system

Abstract

Provide a system. [Solution] an interface means for user input; a terminal means for transmitting input data to a server; A means for parsing and validating the data received by the server; A means for storing the analyzed and verified data in a database; means for performing additional processing based on the stored data; means for generating a message to respond to a user of the result of the additional processing; means for transmitting the generated message to a terminal; means for displaying to a user messages received by the terminal; 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] In modern information systems, it is important to transmit user-entered data to a server safely and efficiently, and then process and store that data appropriately. However, many systems are prone to errors during data validation and storage, which can detract from the user experience. Furthermore, if processing results are not returned to the user in a timely manner after data transmission, this can cause inconvenience and anxiety. The present invention aims to solve these problems by reliably transmitting user-entered data to a server and providing processing results quickly and accurately. [Means for solving the problem]

[0005] The present invention provides an interface means for user input and has a terminal means for transmitting the input data to a server. The server further includes a means for analyzing and verifying the received data and storing the data in a database. The system also includes a means for performing additional processing based on the stored data and generating a message to respond to the user with the results. This allows the generated message to be sent to the terminal, and the message received by the terminal to be displayed to the user. This invention provides a system in which user input data is reliably processed and results are returned quickly.

[0006] "User" refers to a person who uses the system to enter information into a form, submit data, and view results.

[0007] "Interface means" refers to a user interface such as a screen or form for a user to input information.

[0008] "Terminal means" refers to devices used by users, such as computers, smartphones, and tablets.

[0009] "Server" refers to a central computer that receives, processes, and stores data from multiple devices over a network.

[0010] "Analysis and verification means" refers to the function that analyzes the content of the data received by the server and verifies its legitimacy and completeness.

[0011] A "database" refers to a system for efficiently storing, retrieving, and updating data.

[0012] "Storage" refers to the process by which received, analyzed, and validated data is stored in a database.

[0013] "Additional processing" refers to additional processing based on data stored in the database and collaboration between services.

[0014] "Message generation means" refers to a function for creating a message to notify the user of the results of the additional processing.

[0015] "Transmission means" refers to means for sending a generated message from the server to a user's terminal.

[0016] "Display means" refers to a function that appropriately displays to the user a message received by the terminal from the server. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0025] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0038] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[0039] The processing of the program in the system of the present invention will be explained in natural language below.

[0040] First, a user enters information required for a web form, such as their name, address, and email address, and clicks the submit button. The form-filling interface captures the input data into the terminal.

[0041] Next, the terminal converts the input data into JSON format and sends it to the server using an HTTP POST request. The JSON format data looks like this: { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}

[0042] The server receives the HTTP request sent from the device and analyzes the data sent. After analyzing, it verifies whether the data is valid. For example, it checks whether the email address format is correct and whether all required fields have been entered.

[0043] Data that passes verification is stored in a database by the server. The database serves to securely store registered user information. Based on this, the server performs additional processing. This additional processing may include sending email notifications or linking with other services.

[0044] The server generates a response message for the user based on the information stored in the database and the results of the additional processing. For example, it creates a message such as "Registration completed." This message is then sent to the terminal again as an HTTP response.

[0045] The terminal receives the HTTP response from the server and analyzes the response data. The analyzed data is displayed on the user interface, and a message stating "Registration completed" is displayed to the user. In this way, data transmission, reception, and processing in the system of the present invention are completed.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] A user fills in a web form with required information, such as name, address, and email address, and clicks the submit button, at which point the user's input data is captured in the form interface.

[0049] Step 2:

[0050] The device converts the user's input data into JSON format (e.g., { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}) and sends the data to the server using an HTTP POST request.

[0051] Step 3:

[0052] The server receives the HTTP request from the device and parses the JSON data sent. The server extracts the contents of the request body and each field (name, address, email address, etc.).

[0053] Step 4:

[0054] Validate the data received by the server, specifically checking that email addresses are formatted correctly and that required fields are not missing (for example, that email addresses are in username@domain.com format).

[0055] Step 5:

[0056] The server saves the data that passes validation to the database, storing the name, address, and email address as a new user record in the appropriate tables.

[0057] Step 6:

[0058] The server performs additional processing based on the information stored in the database. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a confirmation email stating "Registration completed" to the user's email address.

[0059] Step 7:

[0060] The server generates a response message for the user based on the results of the addition process. It creates a message stating "Registration completed" and generates this as response data.

[0061] Step 8:

[0062] The server generates a response message and sends it to the terminal as an HTTP response, which includes a success message and additional information.

[0063] Step 9:

[0064] The device receives the HTTP response from the server, analyzes the response body, and extracts the message "Registration completed."

[0065] Step 10:

[0066] The terminal displays the analyzed message on the user interface, and the user can see the message "Registration completed" on the browser.

[0067] Example 1

[0068] 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."

[0069] Existing systems require manual intervention to validate and store data entered by users, resulting in issues with speed and accuracy. Data transmission and reception also requires security and efficiency. Furthermore, there is a lack of a way to quickly and accurately communicate the results of additional processing to users. Therefore, there is a need to automate data processing and transmission while improving user convenience.

[0070] 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.

[0071] In this invention, the server includes an analysis and verification means, a storage means for storing data in a storage device, and a means for performing additional processing, thereby enabling accurate analysis and verification of data, efficient storage, and rapid additional processing.

[0072] An "interface means" is a combination of an input device and software for a user to provide input.

[0073] "Terminal means" refers to a combination of a device and software that has the function of receiving user input data and transmitting it to a communication device.

[0074] "Communication device" refers to a server or network device that receives data sent from a terminal means and further analyzes and verifies it.

[0075] "Analysis and verification means" refers to a combination of software and hardware that has the function of analyzing the contents of received data and checking for errors in format and content.

[0076] "Storage device" refers to a database and storage device for storing analyzed and verified data.

[0077] "Further processing means" is a combination of software and hardware that performs further processing on stored data to generate new results or information.

[0078] The "means for generating a message" is a combination of software and hardware that has the function of creating an appropriate message for the user based on the results of the additional processing.

[0079] A "data interchange format" is a format for expressing data in a unified format, such as JSON or XML.

[0080] A "data exchange protocol" is a protocol that defines the communication methods and rules for sending and receiving data, and examples of this include HTTP and HTTPS.

[0081] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a storage device, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[0082] First, a user inputs necessary information into a web form through a web browser. This form input interface is for accepting user input data, and includes basic information such as name, address, and email address.

[0083] Next, the terminal converts the input data into a data exchange format (e.g., JSON) and sends it to the server using an HTTP request. The software used by the terminal can be the JavaScript (registered trademark) fetch API. For example, if a user inputs the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com," the terminal converts this into JSON format and sends it to the server.

[0084] The server receives HTTP requests sent from the terminal using web server software such as Apache (registered trademark) or Nginx. The received data is parsed and validated using, for example, Python's Django framework, to check whether the email address format is correct and whether all required fields have been entered. Validation is performed using regular expressions, etc.

[0085] Data that passes the verification is stored by the server in a storage device (e.g., an SQL database). The SQL database is used to maintain the reliability and integrity of the data, and databases such as MySQL (registered trademark) and PostgreSQL are used.

[0086] The server then performs additional processing based on the stored data, such as sending email notifications to users or integrating with other services, using the Python smtplib library to send a registration confirmation email.

[0087] Finally, the server generates a message to respond to the user. The generated message is created in JSON format, and has the content, for example, "Registration completed." This message is sent to the terminal as an HTTP response.

[0088] The terminal receives the HTTP response from the server, analyzes the response data, and displays it on the user interface. For example, the terminal performs the analysis using JavaScript and displays a message to the user such as "Registration completed."

[0089] Prompt Sentence Examples

[0090] Please provide a detailed explanation of the steps to implement a system that sends data entered by a user into a web form to a server, where it is parsed, validated, and stored in a database. The system then performs additional processing and displays a response message to the user. Please also specify the specific hardware and software used, as well as the method of data processing.

[0091] This automates the sending, receiving, and processing of data throughout the system and provides an easy-to-use interface for users.

[0092] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0093] Step 1:

[0094] A user inputs the required information into a web form. For example, the user inputs the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com." This input data is imported into the terminal through the form input interface of the web browser. The input data is obtained in text format for processing on the terminal.

[0095] Step 2:

[0096] The device converts the input data into JSON format and sends it to the server using an HTTP POST request. Specifically, it uses the JavaScript fetch API to convert the text data into JSON format data { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"} and generates output. This data is sent to the specified URL.

[0097] Step 3:

[0098] The server receives HTTP requests sent from the terminal using web server software such as Apache or Nginx. JSON format data is given as input. The received data is analyzed using the Python Django framework, and the text data is converted into a dictionary format and output.

[0099] Step 4:

[0100] The server verifies whether the received data is valid. Validation involves checking the format of the email address and whether any required fields are present. For example, the email address is validated using the Python regular expression library "re" to ensure there are no omissions or errors. If the data is valid, the server proceeds to the next step; if it is invalid, an error message is generated and output.

[0101] Step 5:

[0102] Once the data passes validation, it is saved to a storage device (e.g., an SQL database) by the server. The input data remains in dictionary format and is converted to SQL commands using Django models. The output includes the save completion status and the ID of the saved record.

[0103] Step 6:

[0104] The server performs additional processing based on the stored data. This additional processing can include sending email notifications or connecting with external services. For example, it uses the Python smtplib library to send a registration confirmation email to the entered email address. Here, the status of the email sending process is output.

[0105] Step 7:

[0106] The server generates a response message for the user based on the results of the additional processing. For example, it creates a message saying "Registration completed" and converts it into JSON-formatted response data. This generated message is output.

[0107] Step 8:

[0108] The server sends the generated response message to the terminal as an HTTP response, and then executes a process to return the output JSON format message data as an HTTP response.

[0109] Step 9:

[0110] The terminal receives the HTTP response from the server and analyzes the response data. The response data is given in JSON format as input. JavaScript is used to analyze the response data and display a message such as "Registration completed" on the user interface. The message displayed to the user as a result of this process is the final output.

[0111] (Application example 1)

[0112] 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."

[0113] In recent years, robots and machinery have been used to automate and streamline factories, but issuing appropriate operating instructions to these machines has been a difficult challenge. In particular, when users manually input instructions into the machines, input errors and delays are likely to occur, potentially reducing production efficiency. Furthermore, the lack of a mechanism for instantly verifying the content of operating instructions and updating the machines in real time complicates factory management. An effective system that can solve these problems and support automation within factories is needed.

[0114] 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.

[0115] In this invention, the server includes an operation means for user input, a device means for transmitting the input data to the server, a means for analyzing and verifying the data received by the server, a means for saving the analyzed and verified data in a data storage device, a means for performing additional processing based on the saved data, a means for generating a notification message for responding to the user with the result of the additional processing, a means for sending the generated notification message to the device, a means for displaying the notification message received by the device to the user, and an instruction means for issuing operation instructions to machinery in the factory as part of the additional processing. This makes it possible to issue appropriate operation instructions to machinery in the factory in real time, preventing input errors and operation delays and improving production efficiency.

[0116] "Operation means" refers to an interface through which a user inputs data and instructions.

[0117] "Device means" refers to a terminal device for transmitting input data to a server.

[0118] "Means for analysis and verification" refers to the function for analyzing the data received by the server and verifying its validity and accuracy.

[0119] "Data Storage Device" refers to the database within the system for storing analyzed and validated data.

[0120] "Means for further processing" refers to mechanisms for performing further processing based on the stored data.

[0121] The "means for generating a notification message" refers to a function for creating a message to notify the user of the result of the additional processing.

[0122] The "means for sending to the device" refers to a communication means for sending the generated notification message to the user's terminal.

[0123] The "means for displaying" refers to a function for visually displaying to the user the notification message received by the terminal.

[0124] "Instruction means" refers to a function for sending and managing operation instructions to machinery and devices within a factory.

[0125] The present invention is a system in which data entered by a user using an operation means is sent to a server via a device means, and the server analyzes and verifies the data and stores it in an appropriate data storage device.Furthermore, the system performs additional processing based on the stored data, generates a notification message of the results, and sends it again to the user's device means so that the user can check it.

[0126] To realize this invention, a user first inputs a work instruction using the operation means. For example, the user inputs "Please start assembly work on line 1" as an operation instruction for a machine in a factory. This input data is converted into JSON format by the device means and sent to the server using an HTTP POST request.

[0127] The server analyzes the data it receives and verifies its validity and accuracy. For example, it checks that work instructions are entered in the correct format and contain all the required information. This can be done using a web framework such as Flask. The server then securely stores the data in a data store and performs further processing based on the stored data.

[0128] As an additional process, for example, to execute an operation instruction for a machine in a factory, the server sends an instruction to the machine in real time via the instruction means. Based on the result of this instruction, the server generates a notification message for the user. For example, it creates a message such as "Assembly work on line 1 has started" and sends it again to the machine means.

[0129] The device receives notification messages from the server, analyzes them, and displays them on the user interface, allowing the user to confirm that the instructions were executed correctly. Through this series of processes, work efficiency within the factory can be improved and input errors and operational delays can be prevented.

[0130] An example of a specific prompt is as follows:

[0131] "Please begin assembly work on Line 1."

[0132] In this way, the present invention makes it possible to efficiently and accurately execute operating instructions for machinery in a factory, dramatically improving production efficiency.

[0133] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0134] Step 1:

[0135] The user inputs work instructions using the operating means. The input contents include the work target, work content, start time, etc. For example, the user inputs an instruction such as "Please start assembly work on line 1." This information is captured in the operating means.

[0136] Step 2:

[0137] The terminal means converts the data input by the user into JSON format. For example, the input instruction is converted into the following JSON format:

[0138] {

[0139] "line": "Line 1",

[0140] "task": "assembly work",

[0141] "action": "start"

[0142] }

[0143] This JSON data is converted into an HTTP POST request format and sent to the server. The input is a text-formatted work instruction, and the output is JSON-formatted data.

[0144] Step 3:

[0145] The server receives the HTTP POST request from the terminal and analyzes the contents. The analysis reads the JSON data and verifies the data format and content. For example, it checks whether "line" is empty, whether "task" is an allowed operation, and whether "action" is a valid instruction. The input is JSON format data, and the output is the verification result after analysis.

[0146] Step 4:

[0147] The server stores the data that passes validation in a data storage device (database). The stored data includes the user's instructions and a timestamp, allowing for future reference and additional processing. The input is the analyzed and validated data, and the output is the record stored in the database.

[0148] Step 5:

[0149] The server performs additional processing based on the data stored in the data storage device. Specifically, it sends operational instructions based on user input to machinery in the factory in real time. The instructions are sent to the machinery using the necessary protocols and communication methods. The input is the stored data, and the output is the operational instructions sent to the machinery.

[0150] Step 6:

[0151] The server receives responses and operation results from the machine and generates a message to notify the user. For example, it generates a message saying, "Assembly work on line 1 has started." This message is converted back to JSON format and sent to the terminal means. The input is the operation result from the machine, and the output is the generated notification message.

[0152] Step 7:

[0153] The terminal means analyzes the notification message received from the server and displays it on the user interface. This allows the user to confirm that their instructions have been executed correctly. For example, the terminal may display a message saying, "Assembly work on line 1 has started." The input is the notification message from the server, and the output is the confirmation message displayed on the user interface.

[0154] 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.

[0155] The present invention is a system that efficiently processes user input data and further combines it with an emotion engine that recognizes the user's emotions. Below, the program processing in the system of the present invention will be specifically explained in natural language.

[0156] First, a user enters necessary information into a web form, such as name, address, and email address. For example, the user enters the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com," and clicks the submit button. The input data is then imported into the form interface.

[0157] Next, the terminal converts the input data into JSON format. The converted JSON data is in the format { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}. The terminal sends this data to the server in the form of an HTTP POST request.

[0158] The server receives the HTTP request sent from the terminal and parses the JSON data. The server extracts the name, address, and email address fields from the request body and parses and validates the received data. Here, it checks whether the email address format is correct and whether all required fields have been entered.

[0159] After the server has verified the received data, it stores it in the database, which records the new user's information and makes it available for further processing.

[0160] Next, the server performs additional processing based on the stored data. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a registration completion email to "yamada@example.com."

[0161] Furthermore, as a feature of the present invention, the server uses an emotion engine to recognize emotions from the user's input data. For example, if the user inputs a comment such as "I'm so happy!", the emotion engine will identify the user's emotion as "joy." Then, it will create an appropriate message according to the emotion.

[0162] The server generates a response message for the user based on the results of the emotion engine and additional processing. In addition to the basic message "Registration completed," it adds a message according to the emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[0163] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed on the user interface, and a response such as "Registration completed. Your joy has been conveyed" is displayed to the user.

[0164] This allows the system of the present invention to efficiently process user input data and provide responses that recognize and reflect the user's emotions, improving the user experience and enabling more personalized services.

[0165] The processing flow will be explained below.

[0166] Step 1:

[0167] A user enters their name, address, email address, and free-form comments into a web form and clicks the submit button. For example, the user enters the name "Taro Yamada," the address "Tokyo," the email address "yamada@example.com," and the comment "This site is great!"

[0168] Step 2:

[0169] The device converts the user's input data into JSON format. The converted JSON data becomes { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com", "comment": "This site is great!"} The device sends this data to the server in the form of an HTTP POST request.

[0170] Step 3:

[0171] The server receives the HTTP request sent from the device and parses the JSON data. The server extracts the name, address, email address, and comment fields from the request body.

[0172] Step 4:

[0173] The server validates the incoming data, specifically checking that the email address is formatted correctly and that all required fields are filled in. For example, making sure the email address is in the format username@domain.com.

[0174] Step 5:

[0175] The server saves the data that passes validation to the user database, storing the name, address, email address, and comments as a new user record.

[0176] Step 6:

[0177] The server uses the stored data to perform additional processing. For example, it sends a confirmation email. The server calls the API of the email service and sends an email to "yamada@example.com" stating "Registration completed."

[0178] Step 7:

[0179] The server uses an emotion engine to recognize emotions from comments entered by users. For example, the comment "This site is great!" is analyzed and the emotion engine identifies it as "joy."

[0180] Step 8:

[0181] The server generates an appropriate response message for the user based on the emotion recognized by the emotion engine, for example, "Your registration is complete. We feel your joy."

[0182] Step 9:

[0183] The server generates a response message and sends it to the terminal. The message "Registration completed. Your joy has been conveyed" is sent to the terminal in the form of an HTTP response.

[0184] Step 10:

[0185] The device receives the HTTP response from the server and parses the response body, extracting the message "Registration completed. Your joy was conveyed."

[0186] Step 11:

[0187] The terminal displays the analyzed response message on the user interface, and the user can see the message "Registration completed. Your joy has been conveyed" on the browser.

[0188] Example 2

[0189] 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."

[0190] Previous systems simply received and stored user input data, but were unable to identify user sentiment and reflect it in response messages. This resulted in a lack of improved user experience and made it difficult to provide personalized services. Furthermore, there was a lack of efficient means for validating and storing data, increasing the risk of inaccurate data and errors.

[0191] 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.

[0192] In this invention, the server includes a means for analyzing and verifying received data, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for performing emotion analysis as the additional processing, and a means for generating a response message based on the emotion analysis results. This enables the generation of personalized messages that reflect the user's emotions. Furthermore, the accuracy and completeness of the data can be ensured, improving overall system efficiency.

[0193] "User" refers to a person or end user who uses the system.

[0194] "Interface means" refers to the means by which a user inputs data into the system, including web forms and input fields.

[0195] "Terminal means" refers to devices and software for transmitting user input data to a server, and includes personal computers and smartphones.

[0196] "Server" refers to the central computer system that receives, analyzes, and verifies data sent by users.

[0197] "Means for analyzing and verifying received data" refers to the algorithms or programs that analyze the data received by the server and check its accuracy and completeness.

[0198] "Means of storing data in a database" includes systems and methods for permanently storing analyzed and verified data.

[0199] "Means for performing additional processing" refers to programs or algorithms for performing further necessary processing on the stored data.

[0200] "Means for performing emotion analysis" refers to the engine or algorithm used to identify and analyze emotions from user input data.

[0201] "Means for generating a response message" refers to a program or algorithm that allows the system to generate a message to be sent back to the user.

[0202] "Means for sending a message to a terminal" includes any system or protocol for sending the generated response message to the user's terminal.

[0203] "Means for displaying to the user the message received by the terminal" refers to an interface or program for displaying on the screen of the user's terminal the message received from the server.

[0204] This invention is a system that efficiently processes user input data and recognizes and reflects the user's emotions. This system comprises a user interface using a web form, a terminal that sends input data to a server, a server that analyzes and verifies the received data, a database, an emotion analysis engine, and a function for generating and sending response messages.

[0205] First, a user enters information such as their name, address, and email address using a web form. The web form is implemented using HTML and JavaScript. For example, a user enters "Name: Yamada Taro," "Address: Tokyo," and "Email address: yamada@example.com," and then clicks the submit button.

[0206] Next, the terminal converts the input data into JSON format. Specifically, it serializes the JavaScript object into JSON format. This converted data looks like this:

[0207] json

[0208] {

[0209] "name": "Yamada Taro",

[0210] "address": "Tokyo",

[0211] "email": "yamada@example.com"

[0212] }

[0213] The device sends this JSON data to the server as an HTTP POST request, using HTTPS as the communication protocol.

[0214] The server receives this HTTP request. The server is often implemented using Node.js or Python (Flask or Django). It parses the received JSON data and extracts each field, such as name, address, and email address. It then verifies that the data format is correct and that all required fields have been entered.

[0215] Once the verification is complete, the data is stored in a database, typically a relational database such as MySQL or PostgreSQL.

[0216] The server then performs additional processing based on the user information stored in the database. As part of this processing, the server calls a sentiment analysis engine (e.g., IBM Watson® or Google® Cloud Natural Language API) to analyze the emotion from the user's comment. For example, if a user enters the comment "I'm so happy!", the sentiment analysis engine will determine this emotion as "joy."

[0217] The server generates a response message for the user based on the results of the emotion analysis. In addition to the basic message "Registration completed," it adds a message according to the user's emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[0218] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed in the user interface. For example, the response is displayed to the user in the form of "Registration completed. Your joy is conveyed."

[0219] As a concrete example, the same processing can be achieved by inputting the following prompt sentence into the generative AI model:

[0220] "Please explain how to convert the name, address, and email address entered by the user into JSON format and send it to the server."

[0221] "Please explain the steps to parse and validate the JSON data received by the server and save it to the database."

[0222] "Please explain how to determine the sentiment of the input comment and generate a response message accordingly."

[0223] The above is a specific embodiment for carrying out the present invention. This system can improve the user experience by providing a response that reflects the user's emotions.

[0224] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0225] The flow of this system's program processing

[0226] Step 1: User Input

[0227] A user enters name, address, and email information into a web form and clicks the submit button.

[0228] Input: Information entered by the user (name, address, email address)

[0229] Output: The input data is populated into the form interface

[0230] Specific actions

[0231] 1. The user opens a browser.

[0232] 2. Visit the website.

[0233] 3. Fill out the web form.

[0234] 4. Click the Send button.

[0235] Step 2: Convert data to JSON format and send it

[0236] The terminal receives the input data, converts it to JSON format, and sends it to the server in the form of an HTTP POST request.

[0237] Input: Information entered by the user (name, address, email address)

[0238] Data processing: Convert input data into JSON format using JavaScript etc.

[0239] Output: JSON format data is generated and sent to the server.

[0240] Specific actions

[0241] 1. Once the form is completed, the JavaScript code runs.

[0242] 2. The input data is converted to JSON format.

[0243] 3. The converted JSON data is sent to the server via an HTTP POST request.

[0244] Step 3: Data analysis and validation by the server

[0245] The server receives the HTTP request and parses and validates the JSON data.

[0246] Input: JSON data included in the body of the HTTP request

[0247] Data Calculation: Parse JSON data and extract name, address, and email address fields. Check email address format and required fields.

[0248] Output: Analyzed and validated data

[0249] Specific actions

[0250] 1. The server receives an HTTP request.

[0251] 2. Parse the JSON data in the request body.

[0252] 3. Extract names, addresses, and email addresses.

[0253] 4. Validate the data in each field (check email format, check required fields).

[0254] Step 4: Saving to the Database

[0255] The server stores the parsed and verified data in a database.

[0256] Input: Analyzed and validated data

[0257] Data processing: Generate and execute SQL queries to store data in a database

[0258] Output: Data is saved to the database

[0259] Specific actions

[0260] 1. Map the validated data to database objects.

[0261] 2. Execute a SQL query to insert data into the database.

[0262] 3. After the insert is complete, you receive a response from the database.

[0263] Step 5: Send a confirmation email

[0264] The server uses the email service API to send a confirmation email based on the stored data.

[0265] Input: User information stored in the database

[0266] Data operation: Call the email service API and pass the email content and recipient address.

[0267] Output: A confirmation email is sent to the user.

[0268] Specific actions

[0269] 1. The server calls the email sending API.

[0270] 2. Pass the email content and recipient address to the API.

[0271] 3. The email is sent and a response is received from the API.

[0272] Step 6: Emotion Recognition

[0273] The server uses an emotion analysis engine to recognize emotions from the user's input data.

[0274] Input: User comment data

[0275] Data calculation: Send comments to a sentiment analysis engine to analyze sentiment

[0276] Output: Emotion analysis results

[0277] Specific actions

[0278] 1. Send user comment data to a sentiment analysis engine.

[0279] 2. The sentiment analysis engine analyzes the comments and determines their sentiment.

[0280] 3. The result of the judgment is returned to the server.

[0281] Step 7: Generate and send a response message

[0282] The server generates a response message based on the emotion analysis result and the basic message, and sends it to the terminal.

[0283] Input: Sentiment analysis results, information stored in the database

[0284] Data calculation: Generate a response message based on the above data

[0285] Output: A response message is sent to the terminal

[0286] Specific actions

[0287] 1. Generate a response message based on the emotion results.

[0288] 2. Include the response message in the HTTP response.

[0289] 3. Send the HTTP response to the device.

[0290] Step 8: Displaying Messages

[0291] The terminal analyzes the HTTP response received from the server and displays a message on the user interface.

[0292] Input: HTTP response received from the server

[0293] Data operation: Parse the HTTP response body and extract the message

[0294] Output: A message is displayed to the user

[0295] Specific actions

[0296] 1. Receive an HTTP response.

[0297] 2. Parse the JSON data in the response body.

[0298] 3. The parsed message is displayed on the screen in HTML format.

[0299] The above is the specific flow of processing of the program in this system.

[0300] (Application example 2)

[0301] 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."

[0302] While conventional systems can efficiently process data entered by users, they have difficulty analyzing the user's emotional state and taking appropriate measures based on that emotion. Furthermore, particularly in the security field, it has been difficult to determine in real time whether a user is in a dangerous situation and respond immediately. To solve this problem and ensure user safety more reliably, a system is needed that analyzes the user's emotions and surrounding audio and video data to assess danger.

[0303] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing the user's emotional state, means for collecting and analyzing surrounding audio and video data, and means for assessing danger and issuing a warning based on the emotional state. This not only analyzes the data entered by the user, but also monitors the user's emotional state in real time and comprehensively evaluates information obtained from the surrounding environment, making it possible to immediately issue a warning if the user is in danger.

[0304] An "interface means" is a means by which a user inputs data into a system.

[0305] The "terminal means" is a means for transmitting data input by a user to a server.

[0306] "Means for analysis and verification" refers to the means by which the server analyzes the data received and checks the accuracy of the data and whether there are any errors.

[0307] "Means of storage" refers to the means for recording analyzed and verified data in a database.

[0308] "Means for performing additional processing" refers to means for performing further processing based on the stored data.

[0309] "Emotion engine means" means that uses an engine to analyze the emotional state of a user.

[0310] The "means for generating a message" is a means for generating an appropriate response message based on the analysis result.

[0311] "Means for collecting and analyzing" refers to means for collecting and analyzing surrounding audio and video data.

[0312] The "means for assessing danger and issuing a warning" is a means for assessing whether the user is in a dangerous situation based on the user's emotional state and surrounding data, and issuing a warning as necessary.

[0313] The "means for sending" is a means for sending the generated message to the user's terminal.

[0314] The "display means" is a means for visually displaying to the user the message received by the terminal.

[0315] As an embodiment of the present invention, a security system can be constructed that uses smart glasses worn by a user to analyze emotional states and surrounding environmental data in real time. This system is realized using the following hardware and software.

[0316] 1. Hardware

[0317] Smart glasses: built-in camera, microphone, and heart rate sensor

[0318] Server: Data processing and emotion engine execution

[0319] Communication module: Data transfer between smart glasses and server

[0320] 2. Software

[0321] Emotion engine (e.g., TENSORFLOW®, Keras): Analyzes the user's facial expressions and heart rate data

[0322] Voice recognition software: Analyzes surrounding audio data and detects dangerous sounds

[0323] Database (e.g. MySQL, PostgreSQL): Stores user data and analysis results

[0324] Message Generation Algorithm: Create appropriate warning messages

[0325] Detailed explanation of program processing

[0326] 1. Data collection

[0327] Once the user puts on the smart glasses, the camera and microphone begin working, and the heart rate sensor also continuously monitors the heart rate.

[0328] 2. Data Preprocessing

[0329] The smart glasses extract the collected video data frame by frame and perform facial and facial expression recognition, using deep learning models such as TensorFlow and Keras.

[0330] The audio data is analyzed by voice recognition software to detect dangerous sounds (e.g., screaming, breaking glass).

[0331] 3. Operation of the Emotion Engine

[0332] The server inputs the user's facial expressions and heart rate data into an emotion engine to analyze the user's emotional state. For example, TensorFlow and Keras can be used to recognize emotions from micro-expressions.

[0333] 4. Risk Assessment

[0334] Based on the emotional state (e.g., surprise, fear) recognized by the emotion engine and the dangerous sounds detected by the voice recognition software, the server assesses whether the user is in a dangerous situation.

[0335] 5. Generating and Sending Alerts

[0336] If a danger is detected, the server generates an appropriate warning message, which is then sent to the user via the communication module of the smart glasses, and displayed on the display of the smart glasses.

[0337] Specific examples

[0338] For example, when a user is walking down a dark street at night, the smart glasses collect ambient sounds (e.g., sudden footsteps from behind) and images (e.g., a person chasing the user). The emotion engine recognizes fear from the user's facial expression and detects sudden footsteps from the audio data. After comprehensively evaluating the situation, the server generates a warning message saying, "There may be someone behind you. Be careful of danger." This message is then displayed on the smart glasses' display.

[0339] Prompt Sentence Examples

[0340] "A user may hear a scream nearby, and their heart rate may suddenly increase, revealing a look of surprise on their face. From this data, we can analyze the user's emotions and determine whether danger exists."

[0341] This embodiment allows for analyzing emotion and environmental data in real time when a user faces a dangerous situation, and providing prompt and appropriate warnings.

[0342] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0343] Step 1:

[0344] The user puts on the smart glasses. The camera built into the glasses starts collecting video data, and the microphone starts collecting audio data. The heart rate sensor also continuously monitors the user's heart rate. This data is transmitted to the smart glasses terminal in real time.

[0345] Input: User wear, video data, audio data, heart rate data

[0346] Output: Real-time data collected

[0347] Step 2:

[0348] The device extracts the video data collected by the device frame by frame and performs facial and facial expression recognition using TensorFlow and Keras. At the same time, the audio data is analyzed using speech recognition software (e.g., DeepSpeech or Google Speech-to-Text API) to detect dangerous sounds (e.g., screaming, breaking glass). Heart rate data is monitored in real time to check for sudden increases or abnormal values.

[0349] Input: Real-time data collected

[0350] Output: Analyzed facial expression data, voice data, heart rate data

[0351] Step 3:

[0352] The server inputs the analyzed data into the emotion engine, which analyzes the user's emotional state. The emotion engine recognizes the user's emotions (e.g., surprise, fear, joy) based on facial expressions, heart rate, and voice data. This process uses deep learning models (e.g., Long Short-Term Memory, Convolutional Neural Network).

[0353] Input: Analyzed facial expression data, voice data, heart rate data

[0354] Output: Perceived emotional state

[0355] Step 4:

[0356] The server combines the results of the emotion engine's analysis and the results of the dangerous sound detection by the voice recognition software to evaluate whether the user is in a dangerous situation, and generates a warning message if necessary based on the evaluation results.

[0357] Input: Recognized emotional state, analysis results of speech data

[0358] Output: Risk assessment results, warning messages

[0359] Step 5:

[0360] The server generates a warning message and sends it to the smart glasses terminal, which visually displays the received message to the user. For example, a message such as "There may be someone behind you. Beware of danger" is displayed on the display.

[0361] Input: The generated warning message

[0362] Output: Warning message sent to terminal

[0363] Step 6:

[0364] The user checks the displayed message and takes appropriate action, such as looking around, walking faster, or moving to another street.

[0365] Input: The warning message displayed on the terminal

[0366] Output: User behavior change

[0367] 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.

[0368] 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.

[0369] 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.

[0370] [Second embodiment]

[0371] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0372] 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.

[0373] 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).

[0374] 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.

[0375] 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.

[0376] 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).

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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."

[0383] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[0384] The processing of the program in the system of the present invention will be explained in natural language below.

[0385] First, a user enters information required for a web form, such as their name, address, and email address, and clicks the submit button. The form-filling interface captures the input data into the terminal.

[0386] Next, the terminal converts the input data into JSON format and sends it to the server using an HTTP POST request. The JSON format data looks like this: { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}

[0387] The server receives the HTTP request sent from the device and analyzes the data sent. After analyzing, it verifies whether the data is valid. For example, it checks whether the email address format is correct and whether all required fields have been entered.

[0388] Data that passes verification is stored in a database by the server. The database serves to securely store registered user information. Based on this, the server performs additional processing. This additional processing may include sending email notifications or linking with other services.

[0389] The server generates a response message for the user based on the information stored in the database and the results of the additional processing. For example, it creates a message such as "Registration completed." This message is then sent to the terminal again as an HTTP response.

[0390] The terminal receives the HTTP response from the server and analyzes the response data. The analyzed data is displayed on the user interface, and a message stating "Registration completed" is displayed to the user. In this way, data transmission, reception, and processing in the system of the present invention are completed.

[0391] The processing flow will be explained below.

[0392] Step 1:

[0393] A user fills in a web form with required information, such as name, address, and email address, and clicks the submit button, at which point the user's input data is captured in the form interface.

[0394] Step 2:

[0395] The device converts the user's input data into JSON format (e.g., { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}) and sends the data to the server using an HTTP POST request.

[0396] Step 3:

[0397] The server receives the HTTP request from the device and parses the JSON data sent. The server extracts the contents of the request body and each field (name, address, email address, etc.).

[0398] Step 4:

[0399] Validate the data received by the server, specifically checking that email addresses are formatted correctly and that required fields are not missing (for example, that email addresses are in username@domain.com format).

[0400] Step 5:

[0401] The server saves the data that passes validation to the database, storing the name, address, and email address as a new user record in the appropriate tables.

[0402] Step 6:

[0403] The server performs additional processing based on the information stored in the database. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a confirmation email stating "Registration completed" to the user's email address.

[0404] Step 7:

[0405] The server generates a response message for the user based on the results of the addition process. It creates a message stating "Registration completed" and generates this as response data.

[0406] Step 8:

[0407] The server generates a response message and sends it to the terminal as an HTTP response, which includes a success message and additional information.

[0408] Step 9:

[0409] The device receives the HTTP response from the server, analyzes the response body, and extracts the message "Registration completed."

[0410] Step 10:

[0411] The terminal displays the analyzed message on the user interface, and the user can see the message "Registration completed" on the browser.

[0412] Example 1

[0413] 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."

[0414] Existing systems require manual intervention to validate and store data entered by users, resulting in issues with speed and accuracy. Data transmission and reception also requires security and efficiency. Furthermore, there is a lack of a way to quickly and accurately communicate the results of additional processing to users. Therefore, there is a need to automate data processing and transmission while improving user convenience.

[0415] 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.

[0416] In this invention, the server includes an analysis and verification means, a storage means for storing data in a storage device, and a means for performing additional processing, thereby enabling accurate analysis and verification of data, efficient storage, and rapid additional processing.

[0417] An "interface means" is a combination of an input device and software for a user to provide input.

[0418] "Terminal means" refers to a combination of a device and software that has the function of receiving user input data and transmitting it to a communication device.

[0419] "Communication device" refers to a server or network device that receives data sent from a terminal means and further analyzes and verifies it.

[0420] "Analysis and verification means" refers to a combination of software and hardware that has the function of analyzing the contents of received data and checking for errors in format and content.

[0421] "Storage device" refers to a database and storage device for storing analyzed and verified data.

[0422] "Further processing means" is a combination of software and hardware that performs further processing on stored data to generate new results or information.

[0423] The "means for generating a message" is a combination of software and hardware that has the function of creating an appropriate message for the user based on the results of the additional processing.

[0424] A "data interchange format" is a format for expressing data in a unified format, such as JSON or XML.

[0425] A "data exchange protocol" is a protocol that defines the communication methods and rules for sending and receiving data, and examples of this include HTTP and HTTPS.

[0426] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a storage device, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[0427] First, a user inputs necessary information into a web form through a web browser. This form input interface is for accepting user input data, and includes basic information such as name, address, and email address.

[0428] Next, the terminal converts the input data into a data exchange format (e.g., JSON) and sends it to the server using an HTTP request. The software used by the terminal could be the JavaScript fetch API. For example, if a user inputs their name as "Yamada Taro," their address as "Tokyo," and their email address as "yamada@example.com," the terminal converts this into JSON format and sends it to the server.

[0429] The server receives the HTTP request sent from the device using web server software such as Apache or Nginx. The received data is parsed and validated using, for example, the Python Django framework, to check whether the email address is formatted correctly and whether all required fields have been filled in. Validation is performed using regular expressions, for example.

[0430] Data that passes the verification is stored by the server in a storage device (e.g., an SQL database), which is used to maintain the reliability and integrity of the data, and databases such as MySQL or PostgreSQL are used.

[0431] The server then performs additional processing based on the stored data, such as sending email notifications to users or integrating with other services, using the Python smtplib library to send a registration confirmation email.

[0432] Finally, the server generates a message to respond to the user. The generated message is created in JSON format, and has the content, for example, "Registration completed." This message is sent to the terminal as an HTTP response.

[0433] The terminal receives the HTTP response from the server, analyzes the response data, and displays it on the user interface. For example, the terminal performs the analysis using JavaScript and displays a message to the user such as "Registration completed."

[0434] Prompt Sentence Examples

[0435] Please provide a detailed explanation of the steps to implement a system that sends data entered by a user into a web form to a server, where it is parsed, validated, and stored in a database. The system then performs additional processing and displays a response message to the user. Please also specify the specific hardware and software used, as well as the method of data processing.

[0436] This automates the sending, receiving, and processing of data throughout the system and provides an easy-to-use interface for users.

[0437] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0438] Step 1:

[0439] A user inputs the required information into a web form. For example, the user inputs the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com." This input data is imported into the terminal through the form input interface of the web browser. The input data is obtained in text format for processing on the terminal.

[0440] Step 2:

[0441] The device converts the input data into JSON format and sends it to the server using an HTTP POST request. Specifically, it uses the JavaScript fetch API to convert the text data into JSON format data { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"} and generates output. This data is sent to the specified URL.

[0442] Step 3:

[0443] The server receives HTTP requests sent from the terminal using web server software such as Apache or Nginx. JSON format data is given as input. The received data is analyzed using the Python Django framework, and the text data is converted into a dictionary format and output.

[0444] Step 4:

[0445] The server verifies whether the received data is valid. Validation involves checking the format of the email address and whether any required fields are present. For example, the email address is validated using the Python regular expression library "re" to ensure there are no omissions or errors. If the data is valid, the server proceeds to the next step; if it is invalid, an error message is generated and output.

[0446] Step 5:

[0447] Once the data passes validation, it is saved to a storage device (e.g., an SQL database) by the server. The input data remains in dictionary format and is converted to SQL commands using Django models. The output includes the save completion status and the ID of the saved record.

[0448] Step 6:

[0449] The server performs additional processing based on the stored data. This additional processing can include sending email notifications or connecting with external services. For example, it uses the Python smtplib library to send a registration confirmation email to the entered email address. Here, the status of the email sending process is output.

[0450] Step 7:

[0451] The server generates a response message for the user based on the results of the additional processing. For example, it creates a message saying "Registration completed" and converts it into JSON-formatted response data. This generated message is output.

[0452] Step 8:

[0453] The server sends the generated response message to the terminal as an HTTP response, and then executes a process to return the output JSON format message data as an HTTP response.

[0454] Step 9:

[0455] The terminal receives the HTTP response from the server and analyzes the response data. The response data is given in JSON format as input. JavaScript is used to analyze the response data and display a message such as "Registration completed" on the user interface. The message displayed to the user as a result of this process is the final output.

[0456] (Application example 1)

[0457] 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."

[0458] In recent years, robots and machinery have been used to automate and streamline factories, but issuing appropriate operating instructions to these machines has been a difficult challenge. In particular, when users manually input instructions into the machines, input errors and delays are likely to occur, potentially reducing production efficiency. Furthermore, the lack of a mechanism for instantly verifying the content of operating instructions and updating the machines in real time complicates factory management. An effective system that can solve these problems and support automation within factories is needed.

[0459] 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.

[0460] In this invention, the server includes an operation means for user input, a device means for transmitting the input data to the server, a means for analyzing and verifying the data received by the server, a means for saving the analyzed and verified data in a data storage device, a means for performing additional processing based on the saved data, a means for generating a notification message for responding to the user with the result of the additional processing, a means for sending the generated notification message to the device, a means for displaying the notification message received by the device to the user, and an instruction means for issuing operation instructions to machinery in the factory as part of the additional processing. This makes it possible to issue appropriate operation instructions to machinery in the factory in real time, preventing input errors and operation delays and improving production efficiency.

[0461] "Operation means" refers to an interface through which a user inputs data and instructions.

[0462] "Device means" refers to a terminal device for transmitting input data to a server.

[0463] "Means for analysis and verification" refers to the function for analyzing the data received by the server and verifying its validity and accuracy.

[0464] "Data Storage Device" refers to the database within the system for storing analyzed and validated data.

[0465] "Means for further processing" refers to mechanisms for performing further processing based on the stored data.

[0466] The "means for generating a notification message" refers to a function for creating a message to notify the user of the result of the additional processing.

[0467] The "means for sending to the device" refers to a communication means for sending the generated notification message to the user's terminal.

[0468] The "means for displaying" refers to a function for visually displaying to the user the notification message received by the terminal.

[0469] "Instruction means" refers to a function for sending and managing operation instructions to machinery and devices within a factory.

[0470] The present invention is a system in which data entered by a user using an operation means is sent to a server via a device means, and the server analyzes and verifies the data and stores it in an appropriate data storage device.Furthermore, the system performs additional processing based on the stored data, generates a notification message of the results, and sends it again to the user's device means so that the user can check it.

[0471] To realize this invention, a user first inputs a work instruction using the operation means. For example, the user inputs "Please start assembly work on line 1" as an operation instruction for a machine in a factory. This input data is converted into JSON format by the device means and sent to the server using an HTTP POST request.

[0472] The server analyzes the data it receives and verifies its validity and accuracy. For example, it checks that work instructions are entered in the correct format and contain all the required information. This can be done using a web framework such as Flask. The server then securely stores the data in a data store and performs further processing based on the stored data.

[0473] As an additional process, for example, to execute an operation instruction for a machine in a factory, the server sends an instruction to the machine in real time via the instruction means. Based on the result of this instruction, the server generates a notification message for the user. For example, it creates a message such as "Assembly work on line 1 has started" and sends it again to the machine means.

[0474] The device receives notification messages from the server, analyzes them, and displays them on the user interface, allowing the user to confirm that the instructions were executed correctly. Through this series of processes, work efficiency within the factory can be improved and input errors and operational delays can be prevented.

[0475] An example of a specific prompt is as follows:

[0476] "Please begin assembly work on Line 1."

[0477] In this way, the present invention makes it possible to efficiently and accurately execute operating instructions for machinery in a factory, dramatically improving production efficiency.

[0478] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0479] Step 1:

[0480] The user inputs work instructions using the operating means. The input contents include the work target, work content, start time, etc. For example, the user inputs an instruction such as "Please start assembly work on line 1." This information is captured in the operating means.

[0481] Step 2:

[0482] The terminal means converts the data input by the user into JSON format. For example, the input instruction is converted into the following JSON format:

[0483] {

[0484] "line": "Line 1",

[0485] "task": "assembly work",

[0486] "action": "start"

[0487] }

[0488] This JSON data is converted into an HTTP POST request format and sent to the server. The input is a text-formatted work instruction, and the output is JSON-formatted data.

[0489] Step 3:

[0490] The server receives the HTTP POST request from the terminal and analyzes the contents. The analysis reads the JSON data and verifies the data format and content. For example, it checks whether "line" is empty, whether "task" is an allowed operation, and whether "action" is a valid instruction. The input is JSON format data, and the output is the verification result after analysis.

[0491] Step 4:

[0492] The server stores the data that passes validation in a data storage device (database). The stored data includes the user's instructions and a timestamp, allowing for future reference and additional processing. The input is the analyzed and validated data, and the output is the record stored in the database.

[0493] Step 5:

[0494] The server performs additional processing based on the data stored in the data storage device. Specifically, it sends operational instructions based on user input to machinery in the factory in real time. The instructions are sent to the machinery using the necessary protocols and communication methods. The input is the stored data, and the output is the operational instructions sent to the machinery.

[0495] Step 6:

[0496] The server receives responses and operation results from the machine and generates a message to notify the user. For example, it generates a message saying, "Assembly work on line 1 has started." This message is converted back to JSON format and sent to the terminal means. The input is the operation result from the machine, and the output is the generated notification message.

[0497] Step 7:

[0498] The terminal means analyzes the notification message received from the server and displays it on the user interface. This allows the user to confirm that their instructions have been executed correctly. For example, the terminal may display a message saying, "Assembly work on line 1 has started." The input is the notification message from the server, and the output is the confirmation message displayed on the user interface.

[0499] 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.

[0500] The present invention is a system that efficiently processes user input data and further combines it with an emotion engine that recognizes the user's emotions. Below, the program processing in the system of the present invention will be specifically explained in natural language.

[0501] First, a user enters necessary information into a web form, such as name, address, and email address. For example, the user enters the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com," and clicks the submit button. The input data is then imported into the form interface.

[0502] Next, the terminal converts the input data into JSON format. The converted JSON data is in the format { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}. The terminal sends this data to the server in the form of an HTTP POST request.

[0503] The server receives the HTTP request sent from the terminal and parses the JSON data. The server extracts the name, address, and email address fields from the request body and parses and validates the received data. Here, it checks whether the email address format is correct and whether all required fields have been entered.

[0504] After the server has verified the received data, it stores it in the database, which records the new user's information and makes it available for further processing.

[0505] Next, the server performs additional processing based on the stored data. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a registration completion email to "yamada@example.com."

[0506] Furthermore, as a feature of the present invention, the server uses an emotion engine to recognize emotions from the user's input data. For example, if the user inputs a comment such as "I'm so happy!", the emotion engine will identify the user's emotion as "joy." Then, it will create an appropriate message according to the emotion.

[0507] The server generates a response message for the user based on the results of the emotion engine and additional processing. In addition to the basic message "Registration completed," it adds a message according to the emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[0508] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed on the user interface, and a response such as "Registration completed. Your joy has been conveyed" is displayed to the user.

[0509] This allows the system of the present invention to efficiently process user input data and provide responses that recognize and reflect the user's emotions, improving the user experience and enabling more personalized services.

[0510] The processing flow will be explained below.

[0511] Step 1:

[0512] A user enters their name, address, email address, and free-form comments into a web form and clicks the submit button. For example, the user enters the name "Taro Yamada," the address "Tokyo," the email address "yamada@example.com," and the comment "This site is great!"

[0513] Step 2:

[0514] The device converts the user's input data into JSON format. The converted JSON data becomes { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com", "comment": "This site is great!"} The device sends this data to the server in the form of an HTTP POST request.

[0515] Step 3:

[0516] The server receives the HTTP request sent from the device and parses the JSON data. The server extracts the name, address, email address, and comment fields from the request body.

[0517] Step 4:

[0518] The server validates the incoming data, specifically checking that the email address is formatted correctly and that all required fields are filled in. For example, making sure the email address is in the format username@domain.com.

[0519] Step 5:

[0520] The server saves the data that passes validation to the user database, storing the name, address, email address, and comments as a new user record.

[0521] Step 6:

[0522] The server uses the stored data to perform additional processing. For example, it sends a confirmation email. The server calls the API of the email service and sends an email to "yamada@example.com" stating "Registration completed."

[0523] Step 7:

[0524] The server uses an emotion engine to recognize emotions from comments entered by users. For example, the comment "This site is great!" is analyzed and the emotion engine identifies it as "joy."

[0525] Step 8:

[0526] The server generates an appropriate response message for the user based on the emotion recognized by the emotion engine, for example, "Your registration is complete. We feel your joy."

[0527] Step 9:

[0528] The server generates a response message and sends it to the terminal. The message "Registration completed. Your joy has been conveyed" is sent to the terminal in the form of an HTTP response.

[0529] Step 10:

[0530] The device receives the HTTP response from the server and parses the response body, extracting the message "Registration completed. Your joy was conveyed."

[0531] Step 11:

[0532] The terminal displays the analyzed response message on the user interface, and the user can see the message "Registration completed. Your joy has been conveyed" on the browser.

[0533] Example 2

[0534] 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."

[0535] Previous systems simply received and stored user input data, but were unable to identify user sentiment and reflect it in response messages. This resulted in a lack of improved user experience and made it difficult to provide personalized services. Furthermore, there was a lack of efficient means for validating and storing data, increasing the risk of inaccurate data and errors.

[0536] 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.

[0537] In this invention, the server includes a means for analyzing and verifying received data, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for performing emotion analysis as the additional processing, and a means for generating a response message based on the emotion analysis results. This enables the generation of personalized messages that reflect the user's emotions. Furthermore, the accuracy and completeness of the data can be ensured, improving overall system efficiency.

[0538] "User" refers to a person or end user who uses the system.

[0539] "Interface means" refers to the means by which a user inputs data into the system, including web forms and input fields.

[0540] "Terminal means" refers to devices and software for transmitting user input data to a server, and includes personal computers and smartphones.

[0541] "Server" refers to the central computer system that receives, analyzes, and verifies data sent by users.

[0542] "Means for analyzing and verifying received data" refers to the algorithms or programs that analyze the data received by the server and check its accuracy and completeness.

[0543] "Means of storing data in a database" includes systems and methods for permanently storing analyzed and verified data.

[0544] "Means for performing additional processing" refers to programs or algorithms for performing further necessary processing on the stored data.

[0545] "Means for performing emotion analysis" refers to the engine or algorithm used to identify and analyze emotions from user input data.

[0546] "Means for generating a response message" refers to a program or algorithm that allows the system to generate a message to be sent back to the user.

[0547] "Means for sending a message to a terminal" includes any system or protocol for sending the generated response message to the user's terminal.

[0548] "Means for displaying to the user the message received by the terminal" refers to an interface or program for displaying on the screen of the user's terminal the message received from the server.

[0549] This invention is a system that efficiently processes user input data and recognizes and reflects the user's emotions. This system comprises a user interface using a web form, a terminal that sends input data to a server, a server that analyzes and verifies the received data, a database, an emotion analysis engine, and a function for generating and sending response messages.

[0550] First, a user enters information such as their name, address, and email address using a web form. The web form is implemented using HTML and JavaScript. For example, a user enters "Name: Yamada Taro," "Address: Tokyo," and "Email address: yamada@example.com," and then clicks the submit button.

[0551] Next, the terminal converts the input data into JSON format. Specifically, it serializes the JavaScript object into JSON format. This converted data looks like this:

[0552] json

[0553] {

[0554] "name": "Yamada Taro",

[0555] "address": "Tokyo",

[0556] "email": "yamada@example.com"

[0557] }

[0558] The device sends this JSON data to the server as an HTTP POST request, using HTTPS as the communication protocol.

[0559] The server receives this HTTP request. The server is often implemented using Node.js or Python (Flask or Django). It parses the received JSON data and extracts each field, such as name, address, and email address. It then verifies that the data format is correct and that all required fields have been entered.

[0560] Once the verification is complete, the data is stored in a database, typically a relational database such as MySQL or PostgreSQL.

[0561] The server then performs additional processing based on the user information stored in the database. As part of this processing, the server calls a sentiment analysis engine (such as IBM Watson or Google Cloud Natural Language API) to analyze the emotion from the user's comment. For example, if a user enters the comment "I'm so happy!", the sentiment analysis engine will determine this emotion as "joy."

[0562] The server generates a response message for the user based on the results of the emotion analysis. In addition to the basic message "Registration completed," it adds a message according to the user's emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[0563] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed in the user interface. For example, the response is displayed to the user in the form of "Registration completed. Your joy is conveyed."

[0564] As a concrete example, the same processing can be achieved by inputting the following prompt sentence into the generative AI model:

[0565] "Please explain how to convert the name, address, and email address entered by the user into JSON format and send it to the server."

[0566] "Please explain the steps to parse and validate the JSON data received by the server and save it to the database."

[0567] "Please explain how to determine the sentiment of the input comment and generate a response message accordingly."

[0568] The above is a specific embodiment for carrying out the present invention. This system can improve the user experience by providing a response that reflects the user's emotions.

[0569] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0570] The flow of this system's program processing

[0571] Step 1: User Input

[0572] A user enters name, address, and email information into a web form and clicks the submit button.

[0573] Input: Information entered by the user (name, address, email address)

[0574] Output: The input data is populated into the form interface

[0575] Specific actions

[0576] 1. The user opens a browser.

[0577] 2. Visit the website.

[0578] 3. Fill out the web form.

[0579] 4. Click the Send button.

[0580] Step 2: Convert data to JSON format and send it

[0581] The terminal receives the input data, converts it to JSON format, and sends it to the server in the form of an HTTP POST request.

[0582] Input: Information entered by the user (name, address, email address)

[0583] Data processing: Convert input data into JSON format using JavaScript etc.

[0584] Output: JSON format data is generated and sent to the server.

[0585] Specific actions

[0586] 1. Once the form is completed, the JavaScript code runs.

[0587] 2. The input data is converted to JSON format.

[0588] 3. The converted JSON data is sent to the server via an HTTP POST request.

[0589] Step 3: Data analysis and validation by the server

[0590] The server receives the HTTP request and parses and validates the JSON data.

[0591] Input: JSON data included in the body of the HTTP request

[0592] Data Calculation: Parse JSON data and extract name, address, and email address fields. Check email address format and required fields.

[0593] Output: Analyzed and validated data

[0594] Specific actions

[0595] 1. The server receives an HTTP request.

[0596] 2. Parse the JSON data in the request body.

[0597] 3. Extract names, addresses, and email addresses.

[0598] 4. Validate the data in each field (check email format, check required fields).

[0599] Step 4: Saving to the Database

[0600] The server stores the parsed and verified data in a database.

[0601] Input: Analyzed and validated data

[0602] Data processing: Generate and execute SQL queries to store data in a database

[0603] Output: Data is saved to the database

[0604] Specific actions

[0605] 1. Map the validated data to database objects.

[0606] 2. Execute a SQL query to insert data into the database.

[0607] 3. After the insert is complete, you receive a response from the database.

[0608] Step 5: Send a confirmation email

[0609] The server uses the email service API to send a confirmation email based on the stored data.

[0610] Input: User information stored in the database

[0611] Data operation: Call the email service API and pass the email content and recipient address.

[0612] Output: A confirmation email is sent to the user.

[0613] Specific actions

[0614] 1. The server calls the email sending API.

[0615] 2. Pass the email content and recipient address to the API.

[0616] 3. The email is sent and a response is received from the API.

[0617] Step 6: Emotion Recognition

[0618] The server uses an emotion analysis engine to recognize emotions from the user's input data.

[0619] Input: User comment data

[0620] Data calculation: Send comments to a sentiment analysis engine to analyze sentiment

[0621] Output: Emotion analysis results

[0622] Specific actions

[0623] 1. Send user comment data to a sentiment analysis engine.

[0624] 2. The sentiment analysis engine analyzes the comments and determines their sentiment.

[0625] 3. The result of the judgment is returned to the server.

[0626] Step 7: Generate and send a response message

[0627] The server generates a response message based on the emotion analysis result and the basic message, and sends it to the terminal.

[0628] Input: Sentiment analysis results, information stored in the database

[0629] Data calculation: Generate a response message based on the above data

[0630] Output: A response message is sent to the terminal

[0631] Specific actions

[0632] 1. Generate a response message based on the emotion results.

[0633] 2. Include the response message in the HTTP response.

[0634] 3. Send the HTTP response to the device.

[0635] Step 8: Displaying Messages

[0636] The terminal analyzes the HTTP response received from the server and displays a message on the user interface.

[0637] Input: HTTP response received from the server

[0638] Data operation: Parse the HTTP response body and extract the message

[0639] Output: A message is displayed to the user

[0640] Specific actions

[0641] 1. Receive an HTTP response.

[0642] 2. Parse the JSON data in the response body.

[0643] 3. The parsed message is displayed on the screen in HTML format.

[0644] The above is the specific flow of processing of the program in this system.

[0645] (Application example 2)

[0646] 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."

[0647] While conventional systems can efficiently process data entered by users, they have difficulty analyzing the user's emotional state and taking appropriate measures based on that emotion. Furthermore, particularly in the security field, it has been difficult to determine in real time whether a user is in a dangerous situation and respond immediately. To solve this problem and ensure user safety more reliably, a system is needed that analyzes the user's emotions and surrounding audio and video data to assess danger.

[0648] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing the user's emotional state, means for collecting and analyzing surrounding audio and video data, and means for assessing danger and issuing a warning based on the emotional state. This not only analyzes the data entered by the user, but also monitors the user's emotional state in real time and comprehensively evaluates information obtained from the surrounding environment, making it possible to immediately issue a warning if the user is in danger.

[0649] An "interface means" is a means by which a user inputs data into a system.

[0650] The "terminal means" is a means for transmitting data input by a user to a server.

[0651] "Means for analysis and verification" refers to the means by which the server analyzes the data received and checks the accuracy of the data and whether there are any errors.

[0652] "Means of storage" refers to the means for recording analyzed and verified data in a database.

[0653] "Means for performing additional processing" refers to means for performing further processing based on the stored data.

[0654] "Emotion engine means" means that uses an engine to analyze the emotional state of a user.

[0655] The "means for generating a message" is a means for generating an appropriate response message based on the analysis result.

[0656] "Means for collecting and analyzing" refers to means for collecting and analyzing surrounding audio and video data.

[0657] The "means for assessing danger and issuing a warning" is a means for assessing whether the user is in a dangerous situation based on the user's emotional state and surrounding data, and issuing a warning as necessary.

[0658] The "means for sending" is a means for sending the generated message to the user's terminal.

[0659] The "display means" is a means for visually displaying to the user the message received by the terminal.

[0660] As an embodiment of the present invention, a security system can be constructed that uses smart glasses worn by a user to analyze emotional states and surrounding environmental data in real time. This system is realized using the following hardware and software.

[0661] 1. Hardware

[0662] Smart glasses: built-in camera, microphone, and heart rate sensor

[0663] Server: Data processing and emotion engine execution

[0664] Communication module: Data transfer between smart glasses and server

[0665] 2. Software

[0666] Emotion engine (e.g. TensorFlow, Keras): Analyzes the user's facial expressions and heart rate data

[0667] Voice recognition software: Analyzes surrounding audio data and detects dangerous sounds

[0668] Database (e.g. MySQL, PostgreSQL): Stores user data and analysis results

[0669] Message Generation Algorithm: Create appropriate warning messages

[0670] Detailed explanation of program processing

[0671] 1. Data collection

[0672] Once the user puts on the smart glasses, the camera and microphone begin working, and the heart rate sensor also continuously monitors the heart rate.

[0673] 2. Data Preprocessing

[0674] The smart glasses extract the collected video data frame by frame and perform facial and facial expression recognition, using deep learning models such as TensorFlow and Keras.

[0675] The audio data is analyzed by voice recognition software to detect dangerous sounds (e.g., screaming, breaking glass).

[0676] 3. Operation of the Emotion Engine

[0677] The server inputs the user's facial expressions and heart rate data into an emotion engine to analyze the user's emotional state. For example, TensorFlow and Keras can be used to recognize emotions from micro-expressions.

[0678] 4. Risk Assessment

[0679] Based on the emotional state (e.g., surprise, fear) recognized by the emotion engine and the dangerous sounds detected by the voice recognition software, the server assesses whether the user is in a dangerous situation.

[0680] 5. Generating and Sending Alerts

[0681] If a danger is detected, the server generates an appropriate warning message, which is then sent to the user via the communication module of the smart glasses, and displayed on the display of the smart glasses.

[0682] Specific examples

[0683] For example, when a user is walking down a dark street at night, the smart glasses collect ambient sounds (e.g., sudden footsteps from behind) and images (e.g., a person chasing the user). The emotion engine recognizes fear from the user's facial expression and detects sudden footsteps from the audio data. After comprehensively evaluating the situation, the server generates a warning message saying, "There may be someone behind you. Be careful of danger." This message is then displayed on the smart glasses' display.

[0684] Prompt Sentence Examples

[0685] "A user may hear a scream nearby, and their heart rate may suddenly increase, revealing a look of surprise on their face. From this data, we can analyze the user's emotions and determine whether danger exists."

[0686] This embodiment allows for analyzing emotion and environmental data in real time when a user faces a dangerous situation, and providing prompt and appropriate warnings.

[0687] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0688] Step 1:

[0689] The user puts on the smart glasses. The camera built into the glasses starts collecting video data, and the microphone starts collecting audio data. The heart rate sensor also continuously monitors the user's heart rate. This data is transmitted to the smart glasses terminal in real time.

[0690] Input: User wear, video data, audio data, heart rate data

[0691] Output: Real-time data collected

[0692] Step 2:

[0693] The device extracts the video data collected by the device frame by frame and performs facial and facial expression recognition using TensorFlow and Keras. At the same time, the audio data is analyzed using speech recognition software (e.g., DeepSpeech or Google Speech-to-Text API) to detect dangerous sounds (e.g., screaming, breaking glass). Heart rate data is monitored in real time to check for sudden increases or abnormal values.

[0694] Input: Real-time data collected

[0695] Output: Analyzed facial expression data, voice data, heart rate data

[0696] Step 3:

[0697] The server inputs the analyzed data into the emotion engine, which analyzes the user's emotional state. The emotion engine recognizes the user's emotions (e.g., surprise, fear, joy) based on facial expressions, heart rate, and voice data. This process uses deep learning models (e.g., Long Short-Term Memory, Convolutional Neural Network).

[0698] Input: Analyzed facial expression data, voice data, heart rate data

[0699] Output: Perceived emotional state

[0700] Step 4:

[0701] The server combines the results of the emotion engine's analysis and the results of the dangerous sound detection by the voice recognition software to evaluate whether the user is in a dangerous situation, and generates a warning message if necessary based on the evaluation results.

[0702] Input: Recognized emotional state, analysis results of speech data

[0703] Output: Risk assessment results, warning messages

[0704] Step 5:

[0705] The server generates a warning message and sends it to the smart glasses terminal, which visually displays the received message to the user. For example, a message such as "There may be someone behind you. Beware of danger" is displayed on the display.

[0706] Input: The generated warning message

[0707] Output: Warning message sent to terminal

[0708] Step 6:

[0709] The user checks the displayed message and takes appropriate action, such as looking around, walking faster, or moving to another street.

[0710] Input: The warning message displayed on the terminal

[0711] Output: User behavior change

[0712] 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.

[0713] 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.

[0714] 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.

[0715] [Third embodiment]

[0716] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0717] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0718] 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).

[0719] 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.

[0720] 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.

[0721] 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).

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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."

[0728] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[0729] The processing of the program in the system of the present invention will be explained in natural language below.

[0730] First, a user enters information required for a web form, such as their name, address, and email address, and clicks the submit button. The form-filling interface captures the input data into the terminal.

[0731] Next, the terminal converts the input data into JSON format and sends it to the server using an HTTP POST request. The JSON format data looks like this: { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}

[0732] The server receives the HTTP request sent from the device and analyzes the data sent. After analyzing, it verifies whether the data is valid. For example, it checks whether the email address format is correct and whether all required fields have been entered.

[0733] Data that passes verification is stored in a database by the server. The database serves to securely store registered user information. Based on this, the server performs additional processing. This additional processing may include sending email notifications or linking with other services.

[0734] The server generates a response message for the user based on the information stored in the database and the results of the additional processing. For example, it creates a message such as "Registration completed." This message is then sent to the terminal again as an HTTP response.

[0735] The terminal receives the HTTP response from the server and analyzes the response data. The analyzed data is displayed on the user interface, and a message stating "Registration completed" is displayed to the user. In this way, data transmission, reception, and processing in the system of the present invention are completed.

[0736] The processing flow will be explained below.

[0737] Step 1:

[0738] A user fills in a web form with required information, such as name, address, and email address, and clicks the submit button, at which point the user's input data is captured in the form interface.

[0739] Step 2:

[0740] The device converts the user's input data into JSON format (e.g., { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}) and sends the data to the server using an HTTP POST request.

[0741] Step 3:

[0742] The server receives the HTTP request from the device and parses the JSON data sent. The server extracts the contents of the request body and each field (name, address, email address, etc.).

[0743] Step 4:

[0744] Validate the data received by the server, specifically checking that email addresses are formatted correctly and that required fields are not missing (for example, that email addresses are in username@domain.com format).

[0745] Step 5:

[0746] The server saves the data that passes validation to the database, storing the name, address, and email address as a new user record in the appropriate tables.

[0747] Step 6:

[0748] The server performs additional processing based on the information stored in the database. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a confirmation email stating "Registration completed" to the user's email address.

[0749] Step 7:

[0750] The server generates a response message for the user based on the results of the addition process. It creates a message stating "Registration completed" and generates this as response data.

[0751] Step 8:

[0752] The server generates a response message and sends it to the terminal as an HTTP response, which includes a success message and additional information.

[0753] Step 9:

[0754] The device receives the HTTP response from the server, analyzes the response body, and extracts the message "Registration completed."

[0755] Step 10:

[0756] The terminal displays the analyzed message on the user interface, and the user can see the message "Registration completed" on the browser.

[0757] Example 1

[0758] 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."

[0759] Existing systems require manual intervention to validate and store data entered by users, resulting in issues with speed and accuracy. Data transmission and reception also requires security and efficiency. Furthermore, there is a lack of a way to quickly and accurately communicate the results of additional processing to users. Therefore, there is a need to automate data processing and transmission while improving user convenience.

[0760] 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.

[0761] In this invention, the server includes an analysis and verification means, a storage means for storing data in a storage device, and a means for performing additional processing, thereby enabling accurate analysis and verification of data, efficient storage, and rapid additional processing.

[0762] An "interface means" is a combination of an input device and software for a user to provide input.

[0763] "Terminal means" refers to a combination of a device and software that has the function of receiving user input data and transmitting it to a communication device.

[0764] "Communication device" refers to a server or network device that receives data sent from a terminal means and further analyzes and verifies it.

[0765] "Analysis and verification means" refers to a combination of software and hardware that has the function of analyzing the contents of received data and checking for errors in format and content.

[0766] "Storage device" refers to a database and storage device for storing analyzed and verified data.

[0767] "Further processing means" is a combination of software and hardware that performs further processing on stored data to generate new results or information.

[0768] The "means for generating a message" is a combination of software and hardware that has the function of creating an appropriate message for the user based on the results of the additional processing.

[0769] A "data interchange format" is a format for expressing data in a unified format, such as JSON or XML.

[0770] A "data exchange protocol" is a protocol that defines the communication methods and rules for sending and receiving data, and examples of this include HTTP and HTTPS.

[0771] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a storage device, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[0772] First, a user inputs necessary information into a web form through a web browser. This form input interface is for accepting user input data, and includes basic information such as name, address, and email address.

[0773] Next, the terminal converts the input data into a data exchange format (e.g., JSON) and sends it to the server using an HTTP request. The software used by the terminal could be the JavaScript fetch API. For example, if a user inputs their name as "Yamada Taro," their address as "Tokyo," and their email address as "yamada@example.com," the terminal converts this into JSON format and sends it to the server.

[0774] The server receives the HTTP request sent from the device using web server software such as Apache or Nginx. The received data is parsed and validated using, for example, the Python Django framework, to check whether the email address is formatted correctly and whether all required fields have been filled in. Validation is performed using regular expressions, for example.

[0775] Data that passes the verification is stored by the server in a storage device (e.g., an SQL database), which is used to maintain the reliability and integrity of the data, and databases such as MySQL or PostgreSQL are used.

[0776] The server then performs additional processing based on the stored data, such as sending email notifications to users or integrating with other services, using the Python smtplib library to send a registration confirmation email.

[0777] Finally, the server generates a message to respond to the user. The generated message is created in JSON format, and has the content, for example, "Registration completed." This message is sent to the terminal as an HTTP response.

[0778] The terminal receives the HTTP response from the server, analyzes the response data, and displays it on the user interface. For example, the terminal performs the analysis using JavaScript and displays a message to the user such as "Registration completed."

[0779] Prompt Sentence Examples

[0780] Please provide a detailed explanation of the steps to implement a system that sends data entered by a user into a web form to a server, where it is parsed, validated, and stored in a database. The system then performs additional processing and displays a response message to the user. Please also specify the specific hardware and software used, as well as the method of data processing.

[0781] This automates the sending, receiving, and processing of data throughout the system and provides an easy-to-use interface for users.

[0782] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0783] Step 1:

[0784] A user inputs the required information into a web form. For example, the user inputs the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com." This input data is imported into the terminal through the form input interface of the web browser. The input data is obtained in text format for processing on the terminal.

[0785] Step 2:

[0786] The device converts the input data into JSON format and sends it to the server using an HTTP POST request. Specifically, it uses the JavaScript fetch API to convert the text data into JSON format data { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"} and generates output. This data is sent to the specified URL.

[0787] Step 3:

[0788] The server receives HTTP requests sent from the terminal using web server software such as Apache or Nginx. JSON format data is given as input. The received data is analyzed using the Python Django framework, and the text data is converted into a dictionary format and output.

[0789] Step 4:

[0790] The server verifies whether the received data is valid. Validation involves checking the format of the email address and whether any required fields are present. For example, the email address is validated using the Python regular expression library "re" to ensure there are no omissions or errors. If the data is valid, the server proceeds to the next step; if it is invalid, an error message is generated and output.

[0791] Step 5:

[0792] Once the data passes validation, it is saved to a storage device (e.g., an SQL database) by the server. The input data remains in dictionary format and is converted to SQL commands using Django models. The output includes the save completion status and the ID of the saved record.

[0793] Step 6:

[0794] The server performs additional processing based on the stored data. This additional processing can include sending email notifications or connecting with external services. For example, it uses the Python smtplib library to send a registration confirmation email to the entered email address. Here, the status of the email sending process is output.

[0795] Step 7:

[0796] The server generates a response message for the user based on the results of the additional processing. For example, it creates a message saying "Registration completed" and converts it into JSON-formatted response data. This generated message is output.

[0797] Step 8:

[0798] The server sends the generated response message to the terminal as an HTTP response, and then executes a process to return the output JSON format message data as an HTTP response.

[0799] Step 9:

[0800] The terminal receives the HTTP response from the server and analyzes the response data. The response data is given in JSON format as input. JavaScript is used to analyze the response data and display a message such as "Registration completed" on the user interface. The message displayed to the user as a result of this process is the final output.

[0801] (Application example 1)

[0802] 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."

[0803] In recent years, robots and machinery have been used to automate and streamline factories, but issuing appropriate operating instructions to these machines has been a difficult challenge. In particular, when users manually input instructions into the machines, input errors and delays are likely to occur, potentially reducing production efficiency. Furthermore, the lack of a mechanism for instantly verifying the content of operating instructions and updating the machines in real time complicates factory management. An effective system that can solve these problems and support automation within factories is needed.

[0804] 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.

[0805] In this invention, the server includes an operation means for user input, a device means for transmitting the input data to the server, a means for analyzing and verifying the data received by the server, a means for saving the analyzed and verified data in a data storage device, a means for performing additional processing based on the saved data, a means for generating a notification message for responding to the user with the result of the additional processing, a means for sending the generated notification message to the device, a means for displaying the notification message received by the device to the user, and an instruction means for issuing operation instructions to machinery in the factory as part of the additional processing. This makes it possible to issue appropriate operation instructions to machinery in the factory in real time, preventing input errors and operation delays and improving production efficiency.

[0806] "Operation means" refers to an interface through which a user inputs data and instructions.

[0807] "Device means" refers to a terminal device for transmitting input data to a server.

[0808] "Means for analysis and verification" refers to the function for analyzing the data received by the server and verifying its validity and accuracy.

[0809] "Data Storage Device" refers to the database within the system for storing analyzed and validated data.

[0810] "Means for further processing" refers to mechanisms for performing further processing based on the stored data.

[0811] The "means for generating a notification message" refers to a function for creating a message to notify the user of the result of the additional processing.

[0812] The "means for sending to the device" refers to a communication means for sending the generated notification message to the user's terminal.

[0813] The "means for displaying" refers to a function for visually displaying to the user the notification message received by the terminal.

[0814] "Instruction means" refers to a function for sending and managing operation instructions to machinery and devices within a factory.

[0815] The present invention is a system in which data entered by a user using an operation means is sent to a server via a device means, and the server analyzes and verifies the data and stores it in an appropriate data storage device.Furthermore, the system performs additional processing based on the stored data, generates a notification message of the results, and sends it again to the user's device means so that the user can check it.

[0816] To realize this invention, a user first inputs a work instruction using the operation means. For example, the user inputs "Please start assembly work on line 1" as an operation instruction for a machine in a factory. This input data is converted into JSON format by the device means and sent to the server using an HTTP POST request.

[0817] The server analyzes the data it receives and verifies its validity and accuracy. For example, it checks that work instructions are entered in the correct format and contain all the required information. This can be done using a web framework such as Flask. The server then securely stores the data in a data store and performs further processing based on the stored data.

[0818] As an additional process, for example, to execute an operation instruction for a machine in a factory, the server sends an instruction to the machine in real time via the instruction means. Based on the result of this instruction, the server generates a notification message for the user. For example, it creates a message such as "Assembly work on line 1 has started" and sends it again to the machine means.

[0819] The device receives notification messages from the server, analyzes them, and displays them on the user interface, allowing the user to confirm that the instructions were executed correctly. Through this series of processes, work efficiency within the factory can be improved and input errors and operational delays can be prevented.

[0820] An example of a specific prompt is as follows:

[0821] "Please begin assembly work on Line 1."

[0822] In this way, the present invention makes it possible to efficiently and accurately execute operating instructions for machinery in a factory, dramatically improving production efficiency.

[0823] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0824] Step 1:

[0825] The user inputs work instructions using the operating means. The input contents include the work target, work content, start time, etc. For example, the user inputs an instruction such as "Please start assembly work on line 1." This information is captured in the operating means.

[0826] Step 2:

[0827] The terminal means converts the data input by the user into JSON format. For example, the input instruction is converted into the following JSON format:

[0828] {

[0829] "line": "Line 1",

[0830] "task": "assembly work",

[0831] "action": "start"

[0832] }

[0833] This JSON data is converted into an HTTP POST request format and sent to the server. The input is a text-formatted work instruction, and the output is JSON-formatted data.

[0834] Step 3:

[0835] The server receives the HTTP POST request from the terminal and analyzes the contents. The analysis reads the JSON data and verifies the data format and content. For example, it checks whether "line" is empty, whether "task" is an allowed operation, and whether "action" is a valid instruction. The input is JSON format data, and the output is the verification result after analysis.

[0836] Step 4:

[0837] The server stores the data that passes validation in a data storage device (database). The stored data includes the user's instructions and a timestamp, allowing for future reference and additional processing. The input is the analyzed and validated data, and the output is the record stored in the database.

[0838] Step 5:

[0839] The server performs additional processing based on the data stored in the data storage device. Specifically, it sends operational instructions based on user input to machinery in the factory in real time. The instructions are sent to the machinery using the necessary protocols and communication methods. The input is the stored data, and the output is the operational instructions sent to the machinery.

[0840] Step 6:

[0841] The server receives responses and operation results from the machine and generates a message to notify the user. For example, it generates a message saying, "Assembly work on line 1 has started." This message is converted back to JSON format and sent to the terminal means. The input is the operation result from the machine, and the output is the generated notification message.

[0842] Step 7:

[0843] The terminal means analyzes the notification message received from the server and displays it on the user interface. This allows the user to confirm that their instructions have been executed correctly. For example, the terminal may display a message saying, "Assembly work on line 1 has started." The input is the notification message from the server, and the output is the confirmation message displayed on the user interface.

[0844] 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.

[0845] The present invention is a system that efficiently processes user input data and further combines it with an emotion engine that recognizes the user's emotions. Below, the program processing in the system of the present invention will be specifically explained in natural language.

[0846] First, a user enters necessary information into a web form, such as name, address, and email address. For example, the user enters the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com," and clicks the submit button. The input data is then imported into the form interface.

[0847] Next, the terminal converts the input data into JSON format. The converted JSON data is in the format { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}. The terminal sends this data to the server in the form of an HTTP POST request.

[0848] The server receives the HTTP request sent from the terminal and parses the JSON data. The server extracts the name, address, and email address fields from the request body and parses and validates the received data. Here, it checks whether the email address format is correct and whether all required fields have been entered.

[0849] After the server has verified the received data, it stores it in the database, which records the new user's information and makes it available for further processing.

[0850] Next, the server performs additional processing based on the stored data. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a registration completion email to "yamada@example.com."

[0851] Furthermore, as a feature of the present invention, the server uses an emotion engine to recognize emotions from the user's input data. For example, if the user inputs a comment such as "I'm so happy!", the emotion engine will identify the user's emotion as "joy." Then, it will create an appropriate message according to the emotion.

[0852] The server generates a response message for the user based on the results of the emotion engine and additional processing. In addition to the basic message "Registration completed," it adds a message according to the emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[0853] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed on the user interface, and a response such as "Registration completed. Your joy has been conveyed" is displayed to the user.

[0854] This allows the system of the present invention to efficiently process user input data and provide responses that recognize and reflect the user's emotions, improving the user experience and enabling more personalized services.

[0855] The processing flow will be explained below.

[0856] Step 1:

[0857] A user enters their name, address, email address, and free-form comments into a web form and clicks the submit button. For example, the user enters the name "Taro Yamada," the address "Tokyo," the email address "yamada@example.com," and the comment "This site is great!"

[0858] Step 2:

[0859] The device converts the user's input data into JSON format. The converted JSON data becomes { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com", "comment": "This site is great!"} The device sends this data to the server in the form of an HTTP POST request.

[0860] Step 3:

[0861] The server receives the HTTP request sent from the device and parses the JSON data. The server extracts the name, address, email address, and comment fields from the request body.

[0862] Step 4:

[0863] The server validates the incoming data, specifically checking that the email address is formatted correctly and that all required fields are filled in. For example, making sure the email address is in the format username@domain.com.

[0864] Step 5:

[0865] The server saves the data that passes validation to the user database, storing the name, address, email address, and comments as a new user record.

[0866] Step 6:

[0867] The server uses the stored data to perform additional processing. For example, it sends a confirmation email. The server calls the API of the email service and sends an email to "yamada@example.com" stating "Registration completed."

[0868] Step 7:

[0869] The server uses an emotion engine to recognize emotions from comments entered by users. For example, the comment "This site is great!" is analyzed and the emotion engine identifies it as "joy."

[0870] Step 8:

[0871] The server generates an appropriate response message for the user based on the emotion recognized by the emotion engine, for example, "Your registration is complete. We feel your joy."

[0872] Step 9:

[0873] The server generates a response message and sends it to the terminal. The message "Registration completed. Your joy has been conveyed" is sent to the terminal in the form of an HTTP response.

[0874] Step 10:

[0875] The device receives the HTTP response from the server and parses the response body, extracting the message "Registration completed. Your joy was conveyed."

[0876] Step 11:

[0877] The terminal displays the analyzed response message on the user interface, and the user can see the message "Registration completed. Your joy has been conveyed" on the browser.

[0878] Example 2

[0879] 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."

[0880] Previous systems simply received and stored user input data, but were unable to identify user sentiment and reflect it in response messages. This resulted in a lack of improved user experience and made it difficult to provide personalized services. Furthermore, there was a lack of efficient means for validating and storing data, increasing the risk of inaccurate data and errors.

[0881] 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.

[0882] In this invention, the server includes a means for analyzing and verifying received data, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for performing emotion analysis as the additional processing, and a means for generating a response message based on the emotion analysis results. This enables the generation of personalized messages that reflect the user's emotions. Furthermore, the accuracy and completeness of the data can be ensured, improving overall system efficiency.

[0883] "User" refers to a person or end user who uses the system.

[0884] "Interface means" refers to the means by which a user inputs data into the system, including web forms and input fields.

[0885] "Terminal means" refers to devices and software for transmitting user input data to a server, and includes personal computers and smartphones.

[0886] "Server" refers to the central computer system that receives, analyzes, and verifies data sent by users.

[0887] "Means for analyzing and verifying received data" refers to the algorithms or programs that analyze the data received by the server and check its accuracy and completeness.

[0888] "Means of storing data in a database" includes systems and methods for permanently storing analyzed and verified data.

[0889] "Means for performing additional processing" refers to programs or algorithms for performing further necessary processing on the stored data.

[0890] "Means for performing emotion analysis" refers to the engine or algorithm used to identify and analyze emotions from user input data.

[0891] "Means for generating a response message" refers to a program or algorithm that allows the system to generate a message to be sent back to the user.

[0892] "Means for sending a message to a terminal" includes any system or protocol for sending the generated response message to the user's terminal.

[0893] "Means for displaying to the user the message received by the terminal" refers to an interface or program for displaying on the screen of the user's terminal the message received from the server.

[0894] This invention is a system that efficiently processes user input data and recognizes and reflects the user's emotions. This system comprises a user interface using a web form, a terminal that sends input data to a server, a server that analyzes and verifies the received data, a database, an emotion analysis engine, and a function for generating and sending response messages.

[0895] First, a user enters information such as their name, address, and email address using a web form. The web form is implemented using HTML and JavaScript. For example, a user enters "Name: Yamada Taro," "Address: Tokyo," and "Email address: yamada@example.com," and then clicks the submit button.

[0896] Next, the terminal converts the input data into JSON format. Specifically, it serializes the JavaScript object into JSON format. This converted data looks like this:

[0897] json

[0898] {

[0899] "name": "Yamada Taro",

[0900] "address": "Tokyo",

[0901] "email": "yamada@example.com"

[0902] }

[0903] The device sends this JSON data to the server as an HTTP POST request, using HTTPS as the communication protocol.

[0904] The server receives this HTTP request. The server is often implemented using Node.js or Python (Flask or Django). It parses the received JSON data and extracts each field, such as name, address, and email address. It then verifies that the data format is correct and that all required fields have been entered.

[0905] Once the verification is complete, the data is stored in a database, typically a relational database such as MySQL or PostgreSQL.

[0906] The server then performs additional processing based on the user information stored in the database. As part of this processing, the server calls a sentiment analysis engine (such as IBM Watson or Google Cloud Natural Language API) to analyze the emotion from the user's comment. For example, if a user enters the comment "I'm so happy!", the sentiment analysis engine will determine this emotion as "joy."

[0907] The server generates a response message for the user based on the results of the emotion analysis. In addition to the basic message "Registration completed," it adds a message according to the user's emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[0908] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed in the user interface. For example, the response is displayed to the user in the form of "Registration completed. Your joy is conveyed."

[0909] As a concrete example, the same processing can be achieved by inputting the following prompt sentence into the generative AI model:

[0910] "Please explain how to convert the name, address, and email address entered by the user into JSON format and send it to the server."

[0911] "Please explain the steps to parse and validate the JSON data received by the server and save it to the database."

[0912] "Please explain how to determine the sentiment of the input comment and generate a response message accordingly."

[0913] The above is a specific embodiment for carrying out the present invention. This system can improve the user experience by providing a response that reflects the user's emotions.

[0914] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0915] The flow of this system's program processing

[0916] Step 1: User Input

[0917] A user enters name, address, and email information into a web form and clicks the submit button.

[0918] Input: Information entered by the user (name, address, email address)

[0919] Output: The input data is populated into the form interface

[0920] Specific actions

[0921] 1. The user opens a browser.

[0922] 2. Visit the website.

[0923] 3. Fill out the web form.

[0924] 4. Click the Send button.

[0925] Step 2: Convert data to JSON format and send it

[0926] The terminal receives the input data, converts it to JSON format, and sends it to the server in the form of an HTTP POST request.

[0927] Input: Information entered by the user (name, address, email address)

[0928] Data processing: Convert input data into JSON format using JavaScript etc.

[0929] Output: JSON format data is generated and sent to the server.

[0930] Specific actions

[0931] 1. Once the form is completed, the JavaScript code runs.

[0932] 2. The input data is converted to JSON format.

[0933] 3. The converted JSON data is sent to the server via an HTTP POST request.

[0934] Step 3: Data analysis and validation by the server

[0935] The server receives the HTTP request and parses and validates the JSON data.

[0936] Input: JSON data included in the body of the HTTP request

[0937] Data Calculation: Parse JSON data and extract name, address, and email address fields. Check email address format and required fields.

[0938] Output: Analyzed and validated data

[0939] Specific actions

[0940] 1. The server receives an HTTP request.

[0941] 2. Parse the JSON data in the request body.

[0942] 3. Extract names, addresses, and email addresses.

[0943] 4. Validate the data in each field (check email format, check required fields).

[0944] Step 4: Saving to the Database

[0945] The server stores the parsed and verified data in a database.

[0946] Input: Analyzed and validated data

[0947] Data processing: Generate and execute SQL queries to store data in a database

[0948] Output: Data is saved to the database

[0949] Specific actions

[0950] 1. Map the validated data to database objects.

[0951] 2. Execute a SQL query to insert data into the database.

[0952] 3. After the insert is complete, you receive a response from the database.

[0953] Step 5: Send a confirmation email

[0954] The server uses the email service API to send a confirmation email based on the stored data.

[0955] Input: User information stored in the database

[0956] Data operation: Call the email service API and pass the email content and recipient address.

[0957] Output: A confirmation email is sent to the user.

[0958] Specific actions

[0959] 1. The server calls the email sending API.

[0960] 2. Pass the email content and recipient address to the API.

[0961] 3. The email is sent and a response is received from the API.

[0962] Step 6: Emotion Recognition

[0963] The server uses an emotion analysis engine to recognize emotions from the user's input data.

[0964] Input: User comment data

[0965] Data calculation: Send comments to a sentiment analysis engine to analyze sentiment

[0966] Output: Emotion analysis results

[0967] Specific actions

[0968] 1. Send user comment data to a sentiment analysis engine.

[0969] 2. The sentiment analysis engine analyzes the comments and determines their sentiment.

[0970] 3. The result of the judgment is returned to the server.

[0971] Step 7: Generate and send a response message

[0972] The server generates a response message based on the emotion analysis result and the basic message, and sends it to the terminal.

[0973] Input: Sentiment analysis results, information stored in the database

[0974] Data calculation: Generate a response message based on the above data

[0975] Output: A response message is sent to the terminal

[0976] Specific actions

[0977] 1. Generate a response message based on the emotion results.

[0978] 2. Include the response message in the HTTP response.

[0979] 3. Send the HTTP response to the device.

[0980] Step 8: Displaying Messages

[0981] The terminal analyzes the HTTP response received from the server and displays a message on the user interface.

[0982] Input: HTTP response received from the server

[0983] Data operation: Parse the HTTP response body and extract the message

[0984] Output: A message is displayed to the user

[0985] Specific actions

[0986] 1. Receive an HTTP response.

[0987] 2. Parse the JSON data in the response body.

[0988] 3. The parsed message is displayed on the screen in HTML format.

[0989] The above is the specific flow of processing of the program in this system.

[0990] (Application example 2)

[0991] 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."

[0992] While conventional systems can efficiently process data entered by users, they have difficulty analyzing the user's emotional state and taking appropriate measures based on that emotion. Furthermore, particularly in the security field, it has been difficult to determine in real time whether a user is in a dangerous situation and respond immediately. To solve this problem and ensure user safety more reliably, a system is needed that analyzes the user's emotions and surrounding audio and video data to assess danger.

[0993] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing the user's emotional state, means for collecting and analyzing surrounding audio and video data, and means for assessing danger and issuing a warning based on the emotional state. This not only analyzes the data entered by the user, but also monitors the user's emotional state in real time and comprehensively evaluates information obtained from the surrounding environment, making it possible to immediately issue a warning if the user is in danger.

[0994] An "interface means" is a means by which a user inputs data into a system.

[0995] The "terminal means" is a means for transmitting data input by a user to a server.

[0996] "Means for analysis and verification" refers to the means by which the server analyzes the data received and checks the accuracy of the data and whether there are any errors.

[0997] "Means of storage" refers to the means for recording analyzed and verified data in a database.

[0998] "Means for performing additional processing" refers to means for performing further processing based on the stored data.

[0999] "Emotion engine means" means that uses an engine to analyze the emotional state of a user.

[1000] The "means for generating a message" is a means for generating an appropriate response message based on the analysis result.

[1001] "Means for collecting and analyzing" refers to means for collecting and analyzing surrounding audio and video data.

[1002] The "means for assessing danger and issuing a warning" is a means for assessing whether the user is in a dangerous situation based on the user's emotional state and surrounding data, and issuing a warning as necessary.

[1003] The "means for sending" is a means for sending the generated message to the user's terminal.

[1004] The "display means" is a means for visually displaying to the user the message received by the terminal.

[1005] As an embodiment of the present invention, a security system can be constructed that uses smart glasses worn by a user to analyze emotional states and surrounding environmental data in real time. This system is realized using the following hardware and software.

[1006] 1. Hardware

[1007] Smart glasses: built-in camera, microphone, and heart rate sensor

[1008] Server: Data processing and emotion engine execution

[1009] Communication module: Data transfer between smart glasses and server

[1010] 2. Software

[1011] Emotion engine (e.g. TensorFlow, Keras): Analyzes the user's facial expressions and heart rate data

[1012] Voice recognition software: Analyzes surrounding audio data and detects dangerous sounds

[1013] Database (e.g. MySQL, PostgreSQL): Stores user data and analysis results

[1014] Message Generation Algorithm: Create appropriate warning messages

[1015] Detailed explanation of program processing

[1016] 1. Data collection

[1017] Once the user puts on the smart glasses, the camera and microphone begin working, and the heart rate sensor also continuously monitors the heart rate.

[1018] 2. Data Preprocessing

[1019] The smart glasses extract the collected video data frame by frame and perform facial and facial expression recognition, using deep learning models such as TensorFlow and Keras.

[1020] The audio data is analyzed by voice recognition software to detect dangerous sounds (e.g., screaming, breaking glass).

[1021] 3. Operation of the Emotion Engine

[1022] The server inputs the user's facial expressions and heart rate data into an emotion engine to analyze the user's emotional state. For example, TensorFlow and Keras can be used to recognize emotions from micro-expressions.

[1023] 4. Risk Assessment

[1024] Based on the emotional state (e.g., surprise, fear) recognized by the emotion engine and the dangerous sounds detected by the voice recognition software, the server assesses whether the user is in a dangerous situation.

[1025] 5. Generating and Sending Alerts

[1026] If a danger is detected, the server generates an appropriate warning message, which is then sent to the user via the communication module of the smart glasses, and displayed on the display of the smart glasses.

[1027] Specific examples

[1028] For example, when a user is walking down a dark street at night, the smart glasses collect ambient sounds (e.g., sudden footsteps from behind) and images (e.g., a person chasing the user). The emotion engine recognizes fear from the user's facial expression and detects sudden footsteps from the audio data. After comprehensively evaluating the situation, the server generates a warning message saying, "There may be someone behind you. Be careful of danger." This message is then displayed on the smart glasses' display.

[1029] Prompt Sentence Examples

[1030] "A user may hear a scream nearby, and their heart rate may suddenly increase, revealing a look of surprise on their face. From this data, we can analyze the user's emotions and determine whether danger exists."

[1031] This embodiment allows for analyzing emotion and environmental data in real time when a user faces a dangerous situation, and providing prompt and appropriate warnings.

[1032] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1033] Step 1:

[1034] The user puts on the smart glasses. The camera built into the glasses starts collecting video data, and the microphone starts collecting audio data. The heart rate sensor also continuously monitors the user's heart rate. This data is transmitted to the smart glasses terminal in real time.

[1035] Input: User wear, video data, audio data, heart rate data

[1036] Output: Real-time data collected

[1037] Step 2:

[1038] The device extracts the video data collected by the device frame by frame and performs facial and facial expression recognition using TensorFlow and Keras. At the same time, the audio data is analyzed using speech recognition software (e.g., DeepSpeech or Google Speech-to-Text API) to detect dangerous sounds (e.g., screaming, breaking glass). Heart rate data is monitored in real time to check for sudden increases or abnormal values.

[1039] Input: Real-time data collected

[1040] Output: Analyzed facial expression data, voice data, heart rate data

[1041] Step 3:

[1042] The server inputs the analyzed data into the emotion engine, which analyzes the user's emotional state. The emotion engine recognizes the user's emotions (e.g., surprise, fear, joy) based on facial expressions, heart rate, and voice data. This process uses deep learning models (e.g., Long Short-Term Memory, Convolutional Neural Network).

[1043] Input: Analyzed facial expression data, voice data, heart rate data

[1044] Output: Perceived emotional state

[1045] Step 4:

[1046] The server combines the results of the emotion engine's analysis and the results of the dangerous sound detection by the voice recognition software to evaluate whether the user is in a dangerous situation, and generates a warning message if necessary based on the evaluation results.

[1047] Input: Recognized emotional state, analysis results of speech data

[1048] Output: Risk assessment results, warning messages

[1049] Step 5:

[1050] The server generates a warning message and sends it to the smart glasses terminal, which visually displays the received message to the user. For example, a message such as "There may be someone behind you. Beware of danger" is displayed on the display.

[1051] Input: The generated warning message

[1052] Output: Warning message sent to terminal

[1053] Step 6:

[1054] The user checks the displayed message and takes appropriate action, such as looking around, walking faster, or moving to another street.

[1055] Input: The warning message displayed on the terminal

[1056] Output: User behavior change

[1057] 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.

[1058] 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.

[1059] 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.

[1060] [Fourth embodiment]

[1061] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1062] 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.

[1063] 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).

[1064] 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.

[1065] 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.

[1066] 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).

[1067] 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.

[1068] 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.

[1069] 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.

[1070] 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.

[1071] 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.

[1072] 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.

[1073] 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."

[1074] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[1075] The processing of the program in the system of the present invention will be explained in natural language below.

[1076] First, a user enters information required for a web form, such as their name, address, and email address, and clicks the submit button. The form-filling interface captures the input data into the terminal.

[1077] Next, the terminal converts the input data into JSON format and sends it to the server using an HTTP POST request. The JSON format data looks like this: { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}

[1078] The server receives the HTTP request sent from the device and analyzes the data sent. After analyzing, it verifies whether the data is valid. For example, it checks whether the email address format is correct and whether all required fields have been entered.

[1079] Data that passes verification is stored in a database by the server. The database serves to securely store registered user information. Based on this, the server performs additional processing. This additional processing may include sending email notifications or linking with other services.

[1080] The server generates a response message for the user based on the information stored in the database and the results of the additional processing. For example, it creates a message such as "Registration completed." This message is then sent to the terminal again as an HTTP response.

[1081] The terminal receives the HTTP response from the server and analyzes the response data. The analyzed data is displayed on the user interface, and a message stating "Registration completed" is displayed to the user. In this way, data transmission, reception, and processing in the system of the present invention are completed.

[1082] The processing flow will be explained below.

[1083] Step 1:

[1084] A user fills in a web form with required information, such as name, address, and email address, and clicks the submit button, at which point the user's input data is captured in the form interface.

[1085] Step 2:

[1086] The device converts the user's input data into JSON format (e.g., { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}) and sends the data to the server using an HTTP POST request.

[1087] Step 3:

[1088] The server receives the HTTP request from the device and parses the JSON data sent. The server extracts the contents of the request body and each field (name, address, email address, etc.).

[1089] Step 4:

[1090] Validate the data received by the server, specifically checking that email addresses are formatted correctly and that required fields are not missing (for example, that email addresses are in username@domain.com format).

[1091] Step 5:

[1092] The server saves the data that passes validation to the database, storing the name, address, and email address as a new user record in the appropriate tables.

[1093] Step 6:

[1094] The server performs additional processing based on the information stored in the database. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a confirmation email stating "Registration completed" to the user's email address.

[1095] Step 7:

[1096] The server generates a response message for the user based on the results of the addition process. It creates a message stating "Registration completed" and generates this as response data.

[1097] Step 8:

[1098] The server generates a response message and sends it to the terminal as an HTTP response, which includes a success message and additional information.

[1099] Step 9:

[1100] The device receives the HTTP response from the server, analyzes the response body, and extracts the message "Registration completed."

[1101] Step 10:

[1102] The terminal displays the analyzed message on the user interface, and the user can see the message "Registration completed" on the browser.

[1103] Example 1

[1104] 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."

[1105] Existing systems require manual intervention to validate and store data entered by users, resulting in issues with speed and accuracy. Data transmission and reception also requires security and efficiency. Furthermore, there is a lack of a way to quickly and accurately communicate the results of additional processing to users. Therefore, there is a need to automate data processing and transmission while improving user convenience.

[1106] 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.

[1107] In this invention, the server includes an analysis and verification means, a storage means for storing data in a storage device, and a means for performing additional processing, thereby enabling accurate analysis and verification of data, efficient storage, and rapid additional processing.

[1108] An "interface means" is a combination of an input device and software for a user to provide input.

[1109] "Terminal means" refers to a combination of a device and software that has the function of receiving user input data and transmitting it to a communication device.

[1110] "Communication device" refers to a server or network device that receives data sent from a terminal means and further analyzes and verifies it.

[1111] "Analysis and verification means" refers to a combination of software and hardware that has the function of analyzing the contents of received data and checking for errors in format and content.

[1112] "Storage device" refers to a database and storage device for storing analyzed and verified data.

[1113] "Further processing means" is a combination of software and hardware that performs further processing on stored data to generate new results or information.

[1114] The "means for generating a message" is a combination of software and hardware that has the function of creating an appropriate message for the user based on the results of the additional processing.

[1115] A "data interchange format" is a format for expressing data in a unified format, such as JSON or XML.

[1116] A "data exchange protocol" is a protocol that defines the communication methods and rules for sending and receiving data, and examples of this include HTTP and HTTPS.

[1117] The present invention is a system including an interface means for user input, a terminal means for transmitting the input data to a server, a means for analyzing and verifying the data received by the server, a means for storing the analyzed and verified data in a storage device, a means for performing additional processing based on the stored data, a means for generating a message to respond to the user with the result of the additional processing, a means for transmitting the generated message to the terminal, and a means for displaying the message received by the terminal to the user.

[1118] First, a user inputs necessary information into a web form through a web browser. This form input interface is for accepting user input data, and includes basic information such as name, address, and email address.

[1119] Next, the terminal converts the input data into a data exchange format (e.g., JSON) and sends it to the server using an HTTP request. The software used by the terminal could be the JavaScript fetch API. For example, if a user inputs their name as "Yamada Taro," their address as "Tokyo," and their email address as "yamada@example.com," the terminal converts this into JSON format and sends it to the server.

[1120] The server receives the HTTP request sent from the device using web server software such as Apache or Nginx. The received data is parsed and validated using, for example, the Python Django framework, to check whether the email address is formatted correctly and whether all required fields have been filled in. Validation is performed using regular expressions, for example.

[1121] Data that passes the verification is stored by the server in a storage device (e.g., an SQL database), which is used to maintain the reliability and integrity of the data, and databases such as MySQL or PostgreSQL are used.

[1122] The server then performs additional processing based on the stored data, such as sending email notifications to users or integrating with other services, using the Python smtplib library to send a registration confirmation email.

[1123] Finally, the server generates a message to respond to the user. The generated message is created in JSON format, and has the content, for example, "Registration completed." This message is sent to the terminal as an HTTP response.

[1124] The terminal receives the HTTP response from the server, analyzes the response data, and displays it on the user interface. For example, the terminal performs the analysis using JavaScript and displays a message to the user such as "Registration completed."

[1125] Prompt Sentence Examples

[1126] Please provide a detailed explanation of the steps to implement a system that sends data entered by a user into a web form to a server, where it is parsed, validated, and stored in a database. The system then performs additional processing and displays a response message to the user. Please also specify the specific hardware and software used, as well as the method of data processing.

[1127] This automates the sending, receiving, and processing of data throughout the system and provides an easy-to-use interface for users.

[1128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1129] Step 1:

[1130] A user inputs the required information into a web form. For example, the user inputs the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com." This input data is imported into the terminal through the form input interface of the web browser. The input data is obtained in text format for processing on the terminal.

[1131] Step 2:

[1132] The device converts the input data into JSON format and sends it to the server using an HTTP POST request. Specifically, it uses the JavaScript fetch API to convert the text data into JSON format data { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"} and generates output. This data is sent to the specified URL.

[1133] Step 3:

[1134] The server receives HTTP requests sent from the terminal using web server software such as Apache or Nginx. JSON format data is given as input. The received data is analyzed using the Python Django framework, and the text data is converted into a dictionary format and output.

[1135] Step 4:

[1136] The server verifies whether the received data is valid. Validation involves checking the format of the email address and whether any required fields are present. For example, the email address is validated using the Python regular expression library "re" to ensure there are no omissions or errors. If the data is valid, the server proceeds to the next step; if it is invalid, an error message is generated and output.

[1137] Step 5:

[1138] Once the data passes validation, it is saved to a storage device (e.g., an SQL database) by the server. The input data remains in dictionary format and is converted to SQL commands using Django models. The output includes the save completion status and the ID of the saved record.

[1139] Step 6:

[1140] The server performs additional processing based on the stored data. This additional processing can include sending email notifications or connecting with external services. For example, it uses the Python smtplib library to send a registration confirmation email to the entered email address. Here, the status of the email sending process is output.

[1141] Step 7:

[1142] The server generates a response message for the user based on the results of the additional processing. For example, it creates a message saying "Registration completed" and converts it into JSON-formatted response data. This generated message is output.

[1143] Step 8:

[1144] The server sends the generated response message to the terminal as an HTTP response, and then executes a process to return the output JSON format message data as an HTTP response.

[1145] Step 9:

[1146] The terminal receives the HTTP response from the server and analyzes the response data. The response data is given in JSON format as input. JavaScript is used to analyze the response data and display a message such as "Registration completed" on the user interface. The message displayed to the user as a result of this process is the final output.

[1147] (Application example 1)

[1148] 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."

[1149] In recent years, robots and machinery have been used to automate and streamline factories, but issuing appropriate operating instructions to these machines has been a difficult challenge. In particular, when users manually input instructions into the machines, input errors and delays are likely to occur, potentially reducing production efficiency. Furthermore, the lack of a mechanism for instantly verifying the content of operating instructions and updating the machines in real time complicates factory management. An effective system that can solve these problems and support automation within factories is needed.

[1150] 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.

[1151] In this invention, the server includes an operation means for user input, a device means for transmitting the input data to the server, a means for analyzing and verifying the data received by the server, a means for saving the analyzed and verified data in a data storage device, a means for performing additional processing based on the saved data, a means for generating a notification message for responding to the user with the result of the additional processing, a means for sending the generated notification message to the device, a means for displaying the notification message received by the device to the user, and an instruction means for issuing operation instructions to machinery in the factory as part of the additional processing. This makes it possible to issue appropriate operation instructions to machinery in the factory in real time, preventing input errors and operation delays and improving production efficiency.

[1152] "Operation means" refers to an interface through which a user inputs data and instructions.

[1153] "Device means" refers to a terminal device for transmitting input data to a server.

[1154] "Means for analysis and verification" refers to the function for analyzing the data received by the server and verifying its validity and accuracy.

[1155] "Data Storage Device" refers to the database within the system for storing analyzed and validated data.

[1156] "Means for further processing" refers to mechanisms for performing further processing based on the stored data.

[1157] The "means for generating a notification message" refers to a function for creating a message to notify the user of the result of the additional processing.

[1158] The "means for sending to the device" refers to a communication means for sending the generated notification message to the user's terminal.

[1159] The "means for displaying" refers to a function for visually displaying to the user the notification message received by the terminal.

[1160] "Instruction means" refers to a function for sending and managing operation instructions to machinery and devices within a factory.

[1161] The present invention is a system in which data entered by a user using an operation means is sent to a server via a device means, and the server analyzes and verifies the data and stores it in an appropriate data storage device.Furthermore, the system performs additional processing based on the stored data, generates a notification message of the results, and sends it again to the user's device means so that the user can check it.

[1162] To realize this invention, a user first inputs a work instruction using the operation means. For example, the user inputs "Please start assembly work on line 1" as an operation instruction for a machine in a factory. This input data is converted into JSON format by the device means and sent to the server using an HTTP POST request.

[1163] The server analyzes the data it receives and verifies its validity and accuracy. For example, it checks that work instructions are entered in the correct format and contain all the required information. This can be done using a web framework such as Flask. The server then securely stores the data in a data store and performs further processing based on the stored data.

[1164] As an additional process, for example, to execute an operation instruction for a machine in a factory, the server sends an instruction to the machine in real time via the instruction means. Based on the result of this instruction, the server generates a notification message for the user. For example, it creates a message such as "Assembly work on line 1 has started" and sends it again to the machine means.

[1165] The device receives notification messages from the server, analyzes them, and displays them on the user interface, allowing the user to confirm that the instructions were executed correctly. Through this series of processes, work efficiency within the factory can be improved and input errors and operational delays can be prevented.

[1166] An example of a specific prompt is as follows:

[1167] "Please begin assembly work on Line 1."

[1168] In this way, the present invention makes it possible to efficiently and accurately execute operating instructions for machinery in a factory, dramatically improving production efficiency.

[1169] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1170] Step 1:

[1171] The user inputs work instructions using the operating means. The input contents include the work target, work content, start time, etc. For example, the user inputs an instruction such as "Please start assembly work on line 1." This information is captured in the operating means.

[1172] Step 2:

[1173] The terminal means converts the data input by the user into JSON format. For example, the input instruction is converted into the following JSON format:

[1174] {

[1175] "line": "Line 1",

[1176] "task": "assembly work",

[1177] "action": "start"

[1178] }

[1179] This JSON data is converted into an HTTP POST request format and sent to the server. The input is a text-formatted work instruction, and the output is JSON-formatted data.

[1180] Step 3:

[1181] The server receives the HTTP POST request from the terminal and analyzes the contents. The analysis reads the JSON data and verifies the data format and content. For example, it checks whether "line" is empty, whether "task" is an allowed operation, and whether "action" is a valid instruction. The input is JSON format data, and the output is the verification result after analysis.

[1182] Step 4:

[1183] The server stores the data that passes validation in a data storage device (database). The stored data includes the user's instructions and a timestamp, allowing for future reference and additional processing. The input is the analyzed and validated data, and the output is the record stored in the database.

[1184] Step 5:

[1185] The server performs additional processing based on the data stored in the data storage device. Specifically, it sends operational instructions based on user input to machinery in the factory in real time. The instructions are sent to the machinery using the necessary protocols and communication methods. The input is the stored data, and the output is the operational instructions sent to the machinery.

[1186] Step 6:

[1187] The server receives responses and operation results from the machine and generates a message to notify the user. For example, it generates a message saying, "Assembly work on line 1 has started." This message is converted back to JSON format and sent to the terminal means. The input is the operation result from the machine, and the output is the generated notification message.

[1188] Step 7:

[1189] The terminal means analyzes the notification message received from the server and displays it on the user interface. This allows the user to confirm that their instructions have been executed correctly. For example, the terminal may display a message saying, "Assembly work on line 1 has started." The input is the notification message from the server, and the output is the confirmation message displayed on the user interface.

[1190] 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.

[1191] The present invention is a system that efficiently processes user input data and further combines it with an emotion engine that recognizes the user's emotions. Below, the program processing in the system of the present invention will be specifically explained in natural language.

[1192] First, a user enters necessary information into a web form, such as name, address, and email address. For example, the user enters the name "Yamada Taro," the address "Tokyo," and the email address "yamada@example.com," and clicks the submit button. The input data is then imported into the form interface.

[1193] Next, the terminal converts the input data into JSON format. The converted JSON data is in the format { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com"}. The terminal sends this data to the server in the form of an HTTP POST request.

[1194] The server receives the HTTP request sent from the terminal and parses the JSON data. The server extracts the name, address, and email address fields from the request body and parses and validates the received data. Here, it checks whether the email address format is correct and whether all required fields have been entered.

[1195] After the server has verified the received data, it stores it in the database, which records the new user's information and makes it available for further processing.

[1196] Next, the server performs additional processing based on the stored data. For example, it sends a confirmation email based on the user information stored in the database. The server calls the API of the email service and sends a registration completion email to "yamada@example.com."

[1197] Furthermore, as a feature of the present invention, the server uses an emotion engine to recognize emotions from the user's input data. For example, if the user inputs a comment such as "I'm so happy!", the emotion engine will identify the user's emotion as "joy." Then, it will create an appropriate message according to the emotion.

[1198] The server generates a response message for the user based on the results of the emotion engine and additional processing. In addition to the basic message "Registration completed," it adds a message according to the emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[1199] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed on the user interface, and a response such as "Registration completed. Your joy has been conveyed" is displayed to the user.

[1200] This allows the system of the present invention to efficiently process user input data and provide responses that recognize and reflect the user's emotions, improving the user experience and enabling more personalized services.

[1201] The processing flow will be explained below.

[1202] Step 1:

[1203] A user enters their name, address, email address, and free-form comments into a web form and clicks the submit button. For example, the user enters the name "Taro Yamada," the address "Tokyo," the email address "yamada@example.com," and the comment "This site is great!"

[1204] Step 2:

[1205] The device converts the user's input data into JSON format. The converted JSON data becomes { "name": "Yamada Taro", "address": "Tokyo", "email": "yamada@example.com", "comment": "This site is great!"} The device sends this data to the server in the form of an HTTP POST request.

[1206] Step 3:

[1207] The server receives the HTTP request sent from the device and parses the JSON data. The server extracts the name, address, email address, and comment fields from the request body.

[1208] Step 4:

[1209] The server validates the incoming data, specifically checking that the email address is formatted correctly and that all required fields are filled in. For example, making sure the email address is in the format username@domain.com.

[1210] Step 5:

[1211] The server saves the data that passes validation to the user database, storing the name, address, email address, and comments as a new user record.

[1212] Step 6:

[1213] The server uses the stored data to perform additional processing. For example, it sends a confirmation email. The server calls the API of the email service and sends an email to "yamada@example.com" stating "Registration completed."

[1214] Step 7:

[1215] The server uses an emotion engine to recognize emotions from comments entered by users. For example, the comment "This site is great!" is analyzed and the emotion engine identifies it as "joy."

[1216] Step 8:

[1217] The server generates an appropriate response message for the user based on the emotion recognized by the emotion engine, for example, "Your registration is complete. We feel your joy."

[1218] Step 9:

[1219] The server generates a response message and sends it to the terminal. The message "Registration completed. Your joy has been conveyed" is sent to the terminal in the form of an HTTP response.

[1220] Step 10:

[1221] The device receives the HTTP response from the server and parses the response body, extracting the message "Registration completed. Your joy was conveyed."

[1222] Step 11:

[1223] The terminal displays the analyzed response message on the user interface, and the user can see the message "Registration completed. Your joy has been conveyed" on the browser.

[1224] Example 2

[1225] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1226] Previous systems simply received and stored user input data, but were unable to identify user sentiment and reflect it in response messages. This resulted in a lack of improved user experience and made it difficult to provide personalized services. Furthermore, there was a lack of efficient means for validating and storing data, increasing the risk of inaccurate data and errors.

[1227] 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.

[1228] In this invention, the server includes a means for analyzing and verifying received data, a means for storing the analyzed and verified data in a database, a means for performing additional processing based on the stored data, a means for performing emotion analysis as the additional processing, and a means for generating a response message based on the emotion analysis results. This enables the generation of personalized messages that reflect the user's emotions. Furthermore, the accuracy and completeness of the data can be ensured, improving overall system efficiency.

[1229] "User" refers to a person or end user who uses the system.

[1230] "Interface means" refers to the means by which a user inputs data into the system, including web forms and input fields.

[1231] "Terminal means" refers to devices and software for transmitting user input data to a server, and includes personal computers and smartphones.

[1232] "Server" refers to the central computer system that receives, analyzes, and verifies data sent by users.

[1233] "Means for analyzing and verifying received data" refers to the algorithms or programs that analyze the data received by the server and check its accuracy and completeness.

[1234] "Means of storing data in a database" includes systems and methods for permanently storing analyzed and verified data.

[1235] "Means for performing additional processing" refers to programs or algorithms for performing further necessary processing on the stored data.

[1236] "Means for performing emotion analysis" refers to the engine or algorithm used to identify and analyze emotions from user input data.

[1237] "Means for generating a response message" refers to a program or algorithm that allows the system to generate a message to be sent back to the user.

[1238] "Means for sending a message to a terminal" includes any system or protocol for sending the generated response message to the user's terminal.

[1239] "Means for displaying to the user the message received by the terminal" refers to an interface or program for displaying on the screen of the user's terminal the message received from the server.

[1240] This invention is a system that efficiently processes user input data and recognizes and reflects the user's emotions. This system comprises a user interface using a web form, a terminal that sends input data to a server, a server that analyzes and verifies the received data, a database, an emotion analysis engine, and a function for generating and sending response messages.

[1241] First, a user enters information such as their name, address, and email address using a web form. The web form is implemented using HTML and JavaScript. For example, a user enters "Name: Yamada Taro," "Address: Tokyo," and "Email address: yamada@example.com," and then clicks the submit button.

[1242] Next, the terminal converts the input data into JSON format. Specifically, it serializes the JavaScript object into JSON format. This converted data looks like this:

[1243] json

[1244] {

[1245] "name": "Yamada Taro",

[1246] "address": "Tokyo",

[1247] "email": "yamada@example.com"

[1248] }

[1249] The device sends this JSON data to the server as an HTTP POST request, using HTTPS as the communication protocol.

[1250] The server receives this HTTP request. The server is often implemented using Node.js or Python (Flask or Django). It parses the received JSON data and extracts each field, such as name, address, and email address. It then verifies that the data format is correct and that all required fields have been entered.

[1251] Once the verification is complete, the data is stored in a database, typically a relational database such as MySQL or PostgreSQL.

[1252] The server then performs additional processing based on the user information stored in the database. As part of this processing, the server calls a sentiment analysis engine (such as IBM Watson or Google Cloud Natural Language API) to analyze the emotion from the user's comment. For example, if a user enters the comment "I'm so happy!", the sentiment analysis engine will determine this emotion as "joy."

[1253] The server generates a response message for the user based on the results of the emotion analysis. In addition to the basic message "Registration completed," it adds a message according to the user's emotion, such as "Your joy was conveyed." This response message is then sent again to the device as an HTTP response.

[1254] The terminal receives the HTTP response from the server and analyzes the response body. The analyzed message is displayed in the user interface. For example, the response is displayed to the user in the form of "Registration completed. Your joy is conveyed."

[1255] As a concrete example, the same processing can be achieved by inputting the following prompt sentence into the generative AI model:

[1256] "Please explain how to convert the name, address, and email address entered by the user into JSON format and send it to the server."

[1257] "Please explain the steps to parse and validate the JSON data received by the server and save it to the database."

[1258] "Please explain how to determine the sentiment of the input comment and generate a response message accordingly."

[1259] The above is a specific embodiment for carrying out the present invention. This system can improve the user experience by providing a response that reflects the user's emotions.

[1260] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1261] The flow of this system's program processing

[1262] Step 1: User Input

[1263] A user enters name, address, and email information into a web form and clicks the submit button.

[1264] Input: Information entered by the user (name, address, email address)

[1265] Output: The input data is populated into the form interface

[1266] Specific actions

[1267] 1. The user opens a browser.

[1268] 2. Visit the website.

[1269] 3. Fill out the web form.

[1270] 4. Click the Send button.

[1271] Step 2: Convert data to JSON format and send it

[1272] The terminal receives the input data, converts it to JSON format, and sends it to the server in the form of an HTTP POST request.

[1273] Input: Information entered by the user (name, address, email address)

[1274] Data processing: Convert input data into JSON format using JavaScript etc.

[1275] Output: JSON format data is generated and sent to the server.

[1276] Specific actions

[1277] 1. Once the form is completed, the JavaScript code runs.

[1278] 2. The input data is converted to JSON format.

[1279] 3. The converted JSON data is sent to the server via an HTTP POST request.

[1280] Step 3: Data analysis and validation by the server

[1281] The server receives the HTTP request and parses and validates the JSON data.

[1282] Input: JSON data included in the body of the HTTP request

[1283] Data Calculation: Parse JSON data and extract name, address, and email address fields. Check email address format and required fields.

[1284] Output: Analyzed and validated data

[1285] Specific actions

[1286] 1. The server receives an HTTP request.

[1287] 2. Parse the JSON data in the request body.

[1288] 3. Extract names, addresses, and email addresses.

[1289] 4. Validate the data in each field (check email format, check required fields).

[1290] Step 4: Saving to the Database

[1291] The server stores the parsed and verified data in a database.

[1292] Input: Analyzed and validated data

[1293] Data processing: Generate and execute SQL queries to store data in a database

[1294] Output: Data is saved to the database

[1295] Specific actions

[1296] 1. Map the validated data to database objects.

[1297] 2. Execute a SQL query to insert data into the database.

[1298] 3. After the insert is complete, you receive a response from the database.

[1299] Step 5: Send a confirmation email

[1300] The server uses the email service API to send a confirmation email based on the stored data.

[1301] Input: User information stored in the database

[1302] Data operation: Call the email service API and pass the email content and recipient address.

[1303] Output: A confirmation email is sent to the user.

[1304] Specific actions

[1305] 1. The server calls the email sending API.

[1306] 2. Pass the email content and recipient address to the API.

[1307] 3. The email is sent and a response is received from the API.

[1308] Step 6: Emotion Recognition

[1309] The server uses an emotion analysis engine to recognize emotions from the user's input data.

[1310] Input: User comment data

[1311] Data calculation: Send comments to a sentiment analysis engine to analyze sentiment

[1312] Output: Emotion analysis results

[1313] Specific actions

[1314] 1. Send user comment data to a sentiment analysis engine.

[1315] 2. The sentiment analysis engine analyzes the comments and determines their sentiment.

[1316] 3. The result of the judgment is returned to the server.

[1317] Step 7: Generate and send a response message

[1318] The server generates a response message based on the emotion analysis result and the basic message, and sends it to the terminal.

[1319] Input: Sentiment analysis results, information stored in the database

[1320] Data calculation: Generate a response message based on the above data

[1321] Output: A response message is sent to the terminal

[1322] Specific actions

[1323] 1. Generate a response message based on the emotion results.

[1324] 2. Include the response message in the HTTP response.

[1325] 3. Send the HTTP response to the device.

[1326] Step 8: Displaying Messages

[1327] The terminal analyzes the HTTP response received from the server and displays a message on the user interface.

[1328] Input: HTTP response received from the server

[1329] Data operation: Parse the HTTP response body and extract the message

[1330] Output: A message is displayed to the user

[1331] Specific actions

[1332] 1. Receive an HTTP response.

[1333] 2. Parse the JSON data in the response body.

[1334] 3. The parsed message is displayed on the screen in HTML format.

[1335] The above is the specific flow of processing of the program in this system.

[1336] (Application example 2)

[1337] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1338] While conventional systems can efficiently process data entered by users, they have difficulty analyzing the user's emotional state and taking appropriate measures based on that emotion. Furthermore, particularly in the security field, it has been difficult to determine in real time whether a user is in a dangerous situation and respond immediately. To solve this problem and ensure user safety more reliably, a system is needed that analyzes the user's emotions and surrounding audio and video data to assess danger.

[1339] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion engine means for analyzing the user's emotional state, means for collecting and analyzing surrounding audio and video data, and means for assessing danger and issuing a warning based on the emotional state. This not only analyzes the data entered by the user, but also monitors the user's emotional state in real time and comprehensively evaluates information obtained from the surrounding environment, making it possible to immediately issue a warning if the user is in danger.

[1340] An "interface means" is a means by which a user inputs data into a system.

[1341] The "terminal means" is a means for transmitting data input by a user to a server.

[1342] "Means for analysis and verification" refers to the means by which the server analyzes the data received and checks the accuracy of the data and whether there are any errors.

[1343] "Means of storage" refers to the means for recording analyzed and verified data in a database.

[1344] "Means for performing additional processing" refers to means for performing further processing based on the stored data.

[1345] "Emotion engine means" means that uses an engine to analyze the emotional state of a user.

[1346] The "means for generating a message" is a means for generating an appropriate response message based on the analysis result.

[1347] "Means for collecting and analyzing" refers to means for collecting and analyzing surrounding audio and video data.

[1348] The "means for assessing danger and issuing a warning" is a means for assessing whether the user is in a dangerous situation based on the user's emotional state and surrounding data, and issuing a warning as necessary.

[1349] The "means for sending" is a means for sending the generated message to the user's terminal.

[1350] The "display means" is a means for visually displaying to the user the message received by the terminal.

[1351] As an embodiment of the present invention, a security system can be constructed that uses smart glasses worn by a user to analyze emotional states and surrounding environmental data in real time. This system is realized using the following hardware and software.

[1352] 1. Hardware

[1353] Smart glasses: built-in camera, microphone, and heart rate sensor

[1354] Server: Data processing and emotion engine execution

[1355] Communication module: Data transfer between smart glasses and server

[1356] 2. Software

[1357] Emotion engine (e.g. TensorFlow, Keras): Analyzes the user's facial expressions and heart rate data

[1358] Voice recognition software: Analyzes surrounding audio data and detects dangerous sounds

[1359] Database (e.g. MySQL, PostgreSQL): Stores user data and analysis results

[1360] Message Generation Algorithm: Create appropriate warning messages

[1361] Detailed explanation of program processing

[1362] 1. Data collection

[1363] Once the user puts on the smart glasses, the camera and microphone begin working, and the heart rate sensor also continuously monitors the heart rate.

[1364] 2. Data Preprocessing

[1365] The smart glasses extract the collected video data frame by frame and perform facial and facial expression recognition, using deep learning models such as TensorFlow and Keras.

[1366] The audio data is analyzed by voice recognition software to detect dangerous sounds (e.g., screaming, breaking glass).

[1367] 3. Operation of the Emotion Engine

[1368] The server inputs the user's facial expressions and heart rate data into an emotion engine to analyze the user's emotional state. For example, TensorFlow and Keras can be used to recognize emotions from micro-expressions.

[1369] 4. Risk Assessment

[1370] Based on the emotional state (e.g., surprise, fear) recognized by the emotion engine and the dangerous sounds detected by the voice recognition software, the server assesses whether the user is in a dangerous situation.

[1371] 5. Generating and Sending Alerts

[1372] If a danger is detected, the server generates an appropriate warning message, which is then sent to the user via the communication module of the smart glasses, and displayed on the display of the smart glasses.

[1373] Specific examples

[1374] For example, when a user is walking down a dark street at night, the smart glasses collect ambient sounds (e.g., sudden footsteps from behind) and images (e.g., a person chasing the user). The emotion engine recognizes fear from the user's facial expression and detects sudden footsteps from the audio data. After comprehensively evaluating the situation, the server generates a warning message saying, "There may be someone behind you. Be careful of danger." This message is then displayed on the smart glasses' display.

[1375] Prompt Sentence Examples

[1376] "A user may hear a scream nearby, and their heart rate may suddenly increase, revealing a look of surprise on their face. From this data, we can analyze the user's emotions and determine whether danger exists."

[1377] This embodiment allows for analyzing emotion and environmental data in real time when a user faces a dangerous situation, and providing prompt and appropriate warnings.

[1378] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1379] Step 1:

[1380] The user puts on the smart glasses. The camera built into the glasses starts collecting video data, and the microphone starts collecting audio data. The heart rate sensor also continuously monitors the user's heart rate. This data is transmitted to the smart glasses terminal in real time.

[1381] Input: User wear, video data, audio data, heart rate data

[1382] Output: Real-time data collected

[1383] Step 2:

[1384] The device extracts the video data collected by the device frame by frame and performs facial and facial expression recognition using TensorFlow and Keras. At the same time, the audio data is analyzed using speech recognition software (e.g., DeepSpeech or Google Speech-to-Text API) to detect dangerous sounds (e.g., screaming, breaking glass). Heart rate data is monitored in real time to check for sudden increases or abnormal values.

[1385] Input: Real-time data collected

[1386] Output: Analyzed facial expression data, voice data, heart rate data

[1387] Step 3:

[1388] The server inputs the analyzed data into the emotion engine, which analyzes the user's emotional state. The emotion engine recognizes the user's emotions (e.g., surprise, fear, joy) based on facial expressions, heart rate, and voice data. This process uses deep learning models (e.g., Long Short-Term Memory, Convolutional Neural Network).

[1389] Input: Analyzed facial expression data, voice data, heart rate data

[1390] Output: Perceived emotional state

[1391] Step 4:

[1392] The server combines the results of the emotion engine's analysis and the results of the dangerous sound detection by the voice recognition software to evaluate whether the user is in a dangerous situation, and generates a warning message if necessary based on the evaluation results.

[1393] Input: Recognized emotional state, analysis results of speech data

[1394] Output: Risk assessment results, warning messages

[1395] Step 5:

[1396] The server generates a warning message and sends it to the smart glasses terminal, which visually displays the received message to the user. For example, a message such as "There may be someone behind you. Beware of danger" is displayed on the display.

[1397] Input: The generated warning message

[1398] Output: Warning message sent to terminal

[1399] Step 6:

[1400] The user checks the displayed message and takes appropriate action, such as looking around, walking faster, or moving to another street.

[1401] Input: The warning message displayed on the terminal

[1402] Output: User behavior change

[1403] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1404] 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.

[1405] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1406] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1407] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1408] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1409] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1410] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1411] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1412] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1413] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1414] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1415] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1416] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1417] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1418] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1419] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1420] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1421] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1422] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1423] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1424] The following is further disclosed regarding the above embodiment.

[1425] (Claim 1)

[1426] an interface means for user input;

[1427] a terminal means for transmitting input data to a server;

[1428] A means for parsing and validating the data received by the server;

[1429] A means for storing the analyzed and verified data in a database;

[1430] means for performing additional processing based on the stored data;

[1431] means for generating a message to respond to a user of the result of the additional processing;

[1432] means for transmitting the generated message to a terminal;

[1433] means for displaying to a user messages received by the terminal;

[1434] A system including:

[1435] (Claim 2)

[1436] The system according to claim 1, characterized in that the input data is converted into JSON format and transmitted as an HTTP request.

[1437] (Claim 3)

[1438] 10. The system of claim 1, further comprising means for the server to validate the received data to ensure there are no omissions or errors.

[1439] "Example 1"

[1440] (Claim 1)

[1441] an interface means for user input;

[1442] a terminal means for transmitting input data to a communication device;

[1443] means for analyzing and verifying data received by the communication device;

[1444] A means for storing the analyzed and verified data in a storage device;

[1445] means for performing additional processing based on the stored data;

[1446] means for generating a message to respond to a user of the result of the additional processing;

[1447] means for transmitting the generated message to a terminal;

[1448] means for displaying to a user messages received by the terminal;

[1449] A system including:

[1450] (Claim 2)

[1451] 2. The system according to claim 1, wherein input data is converted into a data exchange format and transmitted as a data exchange protocol.

[1452] (Claim 3)

[1453] 10. The system of claim 1, further comprising means for validating data received by the communication device to ensure there are no omissions or errors.

[1454] "Application Example 1"

[1455] (Claim 1)

[1456] an operation means for a user to input;

[1457] device means for transmitting input data to a server;

[1458] A means for parsing and validating the data received by the server;

[1459] A means for storing the analyzed and verified data in a data storage device;

[1460] means for performing additional processing based on the stored data;

[1461] means for generating a notification message to respond to a user of the result of the additional processing;

[1462] means for transmitting the generated notification message to the device;

[1463] means for displaying to a user notification messages received by the device;

[1464] an instruction means for issuing an operation instruction to a machine in a factory as part of the additional processing;

[1465] A system including:

[1466] (Claim 2)

[1467] The system according to claim 1, characterized in that the input data is converted into JSON format and transmitted as an HTTP request.

[1468] (Claim 3)

[1469] 10. The system of claim 1, further comprising means for the server to validate the received data to ensure there are no omissions or errors.

[1470] "Example 2: Combining Emotion Engines"

[1471] (Claim 1)

[1472] an interface means for user input;

[1473] a terminal means for transmitting input data to a server;

[1474] A means for parsing and validating the data received by the server;

[1475] A means for storing the analyzed and verified data in a database;

[1476] means for performing additional processing based on the stored data;

[1477] means for performing sentiment analysis as an additional process;

[1478] A means for generating a response message based on the emotion analysis result;

[1479] means for transmitting the generated message to a terminal;

[1480] means for displaying to a user messages received by the terminal;

[1481] A system including:

[1482] (Claim 2)

[1483] The system according to claim 1, characterized in that the input data is converted into JSON format and transmitted as an HTTP request.

[1484] (Claim 3)

[1485] 10. The system of claim 1, further comprising means for the server to validate the received data to ensure there are no omissions or errors.

[1486] "Application example 2 when combining emotion engines"

[1487] (Claim 1)

[1488] an interface means for user input;

[1489] a terminal means for transmitting input data to a server;

[1490] A means for parsing and validating the data received by the server;

[1491] A means for storing the analyzed and verified data in a database;

[1492] means for performing additional processing based on the stored data;

[1493] emotion engine means for analyzing the user's emotional state;

[1494] means for generating an appropriate message based on the user's emotions;

[1495] means for transmitting the generated message to a terminal;

[1496] means for displaying to a user messages received by the terminal;

[1497] A means of collecting and analyzing surrounding audio and video data;

[1498] a means for assessing and warning about danger based on emotional state;

[1499] A system including:

[1500] (Claim 2)

[1501] The system according to claim 1, characterized in that the input data is converted into JSON format and transmitted as an HTTP request.

[1502] (Claim 3)

[1503] 10. The system of claim 1, further comprising means for the server to validate the received data to ensure there are no omissions or errors. [Explanation of symbols]

[1504] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an interface means for user input; a terminal means for transmitting input data to a server; A means for analyzing and validating the data received by the server; A means of storing the analyzed and verified data in a database; means for performing additional processing based on the stored data; means for generating a message to respond to a user of the result of the additional processing; means for transmitting the generated message to a terminal; means for displaying to a user messages received by the terminal; A system including:

2. The system according to claim 1, wherein input data is converted into JSON format and transmitted as an HTTP request.

3. 10. The system of claim 1, further comprising means for the server to validate the data received to ensure there are no omissions or errors.

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