system

Abstract

Provide a system. An input means for a user to input details of a product or service and desired conditions through a terminal; a transmitting means for transmitting input data from the terminal to the server; a data processing means for analyzing the data received by the server and retrieving price information from a database; a price calculation means for calculating a total price based on the price information acquired by the server; a result generation means for the server to convert the calculation result into well-formed response data and return it to the terminal; a display means for displaying the estimate result received by the terminal to the user; A system including:

Description

[Technical Field]

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

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

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

[0004] In modern business negotiations, it is necessary to provide a quote quickly at the proposal stage, but existing systems require users to go through a complicated process, making it difficult to obtain a quote immediately. This situation hinders the efficient progress of business negotiations. Therefore, a system that allows users to easily and quickly obtain a quote at the proposal stage is needed. [Means for solving the problem]

[0005] The present invention solves the above problem by providing a system that includes an input means for a user to input product or service details and desired conditions via a terminal, a transmission means for the terminal to transmit the input data to a server, a data processing means for the server to analyze the received data and obtain price information from a database, a price calculation means for calculating the total price based on the price information obtained by the server, a result generation means for the server to convert the calculation results into well-formed response data and return it to the terminal, and a display means for displaying the estimate results received by the terminal to the user.

[0006] With this system, data entered by the user is instantly sent to the server, where it is analyzed and the price calculated, resulting in a prompt quotation.In addition, since price information is retrieved from the database and price calculations are performed automatically, the system is easy for users to operate and ensures the accuracy of the quotation.

[0007] "Terminal" refers to an electronic device that a user operates and that transmits input data to a server.

[0008] "Server" refers to the computer system that receives and analyzes data sent from the terminal, interacts with the database, and performs price calculations and generates results.

[0009] "User" refers to an individual or corporation that inputs detailed information about a product or service and desired conditions into a terminal.

[0010] "Input means" refers to an interface that allows a user to input information about a product or service through a terminal.

[0011] "Transmission means" refers to a part that has a function for transmitting data input from the terminal to the server.

[0012] "Data processing means" refers to the part that has the function of analyzing the data received by the server and retrieving price information from the database.

[0013] The "price calculation means" refers to the part that has the function of calculating the total price based on the price information acquired by the server.

[0014] The "result generation means" refers to a part that has the function of generating calculation results as well-formed data by the server and returning them to the terminal.

[0015] The "display means" refers to an interface for visually displaying to the user the estimate results received by the terminal from the server.

[0016] "Database" refers to an electronic storage medium that stores price information such as the base price and option prices of a product and that is referenced by a server.

[0017] "Quote result" refers to the total price information calculated by the server and returned to the terminal.

[0018] "JSON format" is a text format for expressing data simply and lightly, and refers to the format used for data exchange between servers and terminals. [Brief explanation of the drawings]

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

[0020] 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.

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

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

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

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0034] 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.

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

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The present invention relates to an instant quotation system that allows users to quickly obtain a quotation at the proposal stage. This system has a terminal, a server, and a database, and automatically generates a quotation when the user inputs detailed information about a product or service.

[0041] System configuration

[0042] 1. Terminal: A device operated by the user that displays input forms and receives product and service information and desired conditions.

[0043] 2. Server: Receives input data, parses it, retrieves necessary pricing information from the database, performs calculations, and produces well-formed results.

[0044] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[0045] Program processing overview

[0046] User Actions

[0047] The user enters information such as product name, quantity, options, etc. on the terminal and clicks the "Submit" button. For example, if the user wants a quote for "3 units of product A" and "1 unit of option B," they enter these details.

[0048] Terminal handling

[0049] The device converts the information entered by the user into JSON format data, which is then sent to the server as an HTTP POST request. A specific example of JSON data is as follows:

[0050] json

[0051] {

[0052] "Product Name": "Product A",

[0053] "Quantity": 3,

[0054] "options": {

[0055] "Option B": 1

[0056] }

[0057] }

[0058] Server Processing

[0059] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. It then calculates the total price. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, it performs the following calculation:

[0060] Total price of product A: 1,000 yen 3 = 3,000 yen

[0061] Total price of Option B: 500 yen 1 = 500 yen

[0062] Total amount: 3000 yen + 500 yen = 3500 yen

[0063] The server converts the calculation result into well-formed response data and sends it back to the device. The response data has the following format:

[0064] json

[0065] {

[0066] "Total amount": "3500 yen"

[0067] }

[0068] Displaying the results

[0069] The terminal analyzes the response data received from the server and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen" on the screen.

[0070] Specific example explanation

[0071] For example, consider a situation where a user wants to order three units of "Item A" and one unit of "Option B" and would like a quote. The user enters these details on the device and hits the submit button to request a quote. The device sends the data to the server, which parses the data and retrieves the price of each item from a database. The server performs the calculations and sends them back to the device. Finally, the user can quickly see the quote results.

[0072] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, enabling efficient sales activities.

[0073] The processing flow will be explained below.

[0074] Step 1:

[0075] The user accesses the input form on the device and enters detailed product information such as the product name, quantity, options, etc. For example, three "product A"s and one "option B" are entered.

[0076] Step 2:

[0077] The user clicks the "Submit" button on the input form, which causes the information entered by the user to be collected by the device.

[0078] Step 3:

[0079] The terminal converts the data entered by the user into JSON format. For example, the following JSON data is generated:

[0080] json

[0081] {

[0082] "Product Name": "Product A",

[0083] "Quantity": 3,

[0084] "options": {

[0085] "Option B": 1

[0086] }

[0087] }

[0088] Step 4:

[0089] The device sends an HTTP POST request containing the generated JSON data to the server.

[0090] Step 5:

[0091] The server receives an HTTP POST request, parses the received data, and converts the JSON formatted data into an internal format.

[0092] Step 6:

[0093] The server sends a query to the database to obtain the unit price of "Product A" (1,000 yen) and the unit price of "Option B" (500 yen).

[0094] Step 7:

[0095] The server calculates the user's order based on the price information it has obtained. Specifically, it performs the following calculations:

[0096] Total price of product A: 1000 yen 3 = 3000 yen

[0097] Total price of Option B: 500 yen 1 = 500 yen

[0098] Total amount: 3000 yen + 500 yen = 3500 yen

[0099] Step 8:

[0100] The server converts the calculated total price into well-formed response data, for example, in the following JSON format:

[0101] json

[0102] {

[0103] "Total amount": "3500 yen"

[0104] }

[0105] Step 9:

[0106] The server returns the generated response data to the terminal as an HTTP response.

[0107] Step 10:

[0108] The device receives the response data from the server and parses the JSON data.

[0109] Step 11:

[0110] The terminal analyzes the estimate and displays it on the user interface. For example, the screen will say, "The total estimated price is 3,500 yen."

[0111] In this way, the system can quickly perform an estimate calculation based on the information entered by the user and instantly provide the results to the user.

[0112] Example 1

[0113] 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."

[0114] With conventional quotation systems, it often took a long time for users to receive a quote after entering detailed product or service information, hindering efficient sales activities. Another issue was that the input data format was not standardized, making data analysis and price calculations complicated, and prone to errors and delays.

[0115] 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.

[0116] In this invention, the server includes input means for a user to input details of goods or services and desired conditions through an information terminal, transmission means for the information terminal to transmit the input data to the data processing device, data processing means for analyzing the data received by the data processing device and obtaining price information from the storage device, calculation means for calculating the total price based on the price information obtained by the data processing device, response generation means for the data processing device to convert the calculation result into well-formed response data and return it to the information terminal, and display means for displaying the estimate result received by the information terminal to the user. This enables quick and accurate estimate acquisition and realizes efficient sales activities.

[0117] An "information terminal" is a device used by a user to input and display information about products and services.

[0118] A "data processing device" is a device that receives data transmitted from an information terminal, analyzes it, obtains necessary information from a storage device, and processes the data.

[0119] A "memory device" is a database or storage device for storing price information and other related data for goods and services.

[0120] The "input means" is a means for a user to input details and desired conditions of a product or service using an information terminal.

[0121] The "transmitting means" is a means by which the information terminal transmits input data to the data processing device.

[0122] The "data processing means" is a means for analyzing data received by the data processing device and obtaining price information from the storage device.

[0123] The "calculation means" is a means for calculating the total price based on the price information acquired by the data processing device.

[0124] The "response generating means" is a means by which the data processing device converts the calculation result into well-formed response data and returns it to the information terminal.

[0125] The "display means" is a means for displaying the estimate results received by the information terminal to the user.

[0126] The present invention relates to a system that enables a user to quickly and accurately obtain an estimate for a product or service. The system comprises an information terminal, a data processing device, and a storage device.

[0127] User operations

[0128] The user enters the name of the product for which they wish to receive a quote, the quantity, and, if necessary, details of options, via an information terminal (such as a PC or smartphone). For example, the user might enter "three units of product A and one unit of option B." This information is converted by the information terminal into JSON format data and sent to the data processing device as an HTTP POST request.

[0129] Information terminal processing

[0130] The information terminal first converts the information entered by the user into JSON format, and then sends it to the data processing device as an HTTP POST request. As a concrete example, the following data is generated:

[0131] json

[0132] {

[0133] "Product Name": "Product A",

[0134] "Quantity": 3,

[0135] "options": {

[0136] "Option B": 1

[0137] }

[0138] }

[0139] Data processing device processing

[0140] The data processing device receives an HTTP POST request from the information terminal and analyzes the JSON data. Based on the analyzed data, it retrieves the product's base price and option price information from the storage device. For example, if the unit price of product A is 1,000 yen and the unit price of option B is 500 yen, the price is calculated as follows:

[0141] Total price of product A: 1,000 yen 3 = 3,000 yen

[0142] Total price of Option B: 500 yen 1 = 500 yen

[0143] Total amount: 3000 yen + 500 yen = 3500 yen

[0144] Response Generation

[0145] The data processing device converts the calculation result into response data in JSON format and returns it to the information terminal. An example of the response data is as follows:

[0146] json

[0147] {

[0148] "Total amount": "3500 yen"

[0149] }

[0150] Displaying the results

[0151] The information terminal analyzes the JSON data returned from the data processing device and displays the estimate result on the user interface. As a specific example, the terminal screen displays "The total estimated amount is 3,500 yen."

[0152] Specific examples

[0153] For example, a user might get a quote using the following prompt:

[0154] Example prompt sentence:

[0155] I would like to order 3 units of "Item A" and 1 unit of "Option B" and would like a quote. Please calculate the quote.

[0156] This system allows users to obtain quotations quickly and accurately, enabling efficient sales activities. The system efficiently handles a series of processes, from user input to price calculation and result display, significantly improving the accuracy and speed of quotations.

[0157] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0158] Step 1:

[0159] The user enters detailed information about the product or service, as well as desired conditions such as options and quantity, into the input form on the information terminal. For example, the user enters "3 units of product A and 1 unit of option B." The input data format includes items such as product name, quantity, and options.

[0160] input:

[0161] Product name: Product A

[0162] Quantity: 3

[0163] Option: Option B 1 piece

[0164] output:

[0165] The information terminal receives the input data from the user.

[0166] Step 2:

[0167] When the user clicks on the "send" button, a command is initiated to transmit the input data from the information terminal to the data processing device.

[0168] input:

[0169] Detailed product or service information and desired conditions entered by the user.

[0170] output:

[0171] The "Submit" button is clicked and the data is ready to be sent.

[0172] Step 3:

[0173] The terminal converts the user input data into JSON format data. For example, the following JSON data is generated:

[0174] input:

[0175] Detailed product or service information and desired conditions entered by the user.

[0176] output:

[0177] json

[0178] {

[0179] "Product Name": "Product A",

[0180] "Quantity": 3,

[0181] "options": {

[0182] "Option B": 1

[0183] }

[0184] }

[0185] Step 4:

[0186] The terminal transmits the generated JSON data to the data processing device as an HTTP POST request.

[0187] input:

[0188] The data converted to JSON format.

[0189] output:

[0190] It is sent to the data processing device as an HTTP POST request.

[0191] Step 5:

[0192] The server receives the HTTP POST request, parses the JSON data, and extracts information about the product name, quantity, and options from the parsed data.

[0193] input:

[0194] JSON data sent from the terminal.

[0195] output:

[0196] Parsed data (product name, quantity, options).

[0197] Step 6:

[0198] The server queries the storage device to obtain price information for products and options. As a concrete example, assume that the unit price of product A is 1,000 yen and the unit price of option B is 500 yen.

[0199] input:

[0200] Queries based on the parsed data.

[0201] output:

[0202] Price information obtained from storage device (unit price of product A is 1,000 yen, unit price of option B is 500 yen).

[0203] Step 7:

[0204] The server calculates the total price based on the price information it has received. The calculation is done as follows:

[0205] Total price of product A: 1,000 yen 3 = 3,000 yen

[0206] Total price of Option B: 500 yen 1 = 500 yen

[0207] Total amount: 3000 yen + 500 yen = 3500 yen

[0208] input:

[0209] Price information retrieved from storage device.

[0210] output:

[0211] Calculated total price (3,500 yen).

[0212] Step 8:

[0213] The server converts the calculation result into well-formed response data and returns it to the information terminal. For example, the following JSON data is generated:

[0214] input:

[0215] Calculated total price.

[0216] output:

[0217] json

[0218] {

[0219] "Total amount": "3500 yen"

[0220] }

[0221] Step 9:

[0222] The terminal receives the response data returned from the server.

[0223] input:

[0224] The response data sent by the server.

[0225] output:

[0226] Response data received by the terminal.

[0227] Step 10:

[0228] The terminal analyzes the received JSON data and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen."

[0229] input:

[0230] The response data received.

[0231] output:

[0232] The estimate results displayed on the user interface (total estimate amount is 3,500 yen).

[0233] (Application example 1)

[0234] 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."

[0235] In today's world, users require quick quotes when purchasing products or services online. However, conventional systems take a long time to calculate quotes, resulting in a poor user experience. Another issue is that estimating complex combinations of options and quantities is tedious and time-consuming. Therefore, there is a need for a system that allows users to obtain quotes quickly and easily.

[0236] 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.

[0237] In this invention, the server includes a data processing means for analyzing the received data and retrieving price information from a database, a price calculation means for calculating the total price based on the retrieved price information, and a result generation means for converting the calculation result into well-formed response data and returning it to the terminal, thereby enabling the estimate result to be displayed immediately on the user interface.

[0238] "User" means a user of the online system who requests a quote for a product or service.

[0239] A "terminal" is a device operated by a user, and is equipped with input means for inputting detailed information and desired conditions for a product or service.

[0240] The "server" is a central processing unit that analyzes the received data, retrieves the necessary price information from a database, and performs calculations.

[0241] A "database" is an information storage system that stores pricing information such as base prices and option prices for products.

[0242] An "online quote generation system" is a system that instantly generates and provides quotes based on detailed product or service information entered by the user.

[0243] "Data processing means" refers to the function of analyzing data input from a user and making inquiries to a database.

[0244] "Result generation means" refers to the function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[0245] "Price calculation means" refers to a function that calculates the total price using the unit price and quantity of the product and the unit price of the option based on the acquired price information.

[0246] The "user interface" is a display means that displays the estimate results received by the terminal from the server to the user.

[0247] This invention is an online quotation generation system that allows users to input detailed information about products or services online and quickly receive a quotation. The system consists of a terminal operated by the user, a server that analyzes the input data, and a database that stores price information.

[0248] Hardware and software used

[0249] Device: The device that the user operates, such as a smartphone, tablet, or computer.

[0250] Server: A central processing unit that runs the Python-based Flask or Django server software.

[0251] Database: MySQL (registered trademark) or PostgreSQL is used to manage product price information and option prices.

[0252] Communication protocol: HTTP / HTTPS is used to send and receive data between the device and the server.

[0253] System Operation

[0254] 1. User Action:

[0255] The user uses the terminal to input detailed information such as the product name, quantity, options, etc. Specifically, the user inputs the required information into the input form provided in the user interface and clicks the "Submit" button.

[0256] 2. Terminal processing:

[0257] The device converts the information entered by the user into JSON format data and sends it to the server as an HTTP POST request. At this time, the device automatically formats the input data and processes it for sending to the server.

[0258] 3. Server processing:

[0259] The server receives the HTTP request and parses the JSON data. Then, based on the parsed data, it queries the database for product and option price information. Based on the price information retrieved from the database, it calculates the total price using the product unit price and quantity, and the option unit price.

[0260] 4. Generate calculation results:

[0261] The server converts the calculation result into well-formed response data and returns a JSON-formatted response to the terminal.

[0262] 5. Displaying the results:

[0263] The terminal parses the response data received from the server and displays the estimate results on the user interface. The user can check the final result in the form of "The total estimated amount is XX yen."

[0264] Specific examples

[0265] For example, consider the case where a user orders three "Product A" and one "Option B." The user enters "Product A," "Quantity 3," and "Option B" into the input form on the terminal and presses the "Submit" button. This information is sent from the terminal to the server, and the server retrieves the unit price of "Product A" (e.g., 1,000 yen) and the unit price of "Option B" (e.g., 500 yen) from the database. The server responds by sending back a JSON response with the total amount of "3,500 yen," and the terminal parses this and displays the message "The total estimated amount is 3,500 yen."

[0266] Prompt Sentence Examples

[0267] "If I were to order three items of product A and one item of option B, please let me know the estimated price."

[0268] This allows users to easily obtain quotes and make decisions quickly. This system improves the user experience of online shopping and is very convenient.

[0269] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0270] Step 1:

[0271] The user enters detailed information such as the product name, quantity, and options into the input form on the terminal and clicks the "Submit" button. The entered data includes the product name "Product A", the quantity "3", and the option "Option B".

[0272] Step 2:

[0273] The terminal converts the information entered by the user into JSON format data, which looks like this:

[0274] json

[0275] {

[0276] "Product Name": "Product A",

[0277] "Quantity": 3,

[0278] "options": {

[0279] "Option B": 1

[0280] }

[0281] }

[0282] This is sent to the server as the body of an HTTP POST request.

[0283] Step 3:

[0284] The server receives the HTTP request and parses the JSON data included in the body. The parsed data is stored in a temporary data structure (dictionary variable), and the "product name," "quantity," and "options" fields are extracted.

[0285] Step 4:

[0286] The server queries the database to find the unit price of "Product A" and the unit price of "Option B." Specifically, it executes the following SQL query:

[0287] sql

[0288] SELECT price FROM products WHERE name='Product A';

[0289] SELECT price FROM options WHERE name='Option B';

[0290] The result of this query is that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen.

[0291] Step 5:

[0292] The server calculates the total price based on the obtained price information. The specific calculation is as follows:

[0293] Total price of product A: 1,000 yen 3 = 3,000 yen

[0294] Total price of Option B: 500 yen 1 = 500 yen

[0295] Total amount: 3000 yen + 500 yen = 3500 yen

[0296] Step 6:

[0297] The server converts the calculation result into JSON response data and generates a response like this:

[0298] json

[0299] {

[0300] "Total amount": "3500 yen"

[0301] }

[0302] This response data is sent back to the terminal as the body of the HTTP response.

[0303] Step 7:

[0304] The terminal parses the response data received from the server, extracts the "total amount" value from the parsed data, and displays "The total estimated amount is 3,500 yen" on the user interface.

[0305] Specific operations in the processing flow

[0306] In step 1, the user enters detailed information into an input form and clicks a button.

[0307] In step 2, the entered information is converted to JSON format and an HTTP request is issued to the server.

[0308] In step 3, the server parses the received data and processes it to extract the necessary items.

[0309] Step 4 involves a data calculation where the server queries the database to obtain the required pricing information.

[0310] In step 5, the server calculates the total price of each item and performs a data calculation to calculate the total amount.

[0311] In step 6, the calculation result is converted into JSON-formatted response data and sent from the server to the terminal.

[0312] In step 7, the terminal parses the received data and displays the estimate results on the user interface.

[0313] 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.

[0314] The present invention combines an instant quote system that allows users to quickly obtain quotes with an emotion engine that recognizes the user's emotions and adjusts the output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[0315] System configuration

[0316] 1. Terminal: A device operated by the user that displays input forms, receives product and service information and desired conditions, and also captures the user's facial expressions and voice input.

[0317] 2. Server: Receives input data and sentiment data, analyzes them, retrieves necessary price information from the database, performs calculations, and generates well-formed results.

[0318] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[0319] 4. Emotion engine: Recognizes emotions from the user's facial expressions and voice and provides that information to the server.

[0320] Program processing overview

[0321] User Actions

[0322] The user enters detailed information such as the product name, quantity, and options on the device and clicks the "Submit" button. For example, three "Product A"s and one "Option B" are entered. The device also captures the user's facial expressions and voice.

[0323] Terminal handling

[0324] The device converts the product information entered by the user into JSON format, while at the same time recognizing emotions from the user's facial expressions and voice. For example, if the user's facial expression indicates that they are "considering purchasing" or that they would be happy if there was a discount, the device sends this information to the emotion engine, which then interprets the user's emotion as "expecting."

[0325] The device sends the following JSON data to the server:

[0326] json

[0327] {

[0328] "Product Name": "Product A",

[0329] "Quantity": 3,

[0330] "options": {

[0331] "Option B": 1

[0332] },

[0333] "Emotion": "Expecting"

[0334] }

[0335] Server Processing

[0336] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen:

[0337] Total price of product A: 1000 yen 3 = 3000 yen

[0338] Total price of Option B: 500 yen 1 = 500 yen

[0339] Total amount: 3000 yen + 500 yen = 3500 yen

[0340] Furthermore, the server takes into account the emotion data received from the emotion engine and outputs accordingly. For example, if the user expresses the emotion "expecting," the server may apply special offers or discounts. As a result, the total price may be 3,000 yen.

[0341] The server converts the results into well-formed data in JSON format, such as:

[0342] json

[0343] {

[0344] "Total amount": "3000 yen",

[0345] "Message": "Special offer discount applied."

[0346] }

[0347] Displaying the results

[0348] The terminal analyzes the response data received from the server and displays it in the user interface. For example, it displays "The total estimated amount is 3000 yen. A discount has been applied due to a special offer."

[0349] Specific example explanation

[0350] For example, if a user orders three "product A" and one "option B" and requests a quote, the user enters the information through the terminal and presses the send button to request a quote. In addition, the user's emotion is recognized as "expecting." Based on this information, the server calculates the product price and applies special offers. Finally, the user confirms the quote result, and the discount applied increases the likelihood of closing the deal.

[0351] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, and enables flexible responses based on emotions, resulting in efficient sales activities.

[0352] The processing flow will be explained below.

[0353] Step 1:

[0354] The user accesses the input form on the device and enters detailed product or service information such as product name, quantity, options, etc. For example, three "products A" and one "option B" are entered.

[0355] Step 2:

[0356] The user clicks the "Submit" button on the input form, which causes the entered information to be collected by the device.

[0357] Step 3:

[0358] The device converts the data entered by the user into JSON format, and simultaneously analyzes the user's facial expressions and voice using an emotion engine.

[0359] Step 4:

[0360] The emotion engine analyzes the user's facial expressions and voice and generates emotional data indicating "expectation."

[0361] Step 5:

[0362] The JSON data generated by the device is combined with emotion data and sent as an HTTP POST request to the server. For example, the following JSON data is sent:

[0363] json

[0364] {

[0365] "Product Name": "Product A",

[0366] "Quantity": 3,

[0367] "options": {

[0368] "Option B": 1

[0369] },

[0370] "Emotion": "Expecting"

[0371] }

[0372] Step 6:

[0373] The server receives the HTTP POST request and parses the received JSON data to obtain the details and sentiment of the user's desired product.

[0374] Step 7:

[0375] The server sends a query to the database to get the unit prices of "Product A" and "Option B." For example, the unit price of "Product A" is 1,000 yen, and the unit price of "Option B" is 500 yen.

[0376] Step 8:

[0377] The server calculates the total price based on the unit price obtained. Specifically, it calculates the following:

[0378] Total price of product A: 1,000 yen 3 = 3,000 yen

[0379] Total price of Option B: 500 yen 1 = 500 yen

[0380] Total amount: 3000 yen + 500 yen = 3500 yen

[0381] Step 9:

[0382] The server considers the emotion data and if the user shows the "expected" emotion, it will apply a special offer or discount, for example, a discount that brings the total price to 3000 yen.

[0383] Step 10:

[0384] The server converts the result of the calculation into well-formed response data, for example generating the following JSON data:

[0385] json

[0386] {

[0387] "Total amount": "3000 yen",

[0388] "Message": "Special offer discount applied."

[0389] }

[0390] Step 11:

[0391] The server returns the generated response data to the terminal as an HTTP response.

[0392] Step 12:

[0393] The terminal analyzes the response data received from the server.

[0394] Step 13:

[0395] The terminal analyzes the estimate and displays the result on the user interface. For example, it displays "The total estimate is 3000 yen. A discount has been applied due to a special offer."

[0396] This process allows the system to generate and provide quick and flexible estimates to users based on their input information and emotions.

[0397] Example 2

[0398] 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."

[0399] In conventional quotation systems, it was difficult for users to obtain a quick and accurate quotation, and it was also difficult to respond flexibly while taking into account the user's feelings. In particular, quotation results that ignored the user's feelings, such as expectations, reduced the possibility of concluding a business deal.

[0400] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a data processing means for analyzing received data and acquiring price information from a database, an emotion response means for adjusting output based on emotion data received from the emotion engine, and a price calculation means for calculating the total price based on the acquired price information. This makes it possible to provide a quick and accurate estimate and flexibly respond to the user's emotions.

[0401] "Input means" is a function that allows a user to input details of goods or services and desired conditions through a terminal.

[0402] The "transmission means" is a function that allows the terminal to transmit input data to the server.

[0403] "Emotion recognition means" is a function that allows the terminal to acquire the user's facial expressions and voice and generate emotion data.

[0404] The "emotion engine" is a system that analyzes the emotion data sent from the emotion recognition means and determines the user's emotional state.

[0405] The "data processing means" is a function that analyzes the data received by the server and retrieves price information from the database.

[0406] The "emotion response means" is a function that adjusts the output based on the emotion data received by the server from the emotion engine.

[0407] The "price calculation means" is a function that calculates the total price based on the price information acquired by the server.

[0408] The "result generation means" is a function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[0409] The "display means" is a function that displays the estimate results received by the terminal to the user.

[0410] The present invention provides a system for providing a user with a quick and accurate estimate, and further has a function for recognizing and responding to the user's emotions. Specific embodiments of the system will be described below.

[0411] System Configuration

[0412] Terminal

[0413] A terminal is a device operated by a user, and is equipped with an input means for the user to input detailed information about products and services and their desired conditions. It also includes emotion recognition means for acquiring the user's facial expressions and voice and processing them as emotional data. Specific examples of hardware include personal computers (PCs), tablets, and smartphones. Software used includes a web browser and dedicated applications for displaying input forms and transmitting data. A camera is used for facial recognition, and a microphone is used for voice recognition.

[0414] server

[0415] The server has a data processing means for receiving and analyzing data sent from the terminal. The server has an emotion response means for acquiring price information from the database and adjusting output based on emotion data analyzed by the emotion engine. The server also has a price calculation means and a result generation means for calculating the total price based on the price information and returning the result to the terminal as well-formed response data. The server and the database are connected via a network.

[0416] Emotion Engine

[0417] The emotion engine is a system that analyzes the data sent from the emotion recognition means and determines the user's emotional state. The emotion engine is managed by the server and generates information to provide offers and discounts according to the user's emotions.

[0418] Specific example explanation

[0419] As a concrete example, let's consider a case where a user orders three "Product A" and one "Option B" and requests a quote. The user enters the necessary information into the input form on the device and presses the "Submit" button to request a quote. At the same time, the device acquires the user's facial expressions and voice, and recognizes emotions such as "I'd be happy if there was a discount."

[0420] The device converts this information into JSON format and sends it to the server. For example, the following data is generated:

[0421] json

[0422] {

[0423] "Product Name": "Product A",

[0424] "Quantity": 3,

[0425] "options": {

[0426] "Option B": 1

[0427] },

[0428] "Emotion": "Expecting"

[0429] }

[0430] The server analyzes the received data and retrieves from the database that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen. The server calculates the total price based on this information and applies a special offer, taking into account the emotional data of "expecting" from the emotion engine.

[0431] The total amount is 3000 yen, and the server converts the calculation result into well-formed data in JSON format as follows:

[0432] json

[0433] {

[0434] "Total amount": "3000 yen",

[0435] "Message": "Special offer discount applied."

[0436] }

[0437] The terminal analyzes the response data from the server and displays on the user interface, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer."

[0438] Prompts for generative AI models

[0439] Here is an example of a prompt to input to a generative AI model:

[0440] I would like to quote a price for a product. The product name is "Product A", the quantity is 3, and the option is "Option B". I would also like a discount.

[0441] This prompt allows the generative AI model to generate an appropriate estimate while taking into account the user's emotions.

[0442] As a result, this system can provide users with quick and accurate estimates and respond flexibly to their emotions.

[0443] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0444] Step 1:

[0445] The user enters product information

[0446] The user enters detailed information such as product name, quantity, and options into the input form on the terminal. For example, the user enters three "Product A"s and one "Option B" and selects "Discount" as a desired condition. This information is used as input data sent to later processing. The input data has the following format:

[0447] Text format

[0448] Product name: Product A

[0449] Quantity: 3

[0450] Option: Option B (Quantity: 1)

[0451] Desired conditions: Discount

[0452] Step 2:

[0453] The user clicks the submit button

[0454] When the user clicks the "Submit" button, the entered data is processed. By clicking the "Submit" button, the terminal sends the data to the next processing step. The input data is converted directly to JSON format data.

[0455] Step 3:

[0456] The terminal converts the input information into JSON format.

[0457] The device converts the product information and desired conditions collected in the input form into JSON format. Specifically, the following JSON data is generated:

[0458] json

[0459] {

[0460] "Product Name": "Product A",

[0461] "Quantity": 3,

[0462] "options": {

[0463] "Option B": 1

[0464] },

[0465] "Desired conditions": "Discount"

[0466] }

[0467] This JSON data will later be the input data to be sent to the server.

[0468] Step 4:

[0469] The device captures the user's facial expressions and voice and generates emotion data.

[0470] The device uses a camera and microphone to capture the user's facial expressions and voice, and uses emotion recognition software to generate emotion data such as "I'm looking forward to it." For example, if a user says, "I'd be happy if there was a discount," the emotion is recognized as "I'm looking forward to it." The generated emotion data is in the following JSON format:

[0471] json

[0472] {

[0473] "Emotion": "Expecting"

[0474] }

[0475] Step 5:

[0476] The device sends the user's input information and emotion data to the server.

[0477] The device sends the converted product information and emotion data to the server as a single JSON data. The final JSON data sent will have the following format:

[0478] json

[0479] {

[0480] "Product Name": "Product A",

[0481] "Quantity": 3,

[0482] "options": {

[0483] "Option B": 1

[0484] },

[0485] "Desired conditions": "Discount",

[0486] "Emotion": "Expecting"

[0487] }

[0488] This data becomes the input data for the next processing step on the server.

[0489] Step 6:

[0490] The server analyzes the received data

[0491] The server parses the JSON data received from the device and extracts the product name, quantity, options, and emotion data. This analysis stores the product information and emotion data in individual variables and data structures, which then become input data for the next price acquisition process.

[0492] Step 7:

[0493] The server retrieves the price information from the database

[0494] The server uses the parsed data to query the database to get pricing information for products and options. For example, the database might return the following pricing information:

[0495] Unit price of product A: 1,000 yen

[0496] Option B unit price: 500 yen

[0497] The acquired price information becomes input data for the next price calculation process.

[0498] Step 8:

[0499] The server calculates the total price

[0500] The server calculates the total price of the items based on the price information it has received. The calculation is done as follows:

[0501] Total price of product A: 1,000 yen x 3 = 3,000 yen

[0502] Total price of Option B: 500 yen x 1 = 500 yen

[0503] Total amount: 3000 yen + 500 yen = 3500 yen

[0504] This 3,500 yen will be the base price and will be the input data for the next emotion response processing.

[0505] Step 9:

[0506] The server adjusts the output taking into account emotional data.

[0507] The server takes into account the emotion data of "expecting" received from the emotion engine and applies special offers and discounts. For example, it adjusts the total price to 500 yen off as a special discount, so that the final total price is 3,000 yen.

[0508] Step 10:

[0509] The server converts the calculation results into well-formed data in JSON format.

[0510] The server converts the final quote result into well-formed data in the following JSON format:

[0511] json

[0512] {

[0513] "Total amount": "3000 yen",

[0514] "Message": "Special offer discount applied."

[0515] }

[0516] This data is sent to the terminal.

[0517] Step 11:

[0518] The device analyzes the response data from the server

[0519] The terminal analyzes the JSON response data received from the server and extracts the total amount and message.

[0520] Step 12:

[0521] The device displays the results in the user interface.

[0522] Based on the data analyzed by the device, the user interface displays the message, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer." This allows the user to quickly and accurately check the estimated results.

[0523] (Application example 2)

[0524] 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."

[0525] Conventional quotation systems provide quick quotes based on detailed product information entered by users, but they lack the flexibility to consider the user's emotional state, which results in insufficient improvement in customer satisfaction or motivation to purchase. Furthermore, they lack the functionality to provide personalized offers and messages when providing user input data and quotation results. This results in a poor user experience.

[0526] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0527] In this invention, the server includes emotion recognition means for analyzing facial expressions and voice data transmitted from a terminal operated by a user to recognize the emotional state, data processing means for analyzing the received data and retrieving price information from a database, price calculation means for calculating a total price based on the retrieved price information and the emotional state, and result generation means for converting the calculation result into well-formed response data and a customized message based on the emotional state and returning it to the terminal, thereby enabling the provision of real-time estimates according to the user's emotions and the application of personalized special offers and discounts.

[0528] The "input means" is a means by which a user inputs detailed information and desired conditions for a product or service.

[0529] The "transmission means" is a means for transmitting the input data, facial expression data, and voice data from the terminal to the server.

[0530] The "emotion recognition means" is a means for analyzing received data, facial expressions, and voice data to recognize an emotional state.

[0531] The "data processing means" is a means for analyzing the data received by the server and obtaining price information from the database.

[0532] The "price calculation means" is a means for calculating the total price based on the price information and emotional state acquired by the server.

[0533] The "result generation means" is a means by which the server converts the calculation result into well-formed response data and a customized message based on the emotional state, and returns the result to the terminal.

[0534] The "display means" is a means for displaying the estimate results and customized messages received by the terminal to the user.

[0535] "Special Offers" are discounts and promotional offers that are tailored to a user's emotional state.

[0536] The present invention provides an instant quote system that allows users to quickly obtain quotes, combined with an emotion engine that recognizes the user's emotions and adjusts output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[0537] First, the device operated by the user provides an interface for inputting detailed product or service information and desired conditions. For example, the user inputs information for purchasing three units of "Product A" and one unit of "Option B." The device also uses a camera and microphone to capture the user's facial expressions and voice, and transmits this as emotion data to the server.

[0538] The server receives the transmitted data and emotional data, and first analyzes the user's emotional state using the emotion recognition means. For example, if the user says, "I'd be happy if there was a discount," the emotion recognition means interprets this as "I'm looking forward to it." Next, the data processing means analyzes the product information entered by the user and retrieves the corresponding price information from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, this information is retrieved.

[0539] The price calculation means calculates the total price based on the acquired price information and the emotional state. For example, if the emotion "expecting" is recognized, the server applies special offers and discounts and adjusts the total price. As a specific example, a quote of 3,500 yen, which is the regular price, may be discounted to 3,000 yen in response to the "expecting" emotion.

[0540] The result generation means converts the calculation result into well-formed response data and creates a customized message based on the emotional state. This data is then sent back to the terminal. The terminal displays the received estimate result and the customized message on the user interface. For example, the user can see a message that reads, "The total estimate is 3,000 yen. A discount has been applied due to a special offer."

[0541] To implement this system, a smartphone (with a camera and microphone) is used. For emotion recognition, a generative AI model called an emotion recognition API is recommended. On the server side, data processing is performed using a web framework such as Flask.

[0542] As a specific example, a prompt sentence is prepared: "Please generate a quote with discounts based on the purchase information for three units of product name 'Product A' and one unit of 'Option B' and the user's expected emotion." Based on this prompt sentence, the system provides an appropriate quote and a message according to the emotion.

[0543] As described above, the instant quotation system of the present invention, which clearly specifies the hardware and software to be used and the specific flow of data processing and calculations, makes it possible to provide highly efficient quotation that will provide high customer satisfaction.

[0544] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0545] Step 1:

[0546] The user inputs details of the product or service and desired conditions through the terminal.

[0547] Specifically, the user enters three "Product A"s and one "Option B" into the input form on the device and clicks the "Submit" button. This information is converted into JSON format data on the device. As a concrete example of input data, the following JSON data is generated:

[0548] json

[0549] {

[0550] "Product Name": "Product A",

[0551] "Quantity": 3,

[0552] "options": {

[0553] "Option B": 1

[0554] }

[0555] }

[0556] Step 2:

[0557] The user's facial expressions and voice are acquired by the terminal.

[0558] The device uses a camera and microphone to capture the user's facial expressions and voice. Specifically, the device captures the user's face in real time and records voice input. The captured emotion data is also converted into JSON format data.

[0559] Step 3:

[0560] The terminal transmits the input product information and emotion data to the server.

[0561] Specifically, the device sends the JSON data of the product information generated earlier and the emotion data obtained from facial and voice analysis to the server as an HTTP request. The sent data will be in the following format:

[0562] json

[0563] {

[0564] "Product information": {

[0565] "Product Name": "Product A",

[0566] "Quantity": 3,

[0567] "options": {

[0568] "Option B": 1

[0569] }

[0570] },

[0571] "Emotion": "Expecting"

[0572] }

[0573] Step 4:

[0574] The server parses the received data.

[0575] The server receives the HTTP request and parses the JSON data. The parsed data is stored in separate variables for further processing. The input includes product information and sentiment data, and the output of the parsing is split into separate variables for each piece of information.

[0576] Step 5:

[0577] An emotion recognition means analyzes emotions.

[0578] The emotion recognition means in the server analyzes the received facial expression and voice data and recognizes the emotional state of the user. The facial expression and voice data are provided as input, and an emotional status such as "expecting" is obtained as output.

[0579] Step 6:

[0580] The data processing means analyzes the product information and obtains price information from the database.

[0581] The data processing means in the server analyzes the product information and queries the database for price information on the corresponding product. As a specific example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, these price information will be obtained. The input is the analyzed product information, and the output is price information for the product and options.

[0582] Step 7:

[0583] A price calculation means calculates the total price.

[0584] The price calculation means in the server calculates the total price based on the acquired price information and emotional state. For example, if the total price of three "products A" and one "option B" is calculated and the emotion is recognized as "expecting," a 10% discount is applied as a special offer. The input is price information and emotional data, and the output is the total price after applying the discount. A specific example is as follows:

[0585] Total price of product A: 1000 yen 3 = 3000 yen

[0586] Total price of Option B: 500 yen 1 = 500 yen

[0587] Total amount: 3000 yen + 500 yen = 3500 yen

[0588] After discount: 3500 yen 0.9 = 3150 yen

[0589] Step 8:

[0590] A result generation means creates well-formed response data and adds a customized message based on the emotion.

[0591] The server converts the results of the calculation into well-formed JSON data and adds a customized message based on the emotion, producing the following example output:

[0592] json

[0593] {

[0594] "Total amount": "3150 yen",

[0595] "Message": "Special offer discount applied."

[0596] }

[0597] Step 9:

[0598] The server transmits the generated response data to the terminal.

[0599] The server sends the generated response data to the terminal as an HTTP response. The input is well-formed data, and the output is an HTTP response.

[0600] Step 10:

[0601] The terminal displays the received estimate result and the customized message to the user.

[0602] The terminal analyzes the response data from the server and displays it on the user interface. The user sees the message "The total estimated price is 3150 yen. A discount has been applied thanks to a special offer." The input is the response data, and the output is the user interface display.

[0603] 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.

[0604] 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.

[0605] 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.

[0606] [Second embodiment]

[0607] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0608] 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.

[0609] 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).

[0610] 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.

[0611] 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.

[0612] 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).

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] In the smart glasses 214, 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.

[0618] 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."

[0619] The present invention relates to an instant quotation system that allows users to quickly obtain a quotation at the proposal stage. This system has a terminal, a server, and a database, and automatically generates a quotation when the user inputs detailed information about a product or service.

[0620] System configuration

[0621] 1. Terminal: A device operated by the user that displays input forms and receives product and service information and desired conditions.

[0622] 2. Server: Receives input data, parses it, retrieves necessary pricing information from the database, performs calculations, and produces well-formed results.

[0623] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[0624] Program processing overview

[0625] User Actions

[0626] The user enters information such as product name, quantity, options, etc. on the terminal and clicks the "Submit" button. For example, if the user wants a quote for "3 units of product A" and "1 unit of option B," they enter these details.

[0627] Terminal handling

[0628] The device converts the information entered by the user into JSON format data, which is then sent to the server as an HTTP POST request. A specific example of JSON data is as follows:

[0629] json

[0630] {

[0631] "Product Name": "Product A",

[0632] "Quantity": 3,

[0633] "options": {

[0634] "Option B": 1

[0635] }

[0636] }

[0637] Server Processing

[0638] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. It then calculates the total price. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, it performs the following calculation:

[0639] Total price of product A: 1,000 yen 3 = 3,000 yen

[0640] Total price of Option B: 500 yen 1 = 500 yen

[0641] Total amount: 3000 yen + 500 yen = 3500 yen

[0642] The server converts the calculation result into well-formed response data and sends it back to the device. The response data has the following format:

[0643] json

[0644] {

[0645] "Total amount": "3500 yen"

[0646] }

[0647] Displaying the results

[0648] The terminal analyzes the response data received from the server and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen" on the screen.

[0649] Specific example explanation

[0650] For example, consider a situation where a user wants to order three units of "Item A" and one unit of "Option B" and would like a quote. The user enters these details on the device and hits the submit button to request a quote. The device sends the data to the server, which parses the data and retrieves the price of each item from a database. The server performs the calculations and sends them back to the device. Finally, the user can quickly see the quote results.

[0651] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, enabling efficient sales activities.

[0652] The processing flow will be explained below.

[0653] Step 1:

[0654] The user accesses the input form on the device and enters detailed product information such as the product name, quantity, options, etc. For example, three "product A"s and one "option B" are entered.

[0655] Step 2:

[0656] The user clicks the "Submit" button on the input form, which causes the information entered by the user to be collected by the device.

[0657] Step 3:

[0658] The terminal converts the data entered by the user into JSON format. For example, the following JSON data is generated:

[0659] json

[0660] {

[0661] "Product Name": "Product A",

[0662] "Quantity": 3,

[0663] "options": {

[0664] "Option B": 1

[0665] }

[0666] }

[0667] Step 4:

[0668] The device sends an HTTP POST request containing the generated JSON data to the server.

[0669] Step 5:

[0670] The server receives an HTTP POST request, parses the received data, and converts the JSON formatted data into an internal format.

[0671] Step 6:

[0672] The server sends a query to the database to obtain the unit price of "Product A" (1,000 yen) and the unit price of "Option B" (500 yen).

[0673] Step 7:

[0674] The server calculates the user's order based on the price information it has obtained. Specifically, it performs the following calculations:

[0675] Total price of product A: 1000 yen 3 = 3000 yen

[0676] Total price of Option B: 500 yen 1 = 500 yen

[0677] Total amount: 3000 yen + 500 yen = 3500 yen

[0678] Step 8:

[0679] The server converts the calculated total price into well-formed response data, for example, in the following JSON format:

[0680] json

[0681] {

[0682] "Total amount": "3500 yen"

[0683] }

[0684] Step 9:

[0685] The server returns the generated response data to the terminal as an HTTP response.

[0686] Step 10:

[0687] The device receives the response data from the server and parses the JSON data.

[0688] Step 11:

[0689] The terminal analyzes the estimate and displays it on the user interface. For example, the screen will say, "The total estimated price is 3,500 yen."

[0690] In this way, the system can quickly perform an estimate calculation based on the information entered by the user and instantly provide the results to the user.

[0691] Example 1

[0692] 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."

[0693] With conventional quotation systems, it often took a long time for users to receive a quote after entering detailed product or service information, hindering efficient sales activities. Another issue was that the input data format was not standardized, making data analysis and price calculations complicated, and prone to errors and delays.

[0694] 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.

[0695] In this invention, the server includes input means for a user to input details of goods or services and desired conditions through an information terminal, transmission means for the information terminal to transmit the input data to the data processing device, data processing means for analyzing the data received by the data processing device and obtaining price information from the storage device, calculation means for calculating the total price based on the price information obtained by the data processing device, response generation means for the data processing device to convert the calculation result into well-formed response data and return it to the information terminal, and display means for displaying the estimate result received by the information terminal to the user. This enables quick and accurate estimate acquisition and realizes efficient sales activities.

[0696] An "information terminal" is a device used by a user to input and display information about products and services.

[0697] A "data processing device" is a device that receives data transmitted from an information terminal, analyzes it, obtains necessary information from a storage device, and processes the data.

[0698] A "memory device" is a database or storage device for storing price information and other related data for goods and services.

[0699] The "input means" is a means for a user to input details and desired conditions of a product or service using an information terminal.

[0700] The "transmitting means" is a means by which the information terminal transmits input data to the data processing device.

[0701] The "data processing means" is a means for analyzing data received by the data processing device and obtaining price information from the storage device.

[0702] The "calculation means" is a means for calculating the total price based on the price information acquired by the data processing device.

[0703] The "response generating means" is a means by which the data processing device converts the calculation result into well-formed response data and returns it to the information terminal.

[0704] The "display means" is a means for displaying the estimate results received by the information terminal to the user.

[0705] The present invention relates to a system that enables a user to quickly and accurately obtain an estimate for a product or service. The system comprises an information terminal, a data processing device, and a storage device.

[0706] User operations

[0707] The user enters the name of the product for which they wish to receive a quote, the quantity, and, if necessary, details of options, via an information terminal (such as a PC or smartphone). For example, the user might enter "three units of product A and one unit of option B." This information is converted by the information terminal into JSON format data and sent to the data processing device as an HTTP POST request.

[0708] Information terminal processing

[0709] The information terminal first converts the information entered by the user into JSON format, and then sends it to the data processing device as an HTTP POST request. As a concrete example, the following data is generated:

[0710] json

[0711] {

[0712] "Product Name": "Product A",

[0713] "Quantity": 3,

[0714] "options": {

[0715] "Option B": 1

[0716] }

[0717] }

[0718] Data processing device processing

[0719] The data processing device receives an HTTP POST request from the information terminal and analyzes the JSON data. Based on the analyzed data, it retrieves the product's base price and option price information from the storage device. For example, if the unit price of product A is 1,000 yen and the unit price of option B is 500 yen, the price is calculated as follows:

[0720] Total price of product A: 1,000 yen 3 = 3,000 yen

[0721] Total price of Option B: 500 yen 1 = 500 yen

[0722] Total amount: 3000 yen + 500 yen = 3500 yen

[0723] Response Generation

[0724] The data processing device converts the calculation result into response data in JSON format and returns it to the information terminal. An example of the response data is as follows:

[0725] json

[0726] {

[0727] "Total amount": "3500 yen"

[0728] }

[0729] Displaying the results

[0730] The information terminal analyzes the JSON data returned from the data processing device and displays the estimate result on the user interface. As a specific example, the terminal screen displays "The total estimated amount is 3,500 yen."

[0731] Specific examples

[0732] For example, a user might get a quote using the following prompt:

[0733] Example prompt sentence:

[0734] I would like to order 3 units of "Item A" and 1 unit of "Option B" and would like a quote. Please calculate the quote.

[0735] This system allows users to obtain quotations quickly and accurately, enabling efficient sales activities. The system efficiently handles a series of processes, from user input to price calculation and result display, significantly improving the accuracy and speed of quotations.

[0736] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0737] Step 1:

[0738] The user enters detailed information about the product or service, as well as desired conditions such as options and quantity, into the input form on the information terminal. For example, the user enters "3 units of product A and 1 unit of option B." The input data format includes items such as product name, quantity, and options.

[0739] input:

[0740] Product name: Product A

[0741] Quantity: 3

[0742] Option: Option B 1 piece

[0743] output:

[0744] The information terminal receives the input data from the user.

[0745] Step 2:

[0746] When the user clicks on the "send" button, a command is initiated to transmit the input data from the information terminal to the data processing device.

[0747] input:

[0748] Detailed product or service information and desired conditions entered by the user.

[0749] output:

[0750] The "Submit" button is clicked and the data is ready to be sent.

[0751] Step 3:

[0752] The terminal converts the user input data into JSON format data. For example, the following JSON data is generated:

[0753] input:

[0754] Detailed product or service information and desired conditions entered by the user.

[0755] output:

[0756] json

[0757] {

[0758] "Product Name": "Product A",

[0759] "Quantity": 3,

[0760] "options": {

[0761] "Option B": 1

[0762] }

[0763] }

[0764] Step 4:

[0765] The terminal transmits the generated JSON data to the data processing device as an HTTP POST request.

[0766] input:

[0767] The data converted to JSON format.

[0768] output:

[0769] It is sent to the data processing device as an HTTP POST request.

[0770] Step 5:

[0771] The server receives the HTTP POST request, parses the JSON data, and extracts information about the product name, quantity, and options from the parsed data.

[0772] input:

[0773] JSON data sent from the terminal.

[0774] output:

[0775] Parsed data (product name, quantity, options).

[0776] Step 6:

[0777] The server queries the storage device to obtain price information for products and options. As a concrete example, assume that the unit price of product A is 1,000 yen and the unit price of option B is 500 yen.

[0778] input:

[0779] Queries based on the parsed data.

[0780] output:

[0781] Price information obtained from storage device (unit price of product A is 1,000 yen, unit price of option B is 500 yen).

[0782] Step 7:

[0783] The server calculates the total price based on the price information it has received. The calculation is done as follows:

[0784] Total price of product A: 1,000 yen 3 = 3,000 yen

[0785] Total price of Option B: 500 yen 1 = 500 yen

[0786] Total amount: 3000 yen + 500 yen = 3500 yen

[0787] input:

[0788] Price information retrieved from storage device.

[0789] output:

[0790] Calculated total price (3,500 yen).

[0791] Step 8:

[0792] The server converts the calculation result into well-formed response data and returns it to the information terminal. For example, the following JSON data is generated:

[0793] input:

[0794] Calculated total price.

[0795] output:

[0796] json

[0797] {

[0798] "Total amount": "3500 yen"

[0799] }

[0800] Step 9:

[0801] The terminal receives the response data returned from the server.

[0802] input:

[0803] The response data sent by the server.

[0804] output:

[0805] Response data received by the terminal.

[0806] Step 10:

[0807] The terminal analyzes the received JSON data and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen."

[0808] input:

[0809] The response data received.

[0810] output:

[0811] The estimate results displayed on the user interface (total estimate amount is 3,500 yen).

[0812] (Application example 1)

[0813] 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."

[0814] In today's world, users require quick quotes when purchasing products or services online. However, conventional systems take a long time to calculate quotes, resulting in a poor user experience. Another issue is that estimating complex combinations of options and quantities is tedious and time-consuming. Therefore, there is a need for a system that allows users to obtain quotes quickly and easily.

[0815] 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.

[0816] In this invention, the server includes a data processing means for analyzing the received data and retrieving price information from a database, a price calculation means for calculating the total price based on the retrieved price information, and a result generation means for converting the calculation result into well-formed response data and returning it to the terminal, thereby enabling the estimate result to be displayed immediately on the user interface.

[0817] "User" means a user of the online system who requests a quote for a product or service.

[0818] A "terminal" is a device operated by a user, and is equipped with input means for inputting detailed information and desired conditions for a product or service.

[0819] The "server" is a central processing unit that analyzes the received data, retrieves the necessary price information from a database, and performs calculations.

[0820] A "database" is an information storage system that stores pricing information such as base prices and option prices for products.

[0821] An "online quote generation system" is a system that instantly generates and provides quotes based on detailed product or service information entered by the user.

[0822] "Data processing means" refers to the function of analyzing data input from a user and making inquiries to a database.

[0823] "Result generation means" refers to the function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[0824] "Price calculation means" refers to a function that calculates the total price using the unit price and quantity of the product and the unit price of the option based on the acquired price information.

[0825] The "user interface" is a display means that displays the estimate results received by the terminal from the server to the user.

[0826] This invention is an online quotation generation system that allows users to input detailed information about products or services online and quickly receive a quotation. The system consists of a terminal operated by the user, a server that analyzes the input data, and a database that stores price information.

[0827] Hardware and software used

[0828] Device: The device that the user operates, such as a smartphone, tablet, or computer.

[0829] Server: A central processing unit that runs the Python-based Flask or Django server software.

[0830] Database: Use MySQL or PostgreSQL to manage product pricing information and option prices.

[0831] Communication protocol: HTTP / HTTPS is used to send and receive data between the device and the server.

[0832] System Operation

[0833] 1. User Action:

[0834] The user uses the terminal to input detailed information such as the product name, quantity, options, etc. Specifically, the user inputs the required information into the input form provided in the user interface and clicks the "Submit" button.

[0835] 2. Terminal processing:

[0836] The device converts the information entered by the user into JSON format data and sends it to the server as an HTTP POST request. At this time, the device automatically formats the input data and processes it for sending to the server.

[0837] 3. Server processing:

[0838] The server receives the HTTP request and parses the JSON data. Then, based on the parsed data, it queries the database for product and option price information. Based on the price information retrieved from the database, it calculates the total price using the product unit price and quantity, and the option unit price.

[0839] 4. Generate calculation results:

[0840] The server converts the calculation result into well-formed response data and returns a JSON-formatted response to the terminal.

[0841] 5. Displaying the results:

[0842] The terminal parses the response data received from the server and displays the estimate results on the user interface. The user can check the final result in the form of "The total estimated amount is XX yen."

[0843] Specific examples

[0844] For example, consider the case where a user orders three "Product A" and one "Option B." The user enters "Product A," "Quantity 3," and "Option B" into the input form on the terminal and presses the "Submit" button. This information is sent from the terminal to the server, and the server retrieves the unit price of "Product A" (e.g., 1,000 yen) and the unit price of "Option B" (e.g., 500 yen) from the database. The server responds by sending back a JSON response with the total amount of "3,500 yen," and the terminal parses this and displays the message "The total estimated amount is 3,500 yen."

[0845] Prompt Sentence Examples

[0846] "If I were to order three items of product A and one item of option B, please let me know the estimated price."

[0847] This allows users to easily obtain quotes and make decisions quickly. This system improves the user experience of online shopping and is very convenient.

[0848] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0849] Step 1:

[0850] The user enters detailed information such as the product name, quantity, and options into the input form on the terminal and clicks the "Submit" button. The entered data includes the product name "Product A", the quantity "3", and the option "Option B".

[0851] Step 2:

[0852] The terminal converts the information entered by the user into JSON format data, which looks like this:

[0853] json

[0854] {

[0855] "Product Name": "Product A",

[0856] "Quantity": 3,

[0857] "options": {

[0858] "Option B": 1

[0859] }

[0860] }

[0861] This is sent to the server as the body of an HTTP POST request.

[0862] Step 3:

[0863] The server receives the HTTP request and parses the JSON data included in the body. The parsed data is stored in a temporary data structure (dictionary variable), and the "product name," "quantity," and "options" fields are extracted.

[0864] Step 4:

[0865] The server queries the database to find the unit price of "Product A" and the unit price of "Option B." Specifically, it executes the following SQL query:

[0866] sql

[0867] SELECT price FROM products WHERE name='Product A';

[0868] SELECT price FROM options WHERE name='Option B';

[0869] The result of this query is that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen.

[0870] Step 5:

[0871] The server calculates the total price based on the obtained price information. The specific calculation is as follows:

[0872] Total price of product A: 1,000 yen 3 = 3,000 yen

[0873] Total price of Option B: 500 yen 1 = 500 yen

[0874] Total amount: 3000 yen + 500 yen = 3500 yen

[0875] Step 6:

[0876] The server converts the calculation result into JSON response data and generates a response like this:

[0877] json

[0878] {

[0879] "Total amount": "3500 yen"

[0880] }

[0881] This response data is sent back to the terminal as the body of the HTTP response.

[0882] Step 7:

[0883] The terminal parses the response data received from the server, extracts the "total amount" value from the parsed data, and displays "The total estimated amount is 3,500 yen" on the user interface.

[0884] Specific operations in the processing flow

[0885] In step 1, the user enters detailed information into an input form and clicks a button.

[0886] In step 2, the entered information is converted to JSON format and an HTTP request is issued to the server.

[0887] In step 3, the server parses the received data and processes it to extract the necessary items.

[0888] Step 4 involves a data calculation where the server queries the database to obtain the required pricing information.

[0889] In step 5, the server calculates the total price of each item and performs a data calculation to calculate the total amount.

[0890] In step 6, the calculation result is converted into JSON-formatted response data and sent from the server to the terminal.

[0891] In step 7, the terminal parses the received data and displays the estimate results on the user interface.

[0892] 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.

[0893] The present invention combines an instant quote system that allows users to quickly obtain quotes with an emotion engine that recognizes the user's emotions and adjusts the output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[0894] System configuration

[0895] 1. Terminal: A device operated by the user that displays input forms, receives product and service information and desired conditions, and also captures the user's facial expressions and voice input.

[0896] 2. Server: Receives input data and sentiment data, analyzes them, retrieves necessary price information from the database, performs calculations, and generates well-formed results.

[0897] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[0898] 4. Emotion engine: Recognizes emotions from the user's facial expressions and voice and provides that information to the server.

[0899] Program processing overview

[0900] User Actions

[0901] The user enters detailed information such as the product name, quantity, and options on the device and clicks the "Submit" button. For example, three "Product A"s and one "Option B" are entered. The device also captures the user's facial expressions and voice.

[0902] Terminal handling

[0903] The device converts the product information entered by the user into JSON format, while at the same time recognizing emotions from the user's facial expressions and voice. For example, if the user's facial expression indicates that they are "considering purchasing" or that they would be happy if there was a discount, the device sends this information to the emotion engine, which then interprets the user's emotion as "expecting."

[0904] The device sends the following JSON data to the server:

[0905] json

[0906] {

[0907] "Product Name": "Product A",

[0908] "Quantity": 3,

[0909] "options": {

[0910] "Option B": 1

[0911] },

[0912] "Emotion": "Expecting"

[0913] }

[0914] Server Processing

[0915] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen:

[0916] Total price of product A: 1000 yen 3 = 3000 yen

[0917] Total price of Option B: 500 yen 1 = 500 yen

[0918] Total amount: 3000 yen + 500 yen = 3500 yen

[0919] Furthermore, the server takes into account the emotion data received from the emotion engine and outputs accordingly. For example, if the user expresses the emotion "expecting," the server may apply special offers or discounts. As a result, the total price may be 3,000 yen.

[0920] The server converts the results into well-formed data in JSON format, such as:

[0921] json

[0922] {

[0923] "Total amount": "3000 yen",

[0924] "Message": "Special offer discount applied."

[0925] }

[0926] Displaying the results

[0927] The terminal analyzes the response data received from the server and displays it in the user interface. For example, it displays "The total estimated amount is 3000 yen. A discount has been applied due to a special offer."

[0928] Specific example explanation

[0929] For example, if a user orders three "product A" and one "option B" and requests a quote, the user enters the information through the terminal and presses the send button to request a quote. In addition, the user's emotion is recognized as "expecting." Based on this information, the server calculates the product price and applies special offers. Finally, the user confirms the quote result, and the discount applied increases the likelihood of closing the deal.

[0930] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, and enables flexible responses based on emotions, resulting in efficient sales activities.

[0931] The processing flow will be explained below.

[0932] Step 1:

[0933] The user accesses the input form on the device and enters detailed product or service information such as product name, quantity, options, etc. For example, three "products A" and one "option B" are entered.

[0934] Step 2:

[0935] The user clicks the "Submit" button on the input form, which causes the entered information to be collected by the device.

[0936] Step 3:

[0937] The device converts the data entered by the user into JSON format, and simultaneously analyzes the user's facial expressions and voice using an emotion engine.

[0938] Step 4:

[0939] The emotion engine analyzes the user's facial expressions and voice and generates emotional data indicating "expectation."

[0940] Step 5:

[0941] The JSON data generated by the device is combined with emotion data and sent as an HTTP POST request to the server. For example, the following JSON data is sent:

[0942] json

[0943] {

[0944] "Product Name": "Product A",

[0945] "Quantity": 3,

[0946] "options": {

[0947] "Option B": 1

[0948] },

[0949] "Emotion": "Expecting"

[0950] }

[0951] Step 6:

[0952] The server receives the HTTP POST request and parses the received JSON data to obtain the details and sentiment of the user's desired product.

[0953] Step 7:

[0954] The server sends a query to the database to get the unit prices of "Product A" and "Option B." For example, the unit price of "Product A" is 1,000 yen, and the unit price of "Option B" is 500 yen.

[0955] Step 8:

[0956] The server calculates the total price based on the unit price obtained. Specifically, it calculates the following:

[0957] Total price of product A: 1,000 yen 3 = 3,000 yen

[0958] Total price of Option B: 500 yen 1 = 500 yen

[0959] Total amount: 3000 yen + 500 yen = 3500 yen

[0960] Step 9:

[0961] The server considers the emotion data and if the user shows the "expected" emotion, it will apply a special offer or discount, for example, a discount that brings the total price to 3000 yen.

[0962] Step 10:

[0963] The server converts the result of the calculation into well-formed response data, for example generating the following JSON data:

[0964] json

[0965] {

[0966] "Total amount": "3000 yen",

[0967] "Message": "Special offer discount applied."

[0968] }

[0969] Step 11:

[0970] The server returns the generated response data to the terminal as an HTTP response.

[0971] Step 12:

[0972] The terminal analyzes the response data received from the server.

[0973] Step 13:

[0974] The terminal analyzes the estimate and displays the result on the user interface. For example, it displays "The total estimate is 3000 yen. A discount has been applied due to a special offer."

[0975] This process allows the system to generate and provide quick and flexible estimates to users based on their input information and emotions.

[0976] Example 2

[0977] 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."

[0978] In conventional quotation systems, it was difficult for users to obtain a quick and accurate quotation, and it was also difficult to respond flexibly while taking into account the user's feelings. In particular, quotation results that ignored the user's feelings, such as expectations, reduced the possibility of concluding a business deal.

[0979] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a data processing means for analyzing received data and acquiring price information from a database, an emotion response means for adjusting output based on emotion data received from the emotion engine, and a price calculation means for calculating the total price based on the acquired price information. This makes it possible to provide a quick and accurate estimate and flexibly respond to the user's emotions.

[0980] "Input means" is a function that allows a user to input details of goods or services and desired conditions through a terminal.

[0981] The "transmission means" is a function that allows the terminal to transmit input data to the server.

[0982] "Emotion recognition means" is a function that allows the terminal to acquire the user's facial expressions and voice and generate emotion data.

[0983] The "emotion engine" is a system that analyzes the emotion data sent from the emotion recognition means and determines the user's emotional state.

[0984] The "data processing means" is a function that analyzes the data received by the server and retrieves price information from the database.

[0985] The "emotion response means" is a function that adjusts the output based on the emotion data received by the server from the emotion engine.

[0986] The "price calculation means" is a function that calculates the total price based on the price information acquired by the server.

[0987] The "result generation means" is a function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[0988] The "display means" is a function that displays the estimate results received by the terminal to the user.

[0989] The present invention provides a system for providing a user with a quick and accurate estimate, and further has a function for recognizing and responding to the user's emotions. Specific embodiments of the system will be described below.

[0990] System Configuration

[0991] Terminal

[0992] A terminal is a device operated by a user, and is equipped with an input means for the user to input detailed information about products and services and their desired conditions. It also includes emotion recognition means for acquiring the user's facial expressions and voice and processing them as emotional data. Specific examples of hardware include personal computers (PCs), tablets, and smartphones. Software used includes a web browser and dedicated applications for displaying input forms and transmitting data. A camera is used for facial recognition, and a microphone is used for voice recognition.

[0993] server

[0994] The server has a data processing means for receiving and analyzing data sent from the terminal. The server has an emotion response means for acquiring price information from the database and adjusting output based on emotion data analyzed by the emotion engine. The server also has a price calculation means and a result generation means for calculating the total price based on the price information and returning the result to the terminal as well-formed response data. The server and the database are connected via a network.

[0995] Emotion Engine

[0996] The emotion engine is a system that analyzes the data sent from the emotion recognition means and determines the user's emotional state. The emotion engine is managed by the server and generates information to provide offers and discounts according to the user's emotions.

[0997] Specific example explanation

[0998] As a concrete example, let's consider a case where a user orders three "Product A" and one "Option B" and requests a quote. The user enters the necessary information into the input form on the device and presses the "Submit" button to request a quote. At the same time, the device acquires the user's facial expressions and voice, and recognizes emotions such as "I'd be happy if there was a discount."

[0999] The device converts this information into JSON format and sends it to the server. For example, the following data is generated:

[1000] json

[1001] {

[1002] "Product Name": "Product A",

[1003] "Quantity": 3,

[1004] "options": {

[1005] "Option B": 1

[1006] },

[1007] "Emotion": "Expecting"

[1008] }

[1009] The server analyzes the received data and retrieves from the database that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen. The server calculates the total price based on this information and applies a special offer, taking into account the emotional data of "expecting" from the emotion engine.

[1010] The total amount is 3000 yen, and the server converts the calculation result into well-formed data in JSON format as follows:

[1011] json

[1012] {

[1013] "Total amount": "3000 yen",

[1014] "Message": "Special offer discount applied."

[1015] }

[1016] The terminal analyzes the response data from the server and displays on the user interface, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer."

[1017] Prompts for generative AI models

[1018] Here is an example of a prompt to input to a generative AI model:

[1019] I would like to quote a price for a product. The product name is "Product A", the quantity is 3, and the option is "Option B". I would also like a discount.

[1020] This prompt allows the generative AI model to generate an appropriate estimate while taking into account the user's emotions.

[1021] As a result, this system can provide users with quick and accurate estimates and respond flexibly to their emotions.

[1022] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1023] Step 1:

[1024] The user enters product information

[1025] The user enters detailed information such as product name, quantity, and options into the input form on the terminal. For example, the user enters three "Product A"s and one "Option B" and selects "Discount" as a desired condition. This information is used as input data sent to later processing. The input data has the following format:

[1026] Text format

[1027] Product name: Product A

[1028] Quantity: 3

[1029] Option: Option B (Quantity: 1)

[1030] Desired conditions: Discount

[1031] Step 2:

[1032] The user clicks the submit button

[1033] When the user clicks the "Submit" button, the entered data is processed. By clicking the "Submit" button, the terminal sends the data to the next processing step. The input data is converted directly to JSON format data.

[1034] Step 3:

[1035] The terminal converts the input information into JSON format.

[1036] The device converts the product information and desired conditions collected in the input form into JSON format. Specifically, the following JSON data is generated:

[1037] json

[1038] {

[1039] "Product Name": "Product A",

[1040] "Quantity": 3,

[1041] "options": {

[1042] "Option B": 1

[1043] },

[1044] "Desired conditions": "Discount"

[1045] }

[1046] This JSON data will later be the input data to be sent to the server.

[1047] Step 4:

[1048] The device captures the user's facial expressions and voice and generates emotion data.

[1049] The device uses a camera and microphone to capture the user's facial expressions and voice, and uses emotion recognition software to generate emotion data such as "I'm looking forward to it." For example, if a user says, "I'd be happy if there was a discount," the emotion is recognized as "I'm looking forward to it." The generated emotion data is in the following JSON format:

[1050] json

[1051] {

[1052] "Emotion": "Expecting"

[1053] }

[1054] Step 5:

[1055] The device sends the user's input information and emotion data to the server.

[1056] The device sends the converted product information and emotion data to the server as a single JSON data. The final JSON data sent will have the following format:

[1057] json

[1058] {

[1059] "Product Name": "Product A",

[1060] "Quantity": 3,

[1061] "options": {

[1062] "Option B": 1

[1063] },

[1064] "Desired conditions": "Discount",

[1065] "Emotion": "Expecting"

[1066] }

[1067] This data becomes the input data for the next processing step on the server.

[1068] Step 6:

[1069] The server analyzes the received data

[1070] The server parses the JSON data received from the device and extracts the product name, quantity, options, and emotion data. This analysis stores the product information and emotion data in individual variables and data structures, which then become input data for the next price acquisition process.

[1071] Step 7:

[1072] The server retrieves the price information from the database

[1073] The server uses the parsed data to query the database to get pricing information for products and options. For example, the database might return the following pricing information:

[1074] Unit price of product A: 1,000 yen

[1075] Option B unit price: 500 yen

[1076] The acquired price information becomes input data for the next price calculation process.

[1077] Step 8:

[1078] The server calculates the total price

[1079] The server calculates the total price of the items based on the price information it has received. The calculation is done as follows:

[1080] Total price of product A: 1,000 yen x 3 = 3,000 yen

[1081] Total price of Option B: 500 yen x 1 = 500 yen

[1082] Total amount: 3000 yen + 500 yen = 3500 yen

[1083] This 3,500 yen will be the base price and will be the input data for the next emotion response processing.

[1084] Step 9:

[1085] The server adjusts the output taking into account emotional data.

[1086] The server takes into account the emotion data of "expecting" received from the emotion engine and applies special offers and discounts. For example, it adjusts the total price to 500 yen off as a special discount, so that the final total price is 3,000 yen.

[1087] Step 10:

[1088] The server converts the calculation results into well-formed data in JSON format.

[1089] The server converts the final quote result into well-formed data in the following JSON format:

[1090] json

[1091] {

[1092] "Total amount": "3000 yen",

[1093] "Message": "Special offer discount applied."

[1094] }

[1095] This data is sent to the terminal.

[1096] Step 11:

[1097] The device analyzes the response data from the server

[1098] The terminal analyzes the JSON response data received from the server and extracts the total amount and message.

[1099] Step 12:

[1100] The device displays the results in the user interface.

[1101] Based on the data analyzed by the device, the user interface displays the message, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer." This allows the user to quickly and accurately check the estimated results.

[1102] (Application example 2)

[1103] 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."

[1104] Conventional quotation systems provide quick quotes based on detailed product information entered by users, but they lack the flexibility to consider the user's emotional state, which results in insufficient improvement in customer satisfaction or motivation to purchase. Furthermore, they lack the functionality to provide personalized offers and messages when providing user input data and quotation results. This results in a poor user experience.

[1105] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1106] In this invention, the server includes emotion recognition means for analyzing facial expressions and voice data transmitted from a terminal operated by a user to recognize the emotional state, data processing means for analyzing the received data and retrieving price information from a database, price calculation means for calculating a total price based on the retrieved price information and the emotional state, and result generation means for converting the calculation result into well-formed response data and a customized message based on the emotional state and returning it to the terminal, thereby enabling the provision of real-time estimates according to the user's emotions and the application of personalized special offers and discounts.

[1107] The "input means" is a means by which a user inputs detailed information and desired conditions for a product or service.

[1108] The "transmission means" is a means for transmitting the input data, facial expression data, and voice data from the terminal to the server.

[1109] The "emotion recognition means" is a means for analyzing received data, facial expressions, and voice data to recognize an emotional state.

[1110] The "data processing means" is a means for analyzing the data received by the server and obtaining price information from the database.

[1111] The "price calculation means" is a means for calculating the total price based on the price information and emotional state acquired by the server.

[1112] The "result generation means" is a means by which the server converts the calculation result into well-formed response data and a customized message based on the emotional state, and returns the result to the terminal.

[1113] The "display means" is a means for displaying the estimate results and customized messages received by the terminal to the user.

[1114] "Special Offers" are discounts and promotional offers that are tailored to a user's emotional state.

[1115] The present invention provides an instant quote system that allows users to quickly obtain quotes, combined with an emotion engine that recognizes the user's emotions and adjusts output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[1116] First, the device operated by the user provides an interface for inputting detailed product or service information and desired conditions. For example, the user inputs information for purchasing three units of "Product A" and one unit of "Option B." The device also uses a camera and microphone to capture the user's facial expressions and voice, and transmits this as emotion data to the server.

[1117] The server receives the transmitted data and emotional data, and first analyzes the user's emotional state using the emotion recognition means. For example, if the user says, "I'd be happy if there was a discount," the emotion recognition means interprets this as "I'm looking forward to it." Next, the data processing means analyzes the product information entered by the user and retrieves the corresponding price information from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, this information is retrieved.

[1118] The price calculation means calculates the total price based on the acquired price information and the emotional state. For example, if the emotion "expecting" is recognized, the server applies special offers and discounts and adjusts the total price. As a specific example, a quote of 3,500 yen, which is the regular price, may be discounted to 3,000 yen in response to the "expecting" emotion.

[1119] The result generation means converts the calculation result into well-formed response data and creates a customized message based on the emotional state. This data is then sent back to the terminal. The terminal displays the received estimate result and the customized message on the user interface. For example, the user can see a message that reads, "The total estimate is 3,000 yen. A discount has been applied due to a special offer."

[1120] To implement this system, a smartphone (with a camera and microphone) is used. For emotion recognition, a generative AI model called an emotion recognition API is recommended. On the server side, data processing is performed using a web framework such as Flask.

[1121] As a specific example, a prompt sentence is prepared: "Please generate a quote with discounts based on the purchase information for three units of product name 'Product A' and one unit of 'Option B' and the user's expected emotion." Based on this prompt sentence, the system provides an appropriate quote and a message according to the emotion.

[1122] As described above, the instant quotation system of the present invention, which clearly specifies the hardware and software to be used and the specific flow of data processing and calculations, makes it possible to provide highly efficient quotation that will provide high customer satisfaction.

[1123] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1124] Step 1:

[1125] The user inputs details of the product or service and desired conditions through the terminal.

[1126] Specifically, the user enters three "Product A"s and one "Option B" into the input form on the device and clicks the "Submit" button. This information is converted into JSON format data on the device. As a concrete example of input data, the following JSON data is generated:

[1127] json

[1128] {

[1129] "Product Name": "Product A",

[1130] "Quantity": 3,

[1131] "options": {

[1132] "Option B": 1

[1133] }

[1134] }

[1135] Step 2:

[1136] The user's facial expressions and voice are acquired by the terminal.

[1137] The device uses a camera and microphone to capture the user's facial expressions and voice. Specifically, the device captures the user's face in real time and records voice input. The captured emotion data is also converted into JSON format data.

[1138] Step 3:

[1139] The terminal transmits the input product information and emotion data to the server.

[1140] Specifically, the device sends the JSON data of the product information generated earlier and the emotion data obtained from facial and voice analysis to the server as an HTTP request. The sent data will be in the following format:

[1141] json

[1142] {

[1143] "Product information": {

[1144] "Product Name": "Product A",

[1145] "Quantity": 3,

[1146] "options": {

[1147] "Option B": 1

[1148] }

[1149] },

[1150] "Emotion": "Expecting"

[1151] }

[1152] Step 4:

[1153] The server parses the received data.

[1154] The server receives the HTTP request and parses the JSON data. The parsed data is stored in separate variables for further processing. The input includes product information and sentiment data, and the output of the parsing is split into separate variables for each piece of information.

[1155] Step 5:

[1156] An emotion recognition means analyzes emotions.

[1157] The emotion recognition means in the server analyzes the received facial expression and voice data and recognizes the emotional state of the user. The facial expression and voice data are provided as input, and an emotional status such as "expecting" is obtained as output.

[1158] Step 6:

[1159] The data processing means analyzes the product information and obtains price information from the database.

[1160] The data processing means in the server analyzes the product information and queries the database for price information on the corresponding product. As a specific example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, these price information will be obtained. The input is the analyzed product information, and the output is price information for the product and options.

[1161] Step 7:

[1162] A price calculation means calculates the total price.

[1163] The price calculation means in the server calculates the total price based on the acquired price information and emotional state. For example, if the total price of three "products A" and one "option B" is calculated and the emotion is recognized as "expecting," a 10% discount is applied as a special offer. The input is price information and emotional data, and the output is the total price after applying the discount. A specific example is as follows:

[1164] Total price of product A: 1000 yen 3 = 3000 yen

[1165] Total price of Option B: 500 yen 1 = 500 yen

[1166] Total amount: 3000 yen + 500 yen = 3500 yen

[1167] After discount: 3500 yen 0.9 = 3150 yen

[1168] Step 8:

[1169] A result generation means creates well-formed response data and adds a customized message based on the emotion.

[1170] The server converts the results of the calculation into well-formed JSON data and adds a customized message based on the emotion, producing the following example output:

[1171] json

[1172] {

[1173] "Total amount": "3150 yen",

[1174] "Message": "Special offer discount applied."

[1175] }

[1176] Step 9:

[1177] The server transmits the generated response data to the terminal.

[1178] The server sends the generated response data to the terminal as an HTTP response. The input is well-formed data, and the output is an HTTP response.

[1179] Step 10:

[1180] The terminal displays the received estimate result and the customized message to the user.

[1181] The terminal analyzes the response data from the server and displays it on the user interface. The user sees the message "The total estimated price is 3150 yen. A discount has been applied thanks to a special offer." The input is the response data, and the output is the user interface display.

[1182] 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.

[1183] 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.

[1184] 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.

[1185] [Third embodiment]

[1186] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1187] 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.

[1188] 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).

[1189] 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.

[1190] 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.

[1191] 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).

[1192] 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.

[1193] 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.

[1194] 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.

[1195] 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.

[1196] 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.

[1197] 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."

[1198] The present invention relates to an instant quotation system that allows users to quickly obtain a quotation at the proposal stage. This system has a terminal, a server, and a database, and automatically generates a quotation when the user inputs detailed information about a product or service.

[1199] System configuration

[1200] 1. Terminal: A device operated by the user that displays input forms and receives product and service information and desired conditions.

[1201] 2. Server: Receives input data, parses it, retrieves necessary pricing information from the database, performs calculations, and produces well-formed results.

[1202] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[1203] Program processing overview

[1204] User Actions

[1205] The user enters information such as product name, quantity, options, etc. on the terminal and clicks the "Submit" button. For example, if the user wants a quote for "3 units of product A" and "1 unit of option B," they enter these details.

[1206] Terminal handling

[1207] The device converts the information entered by the user into JSON format data, which is then sent to the server as an HTTP POST request. A specific example of JSON data is as follows:

[1208] json

[1209] {

[1210] "Product Name": "Product A",

[1211] "Quantity": 3,

[1212] "options": {

[1213] "Option B": 1

[1214] }

[1215] }

[1216] Server Processing

[1217] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. It then calculates the total price. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, it performs the following calculation:

[1218] Total price of product A: 1,000 yen 3 = 3,000 yen

[1219] Total price of Option B: 500 yen 1 = 500 yen

[1220] Total amount: 3000 yen + 500 yen = 3500 yen

[1221] The server converts the calculation result into well-formed response data and sends it back to the device. The response data has the following format:

[1222] json

[1223] {

[1224] "Total amount": "3500 yen"

[1225] }

[1226] Displaying the results

[1227] The terminal analyzes the response data received from the server and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen" on the screen.

[1228] Specific example explanation

[1229] For example, consider a situation where a user wants to order three units of "Item A" and one unit of "Option B" and would like a quote. The user enters these details on the device and hits the submit button to request a quote. The device sends the data to the server, which parses the data and retrieves the price of each item from a database. The server performs the calculations and sends them back to the device. Finally, the user can quickly see the quote results.

[1230] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, enabling efficient sales activities.

[1231] The processing flow will be explained below.

[1232] Step 1:

[1233] The user accesses the input form on the device and enters detailed product information such as the product name, quantity, options, etc. For example, three "product A"s and one "option B" are entered.

[1234] Step 2:

[1235] The user clicks the "Submit" button on the input form, which causes the information entered by the user to be collected by the device.

[1236] Step 3:

[1237] The terminal converts the data entered by the user into JSON format. For example, the following JSON data is generated:

[1238] json

[1239] {

[1240] "Product Name": "Product A",

[1241] "Quantity": 3,

[1242] "options": {

[1243] "Option B": 1

[1244] }

[1245] }

[1246] Step 4:

[1247] The device sends an HTTP POST request containing the generated JSON data to the server.

[1248] Step 5:

[1249] The server receives an HTTP POST request, parses the received data, and converts the JSON formatted data into an internal format.

[1250] Step 6:

[1251] The server sends a query to the database to obtain the unit price of "Product A" (1,000 yen) and the unit price of "Option B" (500 yen).

[1252] Step 7:

[1253] The server calculates the user's order based on the price information it has obtained. Specifically, it performs the following calculations:

[1254] Total price of product A: 1000 yen 3 = 3000 yen

[1255] Total price of Option B: 500 yen 1 = 500 yen

[1256] Total amount: 3000 yen + 500 yen = 3500 yen

[1257] Step 8:

[1258] The server converts the calculated total price into well-formed response data, for example, in the following JSON format:

[1259] json

[1260] {

[1261] "Total amount": "3500 yen"

[1262] }

[1263] Step 9:

[1264] The server returns the generated response data to the terminal as an HTTP response.

[1265] Step 10:

[1266] The device receives the response data from the server and parses the JSON data.

[1267] Step 11:

[1268] The terminal analyzes the estimate and displays it on the user interface. For example, the screen will say, "The total estimated price is 3,500 yen."

[1269] In this way, the system can quickly perform an estimate calculation based on the information entered by the user and instantly provide the results to the user.

[1270] Example 1

[1271] 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."

[1272] With conventional quotation systems, it often took a long time for users to receive a quote after entering detailed product or service information, hindering efficient sales activities. Another issue was that the input data format was not standardized, making data analysis and price calculations complicated, and prone to errors and delays.

[1273] 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.

[1274] In this invention, the server includes input means for a user to input details of goods or services and desired conditions through an information terminal, transmission means for the information terminal to transmit the input data to the data processing device, data processing means for analyzing the data received by the data processing device and obtaining price information from the storage device, calculation means for calculating the total price based on the price information obtained by the data processing device, response generation means for the data processing device to convert the calculation result into well-formed response data and return it to the information terminal, and display means for displaying the estimate result received by the information terminal to the user. This enables quick and accurate estimate acquisition and realizes efficient sales activities.

[1275] An "information terminal" is a device used by a user to input and display information about products and services.

[1276] A "data processing device" is a device that receives data transmitted from an information terminal, analyzes it, obtains necessary information from a storage device, and processes the data.

[1277] A "memory device" is a database or storage device for storing price information and other related data for goods and services.

[1278] The "input means" is a means for a user to input details and desired conditions of a product or service using an information terminal.

[1279] The "transmitting means" is a means by which the information terminal transmits input data to the data processing device.

[1280] The "data processing means" is a means for analyzing data received by the data processing device and obtaining price information from the storage device.

[1281] The "calculation means" is a means for calculating the total price based on the price information acquired by the data processing device.

[1282] The "response generating means" is a means by which the data processing device converts the calculation result into well-formed response data and returns it to the information terminal.

[1283] The "display means" is a means for displaying the estimate results received by the information terminal to the user.

[1284] The present invention relates to a system that enables a user to quickly and accurately obtain an estimate for a product or service. The system comprises an information terminal, a data processing device, and a storage device.

[1285] User operations

[1286] The user enters the name of the product for which they wish to receive a quote, the quantity, and, if necessary, details of options, via an information terminal (such as a PC or smartphone). For example, the user might enter "three units of product A and one unit of option B." This information is converted by the information terminal into JSON format data and sent to the data processing device as an HTTP POST request.

[1287] Information terminal processing

[1288] The information terminal first converts the information entered by the user into JSON format, and then sends it to the data processing device as an HTTP POST request. As a concrete example, the following data is generated:

[1289] json

[1290] {

[1291] "Product Name": "Product A",

[1292] "Quantity": 3,

[1293] "options": {

[1294] "Option B": 1

[1295] }

[1296] }

[1297] Data processing device processing

[1298] The data processing device receives an HTTP POST request from the information terminal and analyzes the JSON data. Based on the analyzed data, it retrieves the product's base price and option price information from the storage device. For example, if the unit price of product A is 1,000 yen and the unit price of option B is 500 yen, the price is calculated as follows:

[1299] Total price of product A: 1,000 yen 3 = 3,000 yen

[1300] Total price of Option B: 500 yen 1 = 500 yen

[1301] Total amount: 3000 yen + 500 yen = 3500 yen

[1302] Response Generation

[1303] The data processing device converts the calculation result into response data in JSON format and returns it to the information terminal. An example of the response data is as follows:

[1304] json

[1305] {

[1306] "Total amount": "3500 yen"

[1307] }

[1308] Displaying the results

[1309] The information terminal analyzes the JSON data returned from the data processing device and displays the estimate result on the user interface. As a specific example, the terminal screen displays "The total estimated amount is 3,500 yen."

[1310] Specific examples

[1311] For example, a user might get a quote using the following prompt:

[1312] Example prompt sentence:

[1313] I would like to order 3 units of "Item A" and 1 unit of "Option B" and would like a quote. Please calculate the quote.

[1314] This system allows users to obtain quotations quickly and accurately, enabling efficient sales activities. The system efficiently handles a series of processes, from user input to price calculation and result display, significantly improving the accuracy and speed of quotations.

[1315] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1316] Step 1:

[1317] The user enters detailed information about the product or service, as well as desired conditions such as options and quantity, into the input form on the information terminal. For example, the user enters "3 units of product A and 1 unit of option B." The input data format includes items such as product name, quantity, and options.

[1318] input:

[1319] Product name: Product A

[1320] Quantity: 3

[1321] Option: Option B 1 piece

[1322] output:

[1323] The information terminal receives the input data from the user.

[1324] Step 2:

[1325] When the user clicks on the "send" button, a command is initiated to transmit the input data from the information terminal to the data processing device.

[1326] input:

[1327] Detailed product or service information and desired conditions entered by the user.

[1328] output:

[1329] The "Submit" button is clicked and the data is ready to be sent.

[1330] Step 3:

[1331] The terminal converts the user input data into JSON format data. For example, the following JSON data is generated:

[1332] input:

[1333] Detailed product or service information and desired conditions entered by the user.

[1334] output:

[1335] json

[1336] {

[1337] "Product Name": "Product A",

[1338] "Quantity": 3,

[1339] "options": {

[1340] "Option B": 1

[1341] }

[1342] }

[1343] Step 4:

[1344] The terminal transmits the generated JSON data to the data processing device as an HTTP POST request.

[1345] input:

[1346] The data converted to JSON format.

[1347] output:

[1348] It is sent to the data processing device as an HTTP POST request.

[1349] Step 5:

[1350] The server receives the HTTP POST request, parses the JSON data, and extracts information about the product name, quantity, and options from the parsed data.

[1351] input:

[1352] JSON data sent from the terminal.

[1353] output:

[1354] Parsed data (product name, quantity, options).

[1355] Step 6:

[1356] The server queries the storage device to obtain price information for products and options. As a concrete example, assume that the unit price of product A is 1,000 yen and the unit price of option B is 500 yen.

[1357] input:

[1358] Queries based on the parsed data.

[1359] output:

[1360] Price information obtained from storage device (unit price of product A is 1,000 yen, unit price of option B is 500 yen).

[1361] Step 7:

[1362] The server calculates the total price based on the price information it has received. The calculation is done as follows:

[1363] Total price of product A: 1,000 yen 3 = 3,000 yen

[1364] Total price of Option B: 500 yen 1 = 500 yen

[1365] Total amount: 3000 yen + 500 yen = 3500 yen

[1366] input:

[1367] Price information retrieved from storage device.

[1368] output:

[1369] Calculated total price (3,500 yen).

[1370] Step 8:

[1371] The server converts the calculation result into well-formed response data and returns it to the information terminal. For example, the following JSON data is generated:

[1372] input:

[1373] Calculated total price.

[1374] output:

[1375] json

[1376] {

[1377] "Total amount": "3500 yen"

[1378] }

[1379] Step 9:

[1380] The terminal receives the response data returned from the server.

[1381] input:

[1382] The response data sent by the server.

[1383] output:

[1384] Response data received by the terminal.

[1385] Step 10:

[1386] The terminal analyzes the received JSON data and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen."

[1387] input:

[1388] The response data received.

[1389] output:

[1390] The estimate results displayed on the user interface (total estimate amount is 3,500 yen).

[1391] (Application example 1)

[1392] 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."

[1393] In today's world, users require quick quotes when purchasing products or services online. However, conventional systems take a long time to calculate quotes, resulting in a poor user experience. Another issue is that estimating complex combinations of options and quantities is tedious and time-consuming. Therefore, there is a need for a system that allows users to obtain quotes quickly and easily.

[1394] 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.

[1395] In this invention, the server includes a data processing means for analyzing the received data and retrieving price information from a database, a price calculation means for calculating the total price based on the retrieved price information, and a result generation means for converting the calculation result into well-formed response data and returning it to the terminal, thereby enabling the estimate result to be displayed immediately on the user interface.

[1396] "User" means a user of the online system who requests a quote for a product or service.

[1397] A "terminal" is a device operated by a user, and is equipped with input means for inputting detailed information and desired conditions for a product or service.

[1398] The "server" is a central processing unit that analyzes the received data, retrieves the necessary price information from a database, and performs calculations.

[1399] A "database" is an information storage system that stores pricing information such as base prices and option prices for products.

[1400] An "online quote generation system" is a system that instantly generates and provides quotes based on detailed product or service information entered by the user.

[1401] "Data processing means" refers to the function of analyzing data input from a user and making inquiries to a database.

[1402] "Result generation means" refers to the function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[1403] "Price calculation means" refers to a function that calculates the total price using the unit price and quantity of the product and the unit price of the option based on the acquired price information.

[1404] The "user interface" is a display means that displays the estimate results received by the terminal from the server to the user.

[1405] This invention is an online quotation generation system that allows users to input detailed information about products or services online and quickly receive a quotation. The system consists of a terminal operated by the user, a server that analyzes the input data, and a database that stores price information.

[1406] Hardware and software used

[1407] Device: The device that the user operates, such as a smartphone, tablet, or computer.

[1408] Server: A central processing unit that runs the Python-based Flask or Django server software.

[1409] Database: Use MySQL or PostgreSQL to manage product pricing information and option prices.

[1410] Communication protocol: HTTP / HTTPS is used to send and receive data between the device and the server.

[1411] System Operation

[1412] 1. User Action:

[1413] The user uses the terminal to input detailed information such as the product name, quantity, options, etc. Specifically, the user inputs the required information into the input form provided in the user interface and clicks the "Submit" button.

[1414] 2. Terminal processing:

[1415] The device converts the information entered by the user into JSON format data and sends it to the server as an HTTP POST request. At this time, the device automatically formats the input data and processes it for sending to the server.

[1416] 3. Server processing:

[1417] The server receives the HTTP request and parses the JSON data. Then, based on the parsed data, it queries the database for product and option price information. Based on the price information retrieved from the database, it calculates the total price using the product unit price and quantity, and the option unit price.

[1418] 4. Generate calculation results:

[1419] The server converts the calculation result into well-formed response data and returns a JSON-formatted response to the terminal.

[1420] 5. Displaying the results:

[1421] The terminal parses the response data received from the server and displays the estimate results on the user interface. The user can check the final result in the form of "The total estimated amount is XX yen."

[1422] Specific examples

[1423] For example, consider the case where a user orders three "Product A" and one "Option B." The user enters "Product A," "Quantity 3," and "Option B" into the input form on the terminal and presses the "Submit" button. This information is sent from the terminal to the server, and the server retrieves the unit price of "Product A" (e.g., 1,000 yen) and the unit price of "Option B" (e.g., 500 yen) from the database. The server responds by sending back a JSON response with the total amount of "3,500 yen," and the terminal parses this and displays the message "The total estimated amount is 3,500 yen."

[1424] Prompt Sentence Examples

[1425] "If I were to order three items of product A and one item of option B, please let me know the estimated price."

[1426] This allows users to easily obtain quotes and make decisions quickly. This system improves the user experience of online shopping and is very convenient.

[1427] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1428] Step 1:

[1429] The user enters detailed information such as the product name, quantity, and options into the input form on the terminal and clicks the "Submit" button. The entered data includes the product name "Product A", the quantity "3", and the option "Option B".

[1430] Step 2:

[1431] The terminal converts the information entered by the user into JSON format data, which looks like this:

[1432] json

[1433] {

[1434] "Product Name": "Product A",

[1435] "Quantity": 3,

[1436] "options": {

[1437] "Option B": 1

[1438] }

[1439] }

[1440] This is sent to the server as the body of an HTTP POST request.

[1441] Step 3:

[1442] The server receives the HTTP request and parses the JSON data included in the body. The parsed data is stored in a temporary data structure (dictionary variable), and the "product name," "quantity," and "options" fields are extracted.

[1443] Step 4:

[1444] The server queries the database to find the unit price of "Product A" and the unit price of "Option B." Specifically, it executes the following SQL query:

[1445] sql

[1446] SELECT price FROM products WHERE name='Product A';

[1447] SELECT price FROM options WHERE name='Option B';

[1448] The result of this query is that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen.

[1449] Step 5:

[1450] The server calculates the total price based on the obtained price information. The specific calculation is as follows:

[1451] Total price of product A: 1,000 yen 3 = 3,000 yen

[1452] Total price of Option B: 500 yen 1 = 500 yen

[1453] Total amount: 3000 yen + 500 yen = 3500 yen

[1454] Step 6:

[1455] The server converts the calculation result into JSON response data and generates a response like this:

[1456] json

[1457] {

[1458] "Total amount": "3500 yen"

[1459] }

[1460] This response data is sent back to the terminal as the body of the HTTP response.

[1461] Step 7:

[1462] The terminal parses the response data received from the server, extracts the "total amount" value from the parsed data, and displays "The total estimated amount is 3,500 yen" on the user interface.

[1463] Specific operations in the processing flow

[1464] In step 1, the user enters detailed information into an input form and clicks a button.

[1465] In step 2, the entered information is converted to JSON format and an HTTP request is issued to the server.

[1466] In step 3, the server parses the received data and processes it to extract the necessary items.

[1467] Step 4 involves a data calculation where the server queries the database to obtain the required pricing information.

[1468] In step 5, the server calculates the total price of each item and performs a data calculation to calculate the total amount.

[1469] In step 6, the calculation result is converted into JSON-formatted response data and sent from the server to the terminal.

[1470] In step 7, the terminal parses the received data and displays the estimate results on the user interface.

[1471] 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.

[1472] The present invention combines an instant quote system that allows users to quickly obtain quotes with an emotion engine that recognizes the user's emotions and adjusts the output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[1473] System configuration

[1474] 1. Terminal: A device operated by the user that displays input forms, receives product and service information and desired conditions, and also captures the user's facial expressions and voice input.

[1475] 2. Server: Receives input data and sentiment data, analyzes them, retrieves necessary price information from the database, performs calculations, and generates well-formed results.

[1476] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[1477] 4. Emotion engine: Recognizes emotions from the user's facial expressions and voice and provides that information to the server.

[1478] Program processing overview

[1479] User Actions

[1480] The user enters detailed information such as the product name, quantity, and options on the device and clicks the "Submit" button. For example, three "Product A"s and one "Option B" are entered. The device also captures the user's facial expressions and voice.

[1481] Terminal handling

[1482] The device converts the product information entered by the user into JSON format, while at the same time recognizing emotions from the user's facial expressions and voice. For example, if the user's facial expression indicates that they are "considering purchasing" or that they would be happy if there was a discount, the device sends this information to the emotion engine, which then interprets the user's emotion as "expecting."

[1483] The device sends the following JSON data to the server:

[1484] json

[1485] {

[1486] "Product Name": "Product A",

[1487] "Quantity": 3,

[1488] "options": {

[1489] "Option B": 1

[1490] },

[1491] "Emotion": "Expecting"

[1492] }

[1493] Server Processing

[1494] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen:

[1495] Total price of product A: 1000 yen 3 = 3000 yen

[1496] Total price of Option B: 500 yen 1 = 500 yen

[1497] Total amount: 3000 yen + 500 yen = 3500 yen

[1498] Furthermore, the server takes into account the emotion data received from the emotion engine and outputs accordingly. For example, if the user expresses the emotion "expecting," the server may apply special offers or discounts. As a result, the total price may be 3,000 yen.

[1499] The server converts the results into well-formed data in JSON format, such as:

[1500] json

[1501] {

[1502] "Total amount": "3000 yen",

[1503] "Message": "Special offer discount applied."

[1504] }

[1505] Displaying the results

[1506] The terminal analyzes the response data received from the server and displays it in the user interface. For example, it displays "The total estimated amount is 3000 yen. A discount has been applied due to a special offer."

[1507] Specific example explanation

[1508] For example, if a user orders three "product A" and one "option B" and requests a quote, the user enters the information through the terminal and presses the send button to request a quote. In addition, the user's emotion is recognized as "expecting." Based on this information, the server calculates the product price and applies special offers. Finally, the user confirms the quote result, and the discount applied increases the likelihood of closing the deal.

[1509] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, and enables flexible responses based on emotions, resulting in efficient sales activities.

[1510] The processing flow will be explained below.

[1511] Step 1:

[1512] The user accesses the input form on the device and enters detailed product or service information such as product name, quantity, options, etc. For example, three "products A" and one "option B" are entered.

[1513] Step 2:

[1514] The user clicks the "Submit" button on the input form, which causes the entered information to be collected by the device.

[1515] Step 3:

[1516] The device converts the data entered by the user into JSON format, and simultaneously analyzes the user's facial expressions and voice using an emotion engine.

[1517] Step 4:

[1518] The emotion engine analyzes the user's facial expressions and voice and generates emotional data indicating "expectation."

[1519] Step 5:

[1520] The JSON data generated by the device is combined with emotion data and sent as an HTTP POST request to the server. For example, the following JSON data is sent:

[1521] json

[1522] {

[1523] "Product Name": "Product A",

[1524] "Quantity": 3,

[1525] "options": {

[1526] "Option B": 1

[1527] },

[1528] "Emotion": "Expecting"

[1529] }

[1530] Step 6:

[1531] The server receives the HTTP POST request and parses the received JSON data to obtain the details and sentiment of the user's desired product.

[1532] Step 7:

[1533] The server sends a query to the database to get the unit prices of "Product A" and "Option B." For example, the unit price of "Product A" is 1,000 yen, and the unit price of "Option B" is 500 yen.

[1534] Step 8:

[1535] The server calculates the total price based on the unit price obtained. Specifically, it calculates the following:

[1536] Total price of product A: 1,000 yen 3 = 3,000 yen

[1537] Total price of Option B: 500 yen 1 = 500 yen

[1538] Total amount: 3000 yen + 500 yen = 3500 yen

[1539] Step 9:

[1540] The server considers the emotion data and if the user shows the "expected" emotion, it will apply a special offer or discount, for example, a discount that brings the total price to 3000 yen.

[1541] Step 10:

[1542] The server converts the result of the calculation into well-formed response data, for example generating the following JSON data:

[1543] json

[1544] {

[1545] "Total amount": "3000 yen",

[1546] "Message": "Special offer discount applied."

[1547] }

[1548] Step 11:

[1549] The server returns the generated response data to the terminal as an HTTP response.

[1550] Step 12:

[1551] The terminal analyzes the response data received from the server.

[1552] Step 13:

[1553] The terminal analyzes the estimate and displays the result on the user interface. For example, it displays "The total estimate is 3000 yen. A discount has been applied due to a special offer."

[1554] This process allows the system to generate and provide quick and flexible estimates to users based on their input information and emotions.

[1555] Example 2

[1556] 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."

[1557] In conventional quotation systems, it was difficult for users to obtain a quick and accurate quotation, and it was also difficult to respond flexibly while taking into account the user's feelings. In particular, quotation results that ignored the user's feelings, such as expectations, reduced the possibility of concluding a business deal.

[1558] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a data processing means for analyzing received data and acquiring price information from a database, an emotion response means for adjusting output based on emotion data received from the emotion engine, and a price calculation means for calculating the total price based on the acquired price information. This makes it possible to provide a quick and accurate estimate and flexibly respond to the user's emotions.

[1559] "Input means" is a function that allows a user to input details of goods or services and desired conditions through a terminal.

[1560] The "transmission means" is a function that allows the terminal to transmit input data to the server.

[1561] "Emotion recognition means" is a function that allows the terminal to acquire the user's facial expressions and voice and generate emotion data.

[1562] The "emotion engine" is a system that analyzes the emotion data sent from the emotion recognition means and determines the user's emotional state.

[1563] The "data processing means" is a function that analyzes the data received by the server and retrieves price information from the database.

[1564] The "emotion response means" is a function that adjusts the output based on the emotion data received by the server from the emotion engine.

[1565] The "price calculation means" is a function that calculates the total price based on the price information acquired by the server.

[1566] The "result generation means" is a function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[1567] The "display means" is a function that displays the estimate results received by the terminal to the user.

[1568] The present invention provides a system for providing a user with a quick and accurate estimate, and further has a function for recognizing and responding to the user's emotions. Specific embodiments of the system will be described below.

[1569] System Configuration

[1570] Terminal

[1571] A terminal is a device operated by a user, and is equipped with an input means for the user to input detailed information about products and services and their desired conditions. It also includes emotion recognition means for acquiring the user's facial expressions and voice and processing them as emotional data. Specific examples of hardware include personal computers (PCs), tablets, and smartphones. Software used includes a web browser and dedicated applications for displaying input forms and transmitting data. A camera is used for facial recognition, and a microphone is used for voice recognition.

[1572] server

[1573] The server has a data processing means for receiving and analyzing data sent from the terminal. The server has an emotion response means for acquiring price information from the database and adjusting output based on emotion data analyzed by the emotion engine. The server also has a price calculation means and a result generation means for calculating the total price based on the price information and returning the result to the terminal as well-formed response data. The server and the database are connected via a network.

[1574] Emotion Engine

[1575] The emotion engine is a system that analyzes the data sent from the emotion recognition means and determines the user's emotional state. The emotion engine is managed by the server and generates information to provide offers and discounts according to the user's emotions.

[1576] Specific example explanation

[1577] As a concrete example, let's consider a case where a user orders three "Product A" and one "Option B" and requests a quote. The user enters the necessary information into the input form on the device and presses the "Submit" button to request a quote. At the same time, the device acquires the user's facial expressions and voice, and recognizes emotions such as "I'd be happy if there was a discount."

[1578] The device converts this information into JSON format and sends it to the server. For example, the following data is generated:

[1579] json

[1580] {

[1581] "Product Name": "Product A",

[1582] "Quantity": 3,

[1583] "options": {

[1584] "Option B": 1

[1585] },

[1586] "Emotion": "Expecting"

[1587] }

[1588] The server analyzes the received data and retrieves from the database that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen. The server calculates the total price based on this information and applies a special offer, taking into account the emotional data of "expecting" from the emotion engine.

[1589] The total amount is 3000 yen, and the server converts the calculation result into well-formed data in JSON format as follows:

[1590] json

[1591] {

[1592] "Total amount": "3000 yen",

[1593] "Message": "Special offer discount applied."

[1594] }

[1595] The terminal analyzes the response data from the server and displays on the user interface, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer."

[1596] Prompts for generative AI models

[1597] Here is an example of a prompt to input to a generative AI model:

[1598] I would like to quote a price for a product. The product name is "Product A", the quantity is 3, and the option is "Option B". I would also like a discount.

[1599] This prompt allows the generative AI model to generate an appropriate estimate while taking into account the user's emotions.

[1600] As a result, this system can provide users with quick and accurate estimates and respond flexibly to their emotions.

[1601] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1602] Step 1:

[1603] The user enters product information

[1604] The user enters detailed information such as product name, quantity, and options into the input form on the terminal. For example, the user enters three "Product A"s and one "Option B" and selects "Discount" as a desired condition. This information is used as input data sent to later processing. The input data has the following format:

[1605] Text format

[1606] Product name: Product A

[1607] Quantity: 3

[1608] Option: Option B (Quantity: 1)

[1609] Desired conditions: Discount

[1610] Step 2:

[1611] The user clicks the submit button

[1612] When the user clicks the "Submit" button, the entered data is processed. By clicking the "Submit" button, the terminal sends the data to the next processing step. The input data is converted directly to JSON format data.

[1613] Step 3:

[1614] The terminal converts the input information into JSON format.

[1615] The device converts the product information and desired conditions collected in the input form into JSON format. Specifically, the following JSON data is generated:

[1616] json

[1617] {

[1618] "Product Name": "Product A",

[1619] "Quantity": 3,

[1620] "options": {

[1621] "Option B": 1

[1622] },

[1623] "Desired conditions": "Discount"

[1624] }

[1625] This JSON data will later be the input data to be sent to the server.

[1626] Step 4:

[1627] The device captures the user's facial expressions and voice and generates emotion data.

[1628] The device uses a camera and microphone to capture the user's facial expressions and voice, and uses emotion recognition software to generate emotion data such as "I'm looking forward to it." For example, if a user says, "I'd be happy if there was a discount," the emotion is recognized as "I'm looking forward to it." The generated emotion data is in the following JSON format:

[1629] json

[1630] {

[1631] "Emotion": "Expecting"

[1632] }

[1633] Step 5:

[1634] The device sends the user's input information and emotion data to the server.

[1635] The device sends the converted product information and emotion data to the server as a single JSON data. The final JSON data sent will have the following format:

[1636] json

[1637] {

[1638] "Product Name": "Product A",

[1639] "Quantity": 3,

[1640] "options": {

[1641] "Option B": 1

[1642] },

[1643] "Desired conditions": "Discount",

[1644] "Emotion": "Expecting"

[1645] }

[1646] This data becomes the input data for the next processing step on the server.

[1647] Step 6:

[1648] The server analyzes the received data

[1649] The server parses the JSON data received from the device and extracts the product name, quantity, options, and emotion data. This analysis stores the product information and emotion data in individual variables and data structures, which then become input data for the next price acquisition process.

[1650] Step 7:

[1651] The server retrieves the price information from the database

[1652] The server uses the parsed data to query the database to get pricing information for products and options. For example, the database might return the following pricing information:

[1653] Unit price of product A: 1,000 yen

[1654] Option B unit price: 500 yen

[1655] The acquired price information becomes input data for the next price calculation process.

[1656] Step 8:

[1657] The server calculates the total price

[1658] The server calculates the total price of the items based on the price information it has received. The calculation is done as follows:

[1659] Total price of product A: 1,000 yen x 3 = 3,000 yen

[1660] Total price of Option B: 500 yen x 1 = 500 yen

[1661] Total amount: 3000 yen + 500 yen = 3500 yen

[1662] This 3,500 yen will be the base price and will be the input data for the next emotion response processing.

[1663] Step 9:

[1664] The server adjusts the output taking into account emotional data.

[1665] The server takes into account the emotion data of "expecting" received from the emotion engine and applies special offers and discounts. For example, it adjusts the total price to 500 yen off as a special discount, so that the final total price is 3,000 yen.

[1666] Step 10:

[1667] The server converts the calculation results into well-formed data in JSON format.

[1668] The server converts the final quote result into well-formed data in the following JSON format:

[1669] json

[1670] {

[1671] "Total amount": "3000 yen",

[1672] "Message": "Special offer discount applied."

[1673] }

[1674] This data is sent to the terminal.

[1675] Step 11:

[1676] The device analyzes the response data from the server

[1677] The terminal analyzes the JSON response data received from the server and extracts the total amount and message.

[1678] Step 12:

[1679] The device displays the results in the user interface.

[1680] Based on the data analyzed by the device, the user interface displays the message, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer." This allows the user to quickly and accurately check the estimated results.

[1681] (Application example 2)

[1682] 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."

[1683] Conventional quotation systems provide quick quotes based on detailed product information entered by users, but they lack the flexibility to consider the user's emotional state, which results in insufficient improvement in customer satisfaction or motivation to purchase. Furthermore, they lack the functionality to provide personalized offers and messages when providing user input data and quotation results. This results in a poor user experience.

[1684] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1685] In this invention, the server includes emotion recognition means for analyzing facial expressions and voice data transmitted from a terminal operated by a user to recognize the emotional state, data processing means for analyzing the received data and retrieving price information from a database, price calculation means for calculating a total price based on the retrieved price information and the emotional state, and result generation means for converting the calculation result into well-formed response data and a customized message based on the emotional state and returning it to the terminal, thereby enabling the provision of real-time estimates according to the user's emotions and the application of personalized special offers and discounts.

[1686] The "input means" is a means by which a user inputs detailed information and desired conditions for a product or service.

[1687] The "transmission means" is a means for transmitting the input data, facial expression data, and voice data from the terminal to the server.

[1688] The "emotion recognition means" is a means for analyzing received data, facial expressions, and voice data to recognize an emotional state.

[1689] The "data processing means" is a means for analyzing the data received by the server and obtaining price information from the database.

[1690] The "price calculation means" is a means for calculating the total price based on the price information and emotional state acquired by the server.

[1691] The "result generation means" is a means by which the server converts the calculation result into well-formed response data and a customized message based on the emotional state, and returns the result to the terminal.

[1692] The "display means" is a means for displaying the estimate results and customized messages received by the terminal to the user.

[1693] "Special Offers" are discounts and promotional offers that are tailored to a user's emotional state.

[1694] The present invention provides an instant quote system that allows users to quickly obtain quotes, combined with an emotion engine that recognizes the user's emotions and adjusts output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[1695] First, the device operated by the user provides an interface for inputting detailed product or service information and desired conditions. For example, the user inputs information for purchasing three units of "Product A" and one unit of "Option B." The device also uses a camera and microphone to capture the user's facial expressions and voice, and transmits this as emotion data to the server.

[1696] The server receives the transmitted data and emotional data, and first analyzes the user's emotional state using the emotion recognition means. For example, if the user says, "I'd be happy if there was a discount," the emotion recognition means interprets this as "I'm looking forward to it." Next, the data processing means analyzes the product information entered by the user and retrieves the corresponding price information from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, this information is retrieved.

[1697] The price calculation means calculates the total price based on the acquired price information and the emotional state. For example, if the emotion "expecting" is recognized, the server applies special offers and discounts and adjusts the total price. As a specific example, a quote of 3,500 yen, which is the regular price, may be discounted to 3,000 yen in response to the "expecting" emotion.

[1698] The result generation means converts the calculation result into well-formed response data and creates a customized message based on the emotional state. This data is then sent back to the terminal. The terminal displays the received estimate result and the customized message on the user interface. For example, the user can see a message that reads, "The total estimate is 3,000 yen. A discount has been applied due to a special offer."

[1699] To implement this system, a smartphone (with a camera and microphone) is used. For emotion recognition, a generative AI model called an emotion recognition API is recommended. On the server side, data processing is performed using a web framework such as Flask.

[1700] As a specific example, a prompt sentence is prepared: "Please generate a quote with discounts based on the purchase information for three units of product name 'Product A' and one unit of 'Option B' and the user's expected emotion." Based on this prompt sentence, the system provides an appropriate quote and a message according to the emotion.

[1701] As described above, the instant quotation system of the present invention, which clearly specifies the hardware and software to be used and the specific flow of data processing and calculations, makes it possible to provide highly efficient quotation that will provide high customer satisfaction.

[1702] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1703] Step 1:

[1704] The user inputs details of the product or service and desired conditions through the terminal.

[1705] Specifically, the user enters three "Product A"s and one "Option B" into the input form on the device and clicks the "Submit" button. This information is converted into JSON format data on the device. As a concrete example of input data, the following JSON data is generated:

[1706] json

[1707] {

[1708] "Product Name": "Product A",

[1709] "Quantity": 3,

[1710] "options": {

[1711] "Option B": 1

[1712] }

[1713] }

[1714] Step 2:

[1715] The user's facial expressions and voice are acquired by the terminal.

[1716] The device uses a camera and microphone to capture the user's facial expressions and voice. Specifically, the device captures the user's face in real time and records voice input. The captured emotion data is also converted into JSON format data.

[1717] Step 3:

[1718] The terminal transmits the input product information and emotion data to the server.

[1719] Specifically, the device sends the JSON data of the product information generated earlier and the emotion data obtained from facial and voice analysis to the server as an HTTP request. The sent data will be in the following format:

[1720] json

[1721] {

[1722] "Product information": {

[1723] "Product Name": "Product A",

[1724] "Quantity": 3,

[1725] "options": {

[1726] "Option B": 1

[1727] }

[1728] },

[1729] "Emotion": "Expecting"

[1730] }

[1731] Step 4:

[1732] The server parses the received data.

[1733] The server receives the HTTP request and parses the JSON data. The parsed data is stored in separate variables for further processing. The input includes product information and sentiment data, and the output of the parsing is split into separate variables for each piece of information.

[1734] Step 5:

[1735] An emotion recognition means analyzes emotions.

[1736] The emotion recognition means in the server analyzes the received facial expression and voice data and recognizes the emotional state of the user. The facial expression and voice data are provided as input, and an emotional status such as "expecting" is obtained as output.

[1737] Step 6:

[1738] The data processing means analyzes the product information and obtains price information from the database.

[1739] The data processing means in the server analyzes the product information and queries the database for price information on the corresponding product. As a specific example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, these price information will be obtained. The input is the analyzed product information, and the output is price information for the product and options.

[1740] Step 7:

[1741] A price calculation means calculates the total price.

[1742] The price calculation means in the server calculates the total price based on the acquired price information and emotional state. For example, if the total price of three "products A" and one "option B" is calculated and the emotion is recognized as "expecting," a 10% discount is applied as a special offer. The input is price information and emotional data, and the output is the total price after applying the discount. A specific example is as follows:

[1743] Total price of product A: 1000 yen 3 = 3000 yen

[1744] Total price of Option B: 500 yen 1 = 500 yen

[1745] Total amount: 3000 yen + 500 yen = 3500 yen

[1746] After discount: 3500 yen 0.9 = 3150 yen

[1747] Step 8:

[1748] A result generation means creates well-formed response data and adds a customized message based on the emotion.

[1749] The server converts the results of the calculation into well-formed JSON data and adds a customized message based on the emotion, producing the following example output:

[1750] json

[1751] {

[1752] "Total amount": "3150 yen",

[1753] "Message": "Special offer discount applied."

[1754] }

[1755] Step 9:

[1756] The server transmits the generated response data to the terminal.

[1757] The server sends the generated response data to the terminal as an HTTP response. The input is well-formed data, and the output is an HTTP response.

[1758] Step 10:

[1759] The terminal displays the received estimate result and the customized message to the user.

[1760] The terminal analyzes the response data from the server and displays it on the user interface. The user sees the message "The total estimated price is 3150 yen. A discount has been applied thanks to a special offer." The input is the response data, and the output is the user interface display.

[1761] 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.

[1762] 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.

[1763] 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.

[1764] [Fourth embodiment]

[1765] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1766] 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.

[1767] 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).

[1768] 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.

[1769] 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.

[1770] 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).

[1771] 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.

[1772] 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.

[1773] 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.

[1774] 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.

[1775] 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.

[1776] 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.

[1777] 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."

[1778] The present invention relates to an instant quotation system that allows users to quickly obtain a quotation at the proposal stage. This system has a terminal, a server, and a database, and automatically generates a quotation when the user inputs detailed information about a product or service.

[1779] System configuration

[1780] 1. Terminal: A device operated by the user that displays input forms and receives product and service information and desired conditions.

[1781] 2. Server: Receives input data, parses it, retrieves necessary pricing information from the database, performs calculations, and produces well-formed results.

[1782] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[1783] Program processing overview

[1784] User Actions

[1785] The user enters information such as product name, quantity, options, etc. on the terminal and clicks the "Submit" button. For example, if the user wants a quote for "3 units of product A" and "1 unit of option B," they enter these details.

[1786] Terminal handling

[1787] The device converts the information entered by the user into JSON format data, which is then sent to the server as an HTTP POST request. A specific example of JSON data is as follows:

[1788] json

[1789] {

[1790] "Product Name": "Product A",

[1791] "Quantity": 3,

[1792] "options": {

[1793] "Option B": 1

[1794] }

[1795] }

[1796] Server Processing

[1797] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. It then calculates the total price. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, it performs the following calculation:

[1798] Total price of product A: 1,000 yen 3 = 3,000 yen

[1799] Total price of Option B: 500 yen 1 = 500 yen

[1800] Total amount: 3000 yen + 500 yen = 3500 yen

[1801] The server converts the calculation result into well-formed response data and sends it back to the device. The response data has the following format:

[1802] json

[1803] {

[1804] "Total amount": "3500 yen"

[1805] }

[1806] Displaying the results

[1807] The terminal analyzes the response data received from the server and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen" on the screen.

[1808] Specific example explanation

[1809] For example, consider a situation where a user wants to order three units of "Item A" and one unit of "Option B" and would like a quote. The user enters these details on the device and hits the submit button to request a quote. The device sends the data to the server, which parses the data and retrieves the price of each item from a database. The server performs the calculations and sends them back to the device. Finally, the user can quickly see the quote results.

[1810] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, enabling efficient sales activities.

[1811] The processing flow will be explained below.

[1812] Step 1:

[1813] The user accesses the input form on the device and enters detailed product information such as the product name, quantity, options, etc. For example, three "product A"s and one "option B" are entered.

[1814] Step 2:

[1815] The user clicks the "Submit" button on the input form, which causes the information entered by the user to be collected by the device.

[1816] Step 3:

[1817] The terminal converts the data entered by the user into JSON format. For example, the following JSON data is generated:

[1818] json

[1819] {

[1820] "Product Name": "Product A",

[1821] "Quantity": 3,

[1822] "options": {

[1823] "Option B": 1

[1824] }

[1825] }

[1826] Step 4:

[1827] The device sends an HTTP POST request containing the generated JSON data to the server.

[1828] Step 5:

[1829] The server receives an HTTP POST request, parses the received data, and converts the JSON formatted data into an internal format.

[1830] Step 6:

[1831] The server sends a query to the database to obtain the unit price of "Product A" (1,000 yen) and the unit price of "Option B" (500 yen).

[1832] Step 7:

[1833] The server calculates the user's order based on the price information it has obtained. Specifically, it performs the following calculations:

[1834] Total price of product A: 1000 yen 3 = 3000 yen

[1835] Total price of Option B: 500 yen 1 = 500 yen

[1836] Total amount: 3000 yen + 500 yen = 3500 yen

[1837] Step 8:

[1838] The server converts the calculated total price into well-formed response data, for example, in the following JSON format:

[1839] json

[1840] {

[1841] "Total amount": "3500 yen"

[1842] }

[1843] Step 9:

[1844] The server returns the generated response data to the terminal as an HTTP response.

[1845] Step 10:

[1846] The device receives the response data from the server and parses the JSON data.

[1847] Step 11:

[1848] The terminal analyzes the estimate and displays it on the user interface. For example, the screen will say, "The total estimated price is 3,500 yen."

[1849] In this way, the system can quickly perform an estimate calculation based on the information entered by the user and instantly provide the results to the user.

[1850] Example 1

[1851] 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."

[1852] With conventional quotation systems, it often took a long time for users to receive a quote after entering detailed product or service information, hindering efficient sales activities. Another issue was that the input data format was not standardized, making data analysis and price calculations complicated, and prone to errors and delays.

[1853] 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.

[1854] In this invention, the server includes input means for a user to input details of goods or services and desired conditions through an information terminal, transmission means for the information terminal to transmit the input data to the data processing device, data processing means for analyzing the data received by the data processing device and obtaining price information from the storage device, calculation means for calculating the total price based on the price information obtained by the data processing device, response generation means for the data processing device to convert the calculation result into well-formed response data and return it to the information terminal, and display means for displaying the estimate result received by the information terminal to the user. This enables quick and accurate estimate acquisition and realizes efficient sales activities.

[1855] An "information terminal" is a device used by a user to input and display information about products and services.

[1856] A "data processing device" is a device that receives data transmitted from an information terminal, analyzes it, obtains necessary information from a storage device, and processes the data.

[1857] A "memory device" is a database or storage device for storing price information and other related data for goods and services.

[1858] The "input means" is a means for a user to input details and desired conditions of a product or service using an information terminal.

[1859] The "transmitting means" is a means by which the information terminal transmits input data to the data processing device.

[1860] The "data processing means" is a means for analyzing data received by the data processing device and obtaining price information from the storage device.

[1861] The "calculation means" is a means for calculating the total price based on the price information acquired by the data processing device.

[1862] The "response generating means" is a means by which the data processing device converts the calculation result into well-formed response data and returns it to the information terminal.

[1863] The "display means" is a means for displaying the estimate results received by the information terminal to the user.

[1864] The present invention relates to a system that enables a user to quickly and accurately obtain an estimate for a product or service. The system comprises an information terminal, a data processing device, and a storage device.

[1865] User operations

[1866] The user enters the name of the product for which they wish to receive a quote, the quantity, and, if necessary, details of options, via an information terminal (such as a PC or smartphone). For example, the user might enter "three units of product A and one unit of option B." This information is converted by the information terminal into JSON format data and sent to the data processing device as an HTTP POST request.

[1867] Information terminal processing

[1868] The information terminal first converts the information entered by the user into JSON format, and then sends it to the data processing device as an HTTP POST request. As a concrete example, the following data is generated:

[1869] json

[1870] {

[1871] "Product Name": "Product A",

[1872] "Quantity": 3,

[1873] "options": {

[1874] "Option B": 1

[1875] }

[1876] }

[1877] Data processing device processing

[1878] The data processing device receives an HTTP POST request from the information terminal and analyzes the JSON data. Based on the analyzed data, it retrieves the product's base price and option price information from the storage device. For example, if the unit price of product A is 1,000 yen and the unit price of option B is 500 yen, the price is calculated as follows:

[1879] Total price of product A: 1,000 yen 3 = 3,000 yen

[1880] Total price of Option B: 500 yen 1 = 500 yen

[1881] Total amount: 3000 yen + 500 yen = 3500 yen

[1882] Response Generation

[1883] The data processing device converts the calculation result into response data in JSON format and returns it to the information terminal. An example of the response data is as follows:

[1884] json

[1885] {

[1886] "Total amount": "3500 yen"

[1887] }

[1888] Displaying the results

[1889] The information terminal analyzes the JSON data returned from the data processing device and displays the estimate result on the user interface. As a specific example, the terminal screen displays "The total estimated amount is 3,500 yen."

[1890] Specific examples

[1891] For example, a user might get a quote using the following prompt:

[1892] Example prompt sentence:

[1893] I would like to order 3 units of "Item A" and 1 unit of "Option B" and would like a quote. Please calculate the quote.

[1894] This system allows users to obtain quotations quickly and accurately, enabling efficient sales activities. The system efficiently handles a series of processes, from user input to price calculation and result display, significantly improving the accuracy and speed of quotations.

[1895] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1896] Step 1:

[1897] The user enters detailed information about the product or service, as well as desired conditions such as options and quantity, into the input form on the information terminal. For example, the user enters "3 units of product A and 1 unit of option B." The input data format includes items such as product name, quantity, and options.

[1898] input:

[1899] Product name: Product A

[1900] Quantity: 3

[1901] Option: Option B 1 piece

[1902] output:

[1903] The information terminal receives the input data from the user.

[1904] Step 2:

[1905] When the user clicks on the "send" button, a command is initiated to transmit the input data from the information terminal to the data processing device.

[1906] input:

[1907] Detailed product or service information and desired conditions entered by the user.

[1908] output:

[1909] The "Submit" button is clicked and the data is ready to be sent.

[1910] Step 3:

[1911] The terminal converts the user input data into JSON format data. For example, the following JSON data is generated:

[1912] input:

[1913] Detailed product or service information and desired conditions entered by the user.

[1914] output:

[1915] json

[1916] {

[1917] "Product Name": "Product A",

[1918] "Quantity": 3,

[1919] "options": {

[1920] "Option B": 1

[1921] }

[1922] }

[1923] Step 4:

[1924] The terminal transmits the generated JSON data to the data processing device as an HTTP POST request.

[1925] input:

[1926] The data converted to JSON format.

[1927] output:

[1928] It is sent to the data processing device as an HTTP POST request.

[1929] Step 5:

[1930] The server receives the HTTP POST request, parses the JSON data, and extracts information about the product name, quantity, and options from the parsed data.

[1931] input:

[1932] JSON data sent from the terminal.

[1933] output:

[1934] Parsed data (product name, quantity, options).

[1935] Step 6:

[1936] The server queries the storage device to obtain price information for products and options. As a concrete example, assume that the unit price of product A is 1,000 yen and the unit price of option B is 500 yen.

[1937] input:

[1938] Queries based on the parsed data.

[1939] output:

[1940] Price information obtained from storage device (unit price of product A is 1,000 yen, unit price of option B is 500 yen).

[1941] Step 7:

[1942] The server calculates the total price based on the price information it has received. The calculation is done as follows:

[1943] Total price of product A: 1,000 yen 3 = 3,000 yen

[1944] Total price of Option B: 500 yen 1 = 500 yen

[1945] Total amount: 3000 yen + 500 yen = 3500 yen

[1946] input:

[1947] Price information retrieved from storage device.

[1948] output:

[1949] Calculated total price (3,500 yen).

[1950] Step 8:

[1951] The server converts the calculation result into well-formed response data and returns it to the information terminal. For example, the following JSON data is generated:

[1952] input:

[1953] Calculated total price.

[1954] output:

[1955] json

[1956] {

[1957] "Total amount": "3500 yen"

[1958] }

[1959] Step 9:

[1960] The terminal receives the response data returned from the server.

[1961] input:

[1962] The response data sent by the server.

[1963] output:

[1964] Response data received by the terminal.

[1965] Step 10:

[1966] The terminal analyzes the received JSON data and displays the estimate result on the user interface. For example, it displays "The total estimated amount is 3,500 yen."

[1967] input:

[1968] The response data received.

[1969] output:

[1970] The estimate results displayed on the user interface (total estimate amount is 3,500 yen).

[1971] (Application example 1)

[1972] 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."

[1973] In today's world, users require quick quotes when purchasing products or services online. However, conventional systems take a long time to calculate quotes, resulting in a poor user experience. Another issue is that estimating complex combinations of options and quantities is tedious and time-consuming. Therefore, there is a need for a system that allows users to obtain quotes quickly and easily.

[1974] 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.

[1975] In this invention, the server includes a data processing means for analyzing the received data and retrieving price information from a database, a price calculation means for calculating the total price based on the retrieved price information, and a result generation means for converting the calculation result into well-formed response data and returning it to the terminal, thereby enabling the estimate result to be displayed immediately on the user interface.

[1976] "User" means a user of the online system who requests a quote for a product or service.

[1977] A "terminal" is a device operated by a user, and is equipped with input means for inputting detailed information and desired conditions for a product or service.

[1978] The "server" is a central processing unit that analyzes the received data, retrieves the necessary price information from a database, and performs calculations.

[1979] A "database" is an information storage system that stores pricing information such as base prices and option prices for products.

[1980] An "online quote generation system" is a system that instantly generates and provides quotes based on detailed product or service information entered by the user.

[1981] "Data processing means" refers to the function of analyzing data input from a user and making inquiries to a database.

[1982] "Result generation means" refers to the function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[1983] "Price calculation means" refers to a function that calculates the total price using the unit price and quantity of the product and the unit price of the option based on the acquired price information.

[1984] The "user interface" is a display means that displays the estimate results received by the terminal from the server to the user.

[1985] This invention is an online quotation generation system that allows users to input detailed information about products and services online and quickly receive a quotation. The system consists of a terminal operated by the user, a server that analyzes the input data, and a database that stores price information.

[1986] Hardware and software used

[1987] Device: The device that the user operates, such as a smartphone, tablet, or computer.

[1988] Server: A central processing unit that runs the Python-based Flask or Django server software.

[1989] Database: Use MySQL or PostgreSQL to manage product pricing information and option prices.

[1990] Communication protocol: HTTP / HTTPS is used to send and receive data between the device and the server.

[1991] System Operation

[1992] 1. User Action:

[1993] The user uses the terminal to input detailed information such as the product name, quantity, options, etc. Specifically, the user inputs the required information into the input form provided in the user interface and clicks the "Submit" button.

[1994] 2. Terminal processing:

[1995] The device converts the information entered by the user into JSON format data and sends it to the server as an HTTP POST request. At this time, the device automatically formats the input data and processes it for sending to the server.

[1996] 3. Server processing:

[1997] The server receives the HTTP request and parses the JSON data. Then, based on the parsed data, it queries the database for product and option price information. Based on the price information retrieved from the database, it calculates the total price using the product unit price and quantity, and the option unit price.

[1998] 4. Generate calculation results:

[1999] The server converts the calculation result into well-formed response data and returns a JSON-formatted response to the terminal.

[2000] 5. Displaying the results:

[2001] The terminal parses the response data received from the server and displays the estimate results on the user interface. The user can check the final result in the form of "The total estimated amount is XX yen."

[2002] Specific examples

[2003] For example, consider the case where a user orders three "Product A" and one "Option B." The user enters "Product A," "Quantity 3," and "Option B" into the input form on the terminal and presses the "Submit" button. This information is sent from the terminal to the server, and the server retrieves the unit price of "Product A" (e.g., 1,000 yen) and the unit price of "Option B" (e.g., 500 yen) from the database. The server responds by sending back a JSON response with the total amount of "3,500 yen," and the terminal parses this and displays the message "The total estimated amount is 3,500 yen."

[2004] Prompt Sentence Examples

[2005] "If I were to order three items of product A and one item of option B, please let me know the estimated price."

[2006] This allows users to easily obtain quotes and make decisions quickly. This system improves the user experience of online shopping and is very convenient.

[2007] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2008] Step 1:

[2009] The user enters detailed information such as the product name, quantity, and options into the input form on the terminal and clicks the "Submit" button. The entered data includes the product name "Product A", the quantity "3", and the option "Option B".

[2010] Step 2:

[2011] The terminal converts the information entered by the user into JSON format data, which looks like this:

[2012] json

[2013] {

[2014] "Product Name": "Product A",

[2015] "Quantity": 3,

[2016] "options": {

[2017] "Option B": 1

[2018] }

[2019] }

[2020] This is sent to the server as the body of an HTTP POST request.

[2021] Step 3:

[2022] The server receives the HTTP request and parses the JSON data included in the body. The parsed data is stored in a temporary data structure (dictionary variable), and the "product name," "quantity," and "options" fields are extracted.

[2023] Step 4:

[2024] The server queries the database to find the unit price of "Product A" and the unit price of "Option B." Specifically, it executes the following SQL query:

[2025] sql

[2026] SELECT price FROM products WHERE name='Product A';

[2027] SELECT price FROM options WHERE name='Option B';

[2028] The result of this query is that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen.

[2029] Step 5:

[2030] The server calculates the total price based on the obtained price information. The specific calculation is as follows:

[2031] Total price of product A: 1,000 yen 3 = 3,000 yen

[2032] Total price of Option B: 500 yen 1 = 500 yen

[2033] Total amount: 3000 yen + 500 yen = 3500 yen

[2034] Step 6:

[2035] The server converts the calculation result into JSON response data and generates a response like this:

[2036] json

[2037] {

[2038] "Total amount": "3500 yen"

[2039] }

[2040] This response data is sent back to the terminal as the body of the HTTP response.

[2041] Step 7:

[2042] The terminal parses the response data received from the server, extracts the "total amount" value from the parsed data, and displays "The total estimated amount is 3,500 yen" on the user interface.

[2043] Specific operations in the processing flow

[2044] In step 1, the user enters detailed information into an input form and clicks a button.

[2045] In step 2, the entered information is converted to JSON format and an HTTP request is issued to the server.

[2046] In step 3, the server parses the received data and processes it to extract the necessary items.

[2047] Step 4 involves a data calculation where the server queries the database to obtain the required pricing information.

[2048] In step 5, the server calculates the total price of each item and performs a data calculation to calculate the total amount.

[2049] In step 6, the calculation result is converted into JSON-formatted response data and sent from the server to the terminal.

[2050] In step 7, the terminal parses the received data and displays the estimate results on the user interface.

[2051] 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.

[2052] The present invention combines an instant quote system that allows users to quickly obtain quotes with an emotion engine that recognizes the user's emotions and adjusts the output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[2053] System configuration

[2054] 1. Terminal: A device operated by the user that displays input forms, receives product and service information and desired conditions, and also captures the user's facial expressions and voice input.

[2055] 2. Server: Receives input data and sentiment data, analyzes them, retrieves necessary price information from the database, performs calculations, and generates well-formed results.

[2056] 3. Database: Stores pricing information such as the base price and option prices of products and provides data in response to queries from the server.

[2057] 4. Emotion engine: Recognizes emotions from the user's facial expressions and voice and provides that information to the server.

[2058] Program processing overview

[2059] User Actions

[2060] The user enters detailed information such as the product name, quantity, and options on the device and clicks the "Submit" button. For example, three "Product A"s and one "Option B" are entered. The device also captures the user's facial expressions and voice.

[2061] Terminal handling

[2062] The device converts the product information entered by the user into JSON format, while at the same time recognizing emotions from the user's facial expressions and voice. For example, if the user's facial expression indicates that they are "considering purchasing" or that they would be happy if there was a discount, the device sends this information to the emotion engine, which then interprets the user's emotion as "expecting."

[2063] The device sends the following JSON data to the server:

[2064] json

[2065] {

[2066] "Product Name": "Product A",

[2067] "Quantity": 3,

[2068] "options": {

[2069] "Option B": 1

[2070] },

[2071] "Emotion": "Expecting"

[2072] }

[2073] Server Processing

[2074] The server receives the HTTP request and parses the JSON data. Based on the parsed data, it retrieves the product's base price and option prices from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen:

[2075] Total price of product A: 1000 yen 3 = 3000 yen

[2076] Total price of Option B: 500 yen 1 = 500 yen

[2077] Total amount: 3000 yen + 500 yen = 3500 yen

[2078] Furthermore, the server takes into account the emotion data received from the emotion engine and outputs accordingly. For example, if the user expresses the emotion "expecting," the server may apply special offers or discounts. As a result, the total price may be 3,000 yen.

[2079] The server converts the results into well-formed data in JSON format, such as:

[2080] json

[2081] {

[2082] "Total amount": "3000 yen",

[2083] "Message": "Special offer discount applied."

[2084] }

[2085] Displaying the results

[2086] The terminal analyzes the response data received from the server and displays it in the user interface. For example, it displays "The total estimated amount is 3000 yen. A discount has been applied due to a special offer."

[2087] Specific example explanation

[2088] For example, if a user orders three "product A" and one "option B" and requests a quote, the user enters the information through the terminal and presses the send button to request a quote. In addition, the user's emotion is recognized as "expecting." Based on this information, the server calculates the product price and applies special offers. Finally, the user confirms the quote result, and the discount applied increases the likelihood of closing the deal.

[2089] This system allows users to quickly and easily obtain estimates at the early stages of negotiations, and enables flexible responses based on emotions, resulting in efficient sales activities.

[2090] The processing flow will be explained below.

[2091] Step 1:

[2092] The user accesses the input form on the device and enters detailed product or service information such as product name, quantity, options, etc. For example, three "products A" and one "option B" are entered.

[2093] Step 2:

[2094] The user clicks the "Submit" button on the input form, which causes the entered information to be collected by the device.

[2095] Step 3:

[2096] The device converts the data entered by the user into JSON format, and simultaneously analyzes the user's facial expressions and voice using an emotion engine.

[2097] Step 4:

[2098] The emotion engine analyzes the user's facial expressions and voice and generates emotional data indicating "expectation."

[2099] Step 5:

[2100] The JSON data generated by the device is combined with emotion data and sent as an HTTP POST request to the server. For example, the following JSON data is sent:

[2101] json

[2102] {

[2103] "Product Name": "Product A",

[2104] "Quantity": 3,

[2105] "options": {

[2106] "Option B": 1

[2107] },

[2108] "Emotion": "Expecting"

[2109] }

[2110] Step 6:

[2111] The server receives the HTTP POST request and parses the received JSON data to obtain the details and sentiment of the user's desired product.

[2112] Step 7:

[2113] The server sends a query to the database to get the unit prices of "Product A" and "Option B." For example, the unit price of "Product A" is 1,000 yen, and the unit price of "Option B" is 500 yen.

[2114] Step 8:

[2115] The server calculates the total price based on the unit price obtained. Specifically, it calculates the following:

[2116] Total price of product A: 1,000 yen 3 = 3,000 yen

[2117] Total price of Option B: 500 yen 1 = 500 yen

[2118] Total amount: 3000 yen + 500 yen = 3500 yen

[2119] Step 9:

[2120] The server considers the emotion data and if the user shows the "expected" emotion, it will apply a special offer or discount, for example, a discount that brings the total price to 3000 yen.

[2121] Step 10:

[2122] The server converts the result of the calculation into well-formed response data, for example generating the following JSON data:

[2123] json

[2124] {

[2125] "Total amount": "3000 yen",

[2126] "Message": "Special offer discount applied."

[2127] }

[2128] Step 11:

[2129] The server returns the generated response data to the terminal as an HTTP response.

[2130] Step 12:

[2131] The terminal analyzes the response data received from the server.

[2132] Step 13:

[2133] The terminal analyzes the estimate and displays the result on the user interface. For example, it displays "The total estimate is 3000 yen. A discount has been applied due to a special offer."

[2134] This process allows the system to generate and provide quick and flexible estimates to users based on their input information and emotions.

[2135] Example 2

[2136] 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."

[2137] In conventional quotation systems, it was difficult for users to obtain a quick and accurate quotation, and it was also difficult to respond flexibly while taking into account the user's feelings. In particular, quotation results that ignored the user's feelings, such as expectations, reduced the possibility of concluding a business deal.

[2138] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a data processing means for analyzing received data and acquiring price information from a database, an emotion response means for adjusting output based on emotion data received from the emotion engine, and a price calculation means for calculating the total price based on the acquired price information. This makes it possible to provide a quick and accurate estimate and flexibly respond to the user's emotions.

[2139] "Input means" is a function that allows a user to input details of goods or services and desired conditions through a terminal.

[2140] The "transmission means" is a function that allows the terminal to transmit input data to the server.

[2141] "Emotion recognition means" is a function that allows the terminal to acquire the user's facial expressions and voice and generate emotion data.

[2142] The "emotion engine" is a system that analyzes the emotion data sent from the emotion recognition means and determines the user's emotional state.

[2143] The "data processing means" is a function that analyzes the data received by the server and retrieves price information from the database.

[2144] The "emotion response means" is a function that adjusts the output based on the emotion data received by the server from the emotion engine.

[2145] The "price calculation means" is a function that calculates the total price based on the price information acquired by the server.

[2146] The "result generation means" is a function by which the server converts the calculation result into well-formed response data and returns it to the terminal.

[2147] The "display means" is a function that displays the estimate results received by the terminal to the user.

[2148] The present invention provides a system for providing a user with a quick and accurate estimate, and further has a function for recognizing and responding to the user's emotions. Specific embodiments of the system will be described below.

[2149] System Configuration

[2150] Terminal

[2151] A terminal is a device operated by a user, and is equipped with an input means for the user to input detailed information about products and services and their desired conditions. It also includes emotion recognition means for acquiring the user's facial expressions and voice and processing them as emotional data. Specific examples of hardware include personal computers (PCs), tablets, and smartphones. Software used includes a web browser and dedicated applications for displaying input forms and transmitting data. A camera is used for facial recognition, and a microphone is used for voice recognition.

[2152] server

[2153] The server has a data processing means for receiving and analyzing data sent from the terminal. The server has an emotion response means for acquiring price information from the database and adjusting output based on emotion data analyzed by the emotion engine. The server also has a price calculation means and a result generation means for calculating the total price based on the price information and returning the result to the terminal as well-formed response data. The server and the database are connected via a network.

[2154] Emotion Engine

[2155] The emotion engine is a system that analyzes the data sent from the emotion recognition means and determines the user's emotional state. The emotion engine is managed by the server and generates information to provide offers and discounts according to the user's emotions.

[2156] Specific example explanation

[2157] As a concrete example, let's consider a case where a user orders three "Product A" and one "Option B" and requests a quote. The user enters the necessary information into the input form on the device and presses the "Submit" button to request a quote. At the same time, the device acquires the user's facial expressions and voice, and recognizes emotions such as "I'd be happy if there was a discount."

[2158] The device converts this information into JSON format and sends it to the server. For example, the following data is generated:

[2159] json

[2160] {

[2161] "Product Name": "Product A",

[2162] "Quantity": 3,

[2163] "options": {

[2164] "Option B": 1

[2165] },

[2166] "Emotion": "Expecting"

[2167] }

[2168] The server analyzes the received data and retrieves from the database that the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen. The server calculates the total price based on this information and applies a special offer, taking into account the emotional data of "expecting" from the emotion engine.

[2169] The total amount is 3000 yen, and the server converts the calculation result into well-formed data in JSON format as follows:

[2170] json

[2171] {

[2172] "Total amount": "3000 yen",

[2173] "Message": "Special offer discount applied."

[2174] }

[2175] The terminal analyzes the response data from the server and displays on the user interface, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer."

[2176] Prompts for generative AI models

[2177] Here is an example of a prompt to input to a generative AI model:

[2178] I would like to quote a price for a product. The product name is "Product A", the quantity is 3, and the option is "Option B". I would also like a discount.

[2179] This prompt allows the generative AI model to generate an appropriate estimate while taking into account the user's emotions.

[2180] As a result, this system can provide users with quick and accurate estimates and respond flexibly to their emotions.

[2181] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2182] Step 1:

[2183] The user enters product information

[2184] The user enters detailed information such as product name, quantity, and options into the input form on the terminal. For example, the user enters three "Product A"s and one "Option B" and selects "Discount" as a desired condition. This information is used as input data sent to later processing. The input data has the following format:

[2185] Text format

[2186] Product name: Product A

[2187] Quantity: 3

[2188] Option: Option B (Quantity: 1)

[2189] Desired conditions: Discount

[2190] Step 2:

[2191] The user clicks the submit button

[2192] When the user clicks the "Submit" button, the entered data is processed. By clicking the "Submit" button, the terminal sends the data to the next processing step. The input data is converted directly to JSON format data.

[2193] Step 3:

[2194] The terminal converts the input information into JSON format.

[2195] The device converts the product information and desired conditions collected in the input form into JSON format. Specifically, the following JSON data is generated:

[2196] json

[2197] {

[2198] "Product Name": "Product A",

[2199] "Quantity": 3,

[2200] "options": {

[2201] "Option B": 1

[2202] },

[2203] "Desired conditions": "Discount"

[2204] }

[2205] This JSON data will later be the input data to be sent to the server.

[2206] Step 4:

[2207] The device captures the user's facial expressions and voice and generates emotion data.

[2208] The device uses a camera and microphone to capture the user's facial expressions and voice, and uses emotion recognition software to generate emotion data such as "I'm looking forward to it." For example, if a user says, "I'd be happy if there was a discount," the emotion is recognized as "I'm looking forward to it." The generated emotion data is in the following JSON format:

[2209] json

[2210] {

[2211] "Emotion": "Expecting"

[2212] }

[2213] Step 5:

[2214] The device sends the user's input information and emotion data to the server.

[2215] The device sends the converted product information and emotion data to the server as a single JSON data. The final JSON data sent will have the following format:

[2216] json

[2217] {

[2218] "Product Name": "Product A",

[2219] "Quantity": 3,

[2220] "options": {

[2221] "Option B": 1

[2222] },

[2223] "Desired conditions": "Discount",

[2224] "Emotion": "Expecting"

[2225] }

[2226] This data becomes the input data for the next processing step on the server.

[2227] Step 6:

[2228] The server analyzes the received data

[2229] The server parses the JSON data received from the device and extracts the product name, quantity, options, and emotion data. This analysis stores the product information and emotion data in individual variables and data structures, which then become input data for the next price acquisition process.

[2230] Step 7:

[2231] The server retrieves the price information from the database

[2232] The server uses the parsed data to query the database to get pricing information for products and options. For example, the database might return the following pricing information:

[2233] Unit price of product A: 1,000 yen

[2234] Option B unit price: 500 yen

[2235] The acquired price information becomes input data for the next price calculation process.

[2236] Step 8:

[2237] The server calculates the total price

[2238] The server calculates the total price of the items based on the price information it has received. The calculation is done as follows:

[2239] Total price of product A: 1,000 yen x 3 = 3,000 yen

[2240] Total price of Option B: 500 yen x 1 = 500 yen

[2241] Total amount: 3000 yen + 500 yen = 3500 yen

[2242] This 3,500 yen will be the base price and will be the input data for the next emotion response processing.

[2243] Step 9:

[2244] The server adjusts the output taking into account emotional data.

[2245] The server takes into account the emotion data of "expecting" received from the emotion engine and applies special offers and discounts. For example, it adjusts the total price to 500 yen off as a special discount, so that the final total price is 3,000 yen.

[2246] Step 10:

[2247] The server converts the calculation results into well-formed data in JSON format.

[2248] The server converts the final quote result into well-formed data in the following JSON format:

[2249] json

[2250] {

[2251] "Total amount": "3000 yen",

[2252] "Message": "Special offer discount applied."

[2253] }

[2254] This data is sent to the terminal.

[2255] Step 11:

[2256] The device analyzes the response data from the server

[2257] The terminal analyzes the JSON response data received from the server and extracts the total amount and message.

[2258] Step 12:

[2259] The device displays the results in the user interface.

[2260] Based on the data analyzed by the device, the user interface displays the message, "The total estimated amount is 3,000 yen. A discount has been applied due to a special offer." This allows the user to quickly and accurately check the estimated results.

[2261] (Application example 2)

[2262] 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."

[2263] Conventional quotation systems provide quick quotes based on detailed product information entered by users, but they lack the flexibility to consider the user's emotional state, which results in insufficient improvement in customer satisfaction or motivation to purchase. Furthermore, they lack the functionality to provide personalized offers and messages when providing user input data and quotation results. This results in a poor user experience.

[2264] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2265] In this invention, the server includes emotion recognition means for analyzing facial expressions and voice data transmitted from a terminal operated by a user to recognize the emotional state, data processing means for analyzing the received data and retrieving price information from a database, price calculation means for calculating a total price based on the retrieved price information and the emotional state, and result generation means for converting the calculation result into well-formed response data and a customized message based on the emotional state and returning it to the terminal, thereby enabling the provision of real-time estimates according to the user's emotions and the application of personalized special offers and discounts.

[2266] The "input means" is a means by which a user inputs detailed information and desired conditions for a product or service.

[2267] The "transmission means" is a means for transmitting the input data, facial expression data, and voice data from the terminal to the server.

[2268] The "emotion recognition means" is a means for analyzing received data, facial expressions, and voice data to recognize an emotional state.

[2269] The "data processing means" is a means for analyzing the data received by the server and obtaining price information from the database.

[2270] The "price calculation means" is a means for calculating the total price based on the price information and emotional state acquired by the server.

[2271] The "result generation means" is a means by which the server converts the calculation result into well-formed response data and a customized message based on the emotional state, and returns the result to the terminal.

[2272] The "display means" is a means for displaying the estimate results and customized messages received by the terminal to the user.

[2273] "Special Offers" are discounts and promotional offers that are tailored to a user's emotional state.

[2274] The present invention provides an instant quote system that allows users to quickly obtain quotes, combined with an emotion engine that recognizes the user's emotions and adjusts output based on those emotions. This system has a terminal, a server, a database, and an emotion engine, and allows users to input detailed information about products or services and provides quote results that reflect their emotional state.

[2275] First, the device operated by the user provides an interface for inputting detailed product or service information and desired conditions. For example, the user inputs information for purchasing three units of "Product A" and one unit of "Option B." The device also uses a camera and microphone to capture the user's facial expressions and voice, and transmits this as emotion data to the server.

[2276] The server receives the transmitted data and emotional data, and first analyzes the user's emotional state using the emotion recognition means. For example, if the user says, "I'd be happy if there was a discount," the emotion recognition means interprets this as "I'm looking forward to it." Next, the data processing means analyzes the product information entered by the user and retrieves the corresponding price information from the database. For example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, this information is retrieved.

[2277] The price calculation means calculates the total price based on the acquired price information and the emotional state. For example, if the emotion "expecting" is recognized, the server applies special offers and discounts and adjusts the total price. As a specific example, a quote of 3,500 yen, which is the regular price, may be discounted to 3,000 yen in response to the "expecting" emotion.

[2278] The result generation means converts the calculation result into well-formed response data and creates a customized message based on the emotional state. This data is then sent back to the terminal. The terminal displays the received estimate result and the customized message on the user interface. For example, the user can see a message that reads, "The total estimate is 3,000 yen. A discount has been applied due to a special offer."

[2279] To implement this system, a smartphone (with a camera and microphone) is used. For emotion recognition, a generative AI model called an emotion recognition API is recommended. On the server side, data processing is performed using a web framework such as Flask.

[2280] As a specific example, a prompt sentence is prepared: "Please generate a quote with discounts based on the purchase information for three units of product name 'Product A' and one unit of 'Option B' and the user's expected emotion." Based on this prompt sentence, the system provides an appropriate quote and a message according to the emotion.

[2281] As described above, the instant quotation system of the present invention, which clearly specifies the hardware and software to be used and the specific flow of data processing and calculations, makes it possible to provide highly efficient quotation that will provide high customer satisfaction.

[2282] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2283] Step 1:

[2284] The user inputs details of the product or service and desired conditions through the terminal.

[2285] Specifically, the user enters three "Product A"s and one "Option B" into the input form on the device and clicks the "Submit" button. This information is converted into JSON format data on the device. As a concrete example of input data, the following JSON data is generated:

[2286] json

[2287] {

[2288] "Product Name": "Product A",

[2289] "Quantity": 3,

[2290] "options": {

[2291] "Option B": 1

[2292] }

[2293] }

[2294] Step 2:

[2295] The user's facial expressions and voice are acquired by the terminal.

[2296] The device uses a camera and microphone to capture the user's facial expressions and voice. Specifically, the device captures the user's face in real time and records voice input. The captured emotion data is also converted into JSON format data.

[2297] Step 3:

[2298] The terminal transmits the input product information and emotion data to the server.

[2299] Specifically, the device sends the JSON data of the product information generated earlier and the emotion data obtained from facial and voice analysis to the server as an HTTP request. The sent data will be in the following format:

[2300] json

[2301] {

[2302] "Product information": {

[2303] "Product Name": "Product A",

[2304] "Quantity": 3,

[2305] "options": {

[2306] "Option B": 1

[2307] }

[2308] },

[2309] "Emotion": "Expecting"

[2310] }

[2311] Step 4:

[2312] The server parses the received data.

[2313] The server receives the HTTP request and parses the JSON data. The parsed data is stored in separate variables for further processing. The input includes product information and sentiment data, and the output of the parsing is split into separate variables for each piece of information.

[2314] Step 5:

[2315] An emotion recognition means analyzes emotions.

[2316] The emotion recognition means in the server analyzes the received facial expression and voice data and recognizes the emotional state of the user. The facial expression and voice data are provided as input, and an emotional status such as "expecting" is obtained as output.

[2317] Step 6:

[2318] The data processing means analyzes the product information and obtains price information from the database.

[2319] The data processing means in the server analyzes the product information and queries the database for price information on the corresponding product. As a specific example, if the unit price of "Product A" is 1,000 yen and the unit price of "Option B" is 500 yen, these price information will be obtained. The input is the analyzed product information, and the output is price information for the product and options.

[2320] Step 7:

[2321] A price calculation means calculates the total price.

[2322] The price calculation means in the server calculates the total price based on the acquired price information and emotional state. For example, if the total price of three "products A" and one "option B" is calculated and the emotion is recognized as "expecting," a 10% discount is applied as a special offer. The input is price information and emotional data, and the output is the total price after applying the discount. A specific example is as follows:

[2323] Total price of product A: 1000 yen 3 = 3000 yen

[2324] Total price of Option B: 500 yen 1 = 500 yen

[2325] Total amount: 3000 yen + 500 yen = 3500 yen

[2326] After discount: 3500 yen 0.9 = 3150 yen

[2327] Step 8:

[2328] A result generation means creates well-formed response data and adds a customized message based on the emotion.

[2329] The server converts the results of the calculation into well-formed JSON data and adds a customized message based on the emotion, producing the following example output:

[2330] json

[2331] {

[2332] "Total amount": "3150 yen",

[2333] "Message": "Special offer discount applied."

[2334] }

[2335] Step 9:

[2336] The server transmits the generated response data to the terminal.

[2337] The server sends the generated response data to the terminal as an HTTP response. The input is well-formed data, and the output is an HTTP response.

[2338] Step 10:

[2339] The terminal displays the received estimate result and the customized message to the user.

[2340] The terminal analyzes the response data from the server and displays it on the user interface. The user sees the message "The total estimated price is 3150 yen. A discount has been applied thanks to a special offer." The input is the response data, and the output is the user interface display.

[2341] 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.

[2342] 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.

[2343] 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 robot 414.

[2344] 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.

[2345] FIG. 9 illustrates 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 behaviors 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.

[2346] 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.

[2347] 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).

[2348] 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.

[2349] 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."

[2350] 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.

[2351] 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).

[2352] 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.

[2353] 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.

[2354] 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.

[2355] 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.

[2356] 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.

[2357] 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.

[2358] 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.

[2359] 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.

[2360] 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.

[2361] 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.

[2362] The following is further disclosed regarding the above embodiment.

[2363] (Claim 1)

[2364] An input means for a user to input details of products and services and desired conditions through a terminal;

[2365] a transmitting means for transmitting input data from the terminal to the server;

[2366] a data processing means for analyzing the data received by the server and retrieving price information from a database;

[2367] a price calculation means for calculating a total price based on the price information acquired by the server;

[2368] a result generation means for the server to convert the calculation result into well-formed response data and return it to the terminal;

[2369] a display means for displaying the estimate result received by the terminal to the user;

[2370] A system including:

[2371] (Claim 2)

[2372] 2. The system according to claim 1, wherein the price calculation means includes means for calculating a total price using at least the unit price and quantity of the product and the unit price of the option.

[2373] (Claim 3)

[2374] 2. The system according to claim 1, wherein the data processing means includes means for analyzing input data from a user in JSON format and making a query to a database.

[2375] "Example 1"

[2376] (Claim 1)

[2377] an input means for a user to input details of products or services and desired conditions through an information terminal;

[2378] a transmitting means for transmitting data input by the information terminal to the data processing device;

[2379] data processing means for analyzing data received by the data processing device and acquiring price information from the storage device;

[2380] a calculation means for calculating a total price based on the price information acquired by the data processing device;

[2381] a response generating means for converting the calculation result into well-formatted response data and returning the data to the information terminal;

[2382] a display means for displaying the estimate result received by the information terminal to the user;

[2383] A system including:

[2384] (Claim 2)

[2385] 2. The system according to claim 1, wherein the calculation means includes means for calculating a total price using at least the unit price and quantity of the goods or services and the unit prices of the selected items.

[2386] (Claim 3)

[2387] 2. The system according to claim 1, wherein the data processing means includes means for analyzing input data from a user in a structured data format and for querying the storage device.

[2388] "Application Example 1"

[2389] (Claim 1)

[2390] An input means for a user to input details of products and services and desired conditions through a terminal;

[2391] a transmitting means for transmitting input data from the terminal to the server;

[2392] a data processing means for analyzing the data received by the server and retrieving price information from a database;

[2393] a price calculation means for calculating a total price based on the price information acquired by the server;

[2394] a result generation means for the server to convert the calculation result into well-formed response data and return it to the terminal;

[2395] a display means for instantly displaying the estimate result received by the terminal on a user interface;

[2396] Online quote generation system including.

[2397] (Claim 2)

[2398] 2. The online quote generation system according to claim 1, wherein the price calculation means includes means for calculating a total price using at least the unit price and quantity of the product and the unit price of the option.

[2399] (Claim 3)

[2400] 2. The online quote generation system according to claim 1, wherein the data processing means includes means for analyzing input data from a user in JSON format and making a query to a database.

[2401] "Example 2: Combining Emotion Engines"

[2402] (Claim 1)

[2403] an input means for a user to input details of goods or services and desired conditions through a terminal;

[2404] a transmitting means for transmitting input data from the terminal to the server;

[2405] an emotion recognition means for acquiring facial expressions and voice of a user and generating emotion data;

[2406] a means for generating emotion data from the emotion recognition means and transmitting the emotion data to the emotion engine;

[2407] a data processing means for analyzing the data received by the server and retrieving price information from a database;

[2408] an emotion response means for adjusting an output based on emotion data received by the server from the emotion engine;

[2409] a price calculation means for calculating a total price based on the price information acquired by the server;

[2410] a result generation means for the server to convert the calculation result into well-formed response data and return it to the terminal;

[2411] a display means for displaying the estimate result received by the terminal to the user;

[2412] A system including:

[2413] (Claim 2)

[2414] 2. The system according to claim 1, wherein the price calculation means includes means for calculating a total price using at least the unit price and quantity of the item and the unit price of the option.

[2415] (Claim 3)

[2416] 2. The system according to claim 1, wherein the data processing means includes means for analyzing input data and emotion data from a user in JSON format and for querying a database.

[2417] "Application example 2 when combining emotion engines"

[2418] (Claim 1)

[2419] An input means for a user to input details of products and services and desired conditions through a terminal;

[2420] a transmission means for transmitting the input data, facial expression data, and voice data from the terminal to the server;

[2421] emotion recognition means for receiving and analyzing the data, facial expression and voice data to recognize an emotional state;

[2422] a data processing means for analyzing the data received by the server and retrieving price information from a database;

[2423] a price calculation means for calculating a total price based on the price information and the emotional state acquired by the server;

[2424] a result generation means for the server to convert the calculation result into well-formed response data and a customized message based on the emotional state and return the result to the terminal;

[2425] a display means for displaying the estimate result and the customized message received by the terminal to the user;

[2426] A system including:

[2427] (Claim 2)

[2428] 10. The system of claim 1, further comprising means for taking emotional state into account when calculating the total price and applying special offers and discounts.

[2429] (Claim 3)

[2430] 2. The system of claim 1, wherein the data processing means includes means for parsing input data from a user in JSON format, querying a database, and means for analyzing an emotional state. [Explanation of symbols]

[2431] 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 input means for a user to input details of products and services and desired conditions through a terminal; a transmitting means for transmitting input data from the terminal to the server; a data processing means for analyzing the data received by the server and retrieving price information from a database; a price calculation means for calculating a total price based on the price information acquired by the server; a result generation means for the server to convert the calculation result into well-formed response data and return it to the terminal; a display means for displaying the estimate result received by the terminal to the user; A system including:

2. 2. The system according to claim 1, wherein the price calculation means includes means for calculating a total price using at least the unit price and quantity of the product and the unit price of the option.

3. 2. The system according to claim 1, wherein the data processing means includes means for analyzing input data from a user in JSON format and for querying a database.

Images