason, such as "loan to a friend," with past data to determine whether it is likely to be fraudulent. The server then returns the result of the safety assessment to the device. The device then displays the result to the user, displaying a message such as "Transfer completed" or "Warning: Transfer reason unclear."

[1495] Furthermore, in traffic monitoring systems, the server synchronizes surveillance cameras and sensors in designated cities and intersections and begins collecting data in real time. This allows devices to transmit video data from surveillance cameras and information from sensors to the server in real time. The server then uses AI and machine learning models to analyze the collected video data and sensor data and detect violations of traffic laws, such as running red lights or speeding. If a violation is detected, the server notifies nearby police officers, who then include the location and details of the violation. Police officers then rush to the scene and crack down on the offending vehicle.

[1496] As a specific example, a server may detect a vehicle running a red light while monitoring traffic conditions at a specific intersection. Data from surveillance cameras and sensors is sent to the server in real time, and the server uses AI to confirm the violation. This violation information is notified to police officers, who rush to the scene and crack down on the violating vehicle. At that time, the server stores the video data of the red light violation.

[1497] Examples of prompts for generative AI models include:

[1498] "Please tell me more about your fraud prevention system. If a user goes to an ATM to transfer 50,000 yen to his friend Taro Tanaka, how would fraud prevention work?"

[1499] "Please provide details about your automated AI traffic monitoring system. If a red light is detected at a particular intersection, how will the system respond?"

[1500] With these specific processing and prompt sentence examples, the system of the present invention provides efficient fraud prevention and traffic monitoring, ensuring the safety of users and citizens.

[1501] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1502] Step 1:

[1503] The user opens an ATM or banking app.

[1504] Input: User action (accessing an ATM or launching a banking app)

[1505] Output: ATM main screen or initial screen of bank app

[1506] Specifically, the user accesses the nearest ATM or launches a banking app on their smartphone, for example, by tapping the app on their smartphone at home.

[1507] Step 2:

[1508] The terminal will display the transfer menu.

[1509] Input: User request (Display transfer screen on ATM or app)

[1510] Output: Display of transfer options

[1511] Specifically, buttons such as "Transfer" and "Remittance" will appear on the ATM screen or smartphone display, and the user will select one of them.

[1512] Step 3:

[1513] The user enters the transfer information.

[1514] Input: Transfer information entered by the user (transfer amount, recipient information, reason for transfer)

[1515] Output: Confirmation screen of input information

[1516] Specifically, the user uses a keypad or on-screen keyboard to enter information such as "50,000 yen," "Taro Tanaka," and "loan to a friend." Once the information is complete, it is displayed on a confirmation screen.

[1517] Step 4:

[1518] The terminal transmits the input information to the server.

[1519] Input: User's bank transfer information

[1520] Output: Send confirmation message

[1521] Specifically, the terminal sends the transfer information to the server using a secure communication protocol such as HTTPS. Once the transmission is complete, the terminal displays a confirmation message to the user.

[1522] Step 5:

[1523] The server receives and analyzes the transfer information.

[1524] Input: Transfer information sent from the terminal

[1525] Output: Analysis results

[1526] Specifically, the server uses a fraud detection algorithm to compare the reason for the transfer, such as "loan to a friend," with past data. Once the analysis is complete, the server determines whether the transaction is legitimate or suspicious.

[1527] Step 6:

[1528] The server determines the security of the transfer.

[1529] Input: Analysis result of transfer reason

[1530] Output: Safety judgment result (normal or suspicious)

[1531] Specifically, the server determines whether the transfer is safe based on the analysis results. For example, if the "loan to a friend" matches the usual transaction pattern in the past, it will be deemed normal.

[1532] Step 7:

[1533] The server sends the results back to the terminal.

[1534] Input: Safety judgment result

[1535] Output: Confirmation of sending result data

[1536] Specifically, the server sends a message to the terminal such as "The transfer has been approved" or "The reason for the transfer is unclear. Please check again." Once the transfer is complete, a log of the transfer confirmation is recorded.

[1537] Step 8:

[1538] The terminal displays the results to the user.

[1539] Input: Result data from the server

[1540] Output: Result display screen

[1541] Specifically, the terminal displays the result received from the server to the user, for example, "Transfer completed" or "Warning: Transfer reason unclear" on the screen.

[1542] The above are the specific processing steps of the bank transfer fraud prevention system of the present invention. Next, we will explain the specific processing steps of the automatic AI traffic monitoring system.

[1543] Step 1:

[1544] The server performs a scan to monitor traffic conditions in the designated area.

[1545] Input: Monitoring area settings

[1546] Output: Confirmation that monitoring has started

[1547] Specifically, the server synchronizes surveillance cameras and sensors installed in designated cities and intersections with the system and begins collecting data in real time.

[1548] Step 2:

[1549] The device collects data from surveillance cameras and sensors and sends it to a server.

[1550] Input: Data from surveillance cameras and sensors

[1551] Output: Data transmission confirmation message

[1552] Specifically, the device sends video data from surveillance cameras and information from speed sensors to the server in real time. Once the transmission is complete, a confirmation message is displayed.

[1553] Step 3:

[1554] The server analyzes the data and determines whether a traffic law violation has occurred.

[1555] Input: Data from surveillance cameras and sensors

[1556] Output: Violation judgment result

[1557] Specifically, the server uses AI and machine learning models to analyze the collected data and detect traffic violations, such as running red lights or speeding.

[1558] Step 4:

[1559] If the server detects a violation, it notifies nearby police officers.

[1560] Input: Violation judgment result

[1561] Output: Notification message to police officer

[1562] Specifically, if a violation is detected, the server immediately notifies nearby police officers of the information, including the driver's location and the details of the violation.

[1563] Step 5:

[1564] The user (police officer) receives a notification and rushes to the scene.

[1565] Input: Notification message from the server

[1566] Output: Officer response actions

[1567] Specifically, police officers receive notifications via smartphones or police radio, rush to the designated scene, and crack down on violating vehicles.

[1568] Step 6:

[1569] A server stores evidence data associated with the violation.

[1570] Input: Video and sensor data from the violation

[1571] Output: Confirmation of save completion

[1572] Specifically, the server stores the video and data of the violation in storage so that it can be viewed later. For example, it stores the video of the moment the red light was run and the speed sensor measurement data.

[1573] The above are the specific processing steps of the automatic AI traffic monitoring system of the present invention, which realizes efficient fraud prevention and traffic monitoring.

[1574] (Application example 1)

[1575] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1576] In modern society, bank transfer fraud and traffic violations have become serious problems. Dealing with these problems often relies on manual monitoring, which is not very efficient. In particular, the number of victims of bank transfer fraud is increasing, especially among the elderly, and traffic violations also have a significant social impact as a cause of traffic accidents. To solve these problems, there is a need for a system that can prevent bank transfer fraud and detect traffic violations in real time and respond immediately.

[1577] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1578] In this invention, the server includes an input means for a user to input transfer information, a communication means by which the terminal transmits the transfer information to the server, a fraud detection means by which the server analyzes the reason for the transfer received, an analysis result return means by which the server returns the analysis result to the terminal, a display means by which the terminal displays the analysis result to the user, a monitoring means by which a police officer uses smart glasses to monitor traffic violations in real time, a data collection means by which the smart glasses collect data from surveillance cameras and sensors and transmit it to the server, and a notification means by which the server detects traffic violations using an AI model and notifies the police officer. This makes it possible to prevent transfer fraud and detect traffic violations in real time.

[1579] "Input means" refers to a device or method for a user to input data such as transfer information.

[1580] A "communication means" is a device or method for transmitting data from a terminal to a server.

[1581] "Fraud detection means" refers to a device or method that analyzes the transfer information received by the server and determines the possibility of fraud based on its contents.

[1582] The "analysis result return means" is a device or method for the server to return the analysis results to the terminal.

[1583] The "display means" is a device or method for displaying the analysis results received by the terminal from the server to the user.

[1584] "Monitoring means" means a device or method for officers to monitor traffic conditions in real time using smart glasses.

[1585] "Data collection means" refers to a device or method by which the smart glasses collect traffic data from surveillance cameras and sensors and transmit it to the server.

[1586] The "notification means" is a device or method for notifying police officers of traffic violations detected by the server.

[1587] An "AI model" is a model for data analysis that is trained using machine learning algorithms.

[1588] "Real-time" refers to processing and reacting simultaneously with real-world time.

[1589] "Bank transfer fraud" is a type of criminal activity that involves deceiving users and fraudulently withdrawing funds.

[1590] A "traffic violation" refers to any action or situation that violates a traffic law.

[1591] As an embodiment of the present invention, a fraud prevention and real-time traffic violation detection system is specifically configured. First, each component of the system is described, and then specific program processing is described.

[1592] Main components of the system

[1593] 1. Input method:

[1594] The user uses a device or method to input transfer information, such as an ATM or a smartphone app.

[1595] 2. Means of communication:

[1596] The terminal uses the internet or mobile network to send the transfer information to the server, using the HTTP protocol and secure communication via SSL / TLS.

[1597] 3. Fraud detection measures:

[1598] The server uses a machine learning model (e.g., a neural network trained with Keras) to analyze the reason for the incoming transfer. This model determines the likelihood of transfer fraud based on past data.

[1599] 4. Method of returning analysis results:

[1600] The server has a means to return the analysis results to the device, and this process is also carried out via a secure communication protocol.

[1601] 5. Display means:

[1602] The terminal receives the analysis results from the server and displays them to the user, specifically on the smartphone screen or ATM display.

[1603] 6. Monitoring measures:

[1604] Police officers will monitor traffic conditions in real time using smart glasses, which are equipped with a built-in camera and display, through which AI models can detect traffic violations.

[1605] 7. Data Collection Methods:

[1606] The smart glasses collect traffic data from surveillance cameras and sensors and transmit it to a server in real time using wireless communication technologies such as Wi-Fi and Bluetooth.

[1607] 8. Means of notification:

[1608] The server notifies police officers of detected traffic violations using text displayed on the smart glasses' display and an audible alert.

[1609] Program processing explanation

[1610] In this invention, when a user transfers funds using an ATM or smartphone app, the input information is sent to a server via secure communications. The server uses an AI model to analyze the reason for the transfer and returns the results to the terminal. The user is informed of the security of the transfer on a display, and the transfer is canceled if there is a possibility of fraud.

[1611] Police officers can monitor traffic conditions in real time by wearing smart glasses. The glasses are equipped with a sophisticated camera that transmits video data of traffic conditions to a server. The server then uses an AI model to analyze the video data, and if a traffic violation is detected, a notification will appear on the smart glasses' display.

[1612] Specific examples

[1613] For example, suppose a police officer is using smart glasses at a busy intersection and a vehicle runs a red light. In this case, the camera in the smart glasses captures the vehicle running the red light, and the data is sent to the server in real time. The server uses an AI model to detect the traffic violation and displays a notification on the officer's smart glasses saying, "A red light has been detected!" The officer can then respond quickly and crack down on the violating vehicle.

[1614] Prompt Sentence Examples

[1615] For a wire transfer fraud detection model: "Is this wire transfer reason likely to be fraudulent?"

[1616] For traffic violation detection models: "Does this image contain a red light run?"

[1617] As a result, the present invention can efficiently prevent bank transfer fraud and detect traffic violations in real time.

[1618] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1619] Step 1:

[1620] The user enters transfer information. The user launches the ATM or smartphone app and enters information such as the transfer amount, recipient information, and reason for transfer. The entered information is obtained through the input means.

[1621] Input: User inputs transfer amount, recipient information, and reason for transfer.

[1622] Output: Transfer information data obtained via the input means.

[1623] Step 2:

[1624] The terminal sends the transfer information to the server. The terminal uses a secure communication protocol (e.g. HTTPS, SSL / TLS) to send the transfer information to the server in real time.

[1625] Input: Transfer information data.

[1626] Output: Transfer information data sent to the server.

[1627] Step 3:

[1628] The server analyzes the reason for the transfer received. The server analyzes the received transfer information using a generative AI model to check for possible fraud. This process includes data enrichment and text analysis to compare with historical data.

[1629] Input: Transfer information data received from the terminal.

[1630] Output: Fraud detection result (whether fraud is likely or not).

[1631] Step 4:

[1632] The server returns the analysis results to the terminal. The server generates the analysis results and returns them to the terminal via a secure communication means.

[1633] Input: Fraud detection results.

[1634] Output: Analysis result data returned to the device.

[1635] Step 5:

[1636] The terminal displays the analysis results to the user. The terminal displays the analysis results received from the server on the screen. The user checks them and completes the transfer if it is deemed safe. If there is a problem, a warning message is displayed.

[1637] Input: Analysis result data from the server.

[1638] Output: Analysis results and warning messages displayed on the screen.

[1639] Step 6:

[1640] Police officers monitor traffic conditions using smart glasses, which use built-in cameras to capture and collect data on traffic conditions in real time.

[1641] Input: Smart glasses camera footage.

[1642] Output: Collected real-time traffic data.

[1643] Step 7:

[1644] The smart glasses transmit the data obtained from the surveillance cameras and sensors to the server. The smart glasses use Wi-Fi or Bluetooth to transmit the collected data to the server.

[1645] Input: Collected real-time traffic data.

[1646] Output: Traffic data sent to the server.

[1647] Step 8:

[1648] The server uses an AI model to detect traffic violations. The server uses an AI model (e.g., computer vision algorithm) to analyze the transmitted video data and detect traffic violations.

[1649] Input: Traffic data sent from smart glasses.

[1650] Output: Detected traffic violation information.

[1651] Step 9:

[1652] The server notifies the police officer of the detected traffic violation information. The server generates the detected traffic violation information and displays the notification on the smart glasses display.

[1653] Input: Detected traffic violation information.

[1654] Output: Notifications shown on the smart glasses display.

[1655] By using these steps, the present invention can efficiently prevent bank transfer fraud and detect traffic violations in real time. This program process appropriately processes input data at each step and performs necessary data calculations, ultimately providing important information to users and police officers.

[1656] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1657] The present invention provides a system that combines a system for preventing fraud when users make bank transfers, a system for monitoring traffic conditions to detect traffic violations, and an emotion engine for recognizing user emotions. This not only improves the efficiency of police work and ensures the safety of citizens, but also improves convenience by taking the user's emotional state into consideration. The system of the present invention is realized by the following program, and its processing is performed as follows.

[1658] Transfer reason specification system and emotion engine

[1659] Program processing explanation

[1660] 1. The user opens an ATM or banking app.

[1661] Users can access the main menu by operating the ATM's touchscreen, or they can launch their banking app on their smartphone and log in.

[1662] 2. The terminal will display the transfer menu.

[1663] The terminal will display a "Transfer" option on the screen for the user to select.

[1664] 3. The user selects the "Transfer" option.

[1665] The user taps the "Transfer" button to proceed to the transfer information input screen.

[1666] 4. The terminal will display the transfer information input screen.

[1667] The terminal displays a screen with fields to enter the amount, recipient information, and reason for the transfer.

[1668] 5. The user enters the necessary bank transfer information.

[1669] The user enters information such as "100,000 yen," "Suzuki Ichiro," and "purchase price of the product" into the form on the screen.

[1670] 6. The terminal sends the entered information to the server.

[1671] The terminal encodes the input data and sends it to the server using a secure communication protocol.

[1672] 7. The device activates an emotion engine that recognizes the user's emotions.

[1673] The device uses sensors such as a camera and microphone to transmit the user's facial expressions and tone of voice to the emotion engine.

[1674] 8. The emotion engine analyzes the user's emotions.

[1675] The emotion engine analyzes facial and vocal data to identify the user's emotional state, such as whether they are tense, relaxed, or confused.

[1676] 9. The emotion engine sends the analysis results to the server.

[1677] The emotion engine encodes the analysis results and sends them to the server.

[1678] 10. The server analyzes the reason for the transfer and emotional data.

[1679] The server integrates and analyzes the received reason for the transfer and emotional data to assess the safety of the transfer and the possibility of fraud.

[1680] 11. The server determines the security of the transfer.

[1681] Based on the analysis results, the server determines whether the transfer is safe and sends the result to the terminal.

[1682] 12. The server returns the analysis results to the device.

[1683] The server encodes the safety judgment result and returns it to the terminal using a secure communication protocol.

[1684] 13. The device displays the analysis results to the user.

[1685] The terminal will display messages to the user such as "Transfer completed" or "Warning: Reason for transfer unclear," and will provide additional guidance and assistance as needed based on emotion data.

[1686] Specific examples

[1687] Suppose a user uses an ATM to transfer 50,000 yen to his friend, Tanaka Taro. When the user enters "50,000 yen," "Tanaka Taro," and "loan to friend" into the ATM, the terminal sends this information to the server. At the same time, the emotion engine analyzes the user's facial expression and tone of voice and determines that the user is relaxed. The server analyzes "loan to friend" and the relaxed emotional state, and if it determines that the transfer does not constitute fraud, it sends a result back to the terminal. The terminal displays the message "Transfer completed," and the transfer is carried out.

[1688] Automatic AI traffic monitoring system and emotion engine

[1689] Program processing explanation

[1690] 1. The server performs a scan to monitor traffic conditions in a specified area.

[1691] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[1692] 2. The device collects data from surveillance cameras and sensors.

[1693] The device acquires surveillance camera footage and sensor data in real time and sends it to the server.

[1694] 3. The server receives the collected data and prepares it for analysis.

[1695] The server stores the received video data and sensor data in a temporary database and prepares it for analysis.

[1696] 4. The server analyzes the data and determines whether a traffic law violation has occurred.

[1697] The server uses AI algorithms to analyze the video data and detect traffic violations such as running red lights or speeding.

[1698] 5. If the server detects a violation, it sends a notification to a nearby police officer.

[1699] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[1700] 6. The user (police officer) receives the notification and rushes to the scene.

[1701] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[1702] 7. The server stores evidence data related to the breach.

[1703] The server stores video and sensor data of violations and archives them for future reference.

[1704] 8. The server combines an emotion engine that recognizes the emotions of police officers.

[1705] The server uses an emotion engine to monitor the emotional state of officers as they conduct field enforcement.

[1706] 9. The emotion engine analyzes the emotions of police officers.

[1707] The emotion engine analyzes the officer's facial expressions and tone of voice to detect stress, fatigue, and other symptoms.

[1708] 10. The server stores the results of the emotion engine and monitors the health status of the officers.

[1709] The server records the analysis results of the emotion engine and continuously monitors the health status of the officers.

[1710] Specific examples

[1711] While the server monitors traffic conditions at a specific intersection, it detects a vehicle running a red light. Data from sensors and cameras is sent to the server in real time, and the server uses AI to confirm the red light has been run. The server then notifies nearby police officers that a red light has been run, and the officers rush to the scene to crack down on the violating vehicle. During this process, the emotion engine monitors the officer's stress level, and provides appropriate support if an abnormality is detected.

[1712] Through these specific processes, the system of the present invention realizes efficient fraud prevention and traffic monitoring, and also builds a safe and fair society that takes into account the emotional states of users and police officers.

[1713] The processing flow will be explained below.

[1714] Transfer reason specification system and emotion engine

[1715] Program processing explanation

[1716] Step 1:

[1717] The user opens an ATM or banking app.

[1718] Users interact with the ATM's touchscreen to access the main menu, or they open their banking app on their smartphone and log in to their account.

[1719] Step 2:

[1720] The terminal will display the transfer menu.

[1721] The terminal displays the transfer options on the screen and allows the user to select the "Transfer" button.

[1722] Step 3:

[1723] The user selects the "Transfer" option.

[1724] The user taps the "Transfer" button and proceeds to the next information input screen.

[1725] Step 4:

[1726] The terminal displays the transfer information input screen.

[1727] The terminal displays a screen containing input fields for entering the transfer amount, recipient information, and reason for the transfer.

[1728] Step 5:

[1729] The user enters the necessary transfer information.

[1730] The user enters "100,000 yen" in the amount field, "Suzuki Ichiro" in the recipient information field, and "purchase price of product" in the transfer reason field.

[1731] Step 6:

[1732] The terminal transmits the input information to the server.

[1733] The terminal transmits the input data to the server using a secure communication protocol.

[1734] Step 7:

[1735] The device activates an emotion engine that recognizes the user's emotions.

[1736] The device activates sensors such as a camera and microphone to transmit the user's facial expressions and tone of voice to the emotion engine.

[1737] Step 8:

[1738] The emotion engine analyzes the user's emotions.

[1739] The emotion engine analyzes the collected facial expression and voice data to determine the user's emotional state, such as whether they are nervous, relaxed, or confused.

[1740] Step 9:

[1741] The emotion engine sends the analysis results to the server.

[1742] The emotion engine encodes the analysis results and sends them to the server using a secure communication protocol.

[1743] Step 10:

[1744] The server receives and analyzes the transfer information and emotion data.

[1745] The server integrates and analyzes the individually received transfer information and emotional data to determine whether the transfer is suspected of being fraudulent.

[1746] Step 11:

[1747] The server determines the security of the transfer.

[1748] Based on the analysis results, the server evaluates whether the transfer is safe and sends the result back to the terminal.

[1749] Step 12:

[1750] The server returns the analysis results to the device.

[1751] The server encodes the result of the decision and returns it to the terminal using a secure communication protocol.

[1752] Step 13:

[1753] The device displays the analysis results to the user.

[1754] The terminal will display messages to the user such as "Transfer completed" or "Warning: Reason for transfer unclear" and will also display additional guidance and assistance messages as needed based on emotion data.

[1755] Automatic AI traffic monitoring system and emotion engine

[1756] Program processing explanation

[1757] Step 1:

[1758] The server performs a scan to monitor traffic conditions in the designated area.

[1759] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[1760] Step 2:

[1761] The device collects data from surveillance cameras and sensors.

[1762] The terminal acquires surveillance camera video data and sensor data in real time and sends it to the server.

[1763] Step 3:

[1764] The server receives the collected data and prepares it for analysis.

[1765] The server stores the received video data and sensor data in virtual memory and prepares it for analysis.

[1766] Step 4:

[1767] The server analyzes the data and determines whether any traffic laws have been violated.

[1768] The server uses AI algorithms to analyze the collected video data and detect traffic violations such as running red lights and speeding.

[1769] Step 5:

[1770] If the server detects a violation, it sends a notification to nearby police officers.

[1771] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[1772] Step 6:

[1773] The user (police officer) receives a notification and rushes to the scene.

[1774] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[1775] Step 7:

[1776] A server stores evidence data associated with the violation.

[1777] The server stores video and sensor data of violations and archives them for future evidence.

[1778] Step 8:

[1779] The server combines an emotion engine that recognizes the emotions of the police officers.

[1780] The server uses an emotion engine to monitor emotional data as police officers conduct enforcement in the field.

[1781] Step 9:

[1782] An emotion engine analyzes the emotions of police officers.

[1783] The emotion engine analyzes an officer's facial expressions and tone of voice to identify stress and fatigue.

[1784] Step 10:

[1785] The server stores the results of the emotion engine and monitors the health of the officers.

[1786] The server records the emotion engine's analysis results and continuously tracks the officers' health status.

[1787] Through these specific processing steps, the system of the present invention effectively realizes fraud prevention and traffic monitoring, and supports safe and fair operation taking into account the emotional states of users and police officers.

[1788] Example 2

[1789] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1790] Conventional bank transfer systems and traffic monitoring systems have difficulty in detecting fraud and traffic violations because it is difficult for users to clearly state the reason for a transfer and to monitor traffic conditions in real time. Furthermore, they are unable to take into account the emotional state of users and police officers, which has led to challenges in improving operational efficiency and safety.

[1791] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1792] In this invention, the server comprises means for a user to input transfer information and a reason for transfer using an information processing device, communication means for a terminal to transmit the input transfer information to the server, emotion recognition means for the terminal to acquire the user's facial expression and voice data, emotion analysis means for analyzing the facial expression and voice data acquired by the emotion recognition means, communication means for transmitting the user's emotion data analyzed by the emotion analysis means to the server, fraud detection means for the server to analyze the transfer reason and the emotion data by integrating them, analysis result return means for the server to return the analysis results to the terminal, display means for the terminal to display the analysis results to the user, and The system includes a means for inputting the information, a communication means for the terminal to transmit the input information to a server in real time, a monitoring means for the server to monitor traffic conditions using an AI algorithm, a notification means for the server to detect violations of traffic laws from the monitoring results and notify police officers, a storage means for the server to store evidential data related to traffic violations, a means for completing the transfer if it is determined to be safe based on the analysis results and displaying a warning and stopping the transfer if fraud is suspected, a means for the server to collect and analyze data obtained from surveillance cameras and sensors in real time, and a means for sending a notification to local police officers or remote control devices when a traffic violation is detected. This enables a safe and efficient system that ensures the safety of transfers, effectively monitors and detects violations of traffic laws, and takes into account the emotional states of users and police officers.

[1793] A "user" is an individual or organization that uses the system and is the entity that performs bank transfer operations and receives traffic monitoring data.

[1794] "Information processing device" refers to all hardware and software used for calculations and data processing, and specifically includes ATMs, smartphones, computers, etc.

[1795] A "terminal" is a device that is directly operated by a user, and is used to input and display information and communicate with a server.

[1796] "Communication means" refers to protocols and devices for transmitting and receiving data, including networks, modems, Wi-Fi, and related software.

[1797] "Emotion recognition means" refers to devices such as sensors, cameras, and microphones that acquire the user's facial expressions and voice data and analyze their emotions.

[1798] "Emotion analysis means" refers to algorithms and software for analyzing acquired facial and voice data to identify the user's emotional state.

[1799] A "server" is a high-performance computer system that collects, stores, analyzes, and communicates data, and includes a central processing unit.

[1800] "Fraud detection methods" refers to algorithms and software that analyze transfer reasons and emotional data to assess the likelihood of fraudulent activity.

[1801] "Means for returning analysis results" refers to a communication protocol and related devices for the server to return the analysis results to the user.

[1802] "Display means" refers to devices and software for visually displaying analysis results, warning messages, etc. to the user.

[1803] "Monitoring means" refers to cameras, sensors, and associated software used to monitor traffic conditions in real time and collect data.

[1804] "Means of notification" refers to communications protocols and related devices for notifying police officers when a traffic violation is detected.

[1805] "Storage means" refers to data storage and software for storing evidentiary data related to traffic violations and making it available for reference when necessary.

[1806] A "remote control device" is a device for dealing with traffic violations remotely, including traffic light control systems and automobile control systems.

[1807] The system of the present invention combines a traffic violation detection system that monitors traffic conditions and prevents fraud when making bank transfers with an emotion engine that recognizes the user's emotional state. This not only improves the efficiency of police work and ensures the safety of citizens, but also improves convenience by taking the user's emotional state into consideration.

[1808] The system includes the following main components:

[1809] 1. User: Enters data at an ATM or through a banking app.

[1810] 2. Terminal: A device operated by the user that inputs and displays transfer information and acquires emotional data. Examples include ATMs, smartphones, and computers.

[1811] 3. Server: A central computer system that collects, stores, analyzes, and communicates data.

[1812] Transfer reason specification system and emotion engine

[1813] Hardware and Software

[1814] The user uses an information processing device (an ATM or a smartphone or computer with a banking app running).

[1815] The terminal uses a touch screen and keyboard to input transfer information and the reason for the transfer.

[1816] The device collects the user's facial expressions using a camera and their tone of voice using a microphone, and sends these to emotion recognition software (e.g., Google Cloud Vision API or Amazon Rekognition).

[1817] The server uses AI algorithms (TensorFlow and PyTorch) to analyze the reason for transfer and emotional data in real time.

[1818] Specific examples

[1819] Suppose a user wants to use an ATM to transfer 50,000 yen to their friend, Taro Tanaka. The user enters "50,000 yen," "Taro Tanaka," and "loan to friend" in the ATM's "Transfer" menu. At the same time, the device's emotion recognition function analyzes the user's facial expressions and voice and determines that they are relaxed. This data is sent to a server, which uses AI to analyze the safety of the transfer. If it determines that the transfer is not fraudulent, a "Transfer Completed" notification is displayed on the device and the transfer is carried out.

[1820] Automatic AI traffic monitoring system and emotion engine

[1821] Hardware and Software

[1822] The device collects traffic data from surveillance cameras and sensors and sends it to a server.

[1823] The server uses a database (e.g., AWS S3) and analysis software (e.g., OpenCV, YOLOv3 model) to store and analyze the data collected in real time.

[1824] A communication system in which a server detects violations of traffic laws and notifies police officers.

[1825] Specific examples

[1826] The server monitors traffic conditions at specific intersections and detects vehicles that run red lights. Data from sensors and cameras is sent to the server in real time, and AI confirms that the red light has been run. The server then sends a notification to nearby police officers that a red light has been run. The officers then rush to the scene and crack down on the violating vehicle. At this time, the emotion engine monitors the stress level of the officers, and if an abnormality is detected, appropriate support is provided.

[1827] Example prompts for generative AI models

[1828] "I would like to transfer 50,000 yen to Taro Tanaka using an ATM. However, please tell me the process to check whether this transfer is fraudulent."

[1829] "Please tell me in detail the specific processing steps of an AI system that detects traffic violations using surveillance cameras placed at specific intersections."

[1830] In this way, the system of the present invention realizes efficient fraud prevention and traffic monitoring, and builds a safe and fair society that takes into account the emotional states of users and police officers.

[1831] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1832] Transfer reason specification system and emotion engine

[1833] Processing flow and specific operations

[1834] Step 1:

[1835] The user opens an ATM or banking app.

[1836] Input: Authentication begins when you insert your card into an ATM or launch your banking app on your smartphone.

[1837] Output: After authentication, the main menu will be displayed.

[1838] Specific actions: The user operates the ATM's touch screen to access the main menu, or logs in using their ID and password in the banking app.

[1839] Step 2:

[1840] The terminal will display the transfer menu.

[1841] Input: The authenticated user's request.

[1842] Output: The transfer menu will appear on the screen.

[1843] What it does: The terminal displays the "Transfer" option on the screen for the user to select.

[1844] Step 3:

[1845] The user selects the "Transfer" option.

[1846] Input: Select Transfer menu.

[1847] Output: The transfer information input screen will be displayed.

[1848] Specific operation: The user taps the "Transfer" button and proceeds to the screen to enter transfer information.

[1849] Step 4:

[1850] The terminal displays the transfer information input screen.

[1851] Enter: Select a transfer option.

[1852] Output: Input fields for amount, recipient information, and transfer reason are displayed.

[1853] What it does: The terminal displays a screen with fields for entering the amount, recipient information, and reason for the transfer.

[1854] Step 5:

[1855] The user enters the necessary transfer information.

[1856] Input: Enter the transfer amount, recipient information, and reason for transfer.

[1857] Output: The input data is saved to the device.

[1858] Specific operation: The user enters information such as "50,000 yen," "Taro Tanaka," and "loan to a friend" into the form on the screen.

[1859] Step 6:

[1860] The terminal transmits the input information to the server.

[1861] Input: Transfer information entered by the user.

[1862] Output: The transfer information is sent to the server.

[1863] Specific operation: The terminal encrypts the input data using the SSL / TLS protocol and sends it to the server.

[1864] Step 7:

[1865] The device activates an emotion engine that recognizes the user's emotions.

[1866] Input: User's facial expression and voice data.

[1867] Output: Emotion recognition data is sent to the emotion engine.

[1868] Specific operation: The device's camera captures the user's facial expressions, and the microphone captures the user's voice. This data is then sent to the emotion engine.

[1869] Step 8:

[1870] The emotion engine analyzes the user's emotions.

[1871] Input: facial expression and voice data.

[1872] Output: Emotional state analysis result.

[1873] What it does: The emotion engine uses facial recognition and voice analysis to determine whether the user is relaxed or tense.

[1874] Step 9:

[1875] The emotion engine sends the analysis results to the server.

[1876] Input: Emotional state analysis results.

[1877] Output: Emotion data sent to the server.

[1878] Specific operation: The emotion engine encodes the analysis results and sends them to the server.

[1879] Step 10:

[1880] The server analyzes the reason for the transfer and emotional data.

[1881] Input: Reason for transfer, emotional data.

[1882] Output: A rating of the transfer's safety.

[1883] How it works: The server uses an AI model to comprehensively analyze the reason for the transfer and emotional data to assess the likelihood of fraud.

[1884] Step 11:

[1885] The server determines the security of the transfer.

[1886] Input: A rating of the transfer's safety.

[1887] Output: Safety-based decision result.

[1888] Specific operation: The server determines the safety of the transfer based on the evaluation results and prepares to send the results to the terminal.

[1889] Step 12:

[1890] The server returns the analysis results to the device.

[1891] Input: Safety decision result.

[1892] Output: The result data sent to the terminal.

[1893] Specific operation: The server encodes the security judgment result and sends it to the terminal.

[1894] Step 13:

[1895] The device displays the analysis results to the user.

[1896] Input: Analysis results received from the server.

[1897] Output: The resulting message displayed to the user.

[1898] What it does: The terminal will display a message such as "Transfer complete" or "Warning: Reason for transfer unclear" and provide additional guidance or assistance as needed.

[1899] Automatic AI traffic monitoring system and emotion engine

[1900] Processing flow and specific operations

[1901] Step 1:

[1902] The server performs a scan to monitor traffic conditions in the designated area.

[1903] Input: Specification of the monitoring area.

[1904] Output: Monitoring data collection begins.

[1905] Specific operation: The server activates the surveillance cameras and sensors placed in the designated area and starts collecting data in real time.

[1906] Step 2:

[1907] The device collects data from surveillance cameras and sensors.

[1908] Input: Data from surveillance cameras and sensors.

[1909] Output: Collected data sent to the server.

[1910] Specific operation: The device acquires video data from surveillance cameras and speed information from radar sensors, and sends this data to a server.

[1911] Step 3:

[1912] The server receives the collected data and prepares it for analysis.

[1913] Input: Collected monitoring data.

[1914] Output: Database updates required for analysis.

[1915] Specific operation: The server stores the collected data in temporary data storage (e.g., AWS S3) and prepares it for analysis.

[1916] Step 4:

[1917] The server analyzes the data and determines whether any traffic laws have been violated.

[1918] Input: Stored monitoring data.

[1919] Output: Traffic law violation detection results.

[1920] Specific operation: The server uses AI algorithms (e.g., OpenCV or YOLOv3 models) to analyze video data and detect traffic violations such as running red lights or speeding.

[1921] Step 5:

[1922] If the server detects a violation, it sends a notification to nearby police officers.

[1923] Input: Traffic violation detection results.

[1924] Output: Notification sent to the officer.

[1925] Specific operation: When a violation is detected, the server sends a notification containing the details of the violation and GPS information to the device of a nearby police officer.

[1926] Step 6:

[1927] The user (police officer) receives a notification and rushes to the scene.

[1928] Input: Notification from the server.

[1929] Output: Police arrive on scene and take action.

[1930] Specific operation: The police officer receives a notification from the server and rushes to the designated location to crack down on traffic violators.

[1931] Step 7:

[1932] A server stores evidence data associated with the violation.

[1933] Input: Evidence data related to traffic violations.

[1934] Output: Stored evidence data.

[1935] Specific operation: The server stores video data and sensor data related to violations for a long period of time, making it available for reference when needed.

[1936] Step 8:

[1937] The server combines an emotion engine that recognizes the emotions of the police officers.

[1938] Input: Officer facial and voice data.

[1939] Output: Recognized emotion data.

[1940] How it works: When police officers conduct a police operation, the server activates the emotion engine to monitor their facial expressions and tone of voice, and the collected data is sent to the emotion analysis engine.

[1941] Step 9:

[1942] An emotion engine analyzes the emotions of police officers.

[1943] Input: facial expression and voice data.

[1944] Output: Emotional state analysis result.

[1945] How it works: The emotion engine uses facial recognition technology and voice analysis algorithms to identify officer stress and fatigue.

[1946] Step 10:

[1947] The server stores the results of the emotion engine and monitors the health of the officers.

[1948] Input: Emotional state analysis results.

[1949] Output: Stored officer health data.

[1950] What it does: The server stores the analysis results in a database, continuously monitors the health status of officers, and issues an alert to provide appropriate support if an abnormality is detected.

[1951] (Application example 2)

[1952] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1953] In modern society, preventing fraud during bank transfers, monitoring and detecting traffic violations, and ensuring safety in self-driving vehicles are important challenges. However, existing systems address each problem individually and do not provide a consistent solution that takes into account the emotional state of the user or driver. Therefore, a more effective and comprehensive system is needed.

[1954] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes input means for the user to input bank transfer information, communication means by which the terminal transmits the bank transfer information to the server, fraud detection means for analyzing the reason for the bank transfer received by the server, analysis result return means by which the server transmits the analysis results to the terminal, display means by which the terminal displays the analysis results to the user, collection means by which the terminal collects image information and audio information from inside the vehicle, emotion analysis means by which the emotion engine analyzes the collected data to identify the emotional state, and vehicle control means for controlling the vehicle based on the emotion analysis results. This enables fraud prevention during bank transfers, detection of traffic violations, and comprehensive safety measures that take into account the emotional states of drivers and passengers in self-driving vehicles.

[1955] "User" means a person who uses the system to make bank transfers or operate self-driving vehicles.

[1956] "Transfer information" refers to detailed information required for a user to make a transfer, such as the account number of the transfer recipient, the transfer amount, and the reason for the transfer.

[1957] "Input means" refers to a device or interface through which a user inputs transfer information. Specifically, this includes ATMs and smartphone applications.

[1958] "Communication means" refers to the communication protocol and network functions that allow the terminal to send transfer information to the server.

[1959] "Fraud detection means" refers to algorithms or programs that analyze the reason for transfer received by the server and evaluate and detect the possibility of fraud.

[1960] "Means for returning analysis results" refers to the communication protocol and network functions that allow the server to return analysis results to the terminal.

[1961] The "display means" refers to a display or screen that the terminal uses to display the analysis results to the user.

[1962] "In-vehicle image information and audio information" refers to image and audio data of the driver and passengers collected by cameras and microphones installed inside the vehicle.

[1963] "Collection means" refers to cameras and microphones used to collect image and audio information inside the vehicle, as well as associated sensors and software.

[1964] "Emotion analysis means" refers to AI algorithms or programs for analyzing the emotional state of drivers and passengers from collected image and audio information.

[1965] "Vehicle control means" refers to a device or program for controlling the speed and behavior of a vehicle based on the emotion analysis results.

[1966] "Traffic condition data" refers to information such as traffic flow, traffic light conditions, and vehicle positions collected from surveillance cameras and sensors.

[1967] "Emergency services" refers to services such as police, fire, and ambulances that respond quickly in the event of an accident or dangerous situation.

[1968] An "emotion engine" refers to a program or algorithm for implementing emotion analysis means, which analyzes emotional states from collected image and audio data.

[1969] "Analysis means" refers to the systems and algorithms used to integrate emotion analysis results with traffic data and analyze them using an AI model.

[1970] This invention is a comprehensive system for preventing fraudulent bank transfers, monitoring traffic violations, and improving safety in self-driving vehicles. Each means and process of the system will be described below.

[1971] Bank transfer fraud prevention system

[1972] The user enters transfer information using an ATM or bank app. The entered information is sent to the server via the terminal. The server analyzes the reason for the transfer using fraud detection means. The analysis results are sent back from the server to the terminal, which displays them to the user. If the server detects the possibility of fraud in the transfer information entered by the user, the terminal displays a warning to the user and cancels the transfer.

[1973] Traffic Monitoring System

[1974] The server collects and analyzes traffic data from surveillance cameras and sensors in real time. The server is equipped with AI algorithms that detect traffic violations, such as running red lights and speeding, in real time. Detected violations are reported to police officers or automated control devices. Evidence data related to violations is stored on the server for future reference.

[1975] Safety management systems for autonomous vehicles

[1976] Emotion Monitoring

[1977] The device uses cameras and microphones installed inside the autonomous vehicle to collect image and audio information from the driver and passengers. The collected data is analyzed by an emotion engine to identify the emotional state of the driver and passengers. The behavior of the autonomous vehicle is controlled based on this emotional state. For example, if the emotion engine determines that the driver is fatigued or stressed, it may slow down the vehicle or suggest a break.

[1978] Emergency response

[1979] The server integrates and analyzes traffic data and emotion data to detect accidents and emergencies. If an emergency occurs, the server automatically notifies the police and emergency services. If necessary, an emergency assistance message is displayed to the user.

[1980] Hardware and software used

[1981] Camera and microphone: To monitor what's happening inside the car in real time.

[1982] OpenCV: A library for real-time image processing.

[1983] Emotion Analysis Engine (EmotionEngine): A software module for analyzing the emotional state of drivers and passengers.

[1984] Traffic Monitoring System (TrafficMonitor): A system for monitoring surrounding traffic conditions in real time.

[1985] Emergency Response System (EmergencyResponse): A software module for responding to accidents and emergency situations.

[1986] Specific examples

[1987] A concrete example would be a scenario where an autonomous vehicle is traveling on a highway and the driver is fatigued, and the vehicle detects this emotional state and slows down, encouraging the driver to take a break.

[1988] Prompt Sentence Examples

[1989] "A self-driving vehicle is driving down the highway and the driver's face looks fatigued. What should the self-driving vehicle do next?"

[1990] By implementing this invention, it will be possible to prevent fraud during bank transfers, detect traffic violations, and implement comprehensive safety measures in autonomous vehicles that take into account the emotional state of drivers and passengers.

[1991] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1992] Step 1:

[1993] A user opens an ATM or banking app. They either interact with the ATM's touchscreen to access the main menu or launch the banking app on their smartphone and log in. Inputs include the user's login information and interface interactions. Outputs include the ATM or app's main menu screen.

[1994] Step 2:

[1995] The terminal displays a transfer menu. The terminal displays a "Transfer" option on the screen for the user to select. Input includes the user's selection on the main menu. Output includes a screen where transfer information can be entered.

[1996] Step 3:

[1997] The user selects the "Transfer" option. The user taps the "Transfer" button to proceed to the transfer information input screen. The input includes the user's selection. The output displays the transfer information input screen.

[1998] Step 4:

[1999] The terminal displays a screen for inputting transfer information. The terminal displays a screen containing input fields for the amount, recipient information, and reason for transfer. The input contains the transfer information format held by the system. The output is the screen for inputting transfer information.

[2000] Step 5:

[2001] The user enters the necessary transfer information. The user enters information such as "100,000 yen," "recipient's name," and "purchase price of the product" into the form on the screen. The input includes the transfer information provided by the user. The output is generated as transfer information data.

[2002] Step 6:

[2003] The terminal sends the input information to the server. The terminal encodes the input data and sends it to the server using a secure communication protocol. The input is the encoded transfer information. The output is the transfer information data to be sent to the server.

[2004] Step 7:

[2005] The terminal collects image and audio information from inside the vehicle. Using cameras and microphones installed inside the vehicle, the terminal collects image and audio information from the driver and passengers. The input is real-time data from the cameras and microphones. The output is the collected image and audio data.

[2006] Step 8:

[2007] The emotion engine analyzes the collected data to identify the emotional state. The emotion engine analyzes image and audio information to identify the emotional state, for example, whether the driver is relaxed or tense. The input is the collected image and audio data. The output is the identified emotional state data.

[2008] Step 9:

[2009] The server analyzes the received reason for the transfer. The server uses fraud detection means to analyze the reason for the transfer and evaluate the likelihood of fraud. The inputs are the reason for the transfer and emotional state data. The output is an analysis result regarding the likelihood of fraud.

[2010] Step 10:

[2011] The server returns the analysis results to the device. The server encodes the analysis results and returns them to the device using a secure communication protocol. The input is the analysis results. The output is the returned analysis result data.

[2012] Step 11:

[2013] The terminal displays the analysis results to the user. The terminal displays messages such as "Transfer completed" or "Warning: The reason for transfer is unclear" to the user. It also displays additional guidance or assistance as needed based on the emotion data. The input is the returned analysis result data. The output is the message or guidance to be displayed.

[2014] Step 12:

[2015] The system controls the vehicle based on the emotion analysis results. If the emotional state is recognized as abnormal, it controls the vehicle speed or suggests a break. The input is the identified emotional state data. The output is the vehicle speed control or a suggested message.

[2016] Step 13:

[2017] The server collects and analyzes traffic condition data in real time. The server collects traffic condition data from surveillance cameras and sensors and analyzes it using an AI algorithm. The input is data from surveillance cameras and sensors. The output is data on traffic violation detection results.

[2018] Step 14:

[2019] Detects traffic violations and sends notifications to police officers or automated control devices. When the server detects a traffic violation, it sends a notification to a nearby police officer or automated control device. As input, it has the detection result data. As output, it has the notification data to be sent.

[2020] Step 15:

[2021] Stores evidence data related to violations. The server stores video data and sensor information related to traffic violations and archives it for future reference. The input is the collected and analyzed evidence data. The output is the stored archive data.

[2022] Step 16:

[2023] Automatically notify police and emergency services when an accident or emergency situation occurs. The server sends a notification to police and emergency services when an accident is detected, and appropriate assistance is provided. The input is the accident detection data. The output is the sent emergency notification data.

[2024] Step 17:

[2025] The user follows the messages and suggestions they receive from the system. The user receives suggestions and notifications from the device and takes action based on them. The input is the message or suggestion from the device. The output is the user's actions.

[2026] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2027] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2028] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2029] [Fourth embodiment]

[2030] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2031] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2033] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2034] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2035] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2037] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2038] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2039] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[2040] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2041] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2042] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2043] The present invention provides a system for preventing fraud when users make bank transfers, and a system for monitoring traffic conditions to detect traffic violations, thereby improving the efficiency of police work and ensuring the safety of citizens. The system of the present invention is implemented by a series of programs, and its processing is as follows.

[2044] System for specifying the reason for transfer

[2045] Program processing explanation

[2046] 1. The user opens an ATM or banking app.

[2047] Users first open the ATM's main screen or their bank's app on their smartphone to begin accessing the system.

[2048] 2. The terminal will display the transfer menu.

[2049] The terminal presents the user with a menu of transfer options, from which the user selects "Transfer."

[2050] 3. The user enters the transfer information.

[2051] The user inputs the transfer amount, the recipient's information, and the reason for the transfer. For example, the user inputs information such as "100,000 yen to Ichiro Suzuki as the recipient, and the reason is the purchase price of a product."

[2052] 4. The terminal sends the entered information to the server.

[2053] The terminal transmits all entered information to the server using a secure communication protocol.

[2054] 5. The server receives and analyzes the transfer information.

[2055] The server applies fraud detection algorithms to analyze the reason for the transfer received, checking reasons such as "purchase of goods" or "repayment to a friend," and compares them with historical data.

[2056] 6. The server determines whether the transfer is safe.

[2057] Based on the analysis, the server determines whether the transfer is safe or suspicious. If it is safe, the transfer proceeds, otherwise a warning is issued.

[2058] 7. The server sends the results back to the device.

[2059] The server returns the security result to the terminal, for example, a message saying "The transfer has been approved" or "The reason for the transfer is unclear. Please check again."

[2060] 8. The terminal displays the results to the user.

[2061] The terminal displays the result received from the server to the user, for example, displaying a message such as "Transfer completed" or "Warning: The reason for transfer is unclear" on the screen.

[2062] Specific examples

[2063] Suppose a user uses an ATM to transfer 50,000 yen to his friend, Tanaka Taro. When the user enters "50,000 yen," "Tanaka Taro," and "loan to friend" into the ATM, the terminal sends this information to the server. The server analyzes "loan to friend" and, if it determines that the transfer is not fraudulent, it sends a result back to the terminal. The terminal displays the message "Transfer completed," and the transfer is carried out.

[2064] Automatic AI Traffic Monitoring System

[2065] Program processing explanation

[2066] 1. The server performs a scan to monitor traffic conditions in a specified area.

[2067] The server synchronizes all cameras and sensors in the specified city or intersection and begins collecting data in real time.

[2068] 2. The device collects data from surveillance cameras and sensors and sends it to the server.

[2069] The device transmits video data from surveillance cameras and information obtained from sensors to a server in real time.

[2070] 3. The server analyzes the data and determines whether a traffic law violation has occurred.

[2071] The server uses AI and machine learning models to analyze video and sensor data to detect traffic violations, such as running red lights or speeding.

[2072] 4. If the server detects a violation, it notifies nearby police officers.

[2073] When a violation is detected, the server immediately notifies nearby police officers of the incident, including the location and details of the violation.

[2074] 5. The user (police officer) receives the notification and rushes to the scene.

[2075] Once police receive the notification, they will rush to the designated location and crack down on the offending vehicle.

[2076] 6. The server stores evidence data related to the breach.

[2077] The server stores footage and data of violations so that they can be viewed later.

[2078] Specific examples

[2079] While the server monitors traffic conditions at a specific intersection, it detects vehicles that run red lights. Data from sensors and cameras is sent to the server in real time, and the server uses AI to confirm that a red light has been run. The server then sends a notification to a nearby police officer that a red light has been run, and the officer rushes to the scene to crack down on the violating vehicle. At that time, the server stores the video data of the red light run.

[2080] Through these specific processes, the system of the present invention provides efficient fraud prevention and traffic monitoring.

[2081] The processing flow will be explained below.

[2082] System for specifying the reason for transfer

[2083] Program processing explanation

[2084] Step 1:

[2085] The user opens an ATM or banking app.

[2086] Users operate the ATM's touchscreen to access the main menu, or they launch their banking app on their smartphone and log in.

[2087] Step 2:

[2088] The terminal will display the transfer menu.

[2089] The terminal will display a "Transfer" option on the screen for the user to select.

[2090] Step 3:

[2091] The user selects the "Transfer" option.

[2092] The user taps the "Transfer" button to proceed to the transfer information input screen.

[2093] Step 4:

[2094] The terminal displays the transfer information input screen.

[2095] The terminal displays a screen with fields to enter the amount, recipient information, and reason for the transfer.

[2096] Step 5:

[2097] The user enters the necessary transfer information.

[2098] The user enters information such as "100,000 yen," "Suzuki Ichiro," and "purchase price of the product" into the form on the screen.

[2099] Step 6:

[2100] The terminal transmits the input information to the server.

[2101] The terminal encodes the input data and sends it to the server using a secure communication protocol.

[2102] Step 7:

[2103] The server receives the transfer information.

[2104] The server decodes the received data and prepares it for analysis.

[2105] Step 8:

[2106] The server analyzes the reason for the transfer.

[2107] The server applies fraud detection algorithms to analyze the input reason for the transfer and assess its safety.

[2108] Step 9:

[2109] The server determines the security of the transfer.

[2110] The server will then use the analysis results to determine whether the transfer is safe or not, and if it is determined to be fraudulent, it will also provide the reason for this.

[2111] Step 10:

[2112] The server returns the analysis results to the device.

[2113] The server encodes the safety judgment result and returns it to the terminal using a secure communication protocol.

[2114] Step 11:

[2115] The device displays the analysis results to the user.

[2116] The terminal will display a message to the user such as "Transfer completed" or "Warning: Reason for transfer unclear."

[2117] Automatic AI Traffic Monitoring System

[2118] Program processing explanation

[2119] Step 1:

[2120] The server performs a scan to monitor traffic conditions in the designated area.

[2121] The server activates surveillance cameras and sensors located in a designated area and begins collecting data.

[2122] Step 2:

[2123] The device collects data from surveillance cameras and sensors.

[2124] The device acquires surveillance camera footage and sensor data in real time and sends it to the server.

[2125] Step 3:

[2126] The server receives the collected data and prepares it for analysis.

[2127] The server stores the received video data and sensor data in a temporary database and prepares it for analysis.

[2128] Step 4:

[2129] The server analyzes the data and determines whether any traffic laws have been violated.

[2130] The server uses AI algorithms to analyze the video data and detect traffic violations such as running red lights or speeding.

[2131] Step 5:

[2132] If the server detects a violation, it sends a notification to nearby police officers.

[2133] When a violation is detected, the server notifies the police officer of the details of the violation along with GPS information.

[2134] Step 6:

[2135] The user (police officer) receives a notification and rushes to the scene.

[2136] Police officers receive notifications from the server and rush to the designated location to crack down on traffic violators.

[2137] Step 7:

[2138] A server stores evidence data associated with the violation.

[2139] The server stores video and sensor data of violations and archives them for future reference.

[2140] By these steps, the system of the present invention realizes the user's bank transfer activity and traffic situation monitoring efficiently and safely.

[2141] Example 1

[2142] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2143] Conventional bank transfer systems and traffic monitoring systems are unable to efficiently detect bank transfer fraud and traffic law violations, resulting in insufficient safety for users and the general public. With the rise in bank transfer fraud, real-time fraud detection is required. Furthermore, when detecting traffic law violations, issues arise, such as delayed police response and inability to reliably preserve evidence of violations. To solve these problems, systems using more advanced technology are needed.

[2144] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2145] In this invention, the server includes fraud detection means for analyzing the received reason for transfer, safety determination means for determining the safety of the transfer based on the analysis results, and monitoring means for monitoring traffic conditions to detect violations. This makes it possible to detect transfer fraud in real time, ensure safe transfers, and quickly detect and notify violations of traffic laws.

[2146] "User" refers to an individual or corporation that uses the system to perform transfer operations or check traffic information.

[2147] "Terminal" refers to a device used by a user to input transfer information or display traffic information, such as an ATM or smartphone application.

[2148] A "server" is a computer system that receives and analyzes bank transfer information and traffic information.

[2149] "Input means" refers to the interface (keyboard, touch panel, etc.) through which the user inputs transfer information.

[2150] "Communication means" refers to the network communication protocol (e.g., HTTPS) used by the terminal to send transfer information to the server.

[2151] "Fraud detection means" refers to a function including algorithms and programs that allow the server to analyze the reason for the transfer and detect the possibility of fraud.

[2152] The "analysis result return means" refers to a function by which the server returns the analysis results to the terminal.

[2153] "Display means" refers to a screen or interface that the terminal uses to display the analysis results received from the server to the user.

[2154] "Safety determination means" refers to the function that the server uses to determine the safety of a transfer based on the analysis results.

[2155] "Means for issuing a warning" refers to a function for sending a warning to the user if the server determines that a transfer is suspicious.

[2156] "Monitoring means" refers to the function that enables the server to use AI to monitor traffic conditions in real time and detect violations.

[2157] "Notification means" refers to a function that notifies nearby police officers when the server detects a traffic law violation.

[2158] "Storage means" refers to the storage or database in which the server stores evidence data related to the violation.

[2159] The present invention provides a system for preventing fraud when users make transfers, and a system for monitoring traffic conditions to detect traffic violations. This system is implemented by a series of programs as follows:

[2160] First, a user initiates access to the system by opening an ATM or a banking app on their smartphone. Next, the terminal presents the user with a transfer option, and the user enters the transfer information (transfer amount, recipient information, and reason for the transfer) from the transfer menu. For example, a user might enter "50,000 yen," "Taro Tanaka," and "loan to a friend" at an ATM. The information entered is transmitted from the terminal to the server using a secure communication protocol (e.g., HTTPS).

[2161] The server analyzes the received transfer information in real time and applies a fraud detection algorithm. This algorithm compares the transfer reason, such as "loan to a friend," with past data to determine whether it is likely to be fraudulent. The server then returns the result of the safety assessment to the device. The device then displays the result to the user, displaying a message such as "Transfer completed" or "Warning: Transfer reason unclear."

[2162] Furthermore, in traffic monitoring systems, the server synchronizes surveillance cameras and sensors in designated cities and intersections and begins collecting data in real time. This allows devices to transmit video data from surveillance cameras and information from sensors to the server in real time. The server then uses AI and machine learning models to analyze the collected video data and sensor data and detect violations of traffic laws, such as running red lights or speeding. If a violation is detected, the server notifies nearby police officers, who then include the location and details of the violation. Police officers then rush to the scene and crack down on the offending vehicle.

[2163] As a specific example, a server may detect a vehicle running a red light while monitoring traffic conditions at a specific intersection. Data from surveillance cameras and sensors is sent to the server in real time, and the server uses AI to confirm the violation. This violation information is notified to police officers, who rush to the scene and crack down on the violating vehicle. At that time, the server stores the video data of the red light violation.

[2164] Examples of prompts for generative AI models include:

[2165] "Please tell me more about your fraud prevention system. If a user goes to an ATM to transfer 50,000 yen to his friend Taro Tanaka, how would fraud prevention work?"

[2166] "Please provide details about your automated AI traffic monitoring system. If a red light is detected at a particular intersection, how will the system respond?"

[2167] With these specific processing and prompt sentence examples, the system of the present invention provides efficient fraud prevention and traffic monitoring, ensuring the safety of users and citizens.

[2168] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2169] Step 1:

[2170] The user opens an ATM or banking app.

[2171] Input: User action (accessing an ATM or launching a banking app)

[2172] Output: ATM main screen or initial screen of bank app

[2173] Specifically, the user accesses the nearest ATM or launches a banking app on their smartphone, for example, by tapping the app on their smartphone at home.

[2174] Step 2:

[2175] The terminal will display the transfer menu.

[2176] Input: User request (Display transfer screen on ATM or app)

[2177] Output: Display of transfer options

[2178] Specifically, buttons such as "Transfer" and "Remittance" will appear on the ATM screen or smartphone display, and the user will select one of them.

[2179] Step 3:

[2180] The user enters the transfer information.

[2181] Input: Transfer information entered by the user (transfer amount, recipient information, reason for transfer)

[2182] Output: Confirmation screen of input information

[2183] Specifically, the user uses a keypad or on-screen keyboard to enter information such as "50,000 yen," "Taro Tanaka," and "loan to a friend." Once the information is complete, it is displayed on a confirmation screen.

[2184] Step 4:

[2185] The terminal transmits the input information to the server.

[2186] Input: User's bank transfer information

[2187] Output: Send confirmation message

[2188] Specifically, the terminal sends the transfer information to the server using a secure communication protocol such as HTTPS. Once the transmission is complete, the terminal displays a confirmation message to the user.

[2189] Step 5:

[2190] The server receives and analyzes the transfer information.

[2191] Input: Transfer information sent from the terminal

[2192] Output: Analysis results

[2193] Specifically, the server uses a fraud detection algorithm to compare the reason for the transfer, such as "loan to a friend," with past data. Once the analysis is complete, the server determines whether the transaction is legitimate or suspicious.

[2194] Step 6:

[2195] The server determines the security of the transfer.

[2196] Input: Analysis result of transfer reason

[2197] Output: Safety judgment result (normal or suspicious)

[2198] Specifically, the server determines whether the transfer is safe based on the analysis results. For example, if the "loan to a friend" matches the usual transaction pattern in the past, it will be deemed normal.

[2199] Step 7:

[2200] The server sends the results back to the terminal.

[2201] Input: Safety judgment result

[2202] Output: Confirmation of sending result data

[2203] Specifically, the server sends a message to the terminal such as "The transfer has been approved" or "The reason for the transfer is unclear. Please check again." Once the transfer is complete, a log of the transfer confirmation is recorded.

[2204] Step 8:

[2205] The terminal displays the results to the user.

[2206] Input: Result data from the server

[2207] Output: Result display screen

[2208] Specifically, the terminal displays the result received from the server to the user, for example, "Transfer completed" or "Warning: Transfer reason unclear" on the screen.

[2209] The above are the specific processing steps of the bank transfer fraud prevention system of the present invention. Next, we will explain the specific processing steps of the automatic AI traffic monitoring system.

[2210] Step 1:

[2211] The server performs a scan to monitor traffic conditions in the designated area.

[2212] Input: Monitoring area settings

[2213] Output: Confirmation that monitoring has started

[2214] Specifically, the server synchronizes surveillance cameras and sensors installed in designated cities and intersections with the system and begins collecting data in real time.

[2215] Step 2:

[2216] The device collects data from surveillance cameras and sensors and sends it to a server.

[2217] Input: Data from surveillance cameras and sensors

[2218] Output: Data transmission confirmation message

[2219] Specifically, the device sends video data from surveillance cameras and information from speed sensors to the server in real time. Once the transmission is complete, a confirmation message is displayed.

[2220] Step 3:

[2221] The server analyzes the data and determines whether a traffic law violation has occurred.

[2222] Input: Data from surveillance cameras and sensors

[2223] Output: Violation judgment result

[2224] Specifically, the server uses AI and machine learning models to analyze the collected data and detect traffic violations, such as running red lights or speeding.

[2225] Step 4:

[2226] If the server detects a violation, it notifies nearby police officers.

[2227] Input: Violation judgment result

[2228] Output: Notification message to police officer

[2229] Specifically, if a violation is detected, the server immediately notifies nearby police officers of the information, including the driver's location and the details of the violation.

[2230] Step 5:

[2231] The user (police officer) receives a notification and rushes to the scene.

[2232] Input: Notification message from the server

[2233] Output: Officer response actions

[2234] Specifically, police officers receive notifications via smartphones or police radio, rush to the designated scene, and crack down on violating vehicles.

[2235] Step 6:

[2236] A server stores evidence data associated with the violation.

[2237] Input: Video and sensor data from the violation

[2238] Output: Confirmation of save completion

[2239] Specifically, the server stores the video and data of the violation in storage so that it can be viewed later. For example, it stores the video of the moment the red light was run and the speed sensor measurement data.

[2240] The above are the specific processing steps of the automatic AI traffic monitoring system of the present invention, which realizes efficient fraud prevention and traffic monitoring.

[2241] (Application example 1)

[2242] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2243] In modern society, bank transfer fraud and traffic violations have become serious problems. Dealing with these problems often relies on manual monitoring, which is not very efficient. In particular, the number of victims of bank transfer fraud is increasing, especially among the elderly, and traffic violations also have a significant social impact as a cause of traffic accidents. To solve these problems, there is a need for a system that can prevent bank transfer fraud and detect traffic violations in real time and respond immediately.

[2244] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2245] In this invention, the server includes an input means for a user to input transfer information, a communication means by which the terminal transmits the transfer information to the server, a fraud detection means by which the server analyzes the reason for the transfer received, an analysis result return means by which the server returns the analysis result to the terminal, a display means by which the terminal displays the analysis result to the user, a monitoring means by which a police officer uses smart glasses to monitor traffic violations in real time, a data collection means by which the smart glasses collect data from surveillance cameras and sensors and transmit it to the server, and a notification means by which the server detects traffic violations using an AI model and notifies the police officer. This makes it possible to prevent transfer fraud and detect traffic violations in real time.

[2246] "Input means" refers to a device or method for a user to input data such as transfer information.

[2247] A "communication means" is a device or method for transmitting data from a terminal to a server.

[2248] "Fraud detection means" refers to a device or method that analyzes the transfer information received by the server and determines the possibility of fraud based on its contents.

[2249] The "analysis result return means" is a device or method for the server to return the analysis results to the terminal.

[2250] The "display means" is a device or method for displaying the analysis results received by the terminal from the server to the user.

[2251] "Monitoring means" means a device or method for officers to monitor traffic conditions in real time using smart glasses.

[2252] "Data collection means" refers to a device or method by which the smart glasses collect traffic data from surveillance cameras and sensors and transmit it to the server.

[2253] The "notification means" is a device or method for notifying police officers of traffic violations detected by the server.

[2254] An "AI model" is a model for data analysis that is trained using machine learning algorithms.

[2255] "Real-time" refers to processing and reacting simultaneously with real-world time.

[2256] "Bank transfer fraud" is a type of criminal activity that involves deceiving users and fraudulently withdrawing funds.

[2257] A "traffic violation" refers to any action or situation that violates a traffic law.

[2258] As an embodiment of the present invention, a fraud prevention and real-time traffic violation detection system is specifically configured. First, each component of the system is described, and then specific program processing is described.

[2259] Main components of the system

[2260] 1. Input method:

[2261] The user uses a device or method to input transfer information, such as an ATM or a smartphone app.

[2262] 2. Means of communication:

[2263] The terminal uses the internet or mobile network to send the transfer information to the server, using the HTTP protocol and secure communication via SSL / TLS.

[2264] 3. Fraud detection measures:

[2265] The server uses a machine learning model (e.g., a neural network trained with Keras) to analyze the reason for the incoming transfer. This model determines the likelihood of transfer fraud based on past data.

[2266] 4. Method of returning analysis results:

[2267] The server has a means to return the analysis results to the device, and this process is also carried out via a secure communication protocol.

[2268] 5. Display means:

[2269] The terminal receives the analysis results from the server and displays them to the user, specifically on the smartphone screen or ATM display.

[2270] 6. Monitoring measures:

[2271] Police officers will monitor traffic conditions in real time using smart glasses, which are equipped with a built-in camera and display, through which AI models can detect traffic violations.

[2272] 7. Data Collection Methods:

[2273] The smart glasses collect traffic data from surveillance cameras and sensors and transmit it to a server in real time using wireless communication technologies such as Wi-Fi and Bluetooth.

[2274] 8. Means of notification:

[2275] The server notifies police officers of detected traffic violations using text displayed on the smart glasses' display and an audible alert.

[2276] Program processing explanation

[2277] In this invention, when a user transfers funds using an ATM or smartphone app, the input information is sent to a server via secure communications. The server uses an AI model to analyze the reason for the transfer and returns the results to the terminal. The user is informed of the security of the transfer on a display, and the transfer is canceled if there is a possibility of fraud.

[2278] Police officers can monitor traffic conditions in real time by wearing smart glasses. The glasses are equipped with a sophisticated camera that transmits video data of traffic conditions to a server. The server then uses an AI model to analyze the video data, and if a traffic violation is detected, a notification will appear on the smart glasses' display.

[2279] Specific examples

[2280] For example, suppose a police officer is using smart glasses at a busy intersection and a vehicle runs a red light. In this case, the camera in the smart glasses captures the vehicle running the red light, and the data is sent to the server in real time. The server uses an AI model to detect the traffic violation and displays a notification on the officer's smart glasses saying, "A red light has been detected!" The officer can then respond quickly and crack down on the violating vehicle.

[2281] Prompt Sentence Examples

[2282] For a wire transfer fraud detection model: "Is this wire transfer reason likely to be fraudulent?"

[2283] For traffic violation detection models: "Does this image contain a red light run?"

[2284] As a result, the present invention can efficiently prevent bank transfer fraud and detect traffic violations in real time.

[2285] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2286] Step 1:

[2287] The user enters transfer information. The user launches the ATM or smartphone app and enters information such as the transfer amount, recipient information, and reason for transfer. The entered information is obtained through the input means.

[2288] Input: User inputs transfer amount, recipient information, and reason for transfer.

[2289] Output: Transfer information data obtained via the input means.

[2290] Step 2:

[2291] The terminal sends the transfer information to the server. The terminal uses a secure communication protocol (e.g. HTTPS, SSL / TLS) to send the transfer information to the server in real time.

[2292] Input: Transfer information data.

[2293] Output: Transfer information data sent to the server.

[2294] Step 3:

[2295] The server analyzes the re...

Claims

1. an input means for a user to input transfer information; A communication means for the terminal to transmit transfer information to a server; a fraud detection means for analyzing the reason for the transfer received by the server; analysis result return means for the server to return the analysis result to the terminal; A display means by which the terminal displays the analysis results to the user A system including:

2. A means for users to transfer funds using an ATM or app; A means for the terminal to transmit transfer information to the server in real time; A monitoring means in which the server monitors traffic conditions using AI; A notification means for the server to detect a traffic law violation and notify a police officer; A storage means for the server to store evidence data related to the breach A system including:

3. A means for completing the transfer if it is deemed safe based on the analysis results, and for displaying a warning and canceling the transfer if there is a problem; A means for the server to collect and analyze data from surveillance cameras and sensors in real time, A means of notifying police officers or automated control devices when a traffic law violation is detected The system of claim 1 , comprising:

Images