System

Abstract

A system is provided.SOLUTION: A system comprising: means for communicating with a user using generative artificial intelligence; means for cooperating with an external service and acquiring data based on a request of the user; means for automating a specific task based on the request of the user; and means for monitoring a progress status of the task and notifying the user of a result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's business environment, efficient and rapid responses are required, but traditional inventory management and customer support systems require a lot of manual work, resulting in reduced work efficiency. In addition, inventory shortages and overages, as well as delayed ordering, can easily lead to operational stagnation and delays in customer support. Furthermore, flexible system integration is essential to respond quickly and accurately to user requests. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for communicating with users using generative artificial intelligence, a means for linking with external services and acquiring data based on user requests, a means for automating specific tasks based on user requests, and a means for monitoring the progress of tasks and notifying the user of the results. This system includes a means for automatically checking inventory levels and placing orders when necessary, particularly in inventory management. Furthermore, by using generative artificial intelligence to receive requests from users through a user interface and execute appropriate processing, the system improves work efficiency and prevents business downtime.

[0006] "Generative AI" refers to algorithms and technologies that enable natural dialogue with users and generate information.

[0007] "User" refers to an individual or organization that uses the system.

[0008] "Means of communication" refers to the function of sending and receiving information to and from the user using generative artificial intelligence.

[0009] "External services" refers to other systems or services that the system interacts with, including, for example, inventory management systems and online marketplaces.

[0010] "Means of obtaining data" refers to the function for obtaining the necessary data from external services.

[0011] "Means of automating specific tasks" refers to the ability of a system to automatically perform work or processing in a specific business flow.

[0012] "Means for monitoring task progress" refers to the ability of the system to monitor the progress of automated tasks in real time.

[0013] "Means for notifying the user of the results" refers to a function that notifies the user of the progress of the task and the processing results.

[0014] "Inventory management" refers to the business process of managing the quantity of stocked items and replenishing or ordering as needed.

[0015] "User interface" refers to an interface such as a screen or input device that allows a user to interact with a system. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[0038] System configuration and roles

[0039] server

[0040] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[0041] Terminal

[0042] The terminal operates in cooperation with the server. The terminal provides a user interface and acts as a window through which the user can make requests to the server for inventory management and other matters. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[0043] User

[0044] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[0045] Program processing

[0046] The specific program processing flow is as follows:

[0047] 1. Adding inventory

[0048] User: The user sends a command to the server from their device to add a specific item to their inventory.

[0049] Server: The server receives instructions from the user and updates the inventory information. The updated inventory information is recorded in a log and notified to the user.

[0050] 2. Check inventory

[0051] User: A user checks the stock level of a specific item from a terminal.

[0052] Server: The server provides inventory information for the specified item to the terminal and displays that information to the user.

[0053] 3. Automated ordering

[0054] Terminal: The terminal periodically communicates with the server to check stock availability.

[0055] Server: The server automatically detects items that are below the inventory threshold and calculates the required order quantity. After the calculation, the server sends the order information to an external service and processes the order. The order result is logged and notified to the user via the terminal.

[0056] Specific examples

[0057] For example, if a user wants to add "pens" to the inventory, the user sends an instruction to the server via the terminal interface to "add 50 pens." The server receives this instruction and updates the inventory information, increasing the inventory of pens by 50.

[0058] Next, when the user wants to check the inventory of "notes," he sends a "Check notebook inventory" request to the server through the terminal. The server returns the current inventory of notes to the terminal, and the user can check the information.

[0059] Furthermore, if the system's inventory falls below 10 notebooks, it will automatically order more notebooks. The server calculates the order quantity and processes the order in conjunction with an external service. The order result is notified to the user via their terminal, and the user can check the order progress in real time.

[0060] In this way, this system automates inventory management and ordering through dialogue with users using generative artificial intelligence, supporting efficient business operations.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] User: The user enters an inventory addition through the device's user interface (e.g., "Add 50 pens").

[0064] Step 2:

[0065] Terminal: The terminal prepares a request to send to the server an instruction from the user to add stock.

[0066] Step 3:

[0067] Server: The server parses the inventory addition request received from the terminal and retrieves the specified item and quantity.

[0068] Step 4:

[0069] Server: The server checks the inventory status and updates the quantity if the specified item already exists, otherwise it adds it as a new item.

[0070] Step 5:

[0071] Server: Updates the database with the updated inventory information and logs the inventory change history.

[0072] Step 6:

[0073] Server: Sends inventory update results to the device.

[0074] Step 7:

[0075] Terminal: The terminal receives the response from the server and displays the results on the user interface, allowing the user to see the quantity of stock that has been added.

[0076] Step 8:

[0077] User: A user makes a request through a terminal to check the inventory of a specific item (e.g., a "notebook").

[0078] Step 9:

[0079] Terminal: The terminal prepares the stock check request from the user to send to the server.

[0080] Step 10:

[0081] Server: The server analyzes the stock check request received from the terminal and retrieves the stock amount of the specified item from the database.

[0082] Step 11:

[0083] Server: Sends the acquired inventory information to the terminal.

[0084] Step 12:

[0085] Terminal: The terminal receives the response from the server and displays the inventory information on the user interface. The user can check the stock amount of the item they want to check.

[0086] Step 13:

[0087] Device: Periodically communicates with the server and sends a request to check inventory status.

[0088] Step 14:

[0089] Server: The server checks inventory and determines if a particular item is below a threshold.

[0090] Step 15:

[0091] Server: If the item is below the threshold, automatically calculate the order quantity and send an order request to an external service.

[0092] Step 16:

[0093] External Service: An external service receives the order request and initiates processing.

[0094] Step 17:

[0095] External service: After the order is completed, the result is notified to the server.

[0096] Step 18:

[0097] Server: Records the order result in a log and notifies the terminal.

[0098] Step 19:

[0099] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to see the progress of the automated order.

[0100] In this way, the system can perform tasks such as adding inventory, checking, and auto-ordering in a series of processing steps via a user interface.

[0101] Example 1

[0102] 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."

[0103] In inventory management, manual tasks such as adding, checking, and ordering inventory require time and effort, hindering efficient operations. Furthermore, ordering inventory after inventory runs out can create a time lag, potentially disrupting operations. There is a need for a system that can solve these problems and achieve efficient inventory management and an automated ordering process.

[0104] 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.

[0105] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for cooperating with an external service and acquiring data based on a user request, means for automating a specific task based on a user request, means for monitoring the progress of the task and notifying the user of the result, means for a user to send an instruction to add stock from a terminal and for the server to analyze and process the instruction, means for a user to send an inventory check request from a terminal and for the server to analyze and process the request, means for the server to periodically monitor inventory and automatically order items that are below a threshold, and means for processing orders and notifying the results via an external service, thereby enabling efficient and automated inventory management.

[0106] "Generative AI" refers to artificial intelligence technology that can interact with users and analyze data, and uses natural language processing and machine learning to generate appropriate responses.

[0107] "External services" refer to external systems or applications that provide functions such as data acquisition and order processing through collaboration with the server.

[0108] "User request" refers to an operation or instruction given by a user to the system, and includes processing requests such as adding inventory, checking, and placing an order.

[0109] "Means to automate specific tasks" refers to functions that allow a system to automatically execute business processes that were previously performed manually, including inventory management and order processing.

[0110] "Means for monitoring task progress" refers to the functionality for tracking the status of ongoing tasks and checking completion and progress.

[0111] "Means for a user to send an instruction to add stock from a terminal and for the server to analyze and process that instruction" refers to the function that allows a user to send an instruction to add stock to a server via a terminal, and for the server to interpret and process that instruction.

[0112] "Means for a user to send an inventory check request from a terminal and for the server to analyze and process the request" refers to the function that allows a user to send an inventory check request to a server via a terminal, and the server to analyze the request and provide inventory information.

[0113] "Means for the server to periodically monitor inventory and automatically order items that fall below a threshold" refers to a function in which the server periodically checks inventory information and automatically places an order if it detects that inventory is below a pre-set threshold.

[0114] "Means for processing orders and notifying the results via an external service" refers to a function that enables the server to execute orders in cooperation with an external ordering system and notify the user of the results.

[0115] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[0116] System configuration and roles

[0117] server

[0118] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[0119] Terminal

[0120] The terminal operates in conjunction with the server. The terminal provides a user interface and acts as a window through which users can make requests to the server for inventory management and other purposes. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[0121] User

[0122] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[0123] Program processing

[0124] 1. Adding inventory

[0125] User: The user sends a command to the server from their device to add a specific item to their inventory.

[0126] Server: The server receives instructions from the user and analyzes them using a generative AI model. Based on the analysis results, it updates the stock quantity of the corresponding item in the inventory database. The updated stock information is recorded in a log and notified to the user.

[0127] Terminal: The terminal receives inventory updates from the server and displays them to the user.

[0128] 2. Check inventory

[0129] User: A user sends a request from their device to check the stock level of a specific item.

[0130] Server: The server receives the request, analyzes it using the generative AI model, retrieves the stock information for the specified item from the inventory database, and sends it to the device.

[0131] Terminal: The terminal displays the inventory information received from the server to the user.

[0132] 3. Automated ordering

[0133] Server: The server periodically scans the inventory database to detect items whose stock is below a threshold. It uses a generative AI model to calculate the required order quantity and sends the order information to an external ordering system (e.g., external API). The order result is logged and notified to the user via the terminal.

[0134] Terminal: The terminal displays the order notification received from the server to the user.

[0135] Specific examples

[0136] For example, if a user sends an instruction to "add 50 pens" through the terminal interface, the server will receive this instruction and increase the stock of pens in the inventory database by 50. After updating the stock information, the server will record it in a log and generate a notification to send to the terminal, which will then display this notification to the user.

[0137] Next, when the user sends a request to "check notebook stock amount," the server obtains notebook stock information and sends it to the terminal, allowing the user to check the information.

[0138] Furthermore, if the system detects that the inventory of a notebook falls below 10 units, the server automatically uses the generative AI model to calculate the required order quantity and place an order through the external ordering system. The ordering result is logged and the user is notified via the terminal.

[0139] Example input to a generative AI model

[0140] Below is an example of input to a generative AI model:

[0141] "Add 50 pens"

[0142] Check notebook inventory

[0143] In this way, the present invention is a system that realizes the automation of inventory management and ordering through dialogue with users using generative artificial intelligence, thereby supporting efficient business operations.

[0144] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0145] Step 1:

[0146] Adding inventory

[0147] Input: A user inputs an inventory increase instruction, such as "add 50 pens," into a terminal.

[0148] Action: The user enters "Add 50 pens" into the inventory addition form through the terminal interface and clicks the submit button.

[0149] Specific behavior: The device detects this input and sends the data to the server as an HTTP POST request.

[0150] Data processing / calculation: The server receives the request, analyzes the instruction using the generative AI model, extracts the information "pen" and "50 units", accesses the inventory database, and increases the number of pens in stock by 50 units.

[0151] Output: Generates a success message and updated inventory information and sends them to the terminal.

[0152] Action: The device receives the updated inventory information and displays it to the user.

[0153] Step 2:

[0154] Check inventory

[0155] Input: A user inputs an inventory check request such as "Check notebook inventory" on a device.

[0156] How it works: The user enters "Check notebook inventory" into the inventory check form through the device interface and clicks the submit button.

[0157] Specific behavior: The device detects this input and sends the data to the server as an HTTP GET request.

[0158] Data processing / calculation: The server receives the request, analyzes the request using the generative AI model, and extracts the information "notebook." It then accesses the inventory database to obtain the notebook's inventory information.

[0159] Output: Generates a response with the current note inventory information and sends it to the device.

[0160] Operation: The device receives the notebook inventory information and displays it to the user.

[0161] Step 3:

[0162] Automatic ordering

[0163] Input: The server checks the inventory database on a regular schedule.

[0164] How it works: At regular intervals (e.g., every day at midnight), the server detects items that are below a stock threshold.

[0165] What happens: The server scans the inventory database on a scheduled basis to detect items below a threshold (e.g., fewer than 10 notebooks in stock).

[0166] Data processing / calculation: Use the generative AI model to calculate the required order quantity (e.g., order 20 notebooks), then send the order information to an external ordering system (e.g., external API).

[0167] Output: Receives the response containing the order result, logs it, and generates a notification message to send to the terminal.

[0168] Operation: The terminal displays the order notification received from the server to the user.

[0169] Step 4:

[0170] Order status notification

[0171] Input: Order result feedback from external ordering system.

[0172] How it works: The server periodically calls the API of the external ordering system to check the progress of the order.

[0173] Specific behavior: The server retrieves the order status through the API and records it in a log.

[0174] Data processing / calculation: Analyze the retrieved order status and use a generative AI model to generate a message to notify the user.

[0175] Output: Sends a notification message to the terminal.

[0176] Action: The terminal displays the received notification message to the user.

[0177] (Application example 1)

[0178] 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."

[0179] In current inventory management systems, the processes of adding, checking, and ordering inventory are often all done manually, resulting in reduced work efficiency and a high likelihood of human error. Additionally, inventory information cannot be checked in real time on-site, making it difficult to respond quickly. There is a need for a system that can solve these problems and improve the efficiency and accuracy of inventory management at logistics centers and other facilities.

[0180] 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.

[0181] In this invention, the server includes means for communicating with users using generative artificial intelligence, means for connecting with external services and acquiring data based on user requests, means for automating specific tasks based on user requests, means for monitoring task progress and notifying the user of the results, means for receiving user voice commands using voice recognition and executing processing, and means for visualizing inventory information in real time using a user-portable 3D display device. This allows users to add or check inventory using voice commands and check inventory status in real time through their smart devices. Furthermore, automatic ordering is performed when inventory levels fall below a certain threshold, achieving efficient inventory management.

[0182] "Generative AI" is AI that analyzes data and generates responses and instructions in natural language through dialogue with the user.

[0183] "Means for communicating with the user" refers to an interface that uses generative artificial intelligence to realize two-way dialogue with the user through voice and text.

[0184] "Means of linking with external services" refers to the function of obtaining necessary information from external databases or APIs and using it within the system.

[0185] A "means for automating a task" is a function for executing a task based on a request from a user without manual intervention and managing the progress of the task.

[0186] The "means for monitoring and notifying the progress of a task" is a function for tracking the status of a task currently being executed and notifying the user of the results in real time.

[0187] The "means for receiving user voice commands using voice recognition" is a function for analyzing the user's voice, converting it into text data, and interpreting it as instructions.

[0188] "Means for visualizing inventory information using a portable 3D display device" refers to a function that uses a portable device such as smart glasses or a head-mounted display to display inventory information in three dimensions and present it to the user in an easy-to-understand manner.

[0189] "Inventory management" is the process of managing the quantity of products and parts held in stock and replenishing or ordering as needed.

[0190] An "inventory database" is a database that records information on all items managed as inventory and can be referenced and updated as needed.

[0191] "Automatic ordering" is the process by which the system automatically orders additional stock when inventory falls below a defined threshold.

[0192] This invention is a system that uses generative artificial intelligence to realize communication through voice recognition, visualization of real-time inventory information, and automatic ordering in order to improve the efficiency of inventory management at logistics centers, etc. As an application example of this invention, details of an inventory management system using smart glasses will be described.

[0193] System configuration and roles

[0194] server

[0195] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user and accepts voice commands from the user. It also connects with external services to obtain necessary data and manage inventory information. It also has a function to automatically place an order when inventory levels fall below a threshold. The server uses Python programs and voice recognition libraries (e.g., SpeechRecognition).

[0196] Terminal

[0197] The terminal is a portable device such as smart glasses or a head-mounted display that allows users to input voice commands. The terminal displays inventory information in 3D in real time, allowing users to easily check inventory status on-site.

[0198] User

[0199] Users operate the system through smart glasses to manage inventory. For example, a user might give a voice command such as "add 50 pens." The smart glasses then transmit the voice command to a server, which analyzes the voice and updates the inventory database. When inventory falls below a certain threshold, the server automatically places an order and notifies the user of the result.

[0200] Program Description

[0201] 1. Hardware:

[0202] Server: High-performance server (e.g. Amazon AWS, Google Cloud Platform)

[0203] Devices: Smart glasses (e.g., Google Glass), head-mounted displays (e.g., Microsoft HoloLens)

[0204] 2. Software:

[0205] Server-side program: Python

[0206] Speech recognition library: SpeechRecognition

[0207] Notification Library: Pushbullet API

[0208] 3. Data processing and calculation:

[0209] The user sends a voice command to the smart glasses.

[0210] The smart glasses send the voice data to a server, where a Python program converts the voice into text for analysis.

[0211] The server updates the inventory database based on the instructions and notifies the user of the changes.

[0212] When inventory falls below a threshold, the server automatically places an order and notifies the user of the result.

[0213] Specific examples

[0214] The user commands the smart glasses to "add 50 pens." The smart glasses recognize the voice and send it to the server. The server analyzes the received voice data and updates the inventory database. The user can confirm the completion of the task by seeing the message "50 pens added" on the smart glasses' display.

[0215] Example prompt sentence:

[0216] The user speaks to the smart glasses, "Add 50 pens." This speech information is sent to the server, and the generative AI model interprets it as "Add 50 pens to inventory" and updates the database. At that time, the user should be notified that the addition is complete.

[0217] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0218] Step 1:

[0219] The user speaks the voice command "Add 50 pens" to the smart glasses.

[0220] Input: User's voice command

[0221] Output: Audio data

[0222] What it does: The microphone in the smart glasses captures the user's voice and obtains the voice data.

[0223] Step 2:

[0224] The terminal (smart glasses) transmits the acquired voice data to the server.

[0225] Input: Audio data

[0226] Output: Sending audio data to the server

[0227] What it does: The smart glasses send audio data over the internet to a specified endpoint on the server.

[0228] Step 3:

[0229] The server converts the received voice data into text.

[0230] Input: Audio data

[0231] Output: Converted text data (e.g. "Add 50 pens")

[0232] Specific operation: The server converts the voice data into text using a speech recognition library (e.g., SpeechRecognition).

[0233] Step 4:

[0234] The server parses the text data and updates the inventory database.

[0235] Input: Text data

[0236] Output: Updated inventory database

[0237] Specific operation: The server uses generative artificial intelligence to analyze the text data, interprets it as an instruction to "add 50 pens," and increases the inventory quantity of the corresponding item in the inventory database by 50.

[0238] Step 5:

[0239] The server notifies the user of the results of the inventory database update.

[0240] Input: Updated inventory information

[0241] Output: A notification message to the user (e.g. "50 pens added").

[0242] What it does: The server sends a notification message to the user's smart glasses using a notification library such as the Pushbullet API.

[0243] Step 6:

[0244] The terminal (smart glasses) displays the received notification message to the user.

[0245] Input: Notification message from the server

[0246] Output: Notification message displayed on the smart glasses display

[0247] Specific operation: The smart glasses analyze the received notification message and display the message "50 pens added" on the display.

[0248] Step 7:

[0249] The server automatically places an order if the inventory level falls below a threshold.

[0250] Input: Updated inventory information

[0251] Output: Automatic ordering instructions and notification of ordering results

[0252] Specific operation: The server checks the inventory database, and if the inventory level is below the threshold, it sends an order instruction to an external service, logs the order result, and notifies the user.

[0253] 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.

[0254] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[0255] System configuration and roles

[0256] server

[0257] The server functions as the core of the system and is equipped with a generative artificial intelligence and an emotion engine. The server processes user input received from the user interface and exchanges data with external services. It also automates specific tasks (e.g., inventory management) based on user requests, and monitors and notifies users of their progress. The emotion engine recognizes the user's emotions in real time, and the generative artificial intelligence generates an appropriate response based on those emotions.

[0258] Terminal

[0259] The terminal works in cooperation with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server and also indicates the user's emotional state.

[0260] User

[0261] Users interact with the system through a terminal interface. This system allows users to streamline inventory management tasks and utilize automated ordering processes. Furthermore, appropriate responses based on the user's emotions provide a more comfortable interface experience.

[0262] Program processing

[0263] The specific program processing flow is as follows:

[0264] 1. Emotion Recognition and Dialogue Generation

[0265] User: The user inputs information through the device's user interface. For example, when the user inputs a request such as "add 50 pens," emotions are read from the user's facial expressions and voice.

[0266] Device: The device captures the user's emotional data (facial expressions, voice tone, etc.) and sends it to the server.

[0267] Server: The server uses an emotion engine to recognize the user's emotions. The generative AI then generates an appropriate response based on the emotion and sends it back to the user.

[0268] 2. Add and check inventory

[0269] User: After receiving the appropriate response based on their emotion, the user makes a request to add more stock via the terminal. For example, they send an instruction to the server saying, "Add 50 pens."

[0270] Server: The server updates inventory information and generates a message of acceptance based on the user's emotional state, as recognized by the emotion engine. For example, if the user is nervous, the system can send a message to relax.

[0271] 3. Automated ordering and progress monitoring

[0272] Terminal: Periodically communicates with the server and sends a request to check stock availability.

[0273] Server: The server automatically detects items below the inventory threshold and calculates the order quantity. The order information is sent to the terminal in the form of an appropriate notification based on the user's emotional state recognized by the emotion engine.

[0274] Terminal: The order results are displayed on the user interface, along with the user's emotional state.

[0275] Specific examples

[0276] For example, if a user commands "add 50 pens" through a device, the device captures the user's facial expression along with the command and sends it to the server. The server then uses an emotion engine to analyze the user's emotions, and the generative AI generates and sends a message corresponding to the user's emotions (e.g., "Got it, I'll add 50 pens").

[0277] Similarly, if inventory falls below a threshold, the server automatically initiates the ordering process and notifies the user of the order outcome in an emotionally sensitive manner. For example, if an order is delayed, a comforting message such as "Please wait a moment, we're on our way" can be added.

[0278] In this way, this system has advanced response capabilities that combine generative artificial intelligence and an emotion engine, simultaneously improving the efficiency of inventory management tasks and the user experience.

[0279] The processing flow will be explained below.

[0280] Step 1:

[0281] User: The user inputs a request through the device's user interface, for example, "Add 50 pens." At the same time, the user's facial expressions and tone of voice are captured.

[0282] Step 2:

[0283] Terminal: The terminal sends the user's facial expression data and voice tone data along with the input request to the server.

[0284] Step 3:

[0285] Server: The server processes the received request and emotion data. It uses an emotion engine to recognize the user's emotion (e.g., joy, anger, sadness, surprise, etc.).

[0286] Step 4:

[0287] Server: Based on the emotions recognized by the emotion engine, the generative AI generates an appropriate response message. For example, if the user is tired, it generates a relaxing message such as "Got it. 50 pens have been added. Thank you for your continued patronage."

[0288] Step 5:

[0289] Server: The server generates a response message and sends it to the terminal to notify the user.

[0290] Step 6:

[0291] Terminal: The terminal displays the response message received from the server on the user interface. The user can see the response message and confirm that the stock has been added.

[0292] Step 7:

[0293] User: A user requests an inventory check of a specific item through a terminal, for example, by entering a request such as "Check inventory of notebooks."

[0294] Step 8:

[0295] Terminal: The terminal sends a request to the server.

[0296] Step 9:

[0297] Server: The server retrieves the inventory amount of the specified item from the database.

[0298] Step 10:

[0299] Server: As before, the generative AI generates an appropriate message based on the inventory status, such as "There are 10 notebooks left in stock. You can order more if needed."

[0300] Step 11:

[0301] Server: The server sends the generated message to the terminal and notifies the user.

[0302] Step 12:

[0303] Terminal: The terminal displays the message received from the server on the user interface, and the user can check the stock amount.

[0304] Step 13:

[0305] Terminal: The terminal periodically communicates with the server and sends a request to check stock availability.

[0306] Step 14:

[0307] Server: The server automatically detects items that are below a stock threshold and determines the need for automatic ordering.

[0308] Step 15:

[0309] Server: When automatic ordering is required, the server generates an order in cooperation with an external service. The emotion engine adjusts the notification message of the order progress according to the user's emotion.

[0310] Step 16:

[0311] External Service: An external service receives the order request and initiates processing.

[0312] Step 17:

[0313] External service: Once the order is placed, the result is notified to the server.

[0314] Step 18:

[0315] Server: The server logs the order result and generates a notification message that takes the user's feelings into consideration. For example, if the order is delayed, it adds a comforting message such as "The current shipping status is that the product is being prepared. Please wait a little longer."

[0316] Step 19:

[0317] Server: The server sends a notification message to the terminal.

[0318] Step 20:

[0319] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to view the progress of the automated order and the latest inventory status.

[0320] Through this series of processes, the system recognizes the user's emotions and responds appropriately, thereby improving the user experience and enabling efficient inventory management.

[0321] Example 2

[0322] 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."

[0323] Traditional inventory management systems lack the ability to respond to user emotions, which often results in poor user experience and inefficient inventory management. Furthermore, the lack of automated task management based on user requests and real-time progress notifications hinders smooth business operations.

[0324] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0325] In this invention, the server includes means for communicating with the user using generative artificial intelligence, means for linking with external services and acquiring data based on the user's request, means for recognizing the user's emotions and generating an appropriate response, means for automating specific tasks based on the user's request, and means for monitoring the progress of the tasks and notifying the user of the results. This enables high-quality responses that take the user's emotions into consideration, resulting in more efficient inventory management and an improved user experience.

[0326] "Generative artificial intelligence" is a computer-based technology that interacts with users and uses natural language processing to generate appropriate responses.

[0327] "External services" are online services that allow you to use information and functions, such as APIs and databases, provided outside the system.

[0328] An "emotion engine" is a software module that analyzes emotions from a user's facial expressions, tone of voice, text, etc., and adjusts responses based on those emotions.

[0329] A "user interface" is an interaction means, such as a screen or input device, that allows a user to interact with a system.

[0330] A "database" is an information system for efficiently storing, managing, and retrieving data such as inventory information.

[0331] "Automation" is the process by which a program or machine performs a task based on a user's request without human intervention.

[0332] "Notifications" are messages or alerts that convey important information to the user, such as the progress or results of a task.

[0333] "Inventory management" is the management task of optimizing the amount of goods and materials in stock and replenishing or ordering in a timely manner.

[0334] A "prompt sentence" is a piece of text that is input to a generative AI and serves as the basis for generating a response.

[0335] MODE FOR CARRYING OUT THE INVENTION

[0336] System Overview

[0337] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[0338] Hardware and Software Configuration

[0339] server

[0340] The server functions as the core of the system and is equipped with a generative artificial intelligence and emotion engine. The server processes user input received from the user interface and exchanges data with external services. The server also automates specific tasks (e.g., inventory management) and monitors and notifies progress.

[0341] Terminal

[0342] The terminal works in conjunction with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server, along with the user's emotional state.

[0343] Program processing

[0344] 1. Receiving User Requests

[0345] The user inputs a request, for example, "add 50 pens" via the user interface of the terminal.

[0346] The device captures the user's input and emotional data such as facial expressions and tone of voice at the time of input, and sends this to the server.

[0347] 2. Sentiment Analysis and Response Generation

[0348] The server processes the received request and emotion data and analyzes the user's emotion using the emotion engine.

[0349] The server generates a prompt for the generative AI model. For example, "There is a request to add 50 pens, and the user is nervous."

[0350] The generative AI model generates an appropriate response based on this prompt, for example, "Got it. I'll add 50 pens. Relax."

[0351] 3. Sending and Displaying the Response

[0352] The server sends the generated response to the terminal.

[0353] The terminal displays the response received from the server on the user interface.

[0354] 4. Updating inventory information

[0355] The server updates the inventory database to record that 50 pens have been added.

[0356] The user can check the latest inventory information via the terminal. For example, when the user instructs "display inventory list," the terminal reads and displays the latest inventory information.

[0357] 5. Automated ordering and progress monitoring

[0358] The terminal periodically sends a request to the server to check the stock status.

[0359] The server automatically detects items that are below the inventory threshold and initiates the ordering process.

[0360] The generative AI model generates an appropriate message to inform the user that the ordering process has begun, for example, "We are running low on stock, so we have automatically ordered pens."

[0361] The server sends appropriate notification messages to the terminal to record progress.

[0362] The terminal displays notification messages received from the server on the user interface to provide the user with real-time progress information. For example, when an order is completed, a message such as "Order completed. Waiting for delivery" is displayed.

[0363] Specific examples

[0364] For example, if a user issues an instruction to "add 50 pens" via a device, the device captures the instruction and the user's emotional data and sends them to the server. The server then uses an emotion engine to analyze the user's emotions, and a generative artificial intelligence (AI) system generates a response message appropriate to the user's emotions. For example, the message generated might read, "Got it. I'll add 50 pens. Please relax." This message is then sent to the device and displayed to the user.

[0365] If the stock falls below the threshold, the server automatically starts the ordering process and notifies the user of the result. For example, it generates a message saying, "Stock is low, so pens have been automatically ordered." and notifies the terminal.

[0366] In this way, by combining generative artificial intelligence and an emotion engine, this system provides advanced dialogue and emotion recognition functions, improving inventory management efficiency and the user experience.

[0367] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0368] Step 1:

[0369] The user inputs a request through the user interface of the terminal, for example, "add 50 pens." The input data is the string "add 50 pens," which triggers the next processing step. The terminal sends the input data to the server.

[0370] Step 2:

[0371] The device captures the user's emotional data (such as facial expressions and voice tone) when inputting a request. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice tone, extracting them as digital data. The emotional data and input data are then sent together to the server.

[0372] Step 3:

[0373] The server processes the received request data and emotion data. The input is the user's request and emotion data, and the output is the emotion recognition result and a prompt. Using the emotion engine, the server analyzes the user's emotion and generates a prompt for the generative AI model based on the results. For example, a prompt such as "There is a request to add 50 pens, and the user is nervous" is generated.

[0374] Step 4:

[0375] The generative AI model generates an appropriate response based on the prompt received from the server. The input is the generated prompt, and the output is a generated response message. For example, the generated response message is "Got it. I'll add 50 pens. Relax."

[0376] Step 5:

[0377] The server sends the generated response message to the terminal. The input is the generated response message, and the output is data communication to the terminal. The terminal displays the response message received from the server on its user interface. For example, a message such as "Got it. 50 pens will be added. Please relax." is displayed on the terminal.

[0378] Step 6:

[0379] The server updates the inventory database. The input is the user's request data, and the output is the updated inventory information. Specifically, the addition of 50 pens is recorded in the database. The user can check the latest inventory information through the terminal. For example, if the user instructs "Display inventory list," the terminal will read and display the latest inventory information. Specifically, the server retrieves inventory data from the database and displays it on the user interface.

[0380] Step 7:

[0381] The terminal periodically sends a request to check the stock status to the server. The input is a regular interval (e.g., once a day), and the output is a stock check request sent to the server.

[0382] Step 8:

[0383] The server automatically detects items that fall below an inventory threshold and initiates the ordering process. The input is current inventory data, and the output is the calculated order quantity and ordering information. Specifically, the server scans the inventory database and automatically places an order for items that fall below the threshold.

[0384] Step 9:

[0385] The generative AI model generates an appropriate message to notify the user that the ordering process has begun. The input is the start information of the ordering process, and the output is a notification message. For example, a message such as "We have automatically placed an order for pens as we are running low on stock" is generated.

[0386] Step 10:

[0387] The server sends the generated notification message to the terminal. The input is the generated notification message, and the output is data communication to the terminal. The terminal displays the notification message received from the server on the user interface, providing the user with a progress status in real time. Specifically, when the order processing is complete, the message "Order completed. Waiting for delivery" is displayed.

[0388] (Application example 2)

[0389] 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."

[0390] Although conventional inventory management systems have advanced in terms of automation of inventory management, they have a problem of being unable to respond flexibly based on user emotions. Furthermore, when users check inventory or place orders, they lack appropriate support based on their status and emotions, which tends to reduce the quality of the user experience. Furthermore, there is a need for a method to efficiently manage inventory while taking into consideration the emotions of workers at worksites such as logistics centers.

[0391] 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.

[0392] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for connecting with external services and acquiring data based on a user request, means for automating specific inventory management tasks based on the user request, means for monitoring the progress of the tasks and notifying the user of the results, and means for recognizing the user's emotions and generating responses based on the emotions. This allows the user to receive appropriate support that takes emotions into consideration when performing inventory management tasks. Furthermore, when inventory falls below a threshold, an order notification message generated based on the emotions is sent to the user, thereby realizing efficient and flexible inventory management.

[0393] "Generative AI" is an AI system that has the ability to generate new information and responses based on given data.

[0394] "Means for communicating with the user" refers to means that has the function of receiving input from the user and returning appropriate responses or information in response to that input.

[0395] "Means for linking with external services and acquiring data based on user requests" refers to means that has the function of communicating with other systems and services, acquiring the necessary data, and responding to user requests.

[0396] A "means for automating a specific task" is a means that has the function of automatically executing a specific job or work without human intervention, based on instructions from a user.

[0397] The "means for monitoring the progress of a task and notifying the user of the result" is a means having a function for tracking the progress of an automated task and notifying the user of the result.

[0398] "Means for recognizing emotions and generating a response based on the emotions" refers to means that has the function of analyzing the user's emotions from facial expressions, tone of voice, etc., and generating a response that is adapted to those emotions.

[0399] "Inventory management" refers to the act of keeping track of stock levels and replenishing or ordering as needed.

[0400] A "threshold" is a specific reference value, below which or above which a specific action is executed.

[0401] An "order notification message" is a notification message that is automatically generated and sent to a user when inventory needs to be replenished.

[0402] MODE FOR CARRYING OUT THE INVENTION

[0403] The present invention combines generative artificial intelligence and an emotion engine in an inventory management system at a logistics center, thereby achieving efficient and flexible responses.

[0404] System configuration

[0405] server

[0406] The server is the core of the system and has the following functions:

[0407] It communicates with users using generative artificial intelligence (AI model).

[0408] Data is shared with external services and data is retrieved based on user requests.

[0409] Automate specific inventory management tasks based on user requests.

[0410] Monitor the progress of the task and notify the user of the results.

[0411] An emotion engine is used to recognize the user's emotions and generate responses based on those emotions.

[0412] The specific tools used are IBM Watson Emotion Analysis as the emotion engine and OpenAI GPT-4 as the generative artificial intelligence, with Node.js as the backend server and MongoDB as the database.

[0413] Terminal

[0414] The device works in conjunction with the server and provides the user interface. It is built as a smartphone app and developed using React Native. The device has the following features:

[0415] It uses a camera and microphone to capture the user's facial expressions and tone of voice.

[0416] Send the capture data to the server.

[0417] Provides an interface for checking inventory and requesting additional items.

[0418] Displays the sentiment analysis results received from the server and the generated response.

[0419] User

[0420] The user (worker) interacts with the system through a terminal. They perform tasks such as checking inventory, adding, or reducing it, and receive responses from the system. In addition, receiving responses based on the results of emotion analysis enables efficient and comfortable inventory management.

[0421] Example of a system

[0422] When a user makes a request via a terminal to "add 50 pens," the following happens:

[0423] 1. The device's camera and microphone capture the user's facial expressions and voice.

[0424] 2. The captured data is sent to the backend server in real time.

[0425] 3. The server uses an emotion engine (IBM Watson Emotion Analysis) to analyze the user's emotions.

[0426] 4. Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on the emotion and sends a message to the device such as, "Got it, we'll add 50 pens. Good luck with your future work!"

[0427] 5. When the inventory falls below the threshold, the ordering process will be automatically initiated and an ordering notification message will be sent to the user saying, "Don't worry, we will start the ordering process and replenish the inventory right away. Please wait a moment."

[0428] Prompt Sentence Examples

[0429] User emotion: Happy

[0430] User input: "Add 50 pens"

[0431] Response: "Okay, I'll add 50 pens. Good luck with your work!"

[0432] User emotion: Stressed

[0433] User input: "Stock is low, what should I do?"

[0434] Response: "Don't worry. We'll start the ordering process and replenish your inventory right away. Please be patient."

[0435] This invention improves the efficiency of inventory management tasks at logistics centers and enables flexible responses that take user emotions into consideration. Furthermore, appropriate responses based on emotions improve the quality of the user experience.

[0436] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0437] Step 1:

[0438] The user launches the terminal's user interface and logs in. The input is the user's login information (username, password), and the output is a message indicating whether the login was successful or not. The terminal obtains this information and sends it to the server. The server verifies the login information and returns the result to the terminal.

[0439] Step 2:

[0440] The user inputs a request for inventory check or addition into the terminal. The input is an inventory management request such as "add 50 pens." The terminal receives this input, captures the user's facial expressions and voice with a camera and microphone, and transmits them to the server in real time.

[0441] Step 3:

[0442] The server receives the captured data sent from the device and analyzes it using an emotion engine (IBM Watson Emotion Analysis). The input is the user's facial expression data and voice data, and the output is analyzed emotion data (e.g., "Happy," "Stressed," etc.). The server acquires this emotion data and uses it as a prompt to send to the generative artificial intelligence (OpenAI GPT-4).

[0443] Step 4:

[0444] Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on emotional data and the user's request. The input is the emotional data and the user's request, and the output is a response message based on the emotion. For example, if the emotion is "Happy," the message generated is "Got it, we'll add 50 pens. Good luck with your future work!"

[0445] Step 5:

[0446] The server sends the generated response message to the terminal. The output is the response message displayed on the terminal. The terminal receives this message and displays it on the user interface. The user confirms this message.

[0447] Step 6:

[0448] The server receives inventory management requests and updates the MongoDB database. The input is the inventory addition request (e.g., "add 50 pens") and the output is the updated inventory data. The server updates the inventory information and monitors the results.

[0449] Step 7:

[0450] When inventory falls below the threshold, the server initiates an automatic ordering process. The input is the updated inventory data and threshold information, and the output is an order notification message. Generative AI generates an appropriate order notification message based on emotions, generating messages such as, "Don't worry. We will immediately start the ordering process and replenish the inventory. Please wait a moment."

[0451] Step 8:

[0452] The server sends the generated order notification message to the terminal, which receives the message and displays it on the user interface. The user can then confirm the order notification message and continue working with peace of mind.

[0453] In this way, the user, terminal, and server work together in each processing step, realizing automation of inventory management and appropriate responses according to the user's emotions.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] [Second embodiment]

[0458] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0469] 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."

[0470] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[0471] System configuration and roles

[0472] server

[0473] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[0474] Terminal

[0475] The terminal operates in cooperation with the server. The terminal provides a user interface and acts as a window through which the user can make requests to the server for inventory management and other matters. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[0476] User

[0477] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[0478] Program processing

[0479] The specific program processing flow is as follows:

[0480] 1. Adding inventory

[0481] User: The user sends a command to the server from their device to add a specific item to their inventory.

[0482] Server: The server receives instructions from the user and updates the inventory information. The updated inventory information is recorded in a log and notified to the user.

[0483] 2. Check inventory

[0484] User: A user checks the stock level of a specific item from a terminal.

[0485] Server: The server provides inventory information for the specified item to the terminal and displays that information to the user.

[0486] 3. Automated ordering

[0487] Terminal: The terminal periodically communicates with the server to check stock availability.

[0488] Server: The server automatically detects items that are below the inventory threshold and calculates the required order quantity. After the calculation, the server sends the order information to an external service and processes the order. The order result is logged and notified to the user via the terminal.

[0489] Specific examples

[0490] For example, if a user wants to add "pens" to the inventory, the user sends an instruction to the server via the terminal interface to "add 50 pens." The server receives this instruction and updates the inventory information, increasing the inventory of pens by 50.

[0491] Next, when the user wants to check the inventory of "notes," he sends a "Check notebook inventory" request to the server through the terminal. The server returns the current inventory of notes to the terminal, and the user can check the information.

[0492] Furthermore, if the system's inventory falls below 10 notebooks, it will automatically order more notebooks. The server calculates the order quantity and processes the order in conjunction with an external service. The order result is notified to the user via their terminal, and the user can check the order progress in real time.

[0493] In this way, this system automates inventory management and ordering through dialogue with users using generative artificial intelligence, supporting efficient business operations.

[0494] The processing flow will be explained below.

[0495] Step 1:

[0496] User: The user enters an inventory addition through the device's user interface (e.g., "Add 50 pens").

[0497] Step 2:

[0498] Terminal: The terminal prepares a request to send to the server an instruction from the user to add stock.

[0499] Step 3:

[0500] Server: The server parses the inventory addition request received from the terminal and retrieves the specified item and quantity.

[0501] Step 4:

[0502] Server: The server checks the inventory status and updates the quantity if the specified item already exists, otherwise it adds it as a new item.

[0503] Step 5:

[0504] Server: Updates the database with the updated inventory information and logs the inventory change history.

[0505] Step 6:

[0506] Server: Sends inventory update results to the device.

[0507] Step 7:

[0508] Terminal: The terminal receives the response from the server and displays the results on the user interface, allowing the user to see the quantity of stock that has been added.

[0509] Step 8:

[0510] User: A user makes a request through a terminal to check the inventory of a specific item (e.g., a "notebook").

[0511] Step 9:

[0512] Terminal: The terminal prepares the stock check request from the user to send to the server.

[0513] Step 10:

[0514] Server: The server analyzes the stock check request received from the terminal and retrieves the stock amount of the specified item from the database.

[0515] Step 11:

[0516] Server: Sends the acquired inventory information to the terminal.

[0517] Step 12:

[0518] Terminal: The terminal receives the response from the server and displays the inventory information on the user interface. The user can check the stock amount of the item they want to check.

[0519] Step 13:

[0520] Device: Periodically communicates with the server and sends a request to check inventory status.

[0521] Step 14:

[0522] Server: The server checks inventory and determines if a particular item is below a threshold.

[0523] Step 15:

[0524] Server: If the item is below the threshold, automatically calculate the order quantity and send an order request to an external service.

[0525] Step 16:

[0526] External Service: An external service receives the order request and initiates processing.

[0527] Step 17:

[0528] External service: After the order is completed, the result is notified to the server.

[0529] Step 18:

[0530] Server: Records the order result in a log and notifies the terminal.

[0531] Step 19:

[0532] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to see the progress of the automated order.

[0533] In this way, the system can perform tasks such as adding inventory, checking, and auto-ordering in a series of processing steps via a user interface.

[0534] Example 1

[0535] 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."

[0536] In inventory management, manual tasks such as adding, checking, and ordering inventory require time and effort, hindering efficient operations. Furthermore, ordering inventory after inventory runs out can create a time lag, potentially disrupting operations. There is a need for a system that can solve these problems and achieve efficient inventory management and an automated ordering process.

[0537] 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.

[0538] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for cooperating with an external service and acquiring data based on a user request, means for automating a specific task based on a user request, means for monitoring the progress of the task and notifying the user of the result, means for a user to send an instruction to add stock from a terminal and for the server to analyze and process the instruction, means for a user to send an inventory check request from a terminal and for the server to analyze and process the request, means for the server to periodically monitor inventory and automatically order items that are below a threshold, and means for processing orders and notifying the results via an external service, thereby enabling efficient and automated inventory management.

[0539] "Generative AI" refers to artificial intelligence technology that can interact with users and analyze data, and uses natural language processing and machine learning to generate appropriate responses.

[0540] "External services" refer to external systems or applications that provide functions such as data acquisition and order processing through collaboration with the server.

[0541] "User request" refers to an operation or instruction given by a user to the system, and includes processing requests such as adding inventory, checking, and placing an order.

[0542] "Means to automate specific tasks" refers to functions that allow a system to automatically execute business processes that were previously performed manually, including inventory management and order processing.

[0543] "Means for monitoring task progress" refers to the functionality for tracking the status of ongoing tasks and checking completion and progress.

[0544] "Means for a user to send an instruction to add stock from a terminal and for the server to analyze and process that instruction" refers to the function that allows a user to send an instruction to add stock to a server via a terminal, and for the server to interpret and process that instruction.

[0545] "Means for a user to send an inventory check request from a terminal and for the server to analyze and process the request" refers to the function that allows a user to send an inventory check request to a server via a terminal, and the server to analyze the request and provide inventory information.

[0546] "Means for the server to periodically monitor inventory and automatically order items that fall below a threshold" refers to a function in which the server periodically checks inventory information and automatically places an order if it detects that inventory is below a pre-set threshold.

[0547] "Means for processing orders and notifying the results via an external service" refers to a function that enables the server to execute orders in cooperation with an external ordering system and notify the user of the results.

[0548] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[0549] System configuration and roles

[0550] server

[0551] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[0552] Terminal

[0553] The terminal operates in conjunction with the server. The terminal provides a user interface and acts as a window through which users can make requests to the server for inventory management and other purposes. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[0554] User

[0555] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[0556] Program processing

[0557] 1. Adding inventory

[0558] User: The user sends a command to the server from their device to add a specific item to their inventory.

[0559] Server: The server receives instructions from the user and analyzes them using a generative AI model. Based on the analysis results, it updates the stock quantity of the corresponding item in the inventory database. The updated stock information is recorded in a log and notified to the user.

[0560] Terminal: The terminal receives inventory updates from the server and displays them to the user.

[0561] 2. Check inventory

[0562] User: A user sends a request from their device to check the stock level of a specific item.

[0563] Server: The server receives the request, analyzes it using the generative AI model, retrieves the stock information for the specified item from the inventory database, and sends it to the device.

[0564] Terminal: The terminal displays the inventory information received from the server to the user.

[0565] 3. Automated ordering

[0566] Server: The server periodically scans the inventory database to detect items whose stock is below a threshold. It uses a generative AI model to calculate the required order quantity and sends the order information to an external ordering system (e.g., external API). The order result is logged and notified to the user via the terminal.

[0567] Terminal: The terminal displays the order notification received from the server to the user.

[0568] Specific examples

[0569] For example, if a user sends an instruction to "add 50 pens" through the terminal interface, the server will receive this instruction and increase the stock of pens in the inventory database by 50. After updating the stock information, the server will record it in a log and generate a notification to send to the terminal, which will then display this notification to the user.

[0570] Next, when the user sends a request to "check notebook stock amount," the server obtains notebook stock information and sends it to the terminal, allowing the user to check the information.

[0571] Furthermore, if the system detects that the inventory of a notebook falls below 10 units, the server automatically uses the generative AI model to calculate the required order quantity and place an order through the external ordering system. The ordering result is logged and the user is notified via the terminal.

[0572] Example input to a generative AI model

[0573] Below is an example of input to a generative AI model:

[0574] "Add 50 pens"

[0575] Check notebook inventory

[0576] In this way, the present invention is a system that realizes the automation of inventory management and ordering through dialogue with users using generative artificial intelligence, thereby supporting efficient business operations.

[0577] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0578] Step 1:

[0579] Adding inventory

[0580] Input: A user inputs an inventory increase instruction, such as "add 50 pens," into a terminal.

[0581] Action: The user enters "Add 50 pens" into the inventory addition form through the terminal interface and clicks the submit button.

[0582] Specific behavior: The device detects this input and sends the data to the server as an HTTP POST request.

[0583] Data processing / calculation: The server receives the request, analyzes the instruction using the generative AI model, extracts the information "pen" and "50 units", accesses the inventory database, and increases the number of pens in stock by 50 units.

[0584] Output: Generates a success message and updated inventory information and sends them to the terminal.

[0585] Action: The device receives the updated inventory information and displays it to the user.

[0586] Step 2:

[0587] Check inventory

[0588] Input: A user inputs an inventory check request such as "Check notebook inventory" on a device.

[0589] How it works: The user enters "Check notebook inventory" into the inventory check form through the device interface and clicks the submit button.

[0590] Specific behavior: The device detects this input and sends the data to the server as an HTTP GET request.

[0591] Data processing / calculation: The server receives the request, analyzes the request using the generative AI model, and extracts the information "notebook." It then accesses the inventory database to obtain the notebook's inventory information.

[0592] Output: Generates a response with the current note inventory information and sends it to the device.

[0593] Operation: The device receives the notebook inventory information and displays it to the user.

[0594] Step 3:

[0595] Automatic ordering

[0596] Input: The server checks the inventory database on a regular schedule.

[0597] How it works: At regular intervals (e.g., every day at midnight), the server detects items that are below a stock threshold.

[0598] What happens: The server scans the inventory database on a scheduled basis to detect items below a threshold (e.g., fewer than 10 notebooks in stock).

[0599] Data processing / calculation: Use the generative AI model to calculate the required order quantity (e.g., order 20 notebooks), then send the order information to an external ordering system (e.g., external API).

[0600] Output: Receives the response containing the order result, logs it, and generates a notification message to send to the terminal.

[0601] Operation: The terminal displays the order notification received from the server to the user.

[0602] Step 4:

[0603] Order status notification

[0604] Input: Order result feedback from external ordering system.

[0605] How it works: The server periodically calls the API of the external ordering system to check the progress of the order.

[0606] Specific behavior: The server retrieves the order status through the API and records it in a log.

[0607] Data processing / calculation: Analyze the retrieved order status and use a generative AI model to generate a message to notify the user.

[0608] Output: Sends a notification message to the terminal.

[0609] Action: The terminal displays the received notification message to the user.

[0610] (Application example 1)

[0611] 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."

[0612] In current inventory management systems, the processes of adding, checking, and ordering inventory are often all done manually, resulting in reduced work efficiency and a high likelihood of human error. Additionally, inventory information cannot be checked in real time on-site, making it difficult to respond quickly. There is a need for a system that can solve these problems and improve the efficiency and accuracy of inventory management at logistics centers and other facilities.

[0613] 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.

[0614] In this invention, the server includes means for communicating with users using generative artificial intelligence, means for connecting with external services and acquiring data based on user requests, means for automating specific tasks based on user requests, means for monitoring task progress and notifying the user of the results, means for receiving user voice commands using voice recognition and executing processing, and means for visualizing inventory information in real time using a user-portable 3D display device. This allows users to add or check inventory using voice commands and check inventory status in real time through their smart devices. Furthermore, automatic ordering is performed when inventory levels fall below a certain threshold, achieving efficient inventory management.

[0615] "Generative AI" is AI that analyzes data and generates responses and instructions in natural language through dialogue with the user.

[0616] "Means for communicating with the user" refers to an interface that uses generative artificial intelligence to realize two-way dialogue with the user through voice and text.

[0617] "Means of linking with external services" refers to the function of obtaining necessary information from external databases or APIs and using it within the system.

[0618] A "means for automating a task" is a function for executing a task based on a request from a user without manual intervention and managing the progress of the task.

[0619] The "means for monitoring and notifying the progress of a task" is a function for tracking the status of a task currently being executed and notifying the user of the results in real time.

[0620] The "means for receiving user voice commands using voice recognition" is a function for analyzing the user's voice, converting it into text data, and interpreting it as instructions.

[0621] "Means for visualizing inventory information using a portable 3D display device" refers to a function that uses a portable device such as smart glasses or a head-mounted display to display inventory information in three dimensions and present it to the user in an easy-to-understand manner.

[0622] "Inventory management" is the process of managing the quantity of products and parts held in stock and replenishing or ordering as needed.

[0623] An "inventory database" is a database that records information on all items managed as inventory and can be referenced and updated as needed.

[0624] "Automatic ordering" is the process by which the system automatically orders additional stock when inventory falls below a defined threshold.

[0625] This invention is a system that uses generative artificial intelligence to realize communication through voice recognition, visualization of real-time inventory information, and automatic ordering in order to improve the efficiency of inventory management at logistics centers, etc. As an application example of this invention, details of an inventory management system using smart glasses will be described.

[0626] System configuration and roles

[0627] server

[0628] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user and accepts voice commands from the user. It also connects with external services to obtain necessary data and manage inventory information. It also has a function to automatically place an order when inventory levels fall below a threshold. The server uses Python programs and voice recognition libraries (e.g., SpeechRecognition).

[0629] Terminal

[0630] The terminal is a portable device such as smart glasses or a head-mounted display that allows users to input voice commands. The terminal displays inventory information in 3D in real time, allowing users to easily check inventory status on-site.

[0631] User

[0632] Users operate the system through smart glasses to manage inventory. For example, a user might give a voice command such as "add 50 pens." The smart glasses then transmit the voice command to a server, which analyzes the voice and updates the inventory database. When inventory falls below a certain threshold, the server automatically places an order and notifies the user of the result.

[0633] Program Description

[0634] 1. Hardware:

[0635] Server: High-performance server (e.g. Amazon AWS, Google Cloud Platform)

[0636] Devices: Smart glasses (e.g., Google Glass), head-mounted displays (e.g., Microsoft HoloLens)

[0637] 2. Software:

[0638] Server-side program: Python

[0639] Speech recognition library: SpeechRecognition

[0640] Notification Library: Pushbullet API

[0641] 3. Data processing and calculation:

[0642] The user sends a voice command to the smart glasses.

[0643] The smart glasses send the voice data to a server, where a Python program converts the voice into text for analysis.

[0644] The server updates the inventory database based on the instructions and notifies the user of the changes.

[0645] When inventory falls below a threshold, the server automatically places an order and notifies the user of the result.

[0646] Specific examples

[0647] The user commands the smart glasses to "add 50 pens." The smart glasses recognize the voice and send it to the server. The server analyzes the received voice data and updates the inventory database. The user can confirm the completion of the task by seeing the message "50 pens added" on the smart glasses' display.

[0648] Example prompt sentence:

[0649] The user speaks to the smart glasses, "Add 50 pens." This speech information is sent to the server, and the generative AI model interprets it as "Add 50 pens to inventory" and updates the database. At that time, the user should be notified that the addition is complete.

[0650] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0651] Step 1:

[0652] The user speaks the voice command "Add 50 pens" to the smart glasses.

[0653] Input: User's voice command

[0654] Output: Audio data

[0655] What it does: The microphone in the smart glasses captures the user's voice and obtains the voice data.

[0656] Step 2:

[0657] The terminal (smart glasses) transmits the acquired voice data to the server.

[0658] Input: Audio data

[0659] Output: Sending audio data to the server

[0660] What it does: The smart glasses send audio data over the internet to a specified endpoint on the server.

[0661] Step 3:

[0662] The server converts the received voice data into text.

[0663] Input: Audio data

[0664] Output: Converted text data (e.g. "Add 50 pens")

[0665] Specific operation: The server converts the voice data into text using a speech recognition library (e.g., SpeechRecognition).

[0666] Step 4:

[0667] The server parses the text data and updates the inventory database.

[0668] Input: Text data

[0669] Output: Updated inventory database

[0670] Specific operation: The server uses generative artificial intelligence to analyze the text data, interprets it as an instruction to "add 50 pens," and increases the inventory quantity of the corresponding item in the inventory database by 50.

[0671] Step 5:

[0672] The server notifies the user of the results of the inventory database update.

[0673] Input: Updated inventory information

[0674] Output: A notification message to the user (e.g. "50 pens added").

[0675] What it does: The server sends a notification message to the user's smart glasses using a notification library such as the Pushbullet API.

[0676] Step 6:

[0677] The terminal (smart glasses) displays the received notification message to the user.

[0678] Input: Notification message from the server

[0679] Output: Notification message displayed on the smart glasses display

[0680] Specific operation: The smart glasses analyze the received notification message and display the message "50 pens added" on the display.

[0681] Step 7:

[0682] The server automatically places an order if the inventory level falls below a threshold.

[0683] Input: Updated inventory information

[0684] Output: Automatic ordering instructions and notification of ordering results

[0685] Specific operation: The server checks the inventory database, and if the inventory level is below the threshold, it sends an order instruction to an external service, logs the order result, and notifies the user.

[0686] 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.

[0687] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[0688] System configuration and roles

[0689] server

[0690] The server functions as the core of the system and is equipped with a generative artificial intelligence and an emotion engine. The server processes user input received from the user interface and exchanges data with external services. It also automates specific tasks (e.g., inventory management) based on user requests, and monitors and notifies users of their progress. The emotion engine recognizes the user's emotions in real time, and the generative artificial intelligence generates an appropriate response based on those emotions.

[0691] Terminal

[0692] The terminal works in cooperation with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server and also indicates the user's emotional state.

[0693] User

[0694] Users interact with the system through a terminal interface. This system allows users to streamline inventory management tasks and utilize automated ordering processes. Furthermore, appropriate responses based on the user's emotions provide a more comfortable interface experience.

[0695] Program processing

[0696] The specific program processing flow is as follows:

[0697] 1. Emotion Recognition and Dialogue Generation

[0698] User: The user inputs information through the device's user interface. For example, when the user inputs a request such as "add 50 pens," emotions are read from the user's facial expressions and voice.

[0699] Device: The device captures the user's emotional data (facial expressions, voice tone, etc.) and sends it to the server.

[0700] Server: The server uses an emotion engine to recognize the user's emotions. The generative AI then generates an appropriate response based on the emotion and sends it back to the user.

[0701] 2. Add and check inventory

[0702] User: After receiving the appropriate response based on their emotion, the user makes a request to add more stock via the terminal. For example, they send an instruction to the server saying, "Add 50 pens."

[0703] Server: The server updates inventory information and generates a message of acceptance based on the user's emotional state, as recognized by the emotion engine. For example, if the user is nervous, the system can send a message to relax.

[0704] 3. Automated ordering and progress monitoring

[0705] Terminal: Periodically communicates with the server and sends a request to check stock availability.

[0706] Server: The server automatically detects items below the inventory threshold and calculates the order quantity. The order information is sent to the terminal in the form of an appropriate notification based on the user's emotional state recognized by the emotion engine.

[0707] Terminal: The order results are displayed on the user interface, along with the user's emotional state.

[0708] Specific examples

[0709] For example, if a user commands "add 50 pens" through a device, the device captures the user's facial expression along with the command and sends it to the server. The server then uses an emotion engine to analyze the user's emotions, and the generative AI generates and sends a message corresponding to the user's emotions (e.g., "Got it, I'll add 50 pens").

[0710] Similarly, if inventory falls below a threshold, the server automatically initiates the ordering process and notifies the user of the order outcome in an emotionally sensitive manner. For example, if an order is delayed, a comforting message such as "Please wait a moment, we're on our way" can be added.

[0711] In this way, this system has advanced response capabilities that combine generative artificial intelligence and an emotion engine, simultaneously improving the efficiency of inventory management tasks and the user experience.

[0712] The processing flow will be explained below.

[0713] Step 1:

[0714] User: The user inputs a request through the device's user interface, for example, "Add 50 pens." At the same time, the user's facial expressions and tone of voice are captured.

[0715] Step 2:

[0716] Terminal: The terminal sends the user's facial expression data and voice tone data along with the input request to the server.

[0717] Step 3:

[0718] Server: The server processes the received request and emotion data. It uses an emotion engine to recognize the user's emotion (e.g., joy, anger, sadness, surprise, etc.).

[0719] Step 4:

[0720] Server: Based on the emotions recognized by the emotion engine, the generative AI generates an appropriate response message. For example, if the user is tired, it generates a relaxing message such as "Got it. 50 pens have been added. Thank you for your continued patronage."

[0721] Step 5:

[0722] Server: The server generates a response message and sends it to the terminal to notify the user.

[0723] Step 6:

[0724] Terminal: The terminal displays the response message received from the server on the user interface. The user can see the response message and confirm that the stock has been added.

[0725] Step 7:

[0726] User: A user requests an inventory check of a specific item through a terminal, for example, by entering a request such as "Check inventory of notebooks."

[0727] Step 8:

[0728] Terminal: The terminal sends a request to the server.

[0729] Step 9:

[0730] Server: The server retrieves the inventory amount of the specified item from the database.

[0731] Step 10:

[0732] Server: As before, the generative AI generates an appropriate message based on the inventory status, such as "There are 10 notebooks left in stock. You can order more if needed."

[0733] Step 11:

[0734] Server: The server sends the generated message to the terminal and notifies the user.

[0735] Step 12:

[0736] Terminal: The terminal displays the message received from the server on the user interface, and the user can check the stock amount.

[0737] Step 13:

[0738] Terminal: The terminal periodically communicates with the server and sends a request to check stock availability.

[0739] Step 14:

[0740] Server: The server automatically detects items that are below a stock threshold and determines the need for automatic ordering.

[0741] Step 15:

[0742] Server: When automatic ordering is required, the server generates an order in cooperation with an external service. The emotion engine adjusts the notification message of the order progress according to the user's emotion.

[0743] Step 16:

[0744] External Service: An external service receives the order request and initiates processing.

[0745] Step 17:

[0746] External service: Once the order is placed, the result is notified to the server.

[0747] Step 18:

[0748] Server: The server logs the order result and generates a notification message that takes the user's feelings into consideration. For example, if the order is delayed, it adds a comforting message such as "The current shipping status is that the product is being prepared. Please wait a little longer."

[0749] Step 19:

[0750] Server: The server sends a notification message to the terminal.

[0751] Step 20:

[0752] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to view the progress of the automated order and the latest inventory status.

[0753] Through this series of processes, the system recognizes the user's emotions and responds appropriately, thereby improving the user experience and enabling efficient inventory management.

[0754] Example 2

[0755] 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."

[0756] Traditional inventory management systems lack the ability to respond to user emotions, which often results in poor user experience and inefficient inventory management. Furthermore, the lack of automated task management based on user requests and real-time progress notifications hinders smooth business operations.

[0757] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0758] In this invention, the server includes means for communicating with the user using generative artificial intelligence, means for linking with external services and acquiring data based on the user's request, means for recognizing the user's emotions and generating an appropriate response, means for automating specific tasks based on the user's request, and means for monitoring the progress of the tasks and notifying the user of the results. This enables high-quality responses that take the user's emotions into consideration, resulting in more efficient inventory management and an improved user experience.

[0759] "Generative artificial intelligence" is a computer-based technology that interacts with users and uses natural language processing to generate appropriate responses.

[0760] "External services" are online services that allow you to use information and functions, such as APIs and databases, provided outside the system.

[0761] An "emotion engine" is a software module that analyzes emotions from a user's facial expressions, tone of voice, text, etc., and adjusts responses based on those emotions.

[0762] A "user interface" is an interaction means, such as a screen or input device, that allows a user to interact with a system.

[0763] A "database" is an information system for efficiently storing, managing, and retrieving data such as inventory information.

[0764] "Automation" is the process by which a program or machine performs a task based on a user's request without human intervention.

[0765] "Notifications" are messages or alerts that convey important information to the user, such as the progress or results of a task.

[0766] "Inventory management" is the management task of optimizing the amount of goods and materials in stock and replenishing or ordering in a timely manner.

[0767] A "prompt sentence" is a piece of text that is input to a generative AI and serves as the basis for generating a response.

[0768] MODE FOR CARRYING OUT THE INVENTION

[0769] System Overview

[0770] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[0771] Hardware and Software Configuration

[0772] server

[0773] The server functions as the core of the system and is equipped with a generative artificial intelligence and emotion engine. The server processes user input received from the user interface and exchanges data with external services. The server also automates specific tasks (e.g., inventory management) and monitors and notifies progress.

[0774] Terminal

[0775] The terminal works in conjunction with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server, along with the user's emotional state.

[0776] Program processing

[0777] 1. Receiving User Requests

[0778] The user inputs a request, for example, "add 50 pens" via the user interface of the terminal.

[0779] The device captures the user's input and emotional data such as facial expressions and tone of voice at the time of input, and sends this to the server.

[0780] 2. Sentiment Analysis and Response Generation

[0781] The server processes the received request and emotion data and analyzes the user's emotion using the emotion engine.

[0782] The server generates a prompt for the generative AI model. For example, "There is a request to add 50 pens, and the user is nervous."

[0783] The generative AI model generates an appropriate response based on this prompt, for example, "Got it. I'll add 50 pens. Relax."

[0784] 3. Sending and Displaying the Response

[0785] The server sends the generated response to the terminal.

[0786] The terminal displays the response received from the server on the user interface.

[0787] 4. Updating inventory information

[0788] The server updates the inventory database to record that 50 pens have been added.

[0789] The user can check the latest inventory information via the terminal. For example, when the user instructs "display inventory list," the terminal reads and displays the latest inventory information.

[0790] 5. Automated ordering and progress monitoring

[0791] The terminal periodically sends a request to the server to check the stock status.

[0792] The server automatically detects items that are below the inventory threshold and initiates the ordering process.

[0793] The generative AI model generates an appropriate message to inform the user that the ordering process has begun, for example, "We are running low on stock, so we have automatically ordered pens."

[0794] The server sends appropriate notification messages to the terminal to record progress.

[0795] The terminal displays notification messages received from the server on the user interface to provide the user with real-time progress information. For example, when an order is completed, a message such as "Order completed. Waiting for delivery" is displayed.

[0796] Specific examples

[0797] For example, if a user issues an instruction to "add 50 pens" via a device, the device captures the instruction and the user's emotional data and sends them to the server. The server then uses an emotion engine to analyze the user's emotions, and a generative artificial intelligence (AI) system generates a response message appropriate to the user's emotions. For example, the message generated might read, "Got it. I'll add 50 pens. Please relax." This message is then sent to the device and displayed to the user.

[0798] If the stock falls below the threshold, the server automatically starts the ordering process and notifies the user of the result. For example, it generates a message saying, "Stock is low, so pens have been automatically ordered." and notifies the terminal.

[0799] In this way, by combining generative artificial intelligence and an emotion engine, this system provides advanced dialogue and emotion recognition functions, improving inventory management efficiency and the user experience.

[0800] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0801] Step 1:

[0802] The user inputs a request through the user interface of the terminal, for example, "add 50 pens." The input data is the string "add 50 pens," which triggers the next processing step. The terminal sends the input data to the server.

[0803] Step 2:

[0804] The device captures the user's emotional data (such as facial expressions and voice tone) when inputting a request. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice tone, extracting them as digital data. The emotional data and input data are then sent together to the server.

[0805] Step 3:

[0806] The server processes the received request data and emotion data. The input is the user's request and emotion data, and the output is the emotion recognition result and a prompt. Using the emotion engine, the server analyzes the user's emotion and generates a prompt for the generative AI model based on the results. For example, a prompt such as "There is a request to add 50 pens, and the user is nervous" is generated.

[0807] Step 4:

[0808] The generative AI model generates an appropriate response based on the prompt received from the server. The input is the generated prompt, and the output is a generated response message. For example, the generated response message is "Got it. I'll add 50 pens. Relax."

[0809] Step 5:

[0810] The server sends the generated response message to the terminal. The input is the generated response message, and the output is data communication to the terminal. The terminal displays the response message received from the server on its user interface. For example, a message such as "Got it. 50 pens will be added. Please relax." is displayed on the terminal.

[0811] Step 6:

[0812] The server updates the inventory database. The input is the user's request data, and the output is the updated inventory information. Specifically, the addition of 50 pens is recorded in the database. The user can check the latest inventory information through the terminal. For example, if the user instructs "Display inventory list," the terminal will read and display the latest inventory information. Specifically, the server retrieves inventory data from the database and displays it on the user interface.

[0813] Step 7:

[0814] The terminal periodically sends a request to check the stock status to the server. The input is a regular interval (e.g., once a day), and the output is a stock check request sent to the server.

[0815] Step 8:

[0816] The server automatically detects items that fall below an inventory threshold and initiates the ordering process. The input is current inventory data, and the output is the calculated order quantity and ordering information. Specifically, the server scans the inventory database and automatically places an order for items that fall below the threshold.

[0817] Step 9:

[0818] The generative AI model generates an appropriate message to notify the user that the ordering process has begun. The input is the start information of the ordering process, and the output is a notification message. For example, a message such as "We have automatically placed an order for pens as we are running low on stock" is generated.

[0819] Step 10:

[0820] The server sends the generated notification message to the terminal. The input is the generated notification message, and the output is data communication to the terminal. The terminal displays the notification message received from the server on the user interface, providing the user with a progress status in real time. Specifically, when the order processing is complete, the message "Order completed. Waiting for delivery" is displayed.

[0821] (Application example 2)

[0822] 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."

[0823] Although conventional inventory management systems have advanced in terms of automation of inventory management, they have a problem of being unable to respond flexibly based on user emotions. Furthermore, when users check inventory or place orders, they lack appropriate support based on their status and emotions, which tends to reduce the quality of the user experience. Furthermore, there is a need for a method to efficiently manage inventory while taking into consideration the emotions of workers at worksites such as logistics centers.

[0824] 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.

[0825] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for connecting with external services and acquiring data based on a user request, means for automating specific inventory management tasks based on the user request, means for monitoring the progress of the tasks and notifying the user of the results, and means for recognizing the user's emotions and generating responses based on the emotions. This allows the user to receive appropriate support that takes emotions into consideration when performing inventory management tasks. Furthermore, when inventory falls below a threshold, an order notification message generated based on the emotions is sent to the user, thereby realizing efficient and flexible inventory management.

[0826] "Generative AI" is an AI system that has the ability to generate new information and responses based on given data.

[0827] "Means for communicating with the user" refers to means that has the function of receiving input from the user and returning appropriate responses or information in response to that input.

[0828] "Means for linking with external services and acquiring data based on user requests" refers to means that has the function of communicating with other systems and services, acquiring the necessary data, and responding to user requests.

[0829] A "means for automating a specific task" is a means that has the function of automatically executing a specific job or work without human intervention, based on instructions from a user.

[0830] The "means for monitoring the progress of a task and notifying the user of the result" is a means having a function for tracking the progress of an automated task and notifying the user of the result.

[0831] "Means for recognizing emotions and generating a response based on the emotions" refers to means that has the function of analyzing the user's emotions from facial expressions, tone of voice, etc., and generating a response that is adapted to those emotions.

[0832] "Inventory management" refers to the act of keeping track of stock levels and replenishing or ordering as needed.

[0833] A "threshold" is a specific reference value, below which or above which a specific action is executed.

[0834] An "order notification message" is a notification message that is automatically generated and sent to a user when inventory needs to be replenished.

[0835] MODE FOR CARRYING OUT THE INVENTION

[0836] The present invention combines generative artificial intelligence and an emotion engine in an inventory management system at a logistics center, thereby achieving efficient and flexible responses.

[0837] System configuration

[0838] server

[0839] The server is the core of the system and has the following functions:

[0840] It communicates with users using generative artificial intelligence (AI model).

[0841] Data is shared with external services and data is retrieved based on user requests.

[0842] Automate specific inventory management tasks based on user requests.

[0843] Monitor the progress of the task and notify the user of the results.

[0844] An emotion engine is used to recognize the user's emotions and generate responses based on those emotions.

[0845] The specific tools used are IBM Watson Emotion Analysis as the emotion engine and OpenAI GPT-4 as the generative artificial intelligence, with Node.js as the backend server and MongoDB as the database.

[0846] Terminal

[0847] The device works in conjunction with the server and provides the user interface. It is built as a smartphone app and developed using React Native. The device has the following features:

[0848] It uses a camera and microphone to capture the user's facial expressions and tone of voice.

[0849] Send the capture data to the server.

[0850] Provides an interface for checking inventory and requesting additional items.

[0851] Displays the sentiment analysis results received from the server and the generated response.

[0852] User

[0853] The user (worker) interacts with the system through a terminal. They perform tasks such as checking inventory, adding, or reducing it, and receive responses from the system. In addition, receiving responses based on the results of emotion analysis enables efficient and comfortable inventory management.

[0854] Example of a system

[0855] When a user makes a request via a terminal to "add 50 pens," the following happens:

[0856] 1. The device's camera and microphone capture the user's facial expressions and voice.

[0857] 2. The captured data is sent to the backend server in real time.

[0858] 3. The server uses an emotion engine (IBM Watson Emotion Analysis) to analyze the user's emotions.

[0859] 4. Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on the emotion and sends a message to the device such as, "Got it, we'll add 50 pens. Good luck with your future work!"

[0860] 5. When the inventory falls below the threshold, the ordering process will be automatically initiated and an ordering notification message will be sent to the user saying, "Don't worry, we will start the ordering process and replenish the inventory right away. Please wait a moment."

[0861] Prompt Sentence Examples

[0862] User emotion: Happy

[0863] User input: "Add 50 pens"

[0864] Response: "Okay, I'll add 50 pens. Good luck with your work!"

[0865] User emotion: Stressed

[0866] User input: "Stock is low, what should I do?"

[0867] Response: "Don't worry. We'll start the ordering process and replenish your inventory right away. Please be patient."

[0868] This invention improves the efficiency of inventory management tasks at logistics centers and enables flexible responses that take user emotions into consideration. Furthermore, appropriate responses based on emotions improve the quality of the user experience.

[0869] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0870] Step 1:

[0871] The user launches the terminal's user interface and logs in. The input is the user's login information (username, password), and the output is a message indicating whether the login was successful or not. The terminal obtains this information and sends it to the server. The server verifies the login information and returns the result to the terminal.

[0872] Step 2:

[0873] The user inputs a request for inventory check or addition into the terminal. The input is an inventory management request such as "add 50 pens." The terminal receives this input, captures the user's facial expressions and voice with a camera and microphone, and transmits them to the server in real time.

[0874] Step 3:

[0875] The server receives the captured data sent from the device and analyzes it using an emotion engine (IBM Watson Emotion Analysis). The input is the user's facial expression data and voice data, and the output is analyzed emotion data (e.g., "Happy," "Stressed," etc.). The server acquires this emotion data and uses it as a prompt to send to the generative artificial intelligence (OpenAI GPT-4).

[0876] Step 4:

[0877] Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on emotional data and the user's request. The input is the emotional data and the user's request, and the output is a response message based on the emotion. For example, if the emotion is "Happy," the message generated is "Got it, we'll add 50 pens. Good luck with your future work!"

[0878] Step 5:

[0879] The server sends the generated response message to the terminal. The output is the response message displayed on the terminal. The terminal receives this message and displays it on the user interface. The user confirms this message.

[0880] Step 6:

[0881] The server receives inventory management requests and updates the MongoDB database. The input is the inventory addition request (e.g., "add 50 pens") and the output is the updated inventory data. The server updates the inventory information and monitors the results.

[0882] Step 7:

[0883] When inventory falls below the threshold, the server initiates an automatic ordering process. The input is the updated inventory data and threshold information, and the output is an order notification message. Generative AI generates an appropriate order notification message based on emotions, generating messages such as, "Don't worry. We will immediately start the ordering process and replenish the inventory. Please wait a moment."

[0884] Step 8:

[0885] The server sends the generated order notification message to the terminal, which receives the message and displays it on the user interface. The user can then confirm the order notification message and continue working with peace of mind.

[0886] In this way, the user, terminal, and server work together in each processing step, realizing automation of inventory management and appropriate responses according to the user's emotions.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] [Third embodiment]

[0891] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0892] 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.

[0893] 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).

[0894] 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.

[0895] 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.

[0896] 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).

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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."

[0903] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[0904] System configuration and roles

[0905] server

[0906] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[0907] Terminal

[0908] The terminal operates in cooperation with the server. The terminal provides a user interface and acts as a window through which the user can make requests to the server for inventory management and other matters. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[0909] User

[0910] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[0911] Program processing

[0912] The specific program processing flow is as follows:

[0913] 1. Adding inventory

[0914] User: The user sends a command to the server from their device to add a specific item to their inventory.

[0915] Server: The server receives instructions from the user and updates the inventory information. The updated inventory information is recorded in a log and notified to the user.

[0916] 2. Check inventory

[0917] User: A user checks the stock level of a specific item from a terminal.

[0918] Server: The server provides inventory information for the specified item to the terminal and displays that information to the user.

[0919] 3. Automated ordering

[0920] Terminal: The terminal periodically communicates with the server to check stock availability.

[0921] Server: The server automatically detects items that are below the inventory threshold and calculates the required order quantity. After the calculation, the server sends the order information to an external service and processes the order. The order result is logged and notified to the user via the terminal.

[0922] Specific examples

[0923] For example, if a user wants to add "pens" to the inventory, the user sends an instruction to the server via the terminal interface to "add 50 pens." The server receives this instruction and updates the inventory information, increasing the inventory of pens by 50.

[0924] Next, when the user wants to check the inventory of "notes," he sends a "Check notebook inventory" request to the server through the terminal. The server returns the current inventory of notes to the terminal, and the user can check the information.

[0925] Furthermore, if the system's inventory falls below 10 notebooks, it will automatically order more notebooks. The server calculates the order quantity and processes the order in conjunction with an external service. The order result is notified to the user via their terminal, and the user can check the order progress in real time.

[0926] In this way, this system automates inventory management and ordering through dialogue with users using generative artificial intelligence, supporting efficient business operations.

[0927] The processing flow will be explained below.

[0928] Step 1:

[0929] User: The user enters an inventory addition through the device's user interface (e.g., "Add 50 pens").

[0930] Step 2:

[0931] Terminal: The terminal prepares a request to send to the server an instruction from the user to add stock.

[0932] Step 3:

[0933] Server: The server parses the inventory addition request received from the terminal and retrieves the specified item and quantity.

[0934] Step 4:

[0935] Server: The server checks the inventory status and updates the quantity if the specified item already exists, otherwise it adds it as a new item.

[0936] Step 5:

[0937] Server: Updates the database with the updated inventory information and logs the inventory change history.

[0938] Step 6:

[0939] Server: Sends inventory update results to the device.

[0940] Step 7:

[0941] Terminal: The terminal receives the response from the server and displays the results on the user interface, allowing the user to see the quantity of stock that has been added.

[0942] Step 8:

[0943] User: A user makes a request through a terminal to check the inventory of a specific item (e.g., a "notebook").

[0944] Step 9:

[0945] Terminal: The terminal prepares the stock check request from the user to send to the server.

[0946] Step 10:

[0947] Server: The server analyzes the stock check request received from the terminal and retrieves the stock amount of the specified item from the database.

[0948] Step 11:

[0949] Server: Sends the acquired inventory information to the terminal.

[0950] Step 12:

[0951] Terminal: The terminal receives the response from the server and displays the inventory information on the user interface. The user can check the stock amount of the item they want to check.

[0952] Step 13:

[0953] Device: Periodically communicates with the server and sends a request to check inventory status.

[0954] Step 14:

[0955] Server: The server checks inventory and determines if a particular item is below a threshold.

[0956] Step 15:

[0957] Server: If the item is below the threshold, automatically calculate the order quantity and send an order request to an external service.

[0958] Step 16:

[0959] External Service: An external service receives the order request and initiates processing.

[0960] Step 17:

[0961] External service: After the order is completed, the result is notified to the server.

[0962] Step 18:

[0963] Server: Records the order result in a log and notifies the terminal.

[0964] Step 19:

[0965] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to see the progress of the automated order.

[0966] In this way, the system can perform tasks such as adding inventory, checking, and auto-ordering in a series of processing steps via a user interface.

[0967] Example 1

[0968] 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."

[0969] In inventory management, manual tasks such as adding, checking, and ordering inventory require time and effort, hindering efficient operations. Furthermore, ordering inventory after inventory runs out can create a time lag, potentially disrupting operations. There is a need for a system that can solve these problems and achieve efficient inventory management and an automated ordering process.

[0970] 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.

[0971] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for cooperating with an external service and acquiring data based on a user request, means for automating a specific task based on a user request, means for monitoring the progress of the task and notifying the user of the result, means for a user to send an instruction to add stock from a terminal and for the server to analyze and process the instruction, means for a user to send an inventory check request from a terminal and for the server to analyze and process the request, means for the server to periodically monitor inventory and automatically order items that are below a threshold, and means for processing orders and notifying the results via an external service, thereby enabling efficient and automated inventory management.

[0972] "Generative AI" refers to artificial intelligence technology that can interact with users and analyze data, and uses natural language processing and machine learning to generate appropriate responses.

[0973] "External services" refer to external systems or applications that provide functions such as data acquisition and order processing through collaboration with the server.

[0974] "User request" refers to an operation or instruction given by a user to the system, and includes processing requests such as adding inventory, checking, and placing an order.

[0975] "Means to automate specific tasks" refers to functions that allow a system to automatically execute business processes that were previously performed manually, including inventory management and order processing.

[0976] "Means for monitoring task progress" refers to the functionality for tracking the status of ongoing tasks and checking completion and progress.

[0977] "Means for a user to send an instruction to add stock from a terminal and for the server to analyze and process that instruction" refers to the function that allows a user to send an instruction to add stock to a server via a terminal, and for the server to interpret and process that instruction.

[0978] "Means for a user to send an inventory check request from a terminal and for the server to analyze and process the request" refers to the function that allows a user to send an inventory check request to a server via a terminal, and the server to analyze the request and provide inventory information.

[0979] "Means for the server to periodically monitor inventory and automatically order items that fall below a threshold" refers to a function in which the server periodically checks inventory information and automatically places an order if it detects that inventory is below a pre-set threshold.

[0980] "Means for processing orders and notifying the results via an external service" refers to a function that enables the server to execute orders in cooperation with an external ordering system and notify the user of the results.

[0981] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[0982] System configuration and roles

[0983] server

[0984] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[0985] Terminal

[0986] The terminal operates in conjunction with the server. The terminal provides a user interface and acts as a window through which users can make requests to the server for inventory management and other purposes. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[0987] User

[0988] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[0989] Program processing

[0990] 1. Adding inventory

[0991] User: The user sends a command to the server from their device to add a specific item to their inventory.

[0992] Server: The server receives instructions from the user and analyzes them using a generative AI model. Based on the analysis results, it updates the stock quantity of the corresponding item in the inventory database. The updated stock information is recorded in a log and notified to the user.

[0993] Terminal: The terminal receives inventory updates from the server and displays them to the user.

[0994] 2. Check inventory

[0995] User: A user sends a request from their device to check the stock level of a specific item.

[0996] Server: The server receives the request, analyzes it using the generative AI model, retrieves the stock information for the specified item from the inventory database, and sends it to the device.

[0997] Terminal: The terminal displays the inventory information received from the server to the user.

[0998] 3. Automated ordering

[0999] Server: The server periodically scans the inventory database to detect items whose stock is below a threshold. It uses a generative AI model to calculate the required order quantity and sends the order information to an external ordering system (e.g., external API). The order result is logged and notified to the user via the terminal.

[1000] Terminal: The terminal displays the order notification received from the server to the user.

[1001] Specific examples

[1002] For example, if a user sends an instruction to "add 50 pens" through the terminal interface, the server will receive this instruction and increase the stock of pens in the inventory database by 50. After updating the stock information, the server will record it in a log and generate a notification to send to the terminal, which will then display this notification to the user.

[1003] Next, when the user sends a request to "check notebook stock amount," the server obtains notebook stock information and sends it to the terminal, allowing the user to check the information.

[1004] Furthermore, if the system detects that the inventory of a notebook falls below 10 units, the server automatically uses the generative AI model to calculate the required order quantity and place an order through the external ordering system. The ordering result is logged and the user is notified via the terminal.

[1005] Example input to a generative AI model

[1006] Below is an example of input to a generative AI model:

[1007] "Add 50 pens"

[1008] Check notebook inventory

[1009] In this way, the present invention is a system that realizes the automation of inventory management and ordering through dialogue with users using generative artificial intelligence, thereby supporting efficient business operations.

[1010] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1011] Step 1:

[1012] Adding inventory

[1013] Input: A user inputs an inventory increase instruction, such as "add 50 pens," into a terminal.

[1014] Action: The user enters "Add 50 pens" into the inventory addition form through the terminal interface and clicks the submit button.

[1015] Specific behavior: The device detects this input and sends the data to the server as an HTTP POST request.

[1016] Data processing / calculation: The server receives the request, analyzes the instruction using the generative AI model, extracts the information "pen" and "50 units", accesses the inventory database, and increases the number of pens in stock by 50 units.

[1017] Output: Generates a success message and updated inventory information and sends them to the terminal.

[1018] Action: The device receives the updated inventory information and displays it to the user.

[1019] Step 2:

[1020] Check inventory

[1021] Input: A user inputs an inventory check request such as "Check notebook inventory" on a device.

[1022] How it works: The user enters "Check notebook inventory" into the inventory check form through the device interface and clicks the submit button.

[1023] Specific behavior: The device detects this input and sends the data to the server as an HTTP GET request.

[1024] Data processing / calculation: The server receives the request, analyzes the request using the generative AI model, and extracts the information "notebook." It then accesses the inventory database to obtain the notebook's inventory information.

[1025] Output: Generates a response with the current note inventory information and sends it to the device.

[1026] Operation: The device receives the notebook inventory information and displays it to the user.

[1027] Step 3:

[1028] Automatic ordering

[1029] Input: The server checks the inventory database on a regular schedule.

[1030] How it works: At regular intervals (e.g., every day at midnight), the server detects items that are below a stock threshold.

[1031] What happens: The server scans the inventory database on a scheduled basis to detect items below a threshold (e.g., fewer than 10 notebooks in stock).

[1032] Data processing / calculation: Use the generative AI model to calculate the required order quantity (e.g., order 20 notebooks), then send the order information to an external ordering system (e.g., external API).

[1033] Output: Receives the response containing the order result, logs it, and generates a notification message to send to the terminal.

[1034] Operation: The terminal displays the order notification received from the server to the user.

[1035] Step 4:

[1036] Order status notification

[1037] Input: Order result feedback from external ordering system.

[1038] How it works: The server periodically calls the API of the external ordering system to check the progress of the order.

[1039] Specific behavior: The server retrieves the order status through the API and records it in a log.

[1040] Data processing / calculation: Analyze the retrieved order status and use a generative AI model to generate a message to notify the user.

[1041] Output: Sends a notification message to the terminal.

[1042] Action: The terminal displays the received notification message to the user.

[1043] (Application example 1)

[1044] 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."

[1045] In current inventory management systems, the processes of adding, checking, and ordering inventory are often all done manually, resulting in reduced work efficiency and a high likelihood of human error. Additionally, inventory information cannot be checked in real time on-site, making it difficult to respond quickly. There is a need for a system that can solve these problems and improve the efficiency and accuracy of inventory management at logistics centers and other facilities.

[1046] 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.

[1047] In this invention, the server includes means for communicating with users using generative artificial intelligence, means for connecting with external services and acquiring data based on user requests, means for automating specific tasks based on user requests, means for monitoring task progress and notifying the user of the results, means for receiving user voice commands using voice recognition and executing processing, and means for visualizing inventory information in real time using a user-portable 3D display device. This allows users to add or check inventory using voice commands and check inventory status in real time through their smart devices. Furthermore, automatic ordering is performed when inventory levels fall below a certain threshold, achieving efficient inventory management.

[1048] "Generative AI" is AI that analyzes data and generates responses and instructions in natural language through dialogue with the user.

[1049] "Means for communicating with the user" refers to an interface that uses generative artificial intelligence to realize two-way dialogue with the user through voice and text.

[1050] "Means of linking with external services" refers to the function of obtaining necessary information from external databases or APIs and using it within the system.

[1051] A "means for automating a task" is a function for executing a task based on a request from a user without manual intervention and managing the progress of the task.

[1052] The "means for monitoring and notifying the progress of a task" is a function for tracking the status of a task currently being executed and notifying the user of the results in real time.

[1053] The "means for receiving user voice commands using voice recognition" is a function for analyzing the user's voice, converting it into text data, and interpreting it as instructions.

[1054] "Means for visualizing inventory information using a portable 3D display device" refers to a function that uses a portable device such as smart glasses or a head-mounted display to display inventory information in three dimensions and present it to the user in an easy-to-understand manner.

[1055] "Inventory management" is the process of managing the quantity of products and parts held in stock and replenishing or ordering as needed.

[1056] An "inventory database" is a database that records information on all items managed as inventory and can be referenced and updated as needed.

[1057] "Automatic ordering" is the process by which the system automatically orders additional stock when inventory falls below a defined threshold.

[1058] This invention is a system that uses generative artificial intelligence to realize communication through voice recognition, visualization of real-time inventory information, and automatic ordering in order to improve the efficiency of inventory management at logistics centers, etc. As an application example of this invention, details of an inventory management system using smart glasses will be described.

[1059] System configuration and roles

[1060] server

[1061] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user and accepts voice commands from the user. It also connects with external services to obtain necessary data and manage inventory information. It also has a function to automatically place an order when inventory levels fall below a threshold. The server uses Python programs and voice recognition libraries (e.g., SpeechRecognition).

[1062] Terminal

[1063] The terminal is a portable device such as smart glasses or a head-mounted display that allows users to input voice commands. The terminal displays inventory information in 3D in real time, allowing users to easily check inventory status on-site.

[1064] User

[1065] Users operate the system through smart glasses to manage inventory. For example, a user might give a voice command such as "add 50 pens." The smart glasses then transmit the voice command to a server, which analyzes the voice and updates the inventory database. When inventory falls below a certain threshold, the server automatically places an order and notifies the user of the result.

[1066] Program Description

[1067] 1. Hardware:

[1068] Server: High-performance server (e.g. Amazon AWS, Google Cloud Platform)

[1069] Devices: Smart glasses (e.g., Google Glass), head-mounted displays (e.g., Microsoft HoloLens)

[1070] 2. Software:

[1071] Server-side program: Python

[1072] Speech recognition library: SpeechRecognition

[1073] Notification Library: Pushbullet API

[1074] 3. Data processing and calculation:

[1075] The user sends a voice command to the smart glasses.

[1076] The smart glasses send the voice data to a server, where a Python program converts the voice into text for analysis.

[1077] The server updates the inventory database based on the instructions and notifies the user of the changes.

[1078] When inventory falls below a threshold, the server automatically places an order and notifies the user of the result.

[1079] Specific examples

[1080] The user commands the smart glasses to "add 50 pens." The smart glasses recognize the voice and send it to the server. The server analyzes the received voice data and updates the inventory database. The user can confirm the completion of the task by seeing the message "50 pens added" on the smart glasses' display.

[1081] Example prompt sentence:

[1082] The user speaks to the smart glasses, "Add 50 pens." This speech information is sent to the server, and the generative AI model interprets it as "Add 50 pens to inventory" and updates the database. At that time, the user should be notified that the addition is complete.

[1083] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1084] Step 1:

[1085] The user speaks the voice command "Add 50 pens" to the smart glasses.

[1086] Input: User's voice command

[1087] Output: Audio data

[1088] What it does: The microphone in the smart glasses captures the user's voice and obtains the voice data.

[1089] Step 2:

[1090] The terminal (smart glasses) transmits the acquired voice data to the server.

[1091] Input: Audio data

[1092] Output: Sending audio data to the server

[1093] What it does: The smart glasses send audio data over the internet to a specified endpoint on the server.

[1094] Step 3:

[1095] The server converts the received voice data into text.

[1096] Input: Audio data

[1097] Output: Converted text data (e.g. "Add 50 pens")

[1098] Specific operation: The server converts the voice data into text using a speech recognition library (e.g., SpeechRecognition).

[1099] Step 4:

[1100] The server parses the text data and updates the inventory database.

[1101] Input: Text data

[1102] Output: Updated inventory database

[1103] Specific operation: The server uses generative artificial intelligence to analyze the text data, interprets it as an instruction to "add 50 pens," and increases the inventory quantity of the corresponding item in the inventory database by 50.

[1104] Step 5:

[1105] The server notifies the user of the results of the inventory database update.

[1106] Input: Updated inventory information

[1107] Output: A notification message to the user (e.g. "50 pens added").

[1108] What it does: The server sends a notification message to the user's smart glasses using a notification library such as the Pushbullet API.

[1109] Step 6:

[1110] The terminal (smart glasses) displays the received notification message to the user.

[1111] Input: Notification message from the server

[1112] Output: Notification message displayed on the smart glasses display

[1113] Specific operation: The smart glasses analyze the received notification message and display the message "50 pens added" on the display.

[1114] Step 7:

[1115] The server automatically places an order if the inventory level falls below a threshold.

[1116] Input: Updated inventory information

[1117] Output: Automatic ordering instructions and notification of ordering results

[1118] Specific operation: The server checks the inventory database, and if the inventory level is below the threshold, it sends an order instruction to an external service, logs the order result, and notifies the user.

[1119] 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.

[1120] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[1121] System configuration and roles

[1122] server

[1123] The server functions as the core of the system and is equipped with a generative artificial intelligence and an emotion engine. The server processes user input received from the user interface and exchanges data with external services. It also automates specific tasks (e.g., inventory management) based on user requests, and monitors and notifies users of their progress. The emotion engine recognizes the user's emotions in real time, and the generative artificial intelligence generates an appropriate response based on those emotions.

[1124] Terminal

[1125] The terminal works in cooperation with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server and also indicates the user's emotional state.

[1126] User

[1127] Users interact with the system through a terminal interface. This system allows users to streamline inventory management tasks and utilize automated ordering processes. Furthermore, appropriate responses based on the user's emotions provide a more comfortable interface experience.

[1128] Program processing

[1129] The specific program processing flow is as follows:

[1130] 1. Emotion Recognition and Dialogue Generation

[1131] User: The user inputs information through the device's user interface. For example, when the user inputs a request such as "add 50 pens," emotions are read from the user's facial expressions and voice.

[1132] Device: The device captures the user's emotional data (facial expressions, voice tone, etc.) and sends it to the server.

[1133] Server: The server uses an emotion engine to recognize the user's emotions. The generative AI then generates an appropriate response based on the emotion and sends it back to the user.

[1134] 2. Add and check inventory

[1135] User: After receiving the appropriate response based on their emotion, the user makes a request to add more stock via the terminal. For example, they send an instruction to the server saying, "Add 50 pens."

[1136] Server: The server updates inventory information and generates a message of acceptance based on the user's emotional state, as recognized by the emotion engine. For example, if the user is nervous, the system can send a message to relax.

[1137] 3. Automated ordering and progress monitoring

[1138] Terminal: Periodically communicates with the server and sends a request to check stock availability.

[1139] Server: The server automatically detects items below the inventory threshold and calculates the order quantity. The order information is sent to the terminal in the form of an appropriate notification based on the user's emotional state recognized by the emotion engine.

[1140] Terminal: The order results are displayed on the user interface, along with the user's emotional state.

[1141] Specific examples

[1142] For example, if a user commands "add 50 pens" through a device, the device captures the user's facial expression along with the command and sends it to the server. The server then uses an emotion engine to analyze the user's emotions, and the generative AI generates and sends a message corresponding to the user's emotions (e.g., "Got it, I'll add 50 pens").

[1143] Similarly, if inventory falls below a threshold, the server automatically initiates the ordering process and notifies the user of the order outcome in an emotionally sensitive manner. For example, if an order is delayed, a comforting message such as "Please wait a moment, we're on our way" can be added.

[1144] In this way, this system has advanced response capabilities that combine generative artificial intelligence and an emotion engine, simultaneously improving the efficiency of inventory management tasks and the user experience.

[1145] The processing flow will be explained below.

[1146] Step 1:

[1147] User: The user inputs a request through the device's user interface, for example, "Add 50 pens." At the same time, the user's facial expressions and tone of voice are captured.

[1148] Step 2:

[1149] Terminal: The terminal sends the user's facial expression data and voice tone data along with the input request to the server.

[1150] Step 3:

[1151] Server: The server processes the received request and emotion data. It uses an emotion engine to recognize the user's emotion (e.g., joy, anger, sadness, surprise, etc.).

[1152] Step 4:

[1153] Server: Based on the emotions recognized by the emotion engine, the generative AI generates an appropriate response message. For example, if the user is tired, it generates a relaxing message such as "Got it. 50 pens have been added. Thank you for your continued patronage."

[1154] Step 5:

[1155] Server: The server generates a response message and sends it to the terminal to notify the user.

[1156] Step 6:

[1157] Terminal: The terminal displays the response message received from the server on the user interface. The user can see the response message and confirm that the stock has been added.

[1158] Step 7:

[1159] User: A user requests an inventory check of a specific item through a terminal, for example, by entering a request such as "Check inventory of notebooks."

[1160] Step 8:

[1161] Terminal: The terminal sends a request to the server.

[1162] Step 9:

[1163] Server: The server retrieves the inventory amount of the specified item from the database.

[1164] Step 10:

[1165] Server: As before, the generative AI generates an appropriate message based on the inventory status, such as "There are 10 notebooks left in stock. You can order more if needed."

[1166] Step 11:

[1167] Server: The server sends the generated message to the terminal and notifies the user.

[1168] Step 12:

[1169] Terminal: The terminal displays the message received from the server on the user interface, and the user can check the stock amount.

[1170] Step 13:

[1171] Terminal: The terminal periodically communicates with the server and sends a request to check stock availability.

[1172] Step 14:

[1173] Server: The server automatically detects items that are below a stock threshold and determines the need for automatic ordering.

[1174] Step 15:

[1175] Server: When automatic ordering is required, the server generates an order in cooperation with an external service. The emotion engine adjusts the notification message of the order progress according to the user's emotion.

[1176] Step 16:

[1177] External Service: An external service receives the order request and initiates processing.

[1178] Step 17:

[1179] External service: Once the order is placed, the result is notified to the server.

[1180] Step 18:

[1181] Server: The server logs the order result and generates a notification message that takes the user's feelings into consideration. For example, if the order is delayed, it adds a comforting message such as "The current shipping status is that the product is being prepared. Please wait a little longer."

[1182] Step 19:

[1183] Server: The server sends a notification message to the terminal.

[1184] Step 20:

[1185] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to view the progress of the automated order and the latest inventory status.

[1186] Through this series of processes, the system recognizes the user's emotions and responds appropriately, thereby improving the user experience and enabling efficient inventory management.

[1187] Example 2

[1188] 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."

[1189] Traditional inventory management systems lack the ability to respond to user emotions, which often results in poor user experience and inefficient inventory management. Furthermore, the lack of automated task management based on user requests and real-time progress notifications hinders smooth business operations.

[1190] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1191] In this invention, the server includes means for communicating with the user using generative artificial intelligence, means for linking with external services and acquiring data based on the user's request, means for recognizing the user's emotions and generating an appropriate response, means for automating specific tasks based on the user's request, and means for monitoring the progress of the tasks and notifying the user of the results. This enables high-quality responses that take the user's emotions into consideration, resulting in more efficient inventory management and an improved user experience.

[1192] "Generative artificial intelligence" is a computer-based technology that interacts with users and uses natural language processing to generate appropriate responses.

[1193] "External services" are online services that allow you to use information and functions, such as APIs and databases, provided outside the system.

[1194] An "emotion engine" is a software module that analyzes emotions from a user's facial expressions, tone of voice, text, etc., and adjusts responses based on those emotions.

[1195] A "user interface" is an interaction means, such as a screen or input device, that allows a user to interact with a system.

[1196] A "database" is an information system for efficiently storing, managing, and retrieving data such as inventory information.

[1197] "Automation" is the process by which a program or machine performs a task based on a user's request without human intervention.

[1198] "Notifications" are messages or alerts that convey important information to the user, such as the progress or results of a task.

[1199] "Inventory management" is the management task of optimizing the amount of goods and materials in stock and replenishing or ordering in a timely manner.

[1200] A "prompt sentence" is a piece of text that is input to a generative AI and serves as the basis for generating a response.

[1201] MODE FOR CARRYING OUT THE INVENTION

[1202] System Overview

[1203] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[1204] Hardware and Software Configuration

[1205] server

[1206] The server functions as the core of the system and is equipped with a generative artificial intelligence and emotion engine. The server processes user input received from the user interface and exchanges data with external services. The server also automates specific tasks (e.g., inventory management) and monitors and notifies progress.

[1207] Terminal

[1208] The terminal works in conjunction with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server, along with the user's emotional state.

[1209] Program processing

[1210] 1. Receiving User Requests

[1211] The user inputs a request, for example, "add 50 pens" via the user interface of the terminal.

[1212] The device captures the user's input and emotional data such as facial expressions and tone of voice at the time of input, and sends this to the server.

[1213] 2. Sentiment Analysis and Response Generation

[1214] The server processes the received request and emotion data and analyzes the user's emotion using the emotion engine.

[1215] The server generates a prompt for the generative AI model. For example, "There is a request to add 50 pens, and the user is nervous."

[1216] The generative AI model generates an appropriate response based on this prompt, for example, "Got it. I'll add 50 pens. Relax."

[1217] 3. Sending and Displaying the Response

[1218] The server sends the generated response to the terminal.

[1219] The terminal displays the response received from the server on the user interface.

[1220] 4. Updating inventory information

[1221] The server updates the inventory database to record that 50 pens have been added.

[1222] The user can check the latest inventory information via the terminal. For example, when the user instructs "display inventory list," the terminal reads and displays the latest inventory information.

[1223] 5. Automated ordering and progress monitoring

[1224] The terminal periodically sends a request to the server to check the stock status.

[1225] The server automatically detects items that are below the inventory threshold and initiates the ordering process.

[1226] The generative AI model generates an appropriate message to inform the user that the ordering process has begun, for example, "We are running low on stock, so we have automatically ordered pens."

[1227] The server sends appropriate notification messages to the terminal to record progress.

[1228] The terminal displays notification messages received from the server on the user interface to provide the user with real-time progress information. For example, when an order is completed, a message such as "Order completed. Waiting for delivery" is displayed.

[1229] Specific examples

[1230] For example, if a user issues an instruction to "add 50 pens" via a device, the device captures the instruction and the user's emotional data and sends them to the server. The server then uses an emotion engine to analyze the user's emotions, and a generative artificial intelligence (AI) system generates a response message appropriate to the user's emotions. For example, the message generated might read, "Got it. I'll add 50 pens. Please relax." This message is then sent to the device and displayed to the user.

[1231] If the stock falls below the threshold, the server automatically starts the ordering process and notifies the user of the result. For example, it generates a message saying, "Stock is low, so pens have been automatically ordered." and notifies the terminal.

[1232] In this way, by combining generative artificial intelligence and an emotion engine, this system provides advanced dialogue and emotion recognition functions, improving inventory management efficiency and the user experience.

[1233] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1234] Step 1:

[1235] The user inputs a request through the user interface of the terminal, for example, "add 50 pens." The input data is the string "add 50 pens," which triggers the next processing step. The terminal sends the input data to the server.

[1236] Step 2:

[1237] The device captures the user's emotional data (such as facial expressions and voice tone) when inputting a request. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice tone, extracting them as digital data. The emotional data and input data are then sent together to the server.

[1238] Step 3:

[1239] The server processes the received request data and emotion data. The input is the user's request and emotion data, and the output is the emotion recognition result and a prompt. Using the emotion engine, the server analyzes the user's emotion and generates a prompt for the generative AI model based on the results. For example, a prompt such as "There is a request to add 50 pens, and the user is nervous" is generated.

[1240] Step 4:

[1241] The generative AI model generates an appropriate response based on the prompt received from the server. The input is the generated prompt, and the output is a generated response message. For example, the generated response message is "Got it. I'll add 50 pens. Relax."

[1242] Step 5:

[1243] The server sends the generated response message to the terminal. The input is the generated response message, and the output is data communication to the terminal. The terminal displays the response message received from the server on its user interface. For example, a message such as "Got it. 50 pens will be added. Please relax." is displayed on the terminal.

[1244] Step 6:

[1245] The server updates the inventory database. The input is the user's request data, and the output is the updated inventory information. Specifically, the addition of 50 pens is recorded in the database. The user can check the latest inventory information through the terminal. For example, if the user instructs "Display inventory list," the terminal will read and display the latest inventory information. Specifically, the server retrieves inventory data from the database and displays it on the user interface.

[1246] Step 7:

[1247] The terminal periodically sends a request to check the stock status to the server. The input is a regular interval (e.g., once a day), and the output is a stock check request sent to the server.

[1248] Step 8:

[1249] The server automatically detects items that fall below an inventory threshold and initiates the ordering process. The input is current inventory data, and the output is the calculated order quantity and ordering information. Specifically, the server scans the inventory database and automatically places an order for items that fall below the threshold.

[1250] Step 9:

[1251] The generative AI model generates an appropriate message to notify the user that the ordering process has begun. The input is the start information of the ordering process, and the output is a notification message. For example, a message such as "We have automatically placed an order for pens as we are running low on stock" is generated.

[1252] Step 10:

[1253] The server sends the generated notification message to the terminal. The input is the generated notification message, and the output is data communication to the terminal. The terminal displays the notification message received from the server on the user interface, providing the user with a progress status in real time. Specifically, when the order processing is complete, the message "Order completed. Waiting for delivery" is displayed.

[1254] (Application example 2)

[1255] 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."

[1256] Although conventional inventory management systems have advanced in terms of automation of inventory management, they have a problem of being unable to respond flexibly based on user emotions. Furthermore, when users check inventory or place orders, they lack appropriate support based on their status and emotions, which tends to reduce the quality of the user experience. Furthermore, there is a need for a method to efficiently manage inventory while taking into consideration the emotions of workers at worksites such as logistics centers.

[1257] 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.

[1258] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for connecting with external services and acquiring data based on a user request, means for automating specific inventory management tasks based on the user request, means for monitoring the progress of the tasks and notifying the user of the results, and means for recognizing the user's emotions and generating responses based on the emotions. This allows the user to receive appropriate support that takes emotions into consideration when performing inventory management tasks. Furthermore, when inventory falls below a threshold, an order notification message generated based on the emotions is sent to the user, thereby realizing efficient and flexible inventory management.

[1259] "Generative AI" is an AI system that has the ability to generate new information and responses based on given data.

[1260] "Means for communicating with the user" refers to means that has the function of receiving input from the user and returning appropriate responses or information in response to that input.

[1261] "Means for linking with external services and acquiring data based on user requests" refers to means that has the function of communicating with other systems and services, acquiring the necessary data, and responding to user requests.

[1262] A "means for automating a specific task" is a means that has the function of automatically executing a specific job or work without human intervention, based on instructions from a user.

[1263] The "means for monitoring the progress of a task and notifying the user of the result" is a means having a function for tracking the progress of an automated task and notifying the user of the result.

[1264] "Means for recognizing emotions and generating a response based on the emotions" refers to means that has the function of analyzing the user's emotions from facial expressions, tone of voice, etc., and generating a response that is adapted to those emotions.

[1265] "Inventory management" refers to the act of keeping track of stock levels and replenishing or ordering as needed.

[1266] A "threshold" is a specific reference value, below which or above which a specific action is executed.

[1267] An "order notification message" is a notification message that is automatically generated and sent to a user when inventory needs to be replenished.

[1268] MODE FOR CARRYING OUT THE INVENTION

[1269] The present invention combines generative artificial intelligence and an emotion engine in an inventory management system at a logistics center, thereby achieving efficient and flexible responses.

[1270] System configuration

[1271] server

[1272] The server is the core of the system and has the following functions:

[1273] It communicates with users using generative artificial intelligence (AI model).

[1274] Data is shared with external services and data is retrieved based on user requests.

[1275] Automate specific inventory management tasks based on user requests.

[1276] Monitor the progress of the task and notify the user of the results.

[1277] An emotion engine is used to recognize the user's emotions and generate responses based on those emotions.

[1278] The specific tools used are IBM Watson Emotion Analysis as the emotion engine and OpenAI GPT-4 as the generative artificial intelligence, with Node.js as the backend server and MongoDB as the database.

[1279] Terminal

[1280] The device works in conjunction with the server and provides the user interface. It is built as a smartphone app and developed using React Native. The device has the following features:

[1281] It uses a camera and microphone to capture the user's facial expressions and tone of voice.

[1282] Send the capture data to the server.

[1283] Provides an interface for checking inventory and requesting additional items.

[1284] Displays the sentiment analysis results received from the server and the generated response.

[1285] User

[1286] The user (worker) interacts with the system through a terminal. They perform tasks such as checking inventory, adding, or reducing it, and receive responses from the system. In addition, receiving responses based on the results of emotion analysis enables efficient and comfortable inventory management.

[1287] Example of a system

[1288] When a user makes a request via a terminal to "add 50 pens," the following happens:

[1289] 1. The device's camera and microphone capture the user's facial expressions and voice.

[1290] 2. The captured data is sent to the backend server in real time.

[1291] 3. The server uses an emotion engine (IBM Watson Emotion Analysis) to analyze the user's emotions.

[1292] 4. Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on the emotion and sends a message to the device such as, "Got it, we'll add 50 pens. Good luck with your future work!"

[1293] 5. When the inventory falls below the threshold, the ordering process will be automatically initiated and an ordering notification message will be sent to the user saying, "Don't worry, we will start the ordering process and replenish the inventory right away. Please wait a moment."

[1294] Prompt Sentence Examples

[1295] User emotion: Happy

[1296] User input: "Add 50 pens"

[1297] Response: "Okay, I'll add 50 pens. Good luck with your work!"

[1298] User emotion: Stressed

[1299] User input: "Stock is low, what should I do?"

[1300] Response: "Don't worry. We'll start the ordering process and replenish your inventory right away. Please be patient."

[1301] This invention improves the efficiency of inventory management tasks at logistics centers and enables flexible responses that take user emotions into consideration. Furthermore, appropriate responses based on emotions improve the quality of the user experience.

[1302] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1303] Step 1:

[1304] The user launches the terminal's user interface and logs in. The input is the user's login information (username, password), and the output is a message indicating whether the login was successful or not. The terminal obtains this information and sends it to the server. The server verifies the login information and returns the result to the terminal.

[1305] Step 2:

[1306] The user inputs a request for inventory check or addition into the terminal. The input is an inventory management request such as "add 50 pens." The terminal receives this input, captures the user's facial expressions and voice with a camera and microphone, and transmits them to the server in real time.

[1307] Step 3:

[1308] The server receives the captured data sent from the device and analyzes it using an emotion engine (IBM Watson Emotion Analysis). The input is the user's facial expression data and voice data, and the output is analyzed emotion data (e.g., "Happy," "Stressed," etc.). The server acquires this emotion data and uses it as a prompt to send to the generative artificial intelligence (OpenAI GPT-4).

[1309] Step 4:

[1310] Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on emotional data and the user's request. The input is the emotional data and the user's request, and the output is a response message based on the emotion. For example, if the emotion is "Happy," the message generated is "Got it, we'll add 50 pens. Good luck with your future work!"

[1311] Step 5:

[1312] The server sends the generated response message to the terminal. The output is the response message displayed on the terminal. The terminal receives this message and displays it on the user interface. The user confirms this message.

[1313] Step 6:

[1314] The server receives inventory management requests and updates the MongoDB database. The input is the inventory addition request (e.g., "add 50 pens") and the output is the updated inventory data. The server updates the inventory information and monitors the results.

[1315] Step 7:

[1316] When inventory falls below the threshold, the server initiates an automatic ordering process. The input is the updated inventory data and threshold information, and the output is an order notification message. Generative AI generates an appropriate order notification message based on emotions, generating messages such as, "Don't worry. We will immediately start the ordering process and replenish the inventory. Please wait a moment."

[1317] Step 8:

[1318] The server sends the generated order notification message to the terminal, which receives the message and displays it on the user interface. The user can then confirm the order notification message and continue working with peace of mind.

[1319] In this way, the user, terminal, and server work together in each processing step, realizing automation of inventory management and appropriate responses according to the user's emotions.

[1320] 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.

[1321] 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.

[1322] 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.

[1323] [Fourth embodiment]

[1324] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1325] 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.

[1326] 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).

[1327] 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.

[1328] 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.

[1329] 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).

[1330] 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.

[1331] 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.

[1332] 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.

[1333] 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.

[1334] 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.

[1335] 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.

[1336] 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."

[1337] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[1338] System configuration and roles

[1339] server

[1340] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[1341] Terminal

[1342] The terminal operates in cooperation with the server. The terminal provides a user interface and acts as a window through which the user can make requests to the server for inventory management and other matters. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[1343] User

[1344] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[1345] Program processing

[1346] The specific program processing flow is as follows:

[1347] 1. Adding inventory

[1348] User: The user sends a command to the server from their device to add a specific item to their inventory.

[1349] Server: The server receives instructions from the user and updates the inventory information. The updated inventory information is recorded in a log and notified to the user.

[1350] 2. Check inventory

[1351] User: A user checks the stock level of a specific item from a terminal.

[1352] Server: The server provides inventory information for the specified item to the terminal and displays that information to the user.

[1353] 3. Automated ordering

[1354] Terminal: The terminal periodically communicates with the server to check stock availability.

[1355] Server: The server automatically detects items that are below the inventory threshold and calculates the required order quantity. After the calculation, the server sends the order information to an external service and processes the order. The order result is logged and notified to the user via the terminal.

[1356] Specific examples

[1357] For example, if a user wants to add "pens" to the inventory, the user sends an instruction to the server via the terminal interface to "add 50 pens." The server receives this instruction and updates the inventory information, increasing the inventory of pens by 50.

[1358] Next, when the user wants to check the inventory of "notes," he sends a "Check notebook inventory" request to the server through the terminal. The server returns the current inventory of notes to the terminal, and the user can check the information.

[1359] Furthermore, if the system's inventory falls below 10 notebooks, it will automatically order more notebooks. The server calculates the order quantity and processes the order in conjunction with an external service. The order result is notified to the user via their terminal, and the user can check the order progress in real time.

[1360] In this way, this system automates inventory management and ordering through dialogue with users using generative artificial intelligence, supporting efficient business operations.

[1361] The processing flow will be explained below.

[1362] Step 1:

[1363] User: The user enters an inventory addition through the device's user interface (e.g., "Add 50 pens").

[1364] Step 2:

[1365] Terminal: The terminal prepares a request to send to the server an instruction from the user to add stock.

[1366] Step 3:

[1367] Server: The server parses the inventory addition request received from the terminal and retrieves the specified item and quantity.

[1368] Step 4:

[1369] Server: The server checks the inventory status and updates the quantity if the specified item already exists, otherwise it adds it as a new item.

[1370] Step 5:

[1371] Server: Updates the database with the updated inventory information and logs the inventory change history.

[1372] Step 6:

[1373] Server: Sends inventory update results to the device.

[1374] Step 7:

[1375] Terminal: The terminal receives the response from the server and displays the results on the user interface, allowing the user to see the quantity of stock that has been added.

[1376] Step 8:

[1377] User: A user makes a request through a terminal to check the inventory of a specific item (e.g., a "notebook").

[1378] Step 9:

[1379] Terminal: The terminal prepares the stock check request from the user to send to the server.

[1380] Step 10:

[1381] Server: The server analyzes the stock check request received from the terminal and retrieves the stock amount of the specified item from the database.

[1382] Step 11:

[1383] Server: Sends the acquired inventory information to the terminal.

[1384] Step 12:

[1385] Terminal: The terminal receives the response from the server and displays the inventory information on the user interface. The user can check the stock amount of the item they want to check.

[1386] Step 13:

[1387] Device: Periodically communicates with the server and sends a request to check inventory status.

[1388] Step 14:

[1389] Server: The server checks inventory and determines if a particular item is below a threshold.

[1390] Step 15:

[1391] Server: If the item is below the threshold, automatically calculate the order quantity and send an order request to an external service.

[1392] Step 16:

[1393] External Service: An external service receives the order request and initiates processing.

[1394] Step 17:

[1395] External service: After the order is completed, the result is notified to the server.

[1396] Step 18:

[1397] Server: Records the order result in a log and notifies the terminal.

[1398] Step 19:

[1399] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to see the progress of the automated order.

[1400] In this way, the system can perform tasks such as adding inventory, checking, and auto-ordering in a series of processing steps via a user interface.

[1401] Example 1

[1402] 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."

[1403] In inventory management, manual tasks such as adding, checking, and ordering inventory require time and effort, hindering efficient operations. Furthermore, ordering inventory after inventory runs out can create a time lag, potentially disrupting operations. There is a need for a system that can solve these problems and achieve efficient inventory management and an automated ordering process.

[1404] 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.

[1405] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for cooperating with an external service and acquiring data based on a user request, means for automating a specific task based on a user request, means for monitoring the progress of the task and notifying the user of the result, means for a user to send an instruction to add stock from a terminal and for the server to analyze and process the instruction, means for a user to send an inventory check request from a terminal and for the server to analyze and process the request, means for the server to periodically monitor inventory and automatically order items that are below a threshold, and means for processing orders and notifying the results via an external service, thereby enabling efficient and automated inventory management.

[1406] "Generative AI" refers to artificial intelligence technology that can interact with users and analyze data, and uses natural language processing and machine learning to generate appropriate responses.

[1407] "External services" refer to external systems or applications that provide functions such as data acquisition and order processing through collaboration with the server.

[1408] "User request" refers to an operation or instruction given by a user to the system, and includes processing requests such as adding inventory, checking, and placing an order.

[1409] "Means to automate specific tasks" refers to functions that allow a system to automatically execute business processes that were previously performed manually, including inventory management and order processing.

[1410] "Means for monitoring task progress" refers to the functionality for tracking the status of ongoing tasks and checking completion and progress.

[1411] "Means for a user to send an instruction to add stock from a terminal and for the server to analyze and process that instruction" refers to the function that allows a user to send an instruction to add stock to a server via a terminal, and for the server to interpret and process that instruction.

[1412] "Means for a user to send an inventory check request from a terminal and for the server to analyze and process the request" refers to the function that allows a user to send an inventory check request to a server via a terminal, and the server to analyze the request and provide inventory information.

[1413] "Means for the server to periodically monitor inventory and automatically order items that fall below a threshold" refers to a function in which the server periodically checks inventory information and automatically places an order if it detects that inventory is below a pre-set threshold.

[1414] "Means for processing orders and notifying the results via an external service" refers to a function that enables the server to execute orders in cooperation with an external ordering system and notify the user of the results.

[1415] This invention is a system that uses generative artificial intelligence to communicate with users, share data with external services, automate specific tasks, and monitor and notify their progress. This system is particularly designed to automate inventory management, enabling efficient business operations.

[1416] System configuration and roles

[1417] server

[1418] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user, accepts user requests, and executes appropriate processing. The server manages inventory information, obtains data from external services as needed, and automatically places orders based on the analysis results. It also has the function of monitoring the status of ongoing tasks and notifying the user of the results.

[1419] Terminal

[1420] The terminal operates in conjunction with the server. The terminal provides a user interface and acts as a window through which users can make requests to the server for inventory management and other purposes. Based on the information received from the server, the terminal displays the inventory status and order status to the user in real time.

[1421] User

[1422] Users can operate this system to take advantage of automated inventory management and ordering. They can check inventory information through their terminals and add or modify inventory as needed. They can also receive automatic ordering notifications from the system and keep track of order status.

[1423] Program processing

[1424] 1. Adding inventory

[1425] User: The user sends a command to the server from their device to add a specific item to their inventory.

[1426] Server: The server receives instructions from the user and analyzes them using a generative AI model. Based on the analysis results, it updates the stock quantity of the corresponding item in the inventory database. The updated stock information is recorded in a log and notified to the user.

[1427] Terminal: The terminal receives inventory updates from the server and displays them to the user.

[1428] 2. Check inventory

[1429] User: A user sends a request from their device to check the stock level of a specific item.

[1430] Server: The server receives the request, analyzes it using the generative AI model, retrieves the stock information for the specified item from the inventory database, and sends it to the device.

[1431] Terminal: The terminal displays the inventory information received from the server to the user.

[1432] 3. Automated ordering

[1433] Server: The server periodically scans the inventory database to detect items whose stock is below a threshold. It uses a generative AI model to calculate the required order quantity and sends the order information to an external ordering system (e.g., external API). The order result is logged and notified to the user via the terminal.

[1434] Terminal: The terminal displays the order notification received from the server to the user.

[1435] Specific examples

[1436] For example, if a user sends an instruction to "add 50 pens" through the terminal interface, the server will receive this instruction and increase the stock of pens in the inventory database by 50. After updating the stock information, the server will record it in a log and generate a notification to send to the terminal, which will then display this notification to the user.

[1437] Next, when the user sends a request to "check notebook stock amount," the server obtains notebook stock information and sends it to the terminal, allowing the user to check the information.

[1438] Furthermore, if the system detects that the inventory of a notebook falls below 10 units, the server automatically uses the generative AI model to calculate the required order quantity and place an order through the external ordering system. The ordering result is logged and the user is notified via the terminal.

[1439] Example input to a generative AI model

[1440] Below is an example of input to a generative AI model:

[1441] "Add 50 pens"

[1442] Check notebook inventory

[1443] In this way, the present invention is a system that realizes the automation of inventory management and ordering through dialogue with users using generative artificial intelligence, thereby supporting efficient business operations.

[1444] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1445] Step 1:

[1446] Adding inventory

[1447] Input: A user inputs an inventory increase instruction, such as "add 50 pens," into a terminal.

[1448] Action: The user enters "Add 50 pens" into the inventory addition form through the terminal interface and clicks the submit button.

[1449] Specific behavior: The device detects this input and sends the data to the server as an HTTP POST request.

[1450] Data processing / calculation: The server receives the request, analyzes the instruction using the generative AI model, extracts the information "pen" and "50 units", accesses the inventory database, and increases the number of pens in stock by 50 units.

[1451] Output: Generates a success message and updated inventory information and sends them to the terminal.

[1452] Action: The device receives the updated inventory information and displays it to the user.

[1453] Step 2:

[1454] Check inventory

[1455] Input: A user inputs an inventory check request such as "Check notebook inventory" on a device.

[1456] How it works: The user enters "Check notebook inventory" into the inventory check form through the device interface and clicks the submit button.

[1457] Specific behavior: The device detects this input and sends the data to the server as an HTTP GET request.

[1458] Data processing / calculation: The server receives the request, analyzes the request using the generative AI model, and extracts the information "notebook." It then accesses the inventory database to obtain the notebook's inventory information.

[1459] Output: Generates a response with the current note inventory information and sends it to the device.

[1460] Operation: The device receives the notebook inventory information and displays it to the user.

[1461] Step 3:

[1462] Automatic ordering

[1463] Input: The server checks the inventory database on a regular schedule.

[1464] How it works: At regular intervals (e.g., every day at midnight), the server detects items that are below a stock threshold.

[1465] What happens: The server scans the inventory database on a scheduled basis to detect items below a threshold (e.g., fewer than 10 notebooks in stock).

[1466] Data processing / calculation: Use the generative AI model to calculate the required order quantity (e.g., order 20 notebooks), then send the order information to an external ordering system (e.g., external API).

[1467] Output: Receives the response containing the order result, logs it, and generates a notification message to send to the terminal.

[1468] Operation: The terminal displays the order notification received from the server to the user.

[1469] Step 4:

[1470] Order status notification

[1471] Input: Order result feedback from external ordering system.

[1472] How it works: The server periodically calls the API of the external ordering system to check the progress of the order.

[1473] Specific behavior: The server retrieves the order status through the API and records it in a log.

[1474] Data processing / calculation: Analyze the retrieved order status and use a generative AI model to generate a message to notify the user.

[1475] Output: Sends a notification message to the terminal.

[1476] Action: The terminal displays the received notification message to the user.

[1477] (Application example 1)

[1478] 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."

[1479] In current inventory management systems, the processes of adding, checking, and ordering inventory are often all done manually, resulting in reduced work efficiency and a high likelihood of human error. Additionally, inventory information cannot be checked in real time on-site, making it difficult to respond quickly. There is a need for a system that can solve these problems and improve the efficiency and accuracy of inventory management at logistics centers and other facilities.

[1480] 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.

[1481] In this invention, the server includes means for communicating with users using generative artificial intelligence, means for connecting with external services and acquiring data based on user requests, means for automating specific tasks based on user requests, means for monitoring task progress and notifying the user of the results, means for receiving user voice commands using voice recognition and executing processing, and means for visualizing inventory information in real time using a user-portable 3D display device. This allows users to add or check inventory using voice commands and check inventory status in real time through their smart devices. Furthermore, automatic ordering is performed when inventory levels fall below a certain threshold, achieving efficient inventory management.

[1482] "Generative AI" is AI that analyzes data and generates responses and instructions in natural language through dialogue with the user.

[1483] "Means for communicating with the user" refers to an interface that uses generative artificial intelligence to realize two-way dialogue with the user through voice and text.

[1484] "Means of linking with external services" refers to the function of obtaining necessary information from external databases or APIs and using it within the system.

[1485] A "means for automating a task" is a function for executing a task based on a request from a user without manual intervention and managing the progress of the task.

[1486] The "means for monitoring and notifying the progress of a task" is a function for tracking the status of a task currently being executed and notifying the user of the results in real time.

[1487] The "means for receiving user voice commands using voice recognition" is a function for analyzing the user's voice, converting it into text data, and interpreting it as instructions.

[1488] "Means for visualizing inventory information using a portable 3D display device" refers to a function that uses a portable device such as smart glasses or a head-mounted display to display inventory information in three dimensions and present it to the user in an easy-to-understand manner.

[1489] "Inventory management" is the process of managing the quantity of products and parts held in stock and replenishing or ordering as needed.

[1490] An "inventory database" is a database that records information on all items managed as inventory and can be referenced and updated as needed.

[1491] "Automatic ordering" is the process by which the system automatically orders additional stock when inventory falls below a defined threshold.

[1492] This invention is a system that uses generative artificial intelligence to realize communication through voice recognition, visualization of real-time inventory information, and automatic ordering in order to improve the efficiency of inventory management at logistics centers, etc. As an application example of this invention, details of an inventory management system using smart glasses will be described.

[1493] System configuration and roles

[1494] server

[1495] The server plays a central role in this system. It uses generative artificial intelligence to provide an interface for dialogue with the user and accepts voice commands from the user. It also connects with external services to obtain necessary data and manage inventory information. It also has a function to automatically place an order when inventory levels fall below a threshold. The server uses Python programs and voice recognition libraries (e.g., SpeechRecognition).

[1496] Terminal

[1497] The terminal is a portable device such as smart glasses or a head-mounted display that allows users to input voice commands. The terminal displays inventory information in 3D in real time, allowing users to easily check inventory status on-site.

[1498] User

[1499] Users operate the system through smart glasses to manage inventory. For example, a user might give a voice command such as "add 50 pens." The smart glasses then transmit the voice command to a server, which analyzes the voice and updates the inventory database. When inventory falls below a certain threshold, the server automatically places an order and notifies the user of the result.

[1500] Program Description

[1501] 1. Hardware:

[1502] Server: High-performance server (e.g. Amazon AWS, Google Cloud Platform)

[1503] Devices: Smart glasses (e.g., Google Glass), head-mounted displays (e.g., Microsoft HoloLens)

[1504] 2. Software:

[1505] Server-side program: Python

[1506] Speech recognition library: SpeechRecognition

[1507] Notification Library: Pushbullet API

[1508] 3. Data processing and calculation:

[1509] The user sends a voice command to the smart glasses.

[1510] The smart glasses send the voice data to a server, where a Python program converts the voice into text for analysis.

[1511] The server updates the inventory database based on the instructions and notifies the user of the changes.

[1512] When inventory falls below a threshold, the server automatically places an order and notifies the user of the result.

[1513] Specific examples

[1514] The user commands the smart glasses to "add 50 pens." The smart glasses recognize the voice and send it to the server. The server analyzes the received voice data and updates the inventory database. The user can confirm the completion of the task by seeing the message "50 pens added" on the smart glasses' display.

[1515] Example prompt sentence:

[1516] The user speaks to the smart glasses, "Add 50 pens." This speech information is sent to the server, and the generative AI model interprets it as "Add 50 pens to inventory" and updates the database. At that time, the user should be notified that the addition is complete.

[1517] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1518] Step 1:

[1519] The user speaks the voice command "Add 50 pens" to the smart glasses.

[1520] Input: User's voice command

[1521] Output: Audio data

[1522] What it does: The microphone in the smart glasses captures the user's voice and obtains the voice data.

[1523] Step 2:

[1524] The terminal (smart glasses) transmits the acquired voice data to the server.

[1525] Input: Audio data

[1526] Output: Sending audio data to the server

[1527] What it does: The smart glasses send audio data over the internet to a specified endpoint on the server.

[1528] Step 3:

[1529] The server converts the received voice data into text.

[1530] Input: Audio data

[1531] Output: Converted text data (e.g. "Add 50 pens")

[1532] Specific operation: The server converts the voice data into text using a speech recognition library (e.g., SpeechRecognition).

[1533] Step 4:

[1534] The server parses the text data and updates the inventory database.

[1535] Input: Text data

[1536] Output: Updated inventory database

[1537] Specific operation: The server uses generative artificial intelligence to analyze the text data, interprets it as an instruction to "add 50 pens," and increases the inventory quantity of the corresponding item in the inventory database by 50.

[1538] Step 5:

[1539] The server notifies the user of the results of the inventory database update.

[1540] Input: Updated inventory information

[1541] Output: A notification message to the user (e.g. "50 pens added").

[1542] What it does: The server sends a notification message to the user's smart glasses using a notification library such as the Pushbullet API.

[1543] Step 6:

[1544] The terminal (smart glasses) displays the received notification message to the user.

[1545] Input: Notification message from the server

[1546] Output: Notification message displayed on the smart glasses display

[1547] Specific operation: The smart glasses analyze the received notification message and display the message "50 pens added" on the display.

[1548] Step 7:

[1549] The server automatically places an order if the inventory level falls below a threshold.

[1550] Input: Updated inventory information

[1551] Output: Automatic ordering instructions and notification of ordering results

[1552] Specific operation: The server checks the inventory database, and if the inventory level is below the threshold, it sends an order instruction to an external service, logs the order result, and notifies the user.

[1553] 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.

[1554] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[1555] System configuration and roles

[1556] server

[1557] The server functions as the core of the system and is equipped with a generative artificial intelligence and an emotion engine. The server processes user input received from the user interface and exchanges data with external services. It also automates specific tasks (e.g., inventory management) based on user requests, and monitors and notifies users of their progress. The emotion engine recognizes the user's emotions in real time, and the generative artificial intelligence generates an appropriate response based on those emotions.

[1558] Terminal

[1559] The terminal works in cooperation with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server and also indicates the user's emotional state.

[1560] User

[1561] Users interact with the system through a terminal interface. This system allows users to streamline inventory management tasks and utilize automated ordering processes. Furthermore, appropriate responses based on the user's emotions provide a more comfortable interface experience.

[1562] Program processing

[1563] The specific program processing flow is as follows:

[1564] 1. Emotion Recognition and Dialogue Generation

[1565] User: The user inputs information through the device's user interface. For example, when the user inputs a request such as "add 50 pens," emotions are read from the user's facial expressions and voice.

[1566] Device: The device captures the user's emotional data (facial expressions, voice tone, etc.) and sends it to the server.

[1567] Server: The server uses an emotion engine to recognize the user's emotions. The generative AI then generates an appropriate response based on the emotion and sends it back to the user.

[1568] 2. Add and check inventory

[1569] User: After receiving the appropriate response based on their emotion, the user makes a request to add more stock via the terminal. For example, they send an instruction to the server saying, "Add 50 pens."

[1570] Server: The server updates inventory information and generates a message of acceptance based on the user's emotional state, as recognized by the emotion engine. For example, if the user is nervous, the system can send a message to relax.

[1571] 3. Automated ordering and progress monitoring

[1572] Terminal: Periodically communicates with the server and sends a request to check stock availability.

[1573] Server: The server automatically detects items below the inventory threshold and calculates the order quantity. The order information is sent to the terminal in the form of an appropriate notification based on the user's emotional state recognized by the emotion engine.

[1574] Terminal: The order results are displayed on the user interface, along with the user's emotional state.

[1575] Specific examples

[1576] For example, if a user commands "add 50 pens" through a device, the device captures the user's facial expression along with the command and sends it to the server. The server then uses an emotion engine to analyze the user's emotions, and the generative AI generates and sends a message corresponding to the user's emotions (e.g., "Got it, I'll add 50 pens").

[1577] Similarly, if inventory falls below a threshold, the server automatically initiates the ordering process and notifies the user of the order outcome in an emotionally sensitive manner. For example, if an order is delayed, a comforting message such as "Please wait a moment, we're on our way" can be added.

[1578] In this way, this system has advanced response capabilities that combine generative artificial intelligence and an emotion engine, simultaneously improving the efficiency of inventory management tasks and the user experience.

[1579] The processing flow will be explained below.

[1580] Step 1:

[1581] User: The user inputs a request through the device's user interface, for example, "Add 50 pens." At the same time, the user's facial expressions and tone of voice are captured.

[1582] Step 2:

[1583] Terminal: The terminal sends the user's facial expression data and voice tone data along with the input request to the server.

[1584] Step 3:

[1585] Server: The server processes the received request and emotion data. It uses an emotion engine to recognize the user's emotion (e.g., joy, anger, sadness, surprise, etc.).

[1586] Step 4:

[1587] Server: Based on the emotions recognized by the emotion engine, the generative AI generates an appropriate response message. For example, if the user is tired, it generates a relaxing message such as "Got it. 50 pens have been added. Thank you for your continued patronage."

[1588] Step 5:

[1589] Server: The server generates a response message and sends it to the terminal to notify the user.

[1590] Step 6:

[1591] Terminal: The terminal displays the response message received from the server on the user interface. The user can see the response message and confirm that the stock has been added.

[1592] Step 7:

[1593] User: A user requests an inventory check of a specific item through a terminal, for example, by entering a request such as "Check inventory of notebooks."

[1594] Step 8:

[1595] Terminal: The terminal sends a request to the server.

[1596] Step 9:

[1597] Server: The server retrieves the inventory amount of the specified item from the database.

[1598] Step 10:

[1599] Server: As before, the generative AI generates an appropriate message based on the inventory status, such as "There are 10 notebooks left in stock. You can order more if needed."

[1600] Step 11:

[1601] Server: The server sends the generated message to the terminal and notifies the user.

[1602] Step 12:

[1603] Terminal: The terminal displays the message received from the server on the user interface, and the user can check the stock amount.

[1604] Step 13:

[1605] Terminal: The terminal periodically communicates with the server and sends a request to check stock availability.

[1606] Step 14:

[1607] Server: The server automatically detects items that are below a stock threshold and determines the need for automatic ordering.

[1608] Step 15:

[1609] Server: When automatic ordering is required, the server generates an order in cooperation with an external service. The emotion engine adjusts the notification message of the order progress according to the user's emotion.

[1610] Step 16:

[1611] External Service: An external service receives the order request and initiates processing.

[1612] Step 17:

[1613] External service: Once the order is placed, the result is notified to the server.

[1614] Step 18:

[1615] Server: The server logs the order result and generates a notification message that takes the user's feelings into consideration. For example, if the order is delayed, it adds a comforting message such as "The current shipping status is that the product is being prepared. Please wait a little longer."

[1616] Step 19:

[1617] Server: The server sends a notification message to the terminal.

[1618] Step 20:

[1619] Terminal: The terminal receives updates from the server and displays the order results on the user interface, allowing the user to view the progress of the automated order and the latest inventory status.

[1620] Through this series of processes, the system recognizes the user's emotions and responds appropriately, thereby improving the user experience and enabling efficient inventory management.

[1621] Example 2

[1622] 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."

[1623] Traditional inventory management systems lack the ability to respond to user emotions, which often results in poor user experience and inefficient inventory management. Furthermore, the lack of automated task management based on user requests and real-time progress notifications hinders smooth business operations.

[1624] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1625] In this invention, the server includes means for communicating with the user using generative artificial intelligence, means for linking with external services and acquiring data based on the user's request, means for recognizing the user's emotions and generating an appropriate response, means for automating specific tasks based on the user's request, and means for monitoring the progress of the tasks and notifying the user of the results. This enables high-quality responses that take the user's emotions into consideration, resulting in more efficient inventory management and an improved user experience.

[1626] "Generative artificial intelligence" is a computer-based technology that interacts with users and uses natural language processing to generate appropriate responses.

[1627] "External services" are online services that allow you to use information and functions, such as APIs and databases, provided outside the system.

[1628] An "emotion engine" is a software module that analyzes emotions from a user's facial expressions, tone of voice, text, etc., and adjusts responses based on those emotions.

[1629] A "user interface" is an interaction means, such as a screen or input device, that allows a user to interact with a system.

[1630] A "database" is an information system for efficiently storing, managing, and retrieving data such as inventory information.

[1631] "Automation" is the process by which a program or machine performs a task based on a user's request without human intervention.

[1632] "Notifications" are messages or alerts that convey important information to the user, such as the progress or results of a task.

[1633] "Inventory management" is the management task of optimizing the amount of goods and materials in stock and replenishing or ordering in a timely manner.

[1634] A "prompt sentence" is a piece of text that is input to a generative AI and serves as the basis for generating a response.

[1635] MODE FOR CARRYING OUT THE INVENTION

[1636] System Overview

[1637] This invention is a system that combines generative artificial intelligence and an emotion engine to communicate with users, collaborate with external services, automate specific tasks, and monitor and notify their progress. This system is particularly capable of automating inventory management and recognizing user emotions and adjusting responses accordingly.

[1638] Hardware and Software Configuration

[1639] server

[1640] The server functions as the core of the system and is equipped with a generative artificial intelligence and emotion engine. The server processes user input received from the user interface and exchanges data with external services. The server also automates specific tasks (e.g., inventory management) and monitors and notifies progress.

[1641] Terminal

[1642] The terminal works in conjunction with the server and provides a user interface through which the user can check inventory information, add items, and make other requests. The terminal displays the information received from the server, along with the user's emotional state.

[1643] Program processing

[1644] 1. Receiving User Requests

[1645] The user inputs a request, for example, "add 50 pens" via the user interface of the terminal.

[1646] The device captures the user's input and emotional data such as facial expressions and tone of voice at the time of input, and sends this to the server.

[1647] 2. Sentiment Analysis and Response Generation

[1648] The server processes the received request and emotion data and analyzes the user's emotion using the emotion engine.

[1649] The server generates a prompt for the generative AI model. For example, "There is a request to add 50 pens, and the user is nervous."

[1650] The generative AI model generates an appropriate response based on this prompt, for example, "Got it. I'll add 50 pens. Relax."

[1651] 3. Sending and Displaying the Response

[1652] The server sends the generated response to the terminal.

[1653] The terminal displays the response received from the server on the user interface.

[1654] 4. Updating inventory information

[1655] The server updates the inventory database to record that 50 pens have been added.

[1656] The user can check the latest inventory information via the terminal. For example, when the user instructs "display inventory list," the terminal reads and displays the latest inventory information.

[1657] 5. Automated ordering and progress monitoring

[1658] The terminal periodically sends a request to the server to check the stock status.

[1659] The server automatically detects items that are below the inventory threshold and initiates the ordering process.

[1660] The generative AI model generates an appropriate message to inform the user that the ordering process has begun, for example, "We are running low on stock, so we have automatically ordered pens."

[1661] The server sends appropriate notification messages to the terminal to record progress.

[1662] The terminal displays notification messages received from the server on the user interface to provide the user with real-time progress information. For example, when an order is completed, a message such as "Order completed. Waiting for delivery" is displayed.

[1663] Specific examples

[1664] For example, if a user issues an instruction to "add 50 pens" via a device, the device captures the instruction and the user's emotional data and sends them to the server. The server then uses an emotion engine to analyze the user's emotions, and a generative artificial intelligence (AI) system generates a response message appropriate to the user's emotions. For example, the message generated might read, "Got it. I'll add 50 pens. Please relax." This message is then sent to the device and displayed to the user.

[1665] If the stock falls below the threshold, the server automatically starts the ordering process and notifies the user of the result. For example, it generates a message saying, "Stock is low, so pens have been automatically ordered." and notifies the terminal.

[1666] In this way, by combining generative artificial intelligence and an emotion engine, this system provides advanced dialogue and emotion recognition functions, improving inventory management efficiency and the user experience.

[1667] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1668] Step 1:

[1669] The user inputs a request through the user interface of the terminal, for example, "add 50 pens." The input data is the string "add 50 pens," which triggers the next processing step. The terminal sends the input data to the server.

[1670] Step 2:

[1671] The device captures the user's emotional data (such as facial expressions and voice tone) when inputting a request. Specifically, it uses a camera and microphone to capture the user's facial expressions and voice tone, extracting them as digital data. The emotional data and input data are then sent together to the server.

[1672] Step 3:

[1673] The server processes the received request data and emotion data. The input is the user's request and emotion data, and the output is the emotion recognition result and a prompt. Using the emotion engine, the server analyzes the user's emotion and generates a prompt for the generative AI model based on the results. For example, a prompt such as "There is a request to add 50 pens, and the user is nervous" is generated.

[1674] Step 4:

[1675] The generative AI model generates an appropriate response based on the prompt received from the server. The input is the generated prompt, and the output is a generated response message. For example, the generated response message is "Got it. I'll add 50 pens. Relax."

[1676] Step 5:

[1677] The server sends the generated response message to the terminal. The input is the generated response message, and the output is data communication to the terminal. The terminal displays the response message received from the server on its user interface. For example, a message such as "Got it. 50 pens will be added. Please relax." is displayed on the terminal.

[1678] Step 6:

[1679] The server updates the inventory database. The input is the user's request data, and the output is the updated inventory information. Specifically, the addition of 50 pens is recorded in the database. The user can check the latest inventory information through the terminal. For example, if the user instructs "Display inventory list," the terminal will read and display the latest inventory information. Specifically, the server retrieves inventory data from the database and displays it on the user interface.

[1680] Step 7:

[1681] The terminal periodically sends a request to check the stock status to the server. The input is a regular interval (e.g., once a day), and the output is a stock check request sent to the server.

[1682] Step 8:

[1683] The server automatically detects items that fall below an inventory threshold and initiates the ordering process. The input is current inventory data, and the output is the calculated order quantity and ordering information. Specifically, the server scans the inventory database and automatically places an order for items that fall below the threshold.

[1684] Step 9:

[1685] The generative AI model generates an appropriate message to notify the user that the ordering process has begun. The input is the start information of the ordering process, and the output is a notification message. For example, a message such as "We have automatically placed an order for pens as we are running low on stock" is generated.

[1686] Step 10:

[1687] The server sends the generated notification message to the terminal. The input is the generated notification message, and the output is data communication to the terminal. The terminal displays the notification message received from the server on the user interface, providing the user with a progress status in real time. Specifically, when the order processing is complete, the message "Order completed. Waiting for delivery" is displayed.

[1688] (Application example 2)

[1689] 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."

[1690] Although conventional inventory management systems have advanced in terms of automation of inventory management, they have a problem of being unable to respond flexibly based on user emotions. Furthermore, when users check inventory or place orders, they lack appropriate support based on their status and emotions, which tends to reduce the quality of the user experience. Furthermore, there is a need for a method to efficiently manage inventory while taking into consideration the emotions of workers at worksites such as logistics centers.

[1691] 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.

[1692] In this invention, the server includes means for communicating with a user using generative artificial intelligence, means for connecting with external services and acquiring data based on a user request, means for automating specific inventory management tasks based on the user request, means for monitoring the progress of the tasks and notifying the user of the results, and means for recognizing the user's emotions and generating responses based on the emotions. This allows the user to receive appropriate support that takes emotions into consideration when performing inventory management tasks. Furthermore, when inventory falls below a threshold, an order notification message generated based on the emotions is sent to the user, thereby realizing efficient and flexible inventory management.

[1693] "Generative AI" is an AI system that has the ability to generate new information and responses based on given data.

[1694] "Means for communicating with the user" refers to means that has the function of receiving input from the user and returning appropriate responses or information in response to that input.

[1695] "Means for linking with external services and acquiring data based on user requests" refers to means that has the function of communicating with other systems and services, acquiring the necessary data, and responding to user requests.

[1696] A "means for automating a specific task" is a means that has the function of automatically executing a specific job or work without human intervention, based on instructions from a user.

[1697] The "means for monitoring the progress of a task and notifying the user of the result" is a means having a function for tracking the progress of an automated task and notifying the user of the result.

[1698] "Means for recognizing emotions and generating a response based on the emotions" refers to means that has the function of analyzing the user's emotions from facial expressions, tone of voice, etc., and generating a response that is adapted to those emotions.

[1699] "Inventory management" refers to the act of keeping track of stock levels and replenishing or ordering as needed.

[1700] A "threshold" is a specific reference value, below which or above which a specific action is executed.

[1701] An "order notification message" is a notification message that is automatically generated and sent to a user when inventory needs to be replenished.

[1702] MODE FOR CARRYING OUT THE INVENTION

[1703] The present invention combines generative artificial intelligence and an emotion engine in an inventory management system at a logistics center, thereby achieving efficient and flexible responses.

[1704] System configuration

[1705] server

[1706] The server is the core of the system and has the following functions:

[1707] It communicates with users using generative artificial intelligence (AI model).

[1708] Data is shared with external services and data is retrieved based on user requests.

[1709] Automate specific inventory management tasks based on user requests.

[1710] Monitor the progress of the task and notify the user of the results.

[1711] An emotion engine is used to recognize the user's emotions and generate responses based on those emotions.

[1712] The specific tools used are IBM Watson Emotion Analysis as the emotion engine and OpenAI GPT-4 as the generative artificial intelligence, with Node.js as the backend server and MongoDB as the database.

[1713] Terminal

[1714] The device works in conjunction with the server and provides the user interface. It is built as a smartphone app and developed using React Native. The device has the following features:

[1715] It uses a camera and microphone to capture the user's facial expressions and tone of voice.

[1716] Send the capture data to the server.

[1717] Provides an interface for checking inventory and requesting additional items.

[1718] Displays the sentiment analysis results received from the server and the generated response.

[1719] User

[1720] The user (worker) interacts with the system through a terminal. They perform tasks such as checking inventory, adding, or reducing it, and receive responses from the system. In addition, receiving responses based on the results of emotion analysis enables efficient and comfortable inventory management.

[1721] Example of a system

[1722] When a user makes a request via a terminal to "add 50 pens," the following happens:

[1723] 1. The device's camera and microphone capture the user's facial expressions and voice.

[1724] 2. The captured data is sent to the backend server in real time.

[1725] 3. The server uses an emotion engine (IBM Watson Emotion Analysis) to analyze the user's emotions.

[1726] 4. Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on the emotion and sends a message to the device such as, "Got it, we'll add 50 pens. Good luck with your future work!"

[1727] 5. When the inventory falls below the threshold, the ordering process will be automatically initiated and an ordering notification message will be sent to the user saying, "Don't worry, we will start the ordering process and replenish the inventory right away. Please wait a moment."

[1728] Prompt Sentence Examples

[1729] User emotion: Happy

[1730] User input: "Add 50 pens"

[1731] Response: "Okay, I'll add 50 pens. Good luck with your work!"

[1732] User emotion: Stressed

[1733] User input: "Stock is low, what should I do?"

[1734] Response: "Don't worry. We'll start the ordering process and replenish your inventory right away. Please be patient."

[1735] This invention improves the efficiency of inventory management tasks at logistics centers and enables flexible responses that take user emotions into consideration. Furthermore, appropriate responses based on emotions improve the quality of the user experience.

[1736] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1737] Step 1:

[1738] The user launches the terminal's user interface and logs in. The input is the user's login information (username, password), and the output is a message indicating whether the login was successful or not. The terminal obtains this information and sends it to the server. The server verifies the login information and returns the result to the terminal.

[1739] Step 2:

[1740] The user inputs a request for inventory check or addition into the terminal. The input is an inventory management request such as "add 50 pens." The terminal receives this input, captures the user's facial expressions and voice with a camera and microphone, and transmits them to the server in real time.

[1741] Step 3:

[1742] The server receives the captured data sent from the device and analyzes it using an emotion engine (IBM Watson Emotion Analysis). The input is the user's facial expression data and voice data, and the output is analyzed emotion data (e.g., "Happy," "Stressed," etc.). The server acquires this emotion data and uses it as a prompt to send to the generative artificial intelligence (OpenAI GPT-4).

[1743] Step 4:

[1744] Generative artificial intelligence (OpenAI GPT-4) generates an appropriate response based on emotional data and the user's request. The input is the emotional data and the user's request, and the output is a response message based on the emotion. For example, if the emotion is "Happy," the message generated is "Got it, we'll add 50 pens. Good luck with your future work!"

[1745] Step 5:

[1746] The server sends the generated response message to the terminal. The output is the response message displayed on the terminal. The terminal receives this message and displays it on the user interface. The user confirms this message.

[1747] Step 6:

[1748] The server receives inventory management requests and updates the MongoDB database. The input is the inventory addition request (e.g., "add 50 pens") and the output is the updated inventory data. The server updates the inventory information and monitors the results.

[1749] Step 7:

[1750] When inventory falls below the threshold, the server initiates an automatic ordering process. The input is the updated inventory data and threshold information, and the output is an order notification message. Generative AI generates an appropriate order notification message based on emotions, generating messages such as, "Don't worry. We will immediately start the ordering process and replenish the inventory. Please wait a moment."

[1751] Step 8:

[1752] The server sends the generated order notification message to the terminal, which receives the message and displays it on the user interface. The user can then confirm the order notification message and continue working with peace of mind.

[1753] In this way, the user, terminal, and server work together in each processing step, realizing automation of inventory management and appropriate responses according to the user's emotions.

[1754] 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.

[1755] 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.

[1756] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1757] 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.

[1758] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1759] 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.

[1760] 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).

[1761] 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.

[1762] 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."

[1763] 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.

[1764] 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).

[1765] 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.

[1766] 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.

[1767] 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.

[1768] 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.

[1769] 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.

[1770] 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.

[1771] 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.

[1772] 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.

[1773] 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.

[1774] 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.

[1775] The following is further disclosed regarding the above embodiment.

[1776] (Claim 1)

[1777] a means for communicating with a user using generative artificial intelligence;

[1778] A means for linking with external services and acquiring data based on user requests;

[1779] a means for automating certain tasks based on user requests;

[1780] a means for monitoring the progress of the task and notifying the user of the results;

[1781] A system including:

[1782] (Claim 2)

[1783] 2. The system according to claim 1, further comprising means for automatically checking inventory levels and placing orders at the required timing, the specific task being inventory management.

[1784] (Claim 3)

[1785] 2. The system according to claim 1, further comprising means for receiving a request from a user through a user interface and executing appropriate processing using the generative artificial intelligence.

[1786] "Example 1"

[1787] (Claim 1)

[1788] a means for communicating with a user using generative artificial intelligence;

[1789] A means for linking with external services and acquiring data based on user requests;

[1790] a means for automating certain tasks based on user requests;

[1791] a means for monitoring the progress of the task and notifying the user of the results;

[1792] A means for a user to send an instruction to add stock from a terminal and for a server to analyze and process the instruction;

[1793] A means for a user to send an inventory check request from a terminal and for a server to analyze and process the request;

[1794] A means for the server to periodically monitor inventory and automatically order items that fall below a threshold;

[1795] A means for processing orders and notifying results via an external service;

[1796] A system including:

[1797] (Claim 2)

[1798] 2. The system according to claim 1, further comprising means for automatically checking inventory levels and placing orders at the required timing, the system having inventory management as a specific task.

[1799] (Claim 3)

[1800] 10. The system of claim 1, further comprising means for receiving a request from a user through a user interface and performing appropriate processing using generative artificial intelligence.

[1801] "Application Example 1"

[1802] (Claim 1)

[1803] a means for communicating with a user using generative artificial intelligence;

[1804] A means for linking with external services and acquiring data based on user requests;

[1805] a means for automating certain tasks based on user requests;

[1806] a means for monitoring the progress of the task and notifying the user of the results;

[1807] means for receiving and processing user voice commands using voice recognition;

[1808] means for visualizing inventory information in real time using a user-portable 3D display device;

[1809] A system including:

[1810] (Claim 2)

[1811] 2. The system according to claim 1, further comprising means for automatically checking inventory levels and placing orders at the required timing, the specific task being inventory management.

[1812] (Claim 3)

[1813] 2. The system according to claim 1, further comprising means for receiving a request from a user through a user interface and executing appropriate processing using the generative artificial intelligence.

[1814] (Claim 4)

[1815] 3. The system of claim 2, further comprising means for receiving user voice commands relating to inventory management using said voice recognition and automatically updating the inventory database.

[1816] "Example 2: Combining Emotion Engines"

[1817] (Claim 1)

[1818] a means for communicating with a user using generative artificial intelligence;

[1819] A means for linking with external services and acquiring data based on user requests;

[1820] means for recognizing a user's emotion and generating an appropriate response;

[1821] a means for automating certain tasks based on user requests;

[1822] a means for monitoring the progress of the task and notifying the user of the results;

[1823] A system including:

[1824] (Claim 2)

[1825] 2. The system according to claim 1, further comprising means for automatically checking inventory levels and placing orders at the required timing, the specific task being inventory management.

[1826] (Claim 3)

[1827] 2. The system according to claim 1, further comprising means for receiving a request from a user through a user interface and executing appropriate processing using the generative artificial intelligence.

[1828] "Application example 2 when combining emotion engines"

[1829] (Claim 1)

[1830] a means for communicating with a user using generative artificial intelligence;

[1831] A means for linking with external services and acquiring data based on user requests;

[1832] a means for automating certain tasks based on user requests;

[1833] a means for monitoring the progress of the task and notifying the user of the results;

[1834] means for recognizing a user's emotion and generating a response based on the emotion;

[1835] A system including:

[1836] (Claim 2)

[1837] 2. The system according to claim 1, further comprising means for automatically checking inventory levels and placing orders at the required timing, the system having inventory management as a specific task.

[1838] (Claim 3)

[1839] 10. The system of claim 1, further comprising means for receiving a request from a user through a user interface and performing appropriate processing using generative artificial intelligence.

[1840] (Claim 4)

[1841] 10. The system of claim 1, further comprising means for capturing a user's emotional data (facial expressions, vocal tone, etc.) and analyzing it with an emotion engine.

[1842] (Claim 5)

[1843] 3. The system of claim 2, further comprising means for sending an emotion-based order notification message to a user when inventory falls below a threshold.

[1844] (Claim 6)

[1845] 2. The system according to claim 1, further comprising means for generating a message according to the user's emotions using generative artificial intelligence and replying to the user. [Explanation of symbols]

[1846] 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. a means for communicating with a user using generative artificial intelligence; A means for linking with external services and acquiring data based on user requests; a means for automating certain tasks based on user requests; a means for monitoring the progress of the task and notifying the user of the results; A system including:

2. 2. The system according to claim 1, further comprising means for automatically checking inventory levels and placing orders at the required timing, the specific task being inventory management.

3. The system according to claim 1 , further comprising means for receiving a request from a user through a user interface and executing an appropriate process using said generative artificial intelligence.

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