system

Abstract

We provide the system. [Solution] A means for obtaining the inventory status of multiple items from an external database, A means to identify the item requested for loan from the user's terminal and to inquire about its availability, A means of analyzing acquired inventory data and returning the analysis results to the user terminal, A means of checking inventory based on user loan requests and determining whether or not to lend the item, A means of requesting processing from an external database to confirm the loan of items that have become available for loan, A means of returning the loan processing results to the user terminal, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional lending system for demonstration machines, it was difficult to perform efficient lending management because it was complicated and time-consuming to check the inventory status and determine whether lending was possible. Also, when a user inputs an item for which they wish to borrow, the lending availability may not be accurately determined because the inventory information is not reflected in real time. Such problems have significantly reduced the convenience for users and caused problems leading to an increase in management costs.

Means for Solving the Problems

[0005] The present invention solves the above problems by providing a system that includes means for obtaining the inventory status of multiple items from an external database, means for identifying items requested for loan from a user terminal and querying their inventory status, means for analyzing the acquired inventory data and returning the analysis results to the user terminal, means for checking inventory based on the user's loan request and determining whether or not to loan the item, means for requesting processing from the external database to confirm the loan of items that have become available for loan, and means for returning the loan processing results to the user terminal. With this system, users can easily check inventory status and determine loan availability in real time, thus enabling efficient and accurate loan management.

[0006] An "external database" is a database that exists outside the system and manages information such as inventory status and loan information for items.

[0007] "Items" refers to the specific products or devices that the user wishes to borrow.

[0008] "Inventory status" refers to information indicating the number of items that are available for loan.

[0009] A "user terminal" refers to a device that a user uses to access and operate a system, such as a personal computer or a smartphone.

[0010] "Loan Request" indicates a user's request to borrow a specific item for a certain period of time.

[0011] "Availability for loan" refers to the result of determining whether the item requested by the user can actually be loaned out.

[0012] "Analysis" is the process of deciphering necessary information from acquired data and transforming it into a meaningful form.

[0013] "Loan confirmation" refers to the state in which the loan of the item requested by the user is finally confirmed, and this information is processed by the system.

[0014] "Requesting processing" means that the system asks an external database to perform a specific operation or update data.

[0015] "Loan processing result" refers to the result information obtained after the loan procedure is completed, including whether the loan was successful or not. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] The system of the present invention allows users to easily check the inventory status of items and make loans by performing the following processes.

[0038] 1. The user operates the terminal and enters the name of the item whose stock status they wish to check. This input triggers the terminal to send a request to the server to inquire about the stock status.

[0039] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. Specifically, the server calls the external database's API to retrieve inventory data.

[0040] 3. The server analyzes the inventory data it has acquired and returns the results to the user's terminal. For example, it notifies the user that "there are 10 iPad® Pro units in stock."

[0041] 4. The user operates the terminal and enters the items and quantities they wish to borrow. This input triggers the terminal to send a borrowing request to the server.

[0042] 5. The server checks the inventory status again and determines whether the loan request can be fulfilled. If there is sufficient inventory, the server notifies the user that the loan is available.

[0043] 6. The user confirms the loan on the terminal. The terminal sends a loan confirmation request to the server.

[0044] 7. The server receives the loan confirmation request and requests the external database to process the loan. The server uses the external database's API to update the inventory information and record that the loan has been made.

[0045] 8. Finally, the server returns the loan processing result to the user's terminal, and the user confirms that the loan is complete.

[0046] Specific example:

[0047] Example 1:

[0048] The user types "I want to check the availability of iPad Pro" on their device. The device sends a request to the server. The server connects to an external database, retrieves the information that "there are 10 iPad Pros in stock," parses it, and returns it to the device. The user then types "I want to borrow one iPad Pro." The device sends a request to the server. The server checks the inventory, determines that it is "available," and notifies the device. The user clicks "Confirm Loan." The device sends a request to the server. The server connects to an external database, updates the inventory, and confirms the loan process. The server notifies the device that "the loan is complete," and the user confirms.

[0049] This system allows users to efficiently and accurately check the inventory status of items and proceed with the lending process.

[0050] The following describes the processing flow.

[0051] Step 1:

[0052] The user operates the device and enters the item whose stock status they want to check (e.g., "iPad Pro"). The device then sends a request to the server to inquire about the stock status based on the entered information.

[0053] Step 2:

[0054] The device sends an API request to the server with the content "Item: Please tell me the stock status of iPad Pro".

[0055] Step 3:

[0056] The server receives the request and connects to the external database's API. At this time, the server sends an API request to the external database to "query the availability of iPad Pro."

[0057] Step 4:

[0058] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[0059] Step 5:

[0060] The server analyzes the received data and converts it into a user-friendly format. Specifically, it generates a message such as, "We have 10 iPad Pros in stock."

[0061] Step 6:

[0062] The server returns a response to the terminal containing the analysis results. It also sends data to the terminal stating, "We have 10 iPad Pros in stock."

[0063] Step 7:

[0064] The terminal displays the inventory status received from the server to the user. The user operates the terminal and enters, "I would like to borrow one iPad Pro."

[0065] Step 8:

[0066] The device sends a "request to lend one iPad Pro" to the server based on the user's input.

[0067] Step 9:

[0068] The server receives the request and checks the inventory data again. The server checks whether there are 10 iPad Pros in stock and available for loan.

[0069] Step 10:

[0070] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan."

[0071] Step 11:

[0072] The user operates the device and enters "Confirm Loan". The device sends a request to the server saying "Confirm loan of 1 iPad Pro".

[0073] Step 12:

[0074] The server receives the request and sends an API request to the external database to perform the lending process.

[0075] Step 13:

[0076] The external database executes the lending process and returns a "lending successful" response to the server. The server receives this response.

[0077] Step 14:

[0078] The server returns the loan success result to the user's device. It sends a message to the device saying, "iPad Pro loan complete."

[0079] Step 15:

[0080] The user checks the loan completion status on their device. The user understands that "the iPad Pro loan has been completed."

[0081] (Example 1)

[0082] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0083] Conventional inventory management and lending systems have made it difficult for users to quickly and accurately check inventory status and to complete lending procedures for multiple items. Furthermore, the process of determining lending eligibility and updating inventory information is time-consuming and inefficient. This invention aims to solve these problems and provide a system that allows users to efficiently and accurately check the inventory status of items and complete lending procedures.

[0084] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0085] In this invention, the server includes means for querying the inventory status of items entered from a user terminal, means for obtaining the inventory status of specified items from an external database, means for analyzing the obtained inventory data and returning the results to the user terminal, means for identifying the items and quantities of items requested for loan from the user terminal, means for reconfirming the inventory status based on the loan request and determining whether or not to loan the items, means for updating inventory information in the external database for items whose loan has been confirmed and recording the loan information, and means for returning the results of the loan process to the user terminal. This enables the user to efficiently and accurately check the inventory status of items and carry out loan procedures.

[0086] A "user terminal" is a device that a user operates to input information and can access a server via a network.

[0087] An "external database" is an information management system that a server connects to to retrieve and update inventory status and loan information.

[0088] "Inventory status" refers to information indicating the quantity of a particular item that is stored.

[0089] "Method of inquiry" refers to the process by which a user's terminal sends a request to a server to retrieve information.

[0090] "Means of acquisition" refers to the process by which a server retrieves necessary data from an external database.

[0091] "Means of analysis" refers to the process by which a server processes acquired data and extracts the necessary information.

[0092] "Items requested for loan" refers to specific items that the user wishes to borrow.

[0093] "Quantity" refers to the specific number of items you wish to borrow.

[0094] The "means of determining eligibility" refers to the process by which the server checks for availability based on a rental request and decides whether or not it is possible to rent it out.

[0095] "Confirmation method" refers to the process by which the server formally records information about items that have been determined to be available for loan.

[0096] "Loan information" refers to detailed data about the items that have been borrowed and their quantities.

[0097] "Means of notification" refers to the process by which the server communicates the processing results to the user's terminal.

[0098] This invention provides a system that allows users to easily check the inventory status of items and efficiently carry out lending procedures. This system operates by coordinating a user terminal, a server, and an external database.

[0099] The user operates their device (e.g., computer, tablet, smartphone) to input the item whose inventory status they want to check. Based on this input, the device sends an inventory status inquiry request to the server. The server parses the received request, extracts the item name, calls an API to an external database, and retrieves the inventory status of the specified item.

[0100] For example, a user enters "Check iPad Pro stock availability" into their device and clicks the submit button. The device sends this input as an HTTP request to the server. The server retrieves the iPad Pro stock availability from an external database, parses the response "Stock Quantity: 10", converts it to JSON format, and returns it to the user's device.

[0101] Next, the user operates their terminal to enter the items they wish to borrow and the quantity. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The terminal then sends a loan request to the server based on this input. The server checks the inventory status again and determines whether the loan request is possible.

[0102] If the server determines that the device is available for loan, the user confirms the loan on their device. The user's action sends a loan confirmation request to the server. The server connects to an external database and sends an API request, " / update_inventory?item=ipad-pro&quantity=-1", to update the inventory information. This updates the inventory count from 10 to 9.

[0103] After the loan information update is complete, the server returns the loan processing result to the user's terminal. Finally, the user receives and confirms a "loan completed" notification on their terminal screen.

[0104] The entire system is efficiently designed, allowing users to complete everything from checking inventory status to loan procedures in a short amount of time. For example, a user might type "I want to check the inventory status of iPad Pros," and the device sends a request to the server. The server retrieves information from an external database, stating "There are 10 iPad Pros in stock," analyzes it, and returns it to the device. Then, the user might type "I want to borrow one iPad Pro," and the server checks the inventory and notifies the user that it is "available." The user confirms the loan, the server connects to the external database to update the inventory, and confirms the loan process. Finally, the server notifies the device that "the loan is complete," and the user confirms it.

[0105] As described above, the present invention provides a system that allows users to efficiently and accurately check the inventory status of items and carry out lending procedures.

[0106] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0107] Step 1:

[0108] The user operates the device and enters the item whose stock status they want to check. Specifically, the user enters "Check iPad Pro stock status" into the device's interface (e.g., a form) and clicks the submit button. The input data is the item name "iPad Pro". As output, the device sends this input content to the server as an HTTP request.

[0109] Step 2:

[0110] The server parses the request received from the terminal. Specifically, the server extracts the item name (e.g., "iPad Pro"). The input data is the HTTP request sent from the terminal, and the output data is the extracted item name. The server then calls an API of an external database to retrieve the item's inventory status. The API call format is " / inventory?item=ipad-pro". The output is the inventory count, which is "10".

[0111] Step 3:

[0112] The server analyzes the acquired inventory data and generates data to be returned to the user's terminal. Specifically, the server converts information such as "There are 10 iPad Pros in stock" into JSON format (e.g., "{ 'item': 'iPad Pro', 'stock': 10}"). The input data is inventory information acquired from an external database, and the output data is the JSON formatted data after analysis. This data is sent to the user's terminal as an HTTP response.

[0113] Step 4:

[0114] The user terminal displays the received inventory information to the user. Specifically, the terminal screen will display "10 iPad Pro units in stock." The input data is inventory information in JSON format sent from the server, and the output data is the inventory information displayed to the user.

[0115] Step 5:

[0116] The user operates the terminal and enters the item and quantity they wish to borrow. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The input data consists of the item name and quantity, and the terminal sends this as a loan request to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1}".

[0117] Step 6:

[0118] The server analyzes the loan request received from the terminal and reconnects to the external database to check the inventory status. The input data is the loan request (item name and quantity), and the output data is the inventory information retrieved again. Specifically, the server confirms that there are 10 iPad Pro units in stock and determines that it is possible to loan the iPad Pro because the requested loan quantity (1 unit) is within the available stock.

[0119] Step 7:

[0120] The server notifies the user terminal of the result of its determination that the item is available for loan. Specifically, it generates a "available for loan" message in JSON format (e.g., "{ 'status': 'possible'}") and sends it as an HTTP response. The input data is the determination result that the item is available for loan, and the output data is the notification message sent to the user terminal.

[0121] Step 8:

[0122] The user confirms the loan on the device. Specifically, the user clicks the "Confirm Loan" button. The input data is the user's confirmation action, and the output is a loan confirmation request sent to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1, 'action': 'confirm'}".

[0123] Step 9:

[0124] The server receives a loan confirmation request, updates the inventory information in an external database, and records the loan information. Specifically, it executes the API call " / update_inventory?item=ipad-pro&quantity=-1" to update the inventory count from 10 to 9. The input data is the loan confirmation request and the current inventory information, and the output data is the updated inventory information.

[0125] Step 10:

[0126] The server returns the result of the loan process to the user's terminal. Specifically, it generates a message indicating "loan completed" in JSON format (e.g., "{ 'status': 'completed'}") and sends it as an HTTP response. The input data is the result of the loan process, and the output data is the notification message sent to the user's terminal.

[0127] Step 11:

[0128] The user terminal displays the results of the loan process received from the server to the user. The user confirms the message "Loan complete" on the screen. The input data is a notification message in JSON format sent from the server, and the output data is the message displayed to the user.

[0129] (Application Example 1)

[0130] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0131] In logistics centers and inventory management systems, the process of checking inventory status and lending items was cumbersome, leading to decreased work efficiency. In particular, manual inventory checks and lending procedures were time-consuming and prone to human error. Furthermore, the inability of on-site workers to quickly search for and lend items resulted in overall reduced work efficiency.

[0132] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0133] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for checking inventory based on the user's loan request and determining whether or not to lend the items; means for requesting processing from the external database to confirm the loan of items that have become available for loan; means for returning the loan processing results to the user terminal; a terminal equipped with a reader for scanning the barcodes of the items; and means for transmitting the information acquired by the reader to the server. This makes it possible for field workers to efficiently check inventory and perform loan procedures via a smartphone application.

[0134] An "external database" is a data storage location located outside the system, where inventory information about goods is stored and provided.

[0135] "Means for obtaining inventory status" refers to a device or method for a server to access an external database and retrieve inventory data of stored items.

[0136] A "user terminal" is a device used by a user to operate, and can take the form of a smartphone, personal computer, or other similar device.

[0137] "Items requested for loan" refers to items in stock that a user wishes to borrow.

[0138] "Means of inquiry" refers to a device or method that transmits information such as inventory checks or loan requests from a user terminal to a server.

[0139] "Means for analyzing inventory data" refers to a device or method for processing and interpreting acquired inventory information and deriving the necessary results.

[0140] "Means for determining whether an item can be lent" refers to a device or method for determining whether an item can be lent based on inventory information and the user's lending request.

[0141] "Means for confirming a loan" refers to a device or method for updating an external database for items whose loan has been approved.

[0142] "Means for returning the loan processing results" refers to a device or method for notifying the user terminal of the final loan status.

[0143] A "barcode reader for scanning items" is a device that reads barcodes attached to items and electronically acquires that information.

[0144] "Means for sending to the server" refers to a device or method for sending information acquired by a reading device to a server.

[0145] The system for implementing this invention is designed to improve the efficiency of inventory checking and item lending in logistics centers. The entire system consists of an external database, a server, user terminals (e.g., smartphones), and barcode readers.

[0146] This system is used by users to check the inventory status of items at the logistics center and to proceed with lending procedures as needed. The system includes the following methods:

[0147] 1. User Terminal: A user terminal is a portable information device such as a smartphone, equipped with an interface for the user to operate the system. The terminal is equipped with a reader for scanning barcodes of items. On this terminal, the user can input the items they wish to borrow and their quantities.

[0148] 2. Server: The server receives requests sent from user terminals and mediates access to external databases. Specifically, it performs the following functions:

[0149] Retrieving inventory status from an external database: The server accesses an external database via an API to retrieve inventory data for items.

[0150] Data Analysis: The acquired inventory data is analyzed and returned to the user's terminal. This analysis includes inventory quantity and loan availability.

[0151] Loan Decision and Confirmation: Based on the user's loan request, inventory is reconfirmed and a decision is made regarding loan eligibility. Then, the external database is updated to record that the loan has been confirmed. This result is also returned to the user's terminal.

[0152] Let's explain the operation of this system using an example. For instance, if a field worker wants to check the inventory status of an "iPad Pro," they open the app on their smartphone, type "iPad Pro," and scan the product with a barcode reader. This information is sent to the server, which retrieves the necessary inventory data from an external database and returns the analysis results to the terminal. If the user wants to borrow one of those products, they enter this into the app and send another request to the server. The server checks the inventory and notifies the user that it is available for loan. After the user confirms the loan, the server updates the external database and returns the processing results to the user's terminal.

[0153] This system will enable on-site workers at logistics centers to efficiently check inventory and process loans.

[0154] Examples of prompts to input into a generative AI model:

[0155] Prompt: Develop an inventory management system application for a logistics center. The following conditions must be met:

[0156] Check the inventory status of items

[0157] Convenient lending procedures

[0158] Improve the work efficiency of on-site workers

[0159] This prompt can provide guidance for building a system that allows field workers to efficiently check inventory and complete lending procedures via a smartphone app.

[0160] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0161] Step 1:

[0162] The user enters the item(s) whose stock status they want to check on their smartphone and scans the item's barcode. The input data includes the item name and barcode information, which is then sent to the server.

[0163] Step 2:

[0164] The server receives item name and barcode information sent from the user terminal and sends a request for inventory status to an external database. The input data includes item name and barcode information, which is used to call the external database API.

[0165] Step 3:

[0166] An external database receives requests from the server and returns inventory data for the specified item. The input data includes the item name, and the output data is the inventory quantity of that item.

[0167] Step 4:

[0168] The server analyzes inventory data retrieved from an external database and returns the results to the user's terminal. The input data is the inventory quantity, which the server analyzes and returns in a user-friendly format. The output data contains information related to the inventory quantity.

[0169] Step 5:

[0170] The user enters the items they wish to borrow and the quantity via their smartphone. This input data, including the item name and the desired quantity, is also sent to the server.

[0171] Step 6:

[0172] The server receives the user's loan request data and checks the inventory status again against an external database. The input data includes the item name and the requested quantity, and the server calls the external database API to check the inventory.

[0173] Step 7:

[0174] The server reconfirms the inventory status and determines whether the item is available for loan. The input data includes the item name, the desired loan quantity, and the latest inventory quantity. Based on this data, the server determines whether the item is available for loan and outputs this information as output data.

[0175] Step 8:

[0176] The system notifies the user terminal that the server is available for use. At this time, it returns information indicating that the server is available for use as notification data to the user terminal.

[0177] Step 9:

[0178] The user confirms the loan using their smartphone. This input data includes information confirming the loan and is sent to the server.

[0179] Step 10:

[0180] The server receives a user's loan confirmation request and requests an external database to update the loan information. The input data is the item name and loan quantity, and an API is called to update the external database and reduce the inventory quantity.

[0181] Step 11:

[0182] The server returns the loan processing result to the user terminal. The final output data is information indicating that the loan has been completed, and this is notified to the user terminal.

[0183] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0184] The system of this invention combines a user emotion recognition engine with conventional inventory management and lending procedures to further enhance them. The specific flow of this process is described below.

[0185] 1. The user operates the terminal and enters the item whose inventory status they want to check. The terminal uses an emotion engine to analyze the user's emotions and sends an inventory status inquiry request to the server based on the user's input.

[0186] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. The server calls the external database's API to retrieve the inventory data.

[0187] 3. When the server analyzes the inventory data it has acquired and returns the results to the user's terminal, it generates a customized message based on the analysis results of the sentiment engine. For example, it notifies the user of the information "There are 10 iPad Pros in stock" in a tone optimized based on sentiment analysis.

[0188] 4. The user operates the terminal and enters the items they wish to borrow and their quantities. The terminal also runs an emotion engine to analyze the user's emotional state. Based on the user's input, the terminal sends a "loan request" to the server.

[0189] 5. When the server receives a loan request, it uses feedback from the emotion engine to optimize the loan decision. For example, if the user is in a state of impatience, the system will provide quick and easy-to-understand feedback.

[0190] 6. The server reconfirms the inventory status and determines whether the loan request is feasible. If there is sufficient inventory, the server determines that it is "available" and sends a message optimized by the emotion engine to the terminal.

[0191] 7. When a user confirms a loan on their device, the emotion engine is used to display the most appropriate confirmation message. The device then sends a "loan confirmation request" to the server.

[0192] 8. The server receives the request and sends an API request to the external database to perform the lending process. The processing result is returned to the terminal, and an optimized feedback message is conveyed to the user based on the analysis results of the emotion engine.

[0193] 9. Finally, when the user checks the loan completion status on their device, the emotion engine optimizes the displayed content to support the user in proceeding with confidence.

[0194] Specific example:

[0195] Example 1:

[0196] The user types "I want to check the availability of iPad Pro" on their device. The device uses an emotion engine to recognize the user's emotional state and sends a request to the server saying, "Yes, you are looking for an iPad Pro. We currently have 10 in stock." The server connects to an external database and retrieves the inventory data. After confirming that there are 10 in stock, the server sends an emotion-optimized message to the device.

[0197] The user types, "I'd like to borrow one iPad Pro." The device uses an emotion engine to recognize the user's emotional state and confirms, "So you'd like to borrow one iPad Pro, is that correct?" The device sends a request to the server. The server checks its inventory, determines that there is sufficient stock and that it is available for loan, and sends an optimized message to the device saying, "One iPad Pro is available for loan."

[0198] The user performs the "Confirm Loan" action. The device sends a request to the server. The server connects to an external database, confirms the loan process, and sends a "Loan Complete" message. The emotion engine analyzes this result and provides appropriate feedback to the user.

[0199] Thus, the system of the present invention recognizes the user's emotions and provides optimal feedback based on them, thereby improving the user experience and enabling efficient and accurate inventory management and lending procedures.

[0200] The following describes the processing flow.

[0201] Step 1:

[0202] The user operates the device and enters the item whose inventory status they want to check (e.g., "iPad Pro"). The device prepares to send an inventory status inquiry request to the server based on the entered information. Simultaneously, it activates an emotion engine to analyze the user's emotional state from their facial expressions and voice.

[0203] Step 2:

[0204] The device sends an inventory status inquiry request to the server based on the emotion engine's analysis results. This request includes reassuring wording for the user. For example, if the system detects the user is anxious, a message such as "We'll check immediately, please wait a moment" will be displayed.

[0205] Step 3:

[0206] The server receives the request, connects to an external database API, and sends a request asking, "Please tell me the availability of iPad Pros."

[0207] Step 4:

[0208] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[0209] Step 5:

[0210] The server analyzes the received data and converts it into a user-friendly format. During this process, it considers the results of the emotion engine's analysis and generates a message with an appropriate tone. For example, "Don't worry, we have 10 iPad Pros in stock."

[0211] Step 6:

[0212] The server returns a response to the device containing the analysis results. Based on the data received by the device, it displays to the user, "We have 10 iPad Pros in stock." An emotion engine is used to optimize the display method and tone.

[0213] Step 7:

[0214] The user operates the device and enters "I would like to borrow one iPad Pro." The device then sends a "loan request" to the server based on this input and the user's sentiment analysis results.

[0215] Step 8:

[0216] The server receives the request and re-checks the inventory data. The server checks whether "there are 10 iPad Pros in stock and they are available for loan."

[0217] Step 9:

[0218] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan." At this point, the emotion engine is used again to provide feedback tailored to the user's emotional state.

[0219] Step 10:

[0220] The user operates the terminal and enters "Confirm Loan". The terminal displays a message based on the results of the emotion engine's analysis. For example, "Please wait with peace of mind. We are confirming the loan process."

[0221] Step 11:

[0222] The device sends a request to the server stating, "I confirm the loan of one iPad Pro."

[0223] Step 12:

[0224] The server receives the request and sends an API request to the external database to execute the lending process. If the process is successful, the external database returns a "lending successful" response to the server.

[0225] Step 13:

[0226] The server returns a "loan successful" result to the device. At this time, the emotion engine generates an appropriate feedback message based on the analysis results. For example, "Your iPad Pro loan is complete. Please use it."

[0227] Step 14:

[0228] The user confirms the loan completion status on their device. The emotion engine analyzes the results and supports the user so that they can confidently proceed to the next step.

[0229] (Example 2)

[0230] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0231] In modern resource management systems, efficient and accurate inventory checks and lending procedures are crucial. However, traditional systems often fail to adequately improve the user experience because they do not consider user emotions. Furthermore, they may not accurately reflect the actual status during inventory checks and lending processes. This can result in user dissatisfaction and confusion.

[0232] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the inventory status of multiple resources from an external database, means for identifying the resource requested for borrowing from the user terminal and querying its inventory status, means for analyzing the acquired inventory data and returning the analysis results to the user terminal, means for checking inventory based on the borrowing request from the user and determining whether borrowing is possible, means for requesting processing from the external database to confirm the borrowing of the resource that has become available for borrowing, means for returning the borrowing processing results to the user terminal, and means for analyzing the user's emotions and optimizing the message based on the analysis results. This makes it possible to perform efficient and accurate inventory confirmation and lending processing while taking the user's emotions into consideration.

[0233] An "external database" is a data storage system located remotely that holds and manages information about specific resources.

[0234] "Resources" refer to items or services managed by the system that users wish to access or borrow.

[0235] "Inventory status" refers to data that shows the current number and condition of resources, and represents information about how much of those resources are available.

[0236] A "user terminal" is a device, such as a computer or smartphone, that a user uses to access a system and perform input or output.

[0237] "Borrowing request" refers to a user requesting the system to use a specific resource for a certain period of time.

[0238] An "emotion engine" is a software module that analyzes a user's emotional state and optimizes messages based on the analysis results.

[0239] "Optimizing a message" means adjusting the tone and content of a message to be appropriate and effective based on the user's emotional state.

[0240] "Borrowing process" refers to a series of operations in which the system accepts a borrowing request from a user, updates an external database, and confirms the borrowing.

[0241] The system of the present invention incorporates an emotion engine to provide optimal feedback based on the user's emotions in order to streamline resource management and borrowing procedures. The following describes how the system of the present invention is specifically implemented.

[0242] This system consists of user terminals, servers, and an external database. The user terminals incorporate an interface for receiving user input and an emotion engine for analyzing emotions.

[0243] For the emotion engine, generally available emotion analysis software, such as "IBM Watson® Emotion Analysis," can be used. For the external database, database servers such as "AWS® RDS" or "MySQL®" can be used to manage inventory and borrowing data.

[0244] The device receives input from the user and analyzes its contents. When the user enters information about a resource they want to check, the emotion engine analyzes the user's emotions and sends the results to the server. An example of a prompt message in this case might be, "I want to check the availability of iPad Pros."

[0245] The server receives this request, connects to an external database, and retrieves inventory data. For example, if the retrieved inventory data shows "10 iPad Pros in stock," it analyzes this information, generates a message optimized by the emotion engine, and returns it to the device. This message is returned in a tone based on the user's emotional state.

[0246] For example, if a user enters "I want to check the stock status of iPad Pro" and the emotion engine analyzes the emotion as "certainty," the server will send a message to the device saying "There are currently 10 iPad Pros in stock" based on the data it has acquired.

[0247] Next, when the user types "I'd like to borrow an iPad Pro," the emotion engine similarly analyzes the user's emotions and generates a confirmation message such as "So you'd like to borrow an iPad Pro?". The borrowing request is then sent to the server. The server re-checks the inventory and uses the emotion engine to provide the user with the most appropriate feedback.

[0248] For example, if there is sufficient stock, the server generates a message saying "One iPad Pro is available for loan" and sends it to the device. When the user confirms the loan, the request is sent to the server, which connects to the external database again and performs the loan process. A message saying "Loan complete" is generated in the appropriate tone and returned to the user.

[0249] This ensures users always receive optimal feedback, and streamlines resource management and borrowing procedures.

[0250] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0251] Step 1:

[0252] The user operates the device and enters information about the resource they want to check (e.g., "iPad Pro"). When the user clicks the "Inventory Search" button and enters "iPad Pro" into the input form, this input data becomes the input data for the next processing step on the device.

[0253] Step 2:

[0254] When the terminal receives user input, it analyzes the user's emotions using its built-in emotion engine (e.g., "IBM Watson Emotion Analysis"). As a result of this analysis, an emotional state (e.g., "confident") is output. Next, the terminal generates a request containing this emotion analysis result and the resource information entered by the user, and sends it to the server.

[0255] Input: Resource information entered by the user: "iPad Pro"

[0256] Data processing: Emotional analysis using an emotion engine

[0257] Output: Request containing "confident" status and resource information (e.g., in JSON format {"item":"iPad Pro", "userEmotion":"confident"})

[0258] Step 3:

[0259] The server receives the request sent from the terminal. Next, it connects to an external database (e.g., "AWS RDS" or "MySQL") and retrieves inventory data for the specified resource. For example, it executes the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and retrieves data indicating that there are 10 units in stock.

[0260] Input: Request data from the terminal

[0261] Data processing: Queries to external databases (execution of SQL queries)

[0262] Output: Inventory data for "iPad Pro" (e.g., "10 units in stock")

[0263] Step 4:

[0264] The server analyzes the inventory data it acquires and uses this data to generate an optimized message using an emotion engine. The tone of this message is adjusted based on the user's emotional state (e.g., "confident"). For example, it might generate a message saying, "We currently have 10 iPad Pros in stock," and send it to the device.

[0265] Input: Inventory data and sentiment analysis data

[0266] Data processing: Message generation and emotion-based tone optimization

[0267] Output: Optimized message (e.g., "We currently have 10 iPad Pros in stock")

[0268] Step 5:

[0269] The terminal receives a message from the server and displays it to the user. The user reviews it and prepares to perform the next action.

[0270] Input: Optimized message from the server

[0271] Output: Display to the user

[0272] Step 6:

[0273] The user operates the terminal to input the resource to be borrowed (e.g., "iPad Pro") and its quantity (e.g., "1 unit"). The user clicks the "Borrow" button and inputs "1" as the quantity.

[0274] Step 7:

[0275] The terminal uses the emotion engine again to analyze the user's emotion. A request containing this analysis result (e.g., "expectation") and the user's input data is sent to the server.

[0276] Input: Resource information and quantity input by the user

[0277] Data processing: Re - analysis by the emotion engine

[0278] Output: A request containing the emotional state, resource information, and quantity (e.g., in JSON format {"item":"iPad Pro", "quantity":1, "userEmotion":"hopeful"})

[0279] Step 8:

[0280] The server receives this request, reconnects to the external database to check the inventory data. Executes the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and determines whether borrowing is possible based on the result. For example, if there is sufficient inventory, the server determines that "borrowing is possible".

[0281] Input: Request data from the terminal

[0282] Data calculation: Query to the external database (execution of SQL query)

[0283] Output: Re - verified inventory data and borrowing availability judgment

[0284] Step 9:

[0285] Based on the inventory data reconfirmed by the server, generate a message optimized by the emotion engine. For example, generate a message like "One iPad Pro is available for borrowing" and send it to the terminal.

[0286] Input: Reconfirmed inventory data and sentiment analysis data

[0287] Data processing: Message generation and optimization based on emotion

[0288] Output: Optimized message (e.g., "One iPad Pro is available for borrowing")

[0289] Step 10:

[0290] The terminal displays this message to the user, and the user operates "Confirm borrowing".

[0291] Input: Optimized message from the server

[0292] Output: Display to the user and user operation

[0293] Step 11:

[0294] The terminal receives the "Confirm borrowing" operation, analyzes it again with the emotion engine, and sends a borrowing confirmation request to the server together with the result.

[0295] Input: User's "Confirm borrowing" operation

[0296] Data processing: Re - analysis by the emotion engine and request generation

[0297] Output: Request to the server (e.g., in JSON format {"action":"confirmLoan", "item":"iPad Pro", "quantity":1, "userEmotion":"relieved"})

[0298] Step 12:

[0299] The server receives this request and executes a borrowing process on the external database. It executes the SQL query "UPDATE inventory SET stock = stock - 1 WHERE item = 'iPad Pro';" and returns the result to the terminal. For example, it generates a message like "The borrowing is completed", optimizes it with the emotion engine, and sends it to the terminal.

[0300] Input: Request data from the terminal

[0301] Data calculation: Update query to the external database (execution of SQL query)

[0302] Output: Borrowing result and optimized message (e.g., "The borrowing is completed")

[0303] Step 13:

[0304] The terminal displays this message to the user, providing a sense of security to the user.

[0305] Input: Optimized message from the server

[0306] Output: Display to the user

[0307] In this way, the system can consider the user's emotions and perform efficient and accurate inventory checking and borrowing processes.

[0308] (Application Example 2)

[0309] Next, Application Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0310] Traditional inventory management and lending systems often failed to flexibly adapt to user emotions and usage patterns, resulting in a uniform processing approach that sometimes compromised the user experience. Furthermore, while there was a need for methods to process inventory information and lending procedures quickly and accurately, there was a lack of ingenuity in improving user satisfaction.

[0311] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0312] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for using an emotion engine to analyze the user's emotions and generating an optimized feedback message based on the emotion analysis results; means for checking inventory based on the user's loan request and determining whether or not to lend the item; means for requesting processing from the external database to confirm the loan of items that have become available for loan; and means for returning the loan processing results to the user terminal and displaying an optimized feedback message based on the emotion analysis results. This makes it possible to provide optimal feedback that reflects the user's emotions, improve the user experience, and realize efficient and accurate inventory management and loan procedures.

[0313] - An "external database" is a database accessible via the internet or a company's internal network, where inventory information and other related data are stored. In most cases, data is retrieved and updated via APIs.

[0314] "Inventory status" refers to the current stock quantity of a particular item and related information. For example, it includes information such as how many units are in stock, which warehouse they are in, and whether they are out of stock.

[0315] A "user terminal" is a device used by a user to operate the system, and includes personal computers, smartphones, tablets, and smart glasses. Through these terminals, users access the system and perform operations.

[0316] "Items requested for loan" refers to items that a user wishes to borrow for a specific period. This includes all items available for loan, such as books, electronic devices, and tools.

[0317] An "emotion engine" is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions. This allows it to recognize the user's current emotional state, such as joy, sadness, or anxiety.

[0318] A "feedback message" is information or a notification that the system provides to the user, and it is an optimized message based on the results of sentiment analysis. For example, it may include information on the availability of an item or the possibility of it being available for loan.

[0319] The "means for determining lending eligibility" refer to a system that receives a user's lending request and checks whether it is feasible. The decision is made considering factors such as inventory status, the user's lending history, and other lending requests.

[0320] "Methods for requesting processing from an external database" refer to methods in which the server calls the API of an external database to perform tasks such as updating inventory or recording loans.

[0321] "Loan processing result" refers to the result of the system's processing in response to a user's loan request, and includes information such as whether the loan was completed and whether the inventory was updated.

[0322] This invention is a system that combines an emotion engine that analyzes user emotions to efficiently and user-friendly manage inventory and lending procedures. The following describes in detail specific embodiments of this invention.

[0323] Hardware and software configuration

[0324] This system includes user terminals, a server, and an external database. It also incorporates an emotion engine for analyzing user emotions. User terminals are devices such as smartphones and smart glasses, which allow users to access and operate the system.

[0325] The role of the emotional engine

[0326] An emotion engine is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions, recognizing the emotional state the user is currently experiencing, such as joy, sadness, or anxiety. Specifically, it uses cameras and microphones built into smart glasses to collect and analyze the user's emotional data in real time.

[0327] Processing flow

[0328] 1. When the user terminal inputs the item whose inventory status they wish to check, the terminal uses an emotion engine to analyze the user's emotions. At this point, it sends an inventory status inquiry request to the server based on the user's input.

[0329] 2. The server connects to an external database to retrieve the inventory status of items. The retrieved inventory data is analyzed by the server, and an optimized feedback message is generated based on the analysis results of the emotion engine.

[0330] 3. The inventory status is returned to the user's terminal, and a feedback message is displayed. For example, if the user is anxious, a message such as "We have plenty of stock, so please rest assured" will be displayed.

[0331] Loan procedures

[0332] 1. When a user enters the item they wish to borrow, the user terminal uses the emotion engine again to analyze the user's emotions and sends a borrowing request to the server based on that information.

[0333] 2. The server reconfirms the inventory status and determines whether or not to lend the item. If there is sufficient inventory, a feedback message such as "Available for loan" is optimized based on the analysis results of the emotion engine and sent to the user's terminal.

[0334] 3. Once the user confirms the loan, the server updates the loan information in the external database and returns the loan processing result to the user's terminal. Here again, the emotion engine generates the most appropriate feedback message according to the user's emotional state.

[0335] Specific example

[0336] As a concrete example, consider a scenario where a user is wearing smart glasses and types, "Please tell me the availability of iPad Pros." In this case, the emotion engine detects the user's state of tension from their facial expression and displays a message such as, "We have 10 units in stock, so please don't worry." Similarly, if the user types, "I would like to borrow an iPad Pro," the emotion engine will provide optimal feedback based on its analysis results.

[0337] Example of a prompt

[0338] "When a user asks about the availability of an item, generate a feedback message that reflects their emotional state. For example, if they are feeling stressed, use a message that will ease their tension."

[0339] As described above, the system of the present invention uses an emotion engine to provide optimal feedback in response to the user's emotions, thereby improving the user experience and achieving efficient inventory management and lending procedures.

[0340] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0341] Step 1:

[0342] The user inputs the items whose inventory status they wish to check using voice or an input device on a smart glasses or smartphone. The device recognizes the user's input and analyzes the user's emotions using an emotion engine. This process retrieves both the user's input and the emotion analysis results.

[0343] Input: The name of the item the user wants to check and sentiment data from the sentiment engine.

[0344] Output: User input and sentiment analysis results

[0345] Step 2:

[0346] The terminal sends an inventory status inquiry request to the server based on the acquired data. The server connects to an external database and sends an API request to retrieve the inventory status of the items.

[0347] Input: User input and sentiment analysis results

[0348] Output: Inventory status query request to external database

[0349] Step 3:

[0350] The server analyzes inventory data retrieved from an external database and returns it to the user's terminal. At this time, it generates an optimized feedback message based on the analysis results of the emotion engine.

[0351] Input: Inventory data retrieved from an external database

[0352] Data processing: Combining inventory data with sentiment analysis results for analysis.

[0353] Output: Feedback message to send to the user's terminal

[0354] Step 4:

[0355] The user receives a feedback message and re-enters the items they wish to borrow. The terminal uses the emotion engine again to analyze the user's emotions and sends the borrowing request to the server.

[0356] Input: User's loan preferences and sentiment data

[0357] Output: Loan request to send to the server

[0358] Step 5:

[0359] The server receives the loan request and rechecks the inventory status. If there is sufficient inventory, it determines whether to grant the loan and generates an optimized feedback message based on the analysis results of the emotion engine.

[0360] Input: User loan requests and sentiment data

[0361] Data processing: Reconfirming inventory data and determining whether items are available for loan.

[0362] Output: Feedback message regarding loan availability.

[0363] Step 6:

[0364] Once the user confirms the loan, the server sends an API request to an external database to update the loan information. The result of the loan process is returned to the server, and a feedback message optimized by the emotion engine is sent again to the user's device.

[0365] Input: User loan confirmation operation and sentiment data

[0366] Output: Loan information update request to external database and feedback message of loan processing result.

[0367] Step 7:

[0368] The user receives a final feedback message, and the lending process is completed. The emotion engine is used to re-analyze the user's emotions and support them in confidently moving on to the next step.

[0369] Input: Loan processing results and sentiment data

[0370] Output: Final feedback message to the user

[0371] Through each of the above steps, the system of the present invention provides optimal feedback based on the user's emotions, improving the user experience and achieving efficient inventory management and lending procedures.

[0372] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0373] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0374] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0375] [Second Embodiment]

[0376] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0377] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0378] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0379] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0380] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0381] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0382] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0383] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0384] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0385] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0386] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0387] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0388] The system of the present invention allows users to easily check the inventory status of items and make loans by performing the following processes.

[0389] 1. The user operates the terminal and enters the name of the item whose stock status they wish to check. This input triggers the terminal to send a request to the server to inquire about the stock status.

[0390] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. Specifically, the server calls the external database's API to retrieve inventory data.

[0391] 3. The server analyzes the inventory data it has acquired and returns the results to the user's terminal. For example, it might notify the user that "there are 10 iPad Pros in stock."

[0392] 4. The user operates the terminal and enters the items and quantities they wish to borrow. This input triggers the terminal to send a borrowing request to the server.

[0393] 5. The server checks the inventory status again and determines whether the loan request can be fulfilled. If there is sufficient inventory, the server notifies the user that the loan is available.

[0394] 6. The user confirms the loan on the terminal. The terminal sends a loan confirmation request to the server.

[0395] 7. The server receives the loan confirmation request and requests the external database to process the loan. The server uses the external database's API to update the inventory information and record that the loan has been made.

[0396] 8. Finally, the server returns the loan processing result to the user's terminal, and the user confirms that the loan is complete.

[0397] Specific example:

[0398] Example 1:

[0399] The user types "I want to check the availability of iPad Pro" on their device. The device sends a request to the server. The server connects to an external database, retrieves the information that "there are 10 iPad Pros in stock," parses it, and returns it to the device. The user then types "I want to borrow one iPad Pro." The device sends a request to the server. The server checks the inventory, determines that it is "available," and notifies the device. The user clicks "Confirm Loan." The device sends a request to the server. The server connects to an external database, updates the inventory, and confirms the loan process. The server notifies the device that "the loan is complete," and the user confirms.

[0400] This system allows users to efficiently and accurately check the inventory status of items and proceed with the lending process.

[0401] The following describes the processing flow.

[0402] Step 1:

[0403] The user operates the device and enters the item whose stock status they want to check (e.g., "iPad Pro"). The device then sends a request to the server to inquire about the stock status based on the entered information.

[0404] Step 2:

[0405] The device sends an API request to the server with the content "Item: Please tell me the stock status of iPad Pro".

[0406] Step 3:

[0407] The server receives the request and connects to the external database's API. At this time, the server sends an API request to the external database to "query the availability of iPad Pro."

[0408] Step 4:

[0409] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[0410] Step 5:

[0411] The server analyzes the received data and converts it into a user-friendly format. Specifically, it generates a message such as, "We have 10 iPad Pros in stock."

[0412] Step 6:

[0413] The server returns a response to the terminal containing the analysis results. It also sends data to the terminal stating, "We have 10 iPad Pros in stock."

[0414] Step 7:

[0415] The terminal displays the inventory status received from the server to the user. The user operates the terminal and enters, "I would like to borrow one iPad Pro."

[0416] Step 8:

[0417] The device sends a "request to lend one iPad Pro" to the server based on the user's input.

[0418] Step 9:

[0419] The server receives the request and checks the inventory data again. The server checks whether there are 10 iPad Pros in stock and available for loan.

[0420] Step 10:

[0421] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan."

[0422] Step 11:

[0423] The user operates the device and enters "Confirm Loan". The device sends a request to the server saying "Confirm loan of 1 iPad Pro".

[0424] Step 12:

[0425] The server receives the request and sends an API request to the external database to perform the lending process.

[0426] Step 13:

[0427] The external database executes the lending process and returns a "lending successful" response to the server. The server receives this response.

[0428] Step 14:

[0429] The server returns the loan success result to the user's device. It sends a message to the device saying, "iPad Pro loan complete."

[0430] Step 15:

[0431] The user checks the loan completion status on their device. The user understands that "the iPad Pro loan has been completed."

[0432] (Example 1)

[0433] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0434] Conventional inventory management and lending systems have made it difficult for users to quickly and accurately check inventory status and to complete lending procedures for multiple items. Furthermore, the process of determining lending eligibility and updating inventory information is time-consuming and inefficient. This invention aims to solve these problems and provide a system that allows users to efficiently and accurately check the inventory status of items and complete lending procedures.

[0435] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0436] In this invention, the server includes means for querying the inventory status of items entered from a user terminal, means for obtaining the inventory status of specified items from an external database, means for analyzing the obtained inventory data and returning the results to the user terminal, means for identifying the items and quantities of items requested for loan from the user terminal, means for reconfirming the inventory status based on the loan request and determining whether or not to loan the items, means for updating inventory information in the external database for items whose loan has been confirmed and recording the loan information, and means for returning the results of the loan process to the user terminal. This enables the user to efficiently and accurately check the inventory status of items and carry out loan procedures.

[0437] A "user terminal" is a device that a user operates to input information and that can access a server via a network.

[0438] An "external database" is an information management system that a server connects to to retrieve and update inventory status and loan information.

[0439] "Inventory status" refers to information indicating the quantity of a particular item that is stored.

[0440] "Method of inquiry" refers to the process by which a user's terminal sends a request to a server to retrieve information.

[0441] "Means of acquisition" refers to the process by which a server retrieves necessary data from an external database.

[0442] "Means of analysis" refers to the process by which a server processes acquired data and extracts the necessary information.

[0443] "Items requested for loan" refers to specific items that the user wishes to borrow.

[0444] "Quantity" refers to the specific number of items you wish to borrow.

[0445] The "means of determining eligibility" refers to the process by which the server checks for availability based on a rental request and decides whether or not it is possible to rent it out.

[0446] "Confirmation method" refers to the process by which the server formally records information about items that have been determined to be available for loan.

[0447] "Loan information" refers to detailed data about the items that have been borrowed and their quantities.

[0448] "Means of notification" refers to the process by which the server communicates the processing results to the user's terminal.

[0449] This invention provides a system that allows users to easily check the inventory status of items and efficiently carry out lending procedures. This system operates by coordinating a user terminal, a server, and an external database.

[0450] The user operates their device (e.g., computer, tablet, smartphone) to input the item whose inventory status they want to check. Based on this input, the device sends an inventory status inquiry request to the server. The server parses the received request, extracts the item name, calls an API to an external database, and retrieves the inventory status of the specified item.

[0451] For example, a user enters "Check iPad Pro stock availability" into their device and clicks the submit button. The device sends this input as an HTTP request to the server. The server retrieves the iPad Pro stock availability from an external database, parses the response "Stock Quantity: 10", converts it to JSON format, and returns it to the user's device.

[0452] Next, the user operates their terminal to enter the items they wish to borrow and the quantity. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The terminal then sends a loan request to the server based on this input. The server checks the inventory status again and determines whether the loan request is possible.

[0453] If the server determines that the device is available for loan, the user confirms the loan on their device. The user's action sends a loan confirmation request to the server. The server connects to an external database and sends an API request, " / update_inventory?item=ipad-pro&quantity=-1", to update the inventory information. This updates the inventory count from 10 to 9.

[0454] After the loan information update is complete, the server returns the loan processing result to the user's terminal. Finally, the user receives and confirms a "loan completed" notification on their terminal screen.

[0455] The entire system is efficiently designed, allowing users to complete everything from checking inventory status to loan procedures in a short amount of time. For example, a user might type "I want to check the inventory status of iPad Pros," and the device sends a request to the server. The server retrieves information from an external database, stating "There are 10 iPad Pros in stock," analyzes it, and returns it to the device. Then, the user might type "I want to borrow one iPad Pro," and the server checks the inventory and notifies the user that it is "available." The user confirms the loan, the server connects to the external database to update the inventory, and confirms the loan process. Finally, the server notifies the device that "the loan is complete," and the user confirms it.

[0456] As described above, the present invention provides a system that allows users to efficiently and accurately check the inventory status of items and carry out lending procedures.

[0457] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0458] Step 1:

[0459] The user operates the device and enters the item whose stock status they want to check. Specifically, the user enters "Check iPad Pro stock status" into the device's interface (e.g., a form) and clicks the submit button. The input data is the item name "iPad Pro". As output, the device sends this input content to the server as an HTTP request.

[0460] Step 2:

[0461] The server parses the request received from the terminal. Specifically, the server extracts the item name (e.g., "iPad Pro"). The input data is the HTTP request sent from the terminal, and the output data is the extracted item name. The server then calls an API of an external database to retrieve the item's inventory status. The API call format is " / inventory?item=ipad-pro". The output is the inventory count, which is "10".

[0462] Step 3:

[0463] The server analyzes the acquired inventory data and generates data to be returned to the user's terminal. Specifically, the server converts information such as "There are 10 iPad Pros in stock" into JSON format (e.g., "{ 'item': 'iPad Pro', 'stock': 10}"). The input data is inventory information acquired from an external database, and the output data is the JSON formatted data after analysis. This data is sent to the user's terminal as an HTTP response.

[0464] Step 4:

[0465] The user terminal displays the received inventory information to the user. Specifically, the terminal screen will display "10 iPad Pro units in stock." The input data is inventory information in JSON format sent from the server, and the output data is the inventory information displayed to the user.

[0466] Step 5:

[0467] The user operates the terminal and enters the item and quantity they wish to borrow. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The input data consists of the item name and quantity, and the terminal sends this as a loan request to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1}".

[0468] Step 6:

[0469] The server analyzes the loan request received from the terminal and reconnects to the external database to check the inventory status. The input data is the loan request (item name and quantity), and the output data is the inventory information retrieved again. Specifically, the server confirms that there are 10 iPad Pro units in stock and determines that it is possible to loan the iPad Pro because the requested loan quantity (1 unit) is within the available stock.

[0470] Step 7:

[0471] The server notifies the user terminal of the result of its determination that the item is available for loan. Specifically, it generates a "available for loan" message in JSON format (e.g., "{ 'status': 'possible'}") and sends it as an HTTP response. The input data is the determination result that the item is available for loan, and the output data is the notification message sent to the user terminal.

[0472] Step 8:

[0473] The user confirms the loan on the device. Specifically, the user clicks the "Confirm Loan" button. The input data is the user's confirmation action, and the output is a loan confirmation request sent to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1, 'action': 'confirm'}".

[0474] Step 9:

[0475] The server receives a loan confirmation request, updates the inventory information in an external database, and records the loan information. Specifically, it executes the API call " / update_inventory?item=ipad-pro&quantity=-1" to update the inventory count from 10 to 9. The input data is the loan confirmation request and the current inventory information, and the output data is the updated inventory information.

[0476] Step 10:

[0477] The server returns the result of the loan process to the user's terminal. Specifically, it generates a message indicating "loan completed" in JSON format (e.g., "{ 'status': 'completed'}") and sends it as an HTTP response. The input data is the result of the loan process, and the output data is the notification message sent to the user's terminal.

[0478] Step 11:

[0479] The user terminal displays the results of the loan process received from the server to the user. The user confirms the message "Loan complete" on the screen. The input data is a notification message in JSON format sent from the server, and the output data is the message displayed to the user.

[0480] (Application Example 1)

[0481] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0482] In logistics centers and inventory management systems, the process of checking inventory status and lending items was cumbersome, leading to decreased work efficiency. In particular, manual inventory checks and lending procedures were time-consuming and prone to human error. Furthermore, the inability of on-site workers to quickly search for and lend items resulted in overall reduced work efficiency.

[0483] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0484] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for checking inventory based on the user's loan request and determining whether or not to lend the items; means for requesting processing from the external database to confirm the loan of items that have become available for loan; means for returning the loan processing results to the user terminal; a terminal equipped with a reader for scanning the barcodes of the items; and means for transmitting the information acquired by the reader to the server. This makes it possible for field workers to efficiently check inventory and perform loan procedures via a smartphone application.

[0485] An "external database" is a data storage location located outside the system, where inventory information about goods is stored and provided.

[0486] "Means for obtaining inventory status" refers to a device or method for a server to access an external database and retrieve inventory data of stored items.

[0487] A "user terminal" is a device used by a user to operate, and can take the form of a smartphone, personal computer, or other similar device.

[0488] "Items requested for loan" refers to items in stock that a user wishes to borrow.

[0489] "Means of inquiry" refers to a device or method that transmits information such as inventory checks or loan requests from a user terminal to a server.

[0490] "Means for analyzing inventory data" refers to a device or method for processing and interpreting acquired inventory information and deriving the necessary results.

[0491] "Means for determining whether an item can be lent" refers to a device or method for determining whether an item can be lent based on inventory information and the user's lending request.

[0492] "Means for confirming a loan" refers to a device or method for updating an external database for items whose loan has been approved.

[0493] "Means for returning the loan processing results" refers to a device or method for notifying the user terminal of the final loan status.

[0494] A "barcode reader for scanning items" is a device that reads barcodes attached to items and electronically acquires that information.

[0495] "Means for sending to the server" refers to a device or method for sending information acquired by a reading device to a server.

[0496] The system for implementing this invention is designed to improve the efficiency of inventory checking and item lending in logistics centers. The entire system consists of an external database, a server, user terminals (e.g., smartphones), and barcode readers.

[0497] This system is used by users to check the inventory status of items at the logistics center and to proceed with lending procedures as needed. The system includes the following methods:

[0498] 1. User Terminal: A user terminal is a portable information device such as a smartphone, equipped with an interface for the user to operate the system. The terminal is equipped with a reader for scanning barcodes of items. On this terminal, the user can input the items they wish to borrow and their quantities.

[0499] 2. Server: The server receives requests sent from user terminals and mediates access to external databases. Specifically, it performs the following functions:

[0500] Retrieving inventory status from an external database: The server accesses an external database via an API to retrieve inventory data for items.

[0501] Data Analysis: The acquired inventory data is analyzed and returned to the user's terminal. This analysis includes inventory quantity and loan availability.

[0502] Loan Decision and Confirmation: Based on the user's loan request, inventory is reconfirmed and a decision is made regarding loan eligibility. Then, the external database is updated to record that the loan has been confirmed. This result is also returned to the user's terminal.

[0503] Let's explain the operation of this system using an example. For instance, if a field worker wants to check the inventory status of an "iPad Pro," they open the app on their smartphone, type "iPad Pro," and scan the product with a barcode reader. This information is sent to the server, which retrieves the necessary inventory data from an external database and returns the analysis results to the terminal. If the user wants to borrow one of those products, they enter this into the app and send another request to the server. The server checks the inventory and notifies the user that it is available for loan. After the user confirms the loan, the server updates the external database and returns the processing results to the user's terminal.

[0504] This system will enable on-site workers at logistics centers to efficiently check inventory and process loans.

[0505] Examples of prompts to input into a generative AI model:

[0506] Prompt: Develop an inventory management system application for a logistics center. The following conditions must be met:

[0507] Check the inventory status of items

[0508] Convenient lending procedures

[0509] Improve the work efficiency of on-site workers

[0510] This prompt can provide guidance for building a system that allows field workers to efficiently check inventory and complete lending procedures via a smartphone app.

[0511] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0512] Step 1:

[0513] The user enters the item(s) whose stock status they want to check on their smartphone and scans the item's barcode. The input data includes the item name and barcode information, which is then sent to the server.

[0514] Step 2:

[0515] The server receives item name and barcode information sent from the user terminal and sends a request for inventory status to an external database. The input data includes item name and barcode information, which is used to call the external database API.

[0516] Step 3:

[0517] An external database receives requests from the server and returns inventory data for the specified item. The input data includes the item name, and the output data is the inventory quantity of that item.

[0518] Step 4:

[0519] The server analyzes inventory data retrieved from an external database and returns the results to the user's terminal. The input data is inventory quantity, which the server analyzes and returns in a user-friendly format. The output data contains information related to inventory quantity.

[0520] Step 5:

[0521] The user enters the items they wish to borrow and the quantity via their smartphone. This input data, including the item name and the desired quantity, is also sent to the server.

[0522] Step 6:

[0523] The server receives the user's loan request data and checks the inventory status again against an external database. The input data includes the item name and the requested quantity, and the server calls the external database API to check the inventory.

[0524] Step 7:

[0525] The server reconfirms the inventory status and determines whether the item is available for loan. The input data includes the item name, the desired loan quantity, and the latest inventory quantity. Based on this data, the server determines whether the item is available for loan and outputs this information as output data.

[0526] Step 8:

[0527] The system notifies the user terminal that the server is available for use. At this time, it returns information indicating that the server is available for use as notification data to the user terminal.

[0528] Step 9:

[0529] The user confirms the loan using their smartphone. This input data includes information confirming the loan and is sent to the server.

[0530] Step 10:

[0531] The server receives a user's loan confirmation request and requests an external database to update the loan information. The input data is the item name and loan quantity, and an API is called to update the external database and reduce the inventory quantity.

[0532] Step 11:

[0533] The server returns the loan processing result to the user terminal. The final output data is information indicating that the loan has been completed, and this is notified to the user terminal.

[0534] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0535] The system of this invention combines a user emotion recognition engine to further enhance conventional inventory management and lending procedures. The specific flow of this process is described below.

[0536] 1. The user operates the terminal and enters the item whose inventory status they want to check. The terminal uses an emotion engine to analyze the user's emotions and sends an inventory status inquiry request to the server based on the user's input.

[0537] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. The server calls the external database's API to retrieve the inventory data.

[0538] 3. When the server analyzes the inventory data it has acquired and returns the results to the user's terminal, it generates a customized message based on the analysis results of the sentiment engine. For example, it notifies the user of the information "There are 10 iPad Pros in stock" in a tone optimized based on sentiment analysis.

[0539] 4. The user operates the terminal and enters the items they wish to borrow and their quantities. The terminal also runs an emotion engine to analyze the user's emotional state. Based on the user's input, the terminal sends a "loan request" to the server.

[0540] 5. When the server receives a loan request, it uses feedback from the emotion engine to optimize the loan approval process. For example, if the user is in a state of impatience, the system will provide quick and easy-to-understand feedback.

[0541] 6. The server reconfirms the inventory status and determines whether the loan request is feasible. If there is sufficient inventory, the server determines that it is "available" and sends a message optimized by the emotion engine to the terminal.

[0542] 7. When the user confirms the loan on the device, the emotion engine is used to display the most appropriate confirmation message. The device sends a "loan confirmation request" to the server.

[0543] 8. The server receives the request and sends an API request to the external database to perform the lending process. The processing result is returned to the terminal, and an optimized feedback message is conveyed to the user based on the analysis results of the emotion engine.

[0544] 9. Finally, when the user checks the loan completion status on their device, the emotion engine optimizes the displayed content to support the user in proceeding with confidence.

[0545] Specific example:

[0546] Example 1:

[0547] The user types "I want to check the availability of iPad Pro" on their device. The device uses an emotion engine to recognize the user's emotional state and sends a request to the server saying, "Yes, you are looking for an iPad Pro. We currently have 10 in stock." The server connects to an external database and retrieves the inventory data. After confirming that there are 10 in stock, the server sends an emotion-optimized message to the device.

[0548] The user types, "I'd like to borrow one iPad Pro." The device uses an emotion engine to recognize the user's emotional state and confirms, "So you'd like to borrow one iPad Pro, is that correct?" The device sends a request to the server. The server checks its inventory, determines that there is sufficient stock and that it is available for loan, and sends an optimized message to the device saying, "One iPad Pro is available for loan."

[0549] The user performs the "Confirm Loan" action. The device sends a request to the server. The server connects to an external database, confirms the loan process, and sends a "Loan Complete" message. The emotion engine analyzes this result and provides appropriate feedback to the user.

[0550] Thus, the system of the present invention recognizes the user's emotions and provides optimal feedback based on them, thereby improving the user experience and enabling efficient and accurate inventory management and lending procedures.

[0551] The following describes the processing flow.

[0552] Step 1:

[0553] The user operates the device and enters the item whose inventory status they want to check (e.g., "iPad Pro"). The device prepares to send an inventory status inquiry request to the server based on the entered information. Simultaneously, it activates an emotion engine to analyze the user's emotional state from their facial expressions and voice.

[0554] Step 2:

[0555] The device sends an inventory status inquiry request to the server based on the emotion engine's analysis results. This request includes reassuring wording for the user. For example, if the system detects the user is anxious, a message such as "We'll check immediately, please wait a moment" will be displayed.

[0556] Step 3:

[0557] The server receives the request, connects to an external database API, and sends a request asking, "Please tell me the availability of iPad Pros."

[0558] Step 4:

[0559] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[0560] Step 5:

[0561] The server analyzes the received data and converts it into a user-friendly format. During this process, it considers the results of the emotion engine's analysis and generates a message with an appropriate tone. For example, "Don't worry, we have 10 iPad Pros in stock."

[0562] Step 6:

[0563] The server returns a response to the device containing the analysis results. Based on the data received by the device, it displays to the user, "We have 10 iPad Pros in stock." An emotion engine is used to optimize the display method and tone.

[0564] Step 7:

[0565] The user operates the device and enters "I would like to borrow one iPad Pro." The device then sends a "loan request" to the server based on this input and the user's sentiment analysis results.

[0566] Step 8:

[0567] The server receives the request and re-checks the inventory data. The server checks whether "there are 10 iPad Pros in stock and they are available for loan."

[0568] Step 9:

[0569] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan." At this point, the emotion engine is used again to provide feedback tailored to the user's emotional state.

[0570] Step 10:

[0571] The user operates the terminal and enters "Confirm Loan". The terminal displays a message based on the results of the emotion engine's analysis. For example, "Please wait with peace of mind. We are confirming the loan process."

[0572] Step 11:

[0573] The device sends a request to the server stating, "I confirm the loan of one iPad Pro."

[0574] Step 12:

[0575] The server receives the request and sends an API request to the external database to execute the lending process. If the process is successful, the external database returns a "lending successful" response to the server.

[0576] Step 13:

[0577] The server returns a "loan successful" result to the device. At this time, the emotion engine generates an appropriate feedback message based on the analysis results. For example, "Your iPad Pro loan is complete. Please use it."

[0578] Step 14:

[0579] The user confirms the loan completion status on their device. The emotion engine analyzes the results and supports the user so that they can confidently proceed to the next step.

[0580] (Example 2)

[0581] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0582] In modern resource management systems, efficient and accurate inventory checks and lending procedures are crucial. However, traditional systems often fail to adequately improve the user experience because they do not consider user emotions. Furthermore, they may not accurately reflect the actual status during inventory checks and lending processes. This can result in user dissatisfaction and confusion.

[0583] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the inventory status of multiple resources from an external database, means for identifying the resource requested for borrowing from the user terminal and querying its inventory status, means for analyzing the acquired inventory data and returning the analysis results to the user terminal, means for checking inventory based on the borrowing request from the user and determining whether borrowing is possible, means for requesting processing from the external database to confirm the borrowing of the resource that has become available for borrowing, means for returning the borrowing processing results to the user terminal, and means for analyzing the user's emotions and optimizing the message based on the analysis results. This makes it possible to perform efficient and accurate inventory confirmation and lending processing while taking the user's emotions into consideration.

[0584] An "external database" is a data storage system located remotely that holds and manages information about specific resources.

[0585] "Resources" refer to items or services managed by the system that users wish to access or borrow.

[0586] "Inventory status" refers to data that shows the current number and condition of resources, and represents information about how much of those resources are available.

[0587] A "user terminal" is a device, such as a computer or smartphone, that a user uses to access a system and perform input or output.

[0588] "Borrowing request" refers to a user requesting the system to use a specific resource for a certain period of time.

[0589] An "emotion engine" is a software module that analyzes a user's emotional state and optimizes messages based on the analysis results.

[0590] "Optimizing a message" means adjusting the tone and content of a message to be appropriate and effective based on the user's emotional state.

[0591] "Borrowing process" refers to a series of operations in which the system accepts a borrowing request from a user, updates an external database, and confirms the borrowing.

[0592] The system of the present invention incorporates an emotion engine to provide optimal feedback based on the user's emotions in order to streamline resource management and borrowing procedures. The following describes how the system of the present invention is specifically implemented.

[0593] This system consists of user terminals, servers, and an external database. The user terminals incorporate an interface for receiving user input and an emotion engine for analyzing emotions.

[0594] For the emotion engine, generally available emotion analysis software, such as "IBM Watson Emotion Analysis," can be used. For the external database, database servers such as "AWS RDS" or "MySQL" can be used to manage inventory and borrowing data.

[0595] The device receives input from the user and analyzes its contents. When the user enters information about a resource they want to check, the emotion engine analyzes the user's emotions and sends the results to the server. An example of a prompt message in this case might be, "I want to check the availability of iPad Pros."

[0596] The server receives this request, connects to an external database, and retrieves inventory data. For example, if the retrieved inventory data shows "10 iPad Pros in stock," it analyzes this information, generates a message optimized by the emotion engine, and returns it to the device. This message is returned in a tone based on the user's emotional state.

[0597] For example, if a user enters "I want to check the stock status of iPad Pro" and the emotion engine analyzes the emotion as "certainty," the server will send a message to the device saying "There are currently 10 iPad Pros in stock" based on the data it has acquired.

[0598] Next, when the user types "I'd like to borrow an iPad Pro," the emotion engine similarly analyzes the user's emotions and generates a confirmation message such as "So you'd like to borrow an iPad Pro?". The borrowing request is then sent to the server. The server re-checks the inventory and uses the emotion engine to provide the user with the most appropriate feedback.

[0599] For example, if there is sufficient stock, the server generates a message saying "One iPad Pro is available for loan" and sends it to the device. When the user confirms the loan, the request is sent to the server, which connects to the external database again and performs the loan process. A message saying "Loan complete" is generated in the appropriate tone and returned to the user.

[0600] This ensures users always receive optimal feedback, and streamlines resource management and borrowing procedures.

[0601] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0602] Step 1:

[0603] The user operates the device and enters information about the resource they want to check (e.g., "iPad Pro"). When the user clicks the "Inventory Search" button and enters "iPad Pro" into the input form, this input data becomes the input data for the next processing step on the device.

[0604] Step 2:

[0605] When the terminal receives user input, it analyzes the user's emotions using its built-in emotion engine (e.g., "IBM Watson Emotion Analysis"). As a result of this analysis, an emotional state (e.g., "confident") is output. Next, the terminal generates a request containing this emotion analysis result and the resource information entered by the user, and sends it to the server.

[0606] Input: Resource information entered by the user: "iPad Pro"

[0607] Data processing: Emotional analysis using an emotion engine

[0608] Output: Request containing "confident" status and resource information (e.g., in JSON format {"item":"iPad Pro", "userEmotion":"confident"})

[0609] Step 3:

[0610] The server receives the request sent from the terminal. Next, it connects to an external database (e.g., "AWS RDS" or "MySQL") and retrieves inventory data for the specified resource. For example, it executes the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and retrieves data indicating that there are 10 units in stock.

[0611] Input: Request data from the terminal

[0612] Data processing: Queries to external databases (execution of SQL queries)

[0613] Output: Inventory data for "iPad Pro" (e.g., "10 units in stock")

[0614] Step 4:

[0615] The server analyzes the inventory data it acquires and uses this data to generate an optimized message using an emotion engine. The tone of this message is adjusted based on the user's emotional state (e.g., "confident"). For example, it might generate a message saying, "We currently have 10 iPad Pros in stock," and send it to the device.

[0616] Input: Inventory data and sentiment analysis data

[0617] Data processing: Message generation and emotion-based tone optimization

[0618] Output: Optimized message (e.g., "We currently have 10 iPad Pros in stock")

[0619] Step 5:

[0620] The terminal receives a message from the server and displays it to the user. The user reviews it and prepares to perform the next action.

[0621] Input: Optimized message from the server

[0622] Output: Display to the user

[0623] Step 6:

[0624] The user operates the device and enters the resource they wish to borrow (e.g., "iPad Pro") and the quantity (e.g., "1 unit"). The user clicks the "Borrow" button and enters "1" as the quantity.

[0625] Step 7:

[0626] The device uses the emotion engine again to analyze the user's emotions. It then sends a request to the server containing this analysis result (e.g., "expectation") and the user's input data.

[0627] Input: Resource information and quantity entered by the user.

[0628] Data processing: Reanalysis using an emotion engine

[0629] Output: Request including emotion state, resource information, and quantity (Example: in JSON format {"item":"iPad Pro", "quantity":1, "userEmotion":"hopeful"})

[0630] Step 8:

[0631] The server receives this request and reconnects to the external database to check the inventory data. It executes the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and determines whether it is available for borrowing based on the results. For example, if there is sufficient stock, the server will determine that it is "available for borrowing".

[0632] Input: Request data from the terminal

[0633] Data processing: Queries to external databases (execution of SQL queries)

[0634] Output: Reconfirmed inventory data and loan eligibility determination

[0635] Step 9:

[0636] Based on the inventory data reconfirmed by the server, an optimized message is generated using an emotion engine. For example, a message such as "One iPad Pro is available for loan" is generated and sent to the device.

[0637] Input: Reconfirmed inventory data and sentiment analysis data

[0638] Data processing: Message generation and emotion-based optimization

[0639] Output: Optimized message (e.g., "One iPad Pro is available for loan")

[0640] Step 10:

[0641] The terminal displays this message to the user, and the user performs the "Confirm Loan" operation.

[0642] Input: Optimized message from the server

[0643] Output: Display to the user and user interaction

[0644] Step 11:

[0645] The terminal receives the "Confirm Borrowing" operation, analyzes it again using the emotion engine, and sends the borrowing confirmation request to the server along with the results.

[0646] Input: User's "Confirm Loan" operation

[0647] Data processing: Re-analysis and request generation using an emotion engine.

[0648] Output: Request to the server (Example: in JSON format {"action":"confirmLoan", "item":"iPad Pro", "quantity":1, "userEmotion":"relieved"})

[0649] Step 12:

[0650] The server receives this request and performs a borrowing operation against the external database. It executes the SQL query `UPDATE inventory SET stock = stock - 1 WHERE item = 'iPad Pro';` and returns the result to the device. For example, it generates a message such as "Borrowing complete," optimizes it with the sentiment engine, and sends it to the device.

[0651] Input: Request data from the terminal

[0652] Data processing: Update queries to external databases (execution of SQL queries)

[0653] Output: Borrowing result and optimized message (e.g., "Borrowing complete")

[0654] Step 13:

[0655] The device displays this message to the user, providing them with a sense of security.

[0656] Input: Optimized message from the server

[0657] Output: Display to the user

[0658] This allows the system to take user emotions into consideration and perform efficient and accurate inventory checks and borrowing processes.

[0659] (Application Example 2)

[0660] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0661] Traditional inventory management and lending systems often failed to flexibly adapt to user emotions and usage patterns, resulting in a uniform processing approach that sometimes compromised the user experience. Furthermore, while there was a need for methods to process inventory information and lending procedures quickly and accurately, there was a lack of ingenuity in improving user satisfaction.

[0662] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0663] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for using an emotion engine to analyze the user's emotions and generating an optimized feedback message based on the emotion analysis results; means for checking inventory based on the user's loan request and determining whether or not to lend the item; means for requesting processing from the external database to confirm the loan of items that have become available for loan; and means for returning the loan processing results to the user terminal and displaying an optimized feedback message based on the emotion analysis results. This makes it possible to provide optimal feedback that reflects the user's emotions, improve the user experience, and realize efficient and accurate inventory management and loan procedures.

[0664] - An "external database" is a database accessible via the internet or a company's internal network, where inventory information and other related data are stored. In most cases, data is retrieved and updated via APIs.

[0665] "Inventory status" refers to the current stock quantity of a particular item and related information. For example, it includes information such as how many units are in stock, which warehouse they are in, and whether they are out of stock.

[0666] A "user terminal" is a device used by a user to operate the system, and includes personal computers, smartphones, tablets, and smart glasses. Through these terminals, users access the system and perform operations.

[0667] "Items requested for loan" refers to items that a user wishes to borrow for a specific period. This includes all items available for loan, such as books, electronic devices, and tools.

[0668] An "emotion engine" is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions. This allows it to recognize the user's current emotional state, such as joy, sadness, or anxiety.

[0669] A "feedback message" is information or a notification that the system provides to the user, and it is an optimized message based on the results of sentiment analysis. For example, it may include information on the availability of an item or the possibility of it being available for loan.

[0670] The "means for determining lending eligibility" refer to a system that receives a user's lending request and checks whether it is feasible. The decision is made considering factors such as inventory status, the user's lending history, and other lending requests.

[0671] "Methods for requesting processing from an external database" refer to methods in which the server calls the API of an external database to perform tasks such as updating inventory or recording loans.

[0672] "Loan processing result" refers to the result of the system's processing in response to a user's loan request, and includes information such as whether the loan was completed and whether the inventory was updated.

[0673] This invention is a system that combines an emotion engine that analyzes user emotions to efficiently and user-friendly manage inventory and lending procedures. The following describes in detail specific embodiments of this invention.

[0674] Hardware and software configuration

[0675] This system includes user terminals, a server, and an external database. It also incorporates an emotion engine for analyzing user emotions. User terminals are devices such as smartphones and smart glasses, which allow users to access and operate the system.

[0676] The role of the emotional engine

[0677] An emotion engine is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions, recognizing the emotional state the user is currently experiencing, such as joy, sadness, or anxiety. Specifically, it uses cameras and microphones built into smart glasses to collect and analyze the user's emotional data in real time.

[0678] Processing flow

[0679] 1. When the user terminal inputs the item whose inventory status they wish to check, the terminal uses an emotion engine to analyze the user's emotions. At this point, it sends an inventory status inquiry request to the server based on the user's input.

[0680] 2. The server connects to an external database to retrieve the inventory status of items. The retrieved inventory data is analyzed by the server, and an optimized feedback message is generated based on the analysis results of the emotion engine.

[0681] 3. The inventory status is returned to the user's terminal, and a feedback message is displayed. For example, if the user is anxious, a message such as "We have plenty of stock, so please rest assured" will be displayed.

[0682] Loan procedure

[0683] 1. When a user enters the item they wish to borrow, the user terminal uses the emotion engine again to analyze the user's emotions and sends a borrowing request to the server based on that information.

[0684] 2. The server reconfirms the inventory status and determines whether or not to lend the item. If there is sufficient inventory, a feedback message such as "Available for loan" is optimized based on the analysis results of the emotion engine and sent to the user's terminal.

[0685] 3. Once the user confirms the loan, the server updates the loan information in the external database and returns the loan processing result to the user's terminal. Here again, the emotion engine generates the most appropriate feedback message according to the user's emotional state.

[0686] Specific example

[0687] As a concrete example, consider a scenario where a user is wearing smart glasses and types, "Please tell me the availability of iPad Pros." In this case, the emotion engine detects the user's state of tension from their facial expression and displays a message such as, "We have 10 units in stock, so please don't worry." Similarly, if the user types, "I would like to borrow an iPad Pro," the emotion engine will provide optimal feedback based on its analysis results.

[0688] Example of a prompt

[0689] "When a user asks about the availability of an item, generate a feedback message that reflects their emotional state. For example, if they are feeling stressed, use a message that will ease their tension."

[0690] As described above, the system of the present invention uses an emotion engine to provide optimal feedback in response to the user's emotions, thereby improving the user experience and achieving efficient inventory management and lending procedures.

[0691] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0692] Step 1:

[0693] The user inputs the items whose inventory status they wish to check using voice or an input device on a smart glasses or smartphone. The device recognizes the user's input and analyzes the user's emotions using an emotion engine. This process retrieves both the user's input and the emotion analysis results.

[0694] Input: The name of the item the user wants to check and sentiment data from the sentiment engine.

[0695] Output: User input and sentiment analysis results

[0696] Step 2:

[0697] The terminal sends an inventory status inquiry request to the server based on the acquired data. The server connects to an external database and sends an API request to retrieve the inventory status of the items.

[0698] Input: User input and sentiment analysis results

[0699] Output: Inventory status query request to external database

[0700] Step 3:

[0701] The server analyzes inventory data retrieved from an external database and returns it to the user's terminal. At this time, it generates an optimized feedback message based on the analysis results of the emotion engine.

[0702] Input: Inventory data retrieved from an external database

[0703] Data processing: Combining inventory data with sentiment analysis results for analysis.

[0704] Output: Feedback message to send to the user's terminal

[0705] Step 4:

[0706] The user receives a feedback message and re-enters the items they wish to borrow. The terminal uses the emotion engine again to analyze the user's emotions and sends the borrowing request to the server.

[0707] Input: User's loan preferences and sentiment data

[0708] Output: Loan request to send to the server

[0709] Step 5:

[0710] The server receives the loan request and rechecks the inventory status. If there is sufficient inventory, it determines whether to grant the loan and generates an optimized feedback message based on the analysis results of the emotion engine.

[0711] Input: User loan requests and sentiment data

[0712] Data processing: Reconfirming inventory data and determining whether items are available for loan.

[0713] Output: Feedback message regarding loan availability.

[0714] Step 6:

[0715] Once the user confirms the loan, the server sends an API request to an external database to update the loan information. The result of the loan process is returned to the server, and a feedback message optimized by the emotion engine is sent again to the user's device.

[0716] Input: User loan confirmation operation and sentiment data

[0717] Output: Loan information update request to external database and feedback message of loan processing result.

[0718] Step 7:

[0719] The user receives a final feedback message, and the lending process is completed. The emotion engine is used to re-analyze the user's emotions and support them in confidently moving on to the next step.

[0720] Input: Loan processing results and sentiment data

[0721] Output: Final feedback message to the user

[0722] Through each of the above steps, the system of the present invention provides optimal feedback based on the user's emotions, improving the user experience and achieving efficient inventory management and lending procedures.

[0723] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0724] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0725] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0726] [Third Embodiment]

[0727] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0728] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0729] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0730] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0731] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0732] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0733] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0734] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0735] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0736] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0737] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0738] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0739] The system of the present invention allows users to easily check the inventory status of items and make loans by performing the following processes.

[0740] 1. The user operates the terminal and enters the name of the item whose stock status they wish to check. This input triggers the terminal to send a request to the server to inquire about the stock status.

[0741] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. Specifically, the server calls the external database's API to retrieve inventory data.

[0742] 3. The server analyzes the inventory data it has acquired and returns the results to the user's terminal. For example, it might notify the user that "there are 10 iPad Pros in stock."

[0743] 4. The user operates the terminal and enters the items and quantities they wish to borrow. This input triggers the terminal to send a borrowing request to the server.

[0744] 5. The server checks the inventory status again and determines whether the loan request can be fulfilled. If there is sufficient inventory, the server notifies the user that the loan is available.

[0745] 6. The user confirms the loan on the terminal. The terminal sends a loan confirmation request to the server.

[0746] 7. The server receives the loan confirmation request and requests the external database to process the loan. The server uses the external database's API to update the inventory information and record that the loan has been made.

[0747] 8. Finally, the server returns the loan processing result to the user's terminal, and the user confirms that the loan is complete.

[0748] Specific example:

[0749] Example 1:

[0750] The user types "I want to check the availability of iPad Pro" on their device. The device sends a request to the server. The server connects to an external database, retrieves the information that "there are 10 iPad Pros in stock," parses it, and returns it to the device. The user then types "I want to borrow one iPad Pro." The device sends a request to the server. The server checks the inventory, determines that it is "available," and notifies the device. The user clicks "Confirm Loan." The device sends a request to the server. The server connects to an external database, updates the inventory, and confirms the loan process. The server notifies the device that "the loan is complete," and the user confirms.

[0751] This system allows users to efficiently and accurately check the inventory status of items and proceed with the lending process.

[0752] The following describes the processing flow.

[0753] Step 1:

[0754] The user operates the device and enters the item whose stock status they want to check (e.g., "iPad Pro"). The device then sends a request to the server to inquire about the stock status based on the entered information.

[0755] Step 2:

[0756] The device sends an API request to the server with the content "Item: Please tell me the stock status of iPad Pro".

[0757] Step 3:

[0758] The server receives the request and connects to the external database's API. At this time, the server sends an API request to the external database to "query the availability of iPad Pro."

[0759] Step 4:

[0760] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[0761] Step 5:

[0762] The server analyzes the received data and converts it into a user-friendly format. Specifically, it generates a message such as, "We have 10 iPad Pros in stock."

[0763] Step 6:

[0764] The server returns a response to the terminal containing the analysis results. It also sends data to the terminal stating, "We have 10 iPad Pros in stock."

[0765] Step 7:

[0766] The terminal displays the inventory status received from the server to the user. The user operates the terminal and enters, "I would like to borrow one iPad Pro."

[0767] Step 8:

[0768] The device sends a "request to lend one iPad Pro" to the server based on the user's input.

[0769] Step 9:

[0770] The server receives the request and checks the inventory data again. The server checks whether there are 10 iPad Pros in stock and available for loan.

[0771] Step 10:

[0772] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan."

[0773] Step 11:

[0774] The user operates the device and enters "Confirm Loan". The device sends a request to the server saying "Confirm loan of 1 iPad Pro".

[0775] Step 12:

[0776] The server receives the request and sends an API request to the external database to perform the lending process.

[0777] Step 13:

[0778] The external database executes the lending process and returns a "lending successful" response to the server. The server receives this response.

[0779] Step 14:

[0780] The server returns the loan success result to the user's device. It sends a message to the device saying, "iPad Pro loan complete."

[0781] Step 15:

[0782] The user checks the loan completion status on their device. The user understands that "the iPad Pro loan has been completed."

[0783] (Example 1)

[0784] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0785] Conventional inventory management and lending systems have made it difficult for users to quickly and accurately check inventory status and to complete lending procedures for multiple items. Furthermore, the process of determining lending eligibility and updating inventory information is time-consuming and inefficient. This invention aims to solve these problems and provide a system that allows users to efficiently and accurately check the inventory status of items and complete lending procedures.

[0786] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0787] In this invention, the server includes means for querying the inventory status of items entered from a user terminal, means for obtaining the inventory status of specified items from an external database, means for analyzing the obtained inventory data and returning the results to the user terminal, means for identifying the items and quantities of items requested for loan from the user terminal, means for reconfirming the inventory status based on the loan request and determining whether or not to loan the items, means for updating inventory information in the external database for items whose loan has been confirmed and recording the loan information, and means for returning the results of the loan process to the user terminal. This enables the user to efficiently and accurately check the inventory status of items and carry out loan procedures.

[0788] A "user terminal" is a device that a user operates to input information and that can access a server via a network.

[0789] An "external database" is an information management system that a server connects to to retrieve and update inventory status and loan information.

[0790] "Inventory status" refers to information indicating the quantity of a particular item that is stored.

[0791] "Method of inquiry" refers to the process by which a user's terminal sends a request to a server to retrieve information.

[0792] "Means of acquisition" refers to the process by which a server retrieves necessary data from an external database.

[0793] "Means of analysis" refers to the process by which a server processes acquired data and extracts the necessary information.

[0794] "Items requested for loan" refers to specific items that the user wishes to borrow.

[0795] "Quantity" refers to the specific number of items you wish to borrow.

[0796] The "means of determining eligibility" refers to the process by which the server checks for availability based on a rental request and decides whether or not it is possible to rent it out.

[0797] "Confirmation method" refers to the process by which the server formally records information about items that have been determined to be available for loan.

[0798] "Loan information" refers to detailed data about the items that have been borrowed and their quantities.

[0799] "Means of notification" refers to the process by which the server communicates the processing results to the user's terminal.

[0800] This invention provides a system that allows users to easily check the inventory status of items and efficiently carry out lending procedures. This system operates by coordinating a user terminal, a server, and an external database.

[0801] The user operates their device (e.g., computer, tablet, smartphone) to input the item whose inventory status they want to check. Based on this input, the device sends an inventory status inquiry request to the server. The server parses the received request, extracts the item name, calls an API to an external database, and retrieves the inventory status of the specified item.

[0802] For example, a user enters "Check iPad Pro stock availability" into their device and clicks the submit button. The device sends this input as an HTTP request to the server. The server retrieves the iPad Pro stock availability from an external database, parses the response "Stock Quantity: 10", converts it to JSON format, and returns it to the user's device.

[0803] Next, the user operates their terminal to enter the items they wish to borrow and the quantity. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The terminal then sends a loan request to the server based on this input. The server checks the inventory status again and determines whether the loan request is possible.

[0804] If the server determines that the device is available for loan, the user confirms the loan on their device. The user's action sends a loan confirmation request to the server. The server connects to an external database and sends an API request, " / update_inventory?item=ipad-pro&quantity=-1", to update the inventory information. This updates the inventory count from 10 to 9.

[0805] After the loan information update is complete, the server returns the loan processing result to the user's terminal. Finally, the user receives and confirms a "loan completed" notification on their terminal screen.

[0806] The entire system is efficiently designed, allowing users to complete everything from checking inventory status to loan procedures in a short amount of time. For example, a user might type "I want to check the inventory status of iPad Pros," and the device sends a request to the server. The server retrieves information from an external database, stating "There are 10 iPad Pros in stock," analyzes it, and returns it to the device. Then, the user might type "I want to borrow one iPad Pro," and the server checks the inventory and notifies the user that it is "available." The user confirms the loan, the server connects to the external database to update the inventory, and confirms the loan process. Finally, the server notifies the device that "the loan is complete," and the user confirms it.

[0807] As described above, the present invention provides a system that allows users to efficiently and accurately check the inventory status of items and carry out lending procedures.

[0808] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0809] Step 1:

[0810] The user operates the device and enters the item whose stock status they want to check. Specifically, the user enters "Check iPad Pro stock status" into the device's interface (e.g., a form) and clicks the submit button. The input data is the item name "iPad Pro". As output, the device sends this input content to the server as an HTTP request.

[0811] Step 2:

[0812] The server parses the request received from the terminal. Specifically, the server extracts the item name (e.g., "iPad Pro"). The input data is the HTTP request sent from the terminal, and the output data is the extracted item name. The server then calls an API of an external database to retrieve the item's inventory status. The API call format is " / inventory?item=ipad-pro". The output is the inventory count, which is "10".

[0813] Step 3:

[0814] The server analyzes the acquired inventory data and generates data to be returned to the user's terminal. Specifically, the server converts information such as "There are 10 iPad Pros in stock" into JSON format (e.g., "{ 'item': 'iPad Pro', 'stock': 10}"). The input data is inventory information acquired from an external database, and the output data is the JSON formatted data after analysis. This data is sent to the user's terminal as an HTTP response.

[0815] Step 4:

[0816] The user terminal displays the received inventory information to the user. Specifically, the terminal screen will display "10 iPad Pro units in stock." The input data is inventory information in JSON format sent from the server, and the output data is the inventory information displayed to the user.

[0817] Step 5:

[0818] The user operates the terminal and enters the item and quantity they wish to borrow. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The input data consists of the item name and quantity, and the terminal sends this as a loan request to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1}".

[0819] Step 6:

[0820] The server analyzes the loan request received from the terminal and reconnects to the external database to check the inventory status. The input data is the loan request (item name and quantity), and the output data is the inventory information retrieved again. Specifically, the server confirms that there are 10 iPad Pro units in stock and determines that it is possible to loan the iPad Pro because the requested loan quantity (1 unit) is within the available stock.

[0821] Step 7:

[0822] The server notifies the user terminal of the result of its determination that the item is available for loan. Specifically, it generates a "available for loan" message in JSON format (e.g., "{ 'status': 'possible'}") and sends it as an HTTP response. The input data is the determination result that the item is available for loan, and the output data is the notification message sent to the user terminal.

[0823] Step 8:

[0824] The user confirms the loan on the device. Specifically, the user clicks the "Confirm Loan" button. The input data is the user's confirmation action, and the output is a loan confirmation request sent to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1, 'action': 'confirm'}".

[0825] Step 9:

[0826] The server receives a loan confirmation request, updates the inventory information in an external database, and records the loan information. Specifically, it executes the API call " / update_inventory?item=ipad-pro&quantity=-1" to update the inventory count from 10 to 9. The input data is the loan confirmation request and the current inventory information, and the output data is the updated inventory information.

[0827] Step 10:

[0828] The server returns the result of the loan process to the user's terminal. Specifically, it generates a message indicating "loan completed" in JSON format (e.g., "{ 'status': 'completed'}") and sends it as an HTTP response. The input data is the result of the loan process, and the output data is the notification message sent to the user's terminal.

[0829] Step 11:

[0830] The user terminal displays the results of the loan process received from the server to the user. The user confirms the message "Loan complete" on the screen. The input data is a notification message in JSON format sent from the server, and the output data is the message displayed to the user.

[0831] (Application Example 1)

[0832] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0833] In logistics centers and inventory management systems, the process of checking inventory status and lending items was cumbersome, leading to decreased work efficiency. In particular, manual inventory checks and lending procedures were time-consuming and prone to human error. Furthermore, the inability of on-site workers to quickly search for and lend items resulted in overall reduced work efficiency.

[0834] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0835] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for checking inventory based on the user's loan request and determining whether or not to lend the items; means for requesting processing from the external database to confirm the loan of items that have become available for loan; means for returning the loan processing results to the user terminal; a terminal equipped with a reader for scanning the barcodes of the items; and means for transmitting the information acquired by the reader to the server. This makes it possible for field workers to efficiently check inventory and perform loan procedures via a smartphone application.

[0836] An "external database" is a data storage location located outside the system, where inventory information about goods is stored and provided.

[0837] "Means for obtaining inventory status" refers to a device or method for a server to access an external database and retrieve inventory data of stored items.

[0838] A "user terminal" is a device used by a user to operate, and can take the form of a smartphone, personal computer, or other similar device.

[0839] "Items requested for loan" refers to items in stock that a user wishes to borrow.

[0840] "Means of inquiry" refers to a device or method that transmits information such as inventory checks or loan requests from a user terminal to a server.

[0841] "Means for analyzing inventory data" refers to a device or method for processing and interpreting acquired inventory information and deriving the necessary results.

[0842] "Means for determining whether an item can be lent" refers to a device or method for determining whether an item can be lent based on inventory information and the user's lending request.

[0843] "Means for confirming a loan" refers to a device or method for updating an external database for items whose loan has been approved.

[0844] "Means for returning the loan processing results" refers to a device or method for notifying the user terminal of the final loan status.

[0845] A "barcode reader for scanning items" is a device that reads barcodes attached to items and electronically acquires that information.

[0846] "Means for sending to the server" refers to a device or method for sending information acquired by a reading device to a server.

[0847] The system for implementing this invention is designed to improve the efficiency of inventory checking and item lending in logistics centers. The entire system consists of an external database, a server, user terminals (e.g., smartphones), and barcode readers.

[0848] This system is used by users to check the inventory status of items at the logistics center and to proceed with lending procedures as needed. The system includes the following methods:

[0849] 1. User Terminal: A user terminal is a portable information device such as a smartphone, equipped with an interface for the user to operate the system. The terminal is equipped with a reader for scanning barcodes of items. On this terminal, the user can input the items they wish to borrow and their quantities.

[0850] 2. Server: The server receives requests sent from user terminals and mediates access to external databases. Specifically, it performs the following functions:

[0851] Retrieving inventory status from an external database: The server accesses an external database via an API to retrieve inventory data for items.

[0852] Data Analysis: The acquired inventory data is analyzed and returned to the user's terminal. This analysis includes inventory quantity and loan availability.

[0853] Loan Decision and Confirmation: Based on the user's loan request, inventory is reconfirmed and a decision is made regarding loan eligibility. Then, the external database is updated to record that the loan has been confirmed. This result is also returned to the user's terminal.

[0854] Let's explain the operation of this system using an example. For instance, if a field worker wants to check the inventory status of an "iPad Pro," they open the app on their smartphone, type "iPad Pro," and scan the product with a barcode reader. This information is sent to the server, which retrieves the necessary inventory data from an external database and returns the analysis results to the terminal. If the user wants to borrow one of those products, they enter this into the app and send another request to the server. The server checks the inventory and notifies the user that it is available for loan. After the user confirms the loan, the server updates the external database and returns the processing results to the user's terminal.

[0855] This system will enable on-site workers at logistics centers to efficiently check inventory and process loans.

[0856] Examples of prompts to input into a generative AI model:

[0857] Prompt: Develop an inventory management system application for a logistics center. The following conditions must be met:

[0858] Check the inventory status of items

[0859] Convenient lending procedures

[0860] Improve the work efficiency of on-site workers

[0861] This prompt can provide guidance for building a system that allows field workers to efficiently check inventory and complete lending procedures via a smartphone app.

[0862] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0863] Step 1:

[0864] The user enters the item(s) whose stock status they want to check on their smartphone and scans the item's barcode. The input data includes the item name and barcode information, which is then sent to the server.

[0865] Step 2:

[0866] The server receives item name and barcode information sent from the user terminal and sends a request for inventory status to an external database. The input data includes item name and barcode information, which is used to call the external database API.

[0867] Step 3:

[0868] An external database receives requests from the server and returns inventory data for the specified item. The input data includes the item name, and the output data is the inventory quantity of that item.

[0869] Step 4:

[0870] The server analyzes inventory data retrieved from an external database and returns the results to the user's terminal. The input data is inventory quantity, which the server analyzes and returns in a user-friendly format. The output data contains information related to inventory quantity.

[0871] Step 5:

[0872] The user enters the items they wish to borrow and the quantity via their smartphone. This input data, including the item name and the desired quantity, is also sent to the server.

[0873] Step 6:

[0874] The server receives the user's loan request data and checks the inventory status again against an external database. The input data includes the item name and the requested quantity, and the server calls the external database API to check the inventory.

[0875] Step 7:

[0876] The server reconfirms the inventory status and determines whether the item is available for loan. The input data includes the item name, the desired loan quantity, and the latest inventory quantity. Based on this data, the server determines whether the item is available for loan and outputs this information as output data.

[0877] Step 8:

[0878] The system notifies the user terminal that the server is available for use. At this time, it returns information indicating that the server is available for use as notification data to the user terminal.

[0879] Step 9:

[0880] The user confirms the loan using their smartphone. This input data includes information confirming the loan and is sent to the server.

[0881] Step 10:

[0882] The server receives a user's loan confirmation request and requests an external database to update the loan information. The input data is the item name and loan quantity, and an API is called to update the external database and reduce the inventory quantity.

[0883] Step 11:

[0884] The server returns the loan processing result to the user terminal. The final output data is information indicating that the loan has been completed, and this is notified to the user terminal.

[0885] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0886] The system of this invention combines a user emotion recognition engine to further enhance conventional inventory management and lending procedures. The specific flow of this process is described below.

[0887] 1. The user operates the terminal and enters the item whose inventory status they want to check. The terminal uses an emotion engine to analyze the user's emotions and sends an inventory status inquiry request to the server based on the user's input.

[0888] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. The server calls the external database's API to retrieve the inventory data.

[0889] 3. When the server analyzes the inventory data it has acquired and returns the results to the user's terminal, it generates a customized message based on the analysis results of the sentiment engine. For example, it notifies the user of the information "There are 10 iPad Pros in stock" in a tone optimized based on sentiment analysis.

[0890] 4. The user operates the terminal and enters the items they wish to borrow and their quantities. The terminal also runs an emotion engine to analyze the user's emotional state. Based on the user's input, the terminal sends a "loan request" to the server.

[0891] 5. When the server receives a loan request, it uses feedback from the emotion engine to optimize the loan approval process. For example, if the user is in a state of impatience, the system will provide quick and easy-to-understand feedback.

[0892] 6. The server reconfirms the inventory status and determines whether the loan request is feasible. If there is sufficient inventory, the server determines that it is "available" and sends a message optimized by the emotion engine to the terminal.

[0893] 7. When the user confirms the loan on the device, the emotion engine is used to display the most appropriate confirmation message. The device sends a "loan confirmation request" to the server.

[0894] 8. The server receives the request and sends an API request to the external database to perform the lending process. The processing result is returned to the terminal, and an optimized feedback message is conveyed to the user based on the analysis results of the emotion engine.

[0895] 9. Finally, when the user checks the loan completion status on their device, the emotion engine optimizes the displayed content to support the user in proceeding with confidence.

[0896] Specific example:

[0897] Example 1:

[0898] The user types "I want to check the availability of iPad Pro" on their device. The device uses an emotion engine to recognize the user's emotional state and sends a request to the server saying, "Yes, you are looking for an iPad Pro. We currently have 10 in stock." The server connects to an external database and retrieves the inventory data. After confirming that there are 10 in stock, the server sends an emotion-optimized message to the device.

[0899] The user types, "I'd like to borrow one iPad Pro." The device uses an emotion engine to recognize the user's emotional state and confirms, "So you'd like to borrow one iPad Pro, is that correct?" The device sends a request to the server. The server checks its inventory, determines that there is sufficient stock and that it is available for loan, and sends an optimized message to the device saying, "One iPad Pro is available for loan."

[0900] The user performs the "Confirm Loan" action. The device sends a request to the server. The server connects to an external database, confirms the loan process, and sends a "Loan Complete" message. The emotion engine analyzes this result and provides appropriate feedback to the user.

[0901] Thus, the system of the present invention recognizes the user's emotions and provides optimal feedback based on them, thereby improving the user experience and enabling efficient and accurate inventory management and lending procedures.

[0902] The following describes the processing flow.

[0903] Step 1:

[0904] The user operates the device and enters the item whose inventory status they want to check (e.g., "iPad Pro"). The device prepares to send an inventory status inquiry request to the server based on the entered information. Simultaneously, it activates an emotion engine to analyze the user's emotional state from their facial expressions and voice.

[0905] Step 2:

[0906] The device sends an inventory status inquiry request to the server based on the emotion engine's analysis results. This request includes reassuring wording for the user. For example, if the system detects the user is anxious, a message such as "We'll check immediately, please wait a moment" will be displayed.

[0907] Step 3:

[0908] The server receives the request, connects to an external database API, and sends a request asking, "Please tell me the availability of iPad Pros."

[0909] Step 4:

[0910] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[0911] Step 5:

[0912] The server analyzes the received data and converts it into a user-friendly format. During this process, it considers the results of the emotion engine's analysis and generates a message with an appropriate tone. For example, "Don't worry, we have 10 iPad Pros in stock."

[0913] Step 6:

[0914] The server returns a response to the device containing the analysis results. Based on the data received by the device, it displays to the user, "We have 10 iPad Pros in stock." An emotion engine is used to optimize the display method and tone.

[0915] Step 7:

[0916] The user operates the device and enters "I would like to borrow one iPad Pro." The device then sends a "loan request" to the server based on this input and the user's sentiment analysis results.

[0917] Step 8:

[0918] The server receives the request and re-checks the inventory data. The server checks whether "there are 10 iPad Pros in stock and they are available for loan."

[0919] Step 9:

[0920] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan." At this point, the emotion engine is used again to provide feedback tailored to the user's emotional state.

[0921] Step 10:

[0922] The user operates the terminal and enters "Confirm Loan". The terminal displays a message based on the results of the emotion engine's analysis. For example, "Please wait with peace of mind. We are confirming the loan process."

[0923] Step 11:

[0924] The device sends a request to the server stating, "I confirm the loan of one iPad Pro."

[0925] Step 12:

[0926] The server receives the request and sends an API request to the external database to execute the lending process. If the process is successful, the external database returns a "lending successful" response to the server.

[0927] Step 13:

[0928] The server returns a "loan successful" result to the device. At this time, the emotion engine generates an appropriate feedback message based on the analysis results. For example, "Your iPad Pro loan is complete. Please use it."

[0929] Step 14:

[0930] The user confirms the loan completion status on their device. The emotion engine analyzes the results and supports the user so that they can confidently proceed to the next step.

[0931] (Example 2)

[0932] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0933] In modern resource management systems, efficient and accurate inventory checks and lending procedures are crucial. However, traditional systems often fail to adequately improve the user experience because they do not consider user emotions. Furthermore, they may not accurately reflect the actual status during inventory checks and lending processes. This can result in user dissatisfaction and confusion.

[0934] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the inventory status of multiple resources from an external database, means for identifying the resource requested for borrowing from the user terminal and querying its inventory status, means for analyzing the acquired inventory data and returning the analysis results to the user terminal, means for checking inventory based on the borrowing request from the user and determining whether borrowing is possible, means for requesting processing from the external database to confirm the borrowing of the resource that has become available for borrowing, means for returning the borrowing processing results to the user terminal, and means for analyzing the user's emotions and optimizing the message based on the analysis results. This makes it possible to perform efficient and accurate inventory confirmation and lending processing while taking the user's emotions into consideration.

[0935] An "external database" is a data storage system located remotely that holds and manages information about specific resources.

[0936] "Resources" refer to items or services managed by the system that users wish to access or borrow.

[0937] "Inventory status" refers to data that shows the current number and condition of resources, and represents information about how much of those resources are available.

[0938] A "user terminal" is a device, such as a computer or smartphone, that a user uses to access a system and perform input or output.

[0939] "Borrowing request" refers to a user requesting the system to use a specific resource for a certain period of time.

[0940] An "emotion engine" is a software module that analyzes a user's emotional state and optimizes messages based on the analysis results.

[0941] "Optimizing a message" means adjusting the tone and content of a message to be appropriate and effective based on the user's emotional state.

[0942] "Borrowing process" refers to a series of operations in which the system accepts a borrowing request from a user, updates an external database, and confirms the borrowing.

[0943] The system of the present invention incorporates an emotion engine to provide optimal feedback based on the user's emotions in order to streamline resource management and borrowing procedures. The following describes how the system of the present invention is specifically implemented.

[0944] This system consists of user terminals, servers, and an external database. The user terminals incorporate an interface for receiving user input and an emotion engine for analyzing emotions.

[0945] For the emotion engine, generally available emotion analysis software, such as "IBM Watson Emotion Analysis," can be used. For the external database, database servers such as "AWS RDS" or "MySQL" can be used to manage inventory and borrowing data.

[0946] The device receives input from the user and analyzes its contents. When the user enters information about a resource they want to check, the emotion engine analyzes the user's emotions and sends the results to the server. An example of a prompt message in this case might be, "I want to check the availability of iPad Pros."

[0947] The server receives this request, connects to an external database, and retrieves inventory data. For example, if the retrieved inventory data shows "10 iPad Pros in stock," it analyzes this information, generates a message optimized by the emotion engine, and returns it to the device. This message is returned in a tone based on the user's emotional state.

[0948] For example, if a user enters "I want to check the stock status of iPad Pro" and the emotion engine analyzes the emotion as "certainty," the server will send a message to the device saying "There are currently 10 iPad Pros in stock" based on the data it has acquired.

[0949] Next, when the user types "I'd like to borrow an iPad Pro," the emotion engine similarly analyzes the user's emotions and generates a confirmation message such as "So you'd like to borrow an iPad Pro?". The borrowing request is then sent to the server. The server re-checks the inventory and uses the emotion engine to provide the user with the most appropriate feedback.

[0950] For example, if there is sufficient stock, the server generates a message saying "One iPad Pro is available for loan" and sends it to the device. When the user confirms the loan, the request is sent to the server, which connects to the external database again and performs the loan process. A message saying "Loan complete" is generated in the appropriate tone and returned to the user.

[0951] This ensures users always receive optimal feedback, and streamlines resource management and borrowing procedures.

[0952] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0953] Step 1:

[0954] The user operates the device and enters information about the resource they want to check (e.g., "iPad Pro"). When the user clicks the "Inventory Search" button and enters "iPad Pro" into the input form, this input data becomes the input data for the next processing step on the device.

[0955] Step 2:

[0956] When the terminal receives user input, it analyzes the user's emotions using its built-in emotion engine (e.g., "IBM Watson Emotion Analysis"). As a result of this analysis, an emotional state (e.g., "confident") is output. Next, the terminal generates a request containing this emotion analysis result and the resource information entered by the user, and sends it to the server.

[0957] Input: Resource information entered by the user: "iPad Pro"

[0958] Data processing: Emotional analysis using an emotion engine

[0959] Output: Request containing "certainty" state and resource information (e.g., {"item":"iPad Pro", "userEmotion":"confident"} in JSON format)

[0960] Step 3:

[0961] The server receives the request sent from the terminal. Next, it connects to an external database (e.g., "AWS RDS" or "MySQL") and retrieves the inventory data of the specified resource. For example, execute the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and obtain data showing "10 units in stock" as a result.

[0962] Input: Request data from the terminal

[0963] Data calculation: Query to the external database (execution of SQL query)

[0964] Output: Inventory data of "iPad Pro" (e.g., "10 units in stock")

[0965] Step 4:

[0966] The server analyzes the retrieved inventory data and generates a message optimized by the emotion engine based on this data. The tone of this message is adjusted based on the user's emotional state (e.g., "certainty"). For example, generate a message like "There are currently 10 units of iPad Pro in stock" and send it to the terminal.

[0967] Input: Inventory data and emotion analysis data

[0968] Data processing: Generation of message and optimization of tone based on emotion

[0969] Output: Optimized message (e.g., "There are currently 10 units of iPad Pro in stock")

[0970] Step 5:

[0971] The terminal receives a message from the server and displays it to the user. The user reviews it and prepares to perform the next action.

[0972] Input: Optimized message from the server

[0973] Output: Display to the user

[0974] Step 6:

[0975] The user operates the device and enters the resource they wish to borrow (e.g., "iPad Pro") and the quantity (e.g., "1 unit"). The user clicks the "Borrow" button and enters "1" as the quantity.

[0976] Step 7:

[0977] The device uses the emotion engine again to analyze the user's emotions. It then sends a request to the server containing this analysis result (e.g., "expectation") and the user's input data.

[0978] Input: Resource information and quantity entered by the user.

[0979] Data processing: Reanalysis using an emotion engine

[0980] Output: Request including emotion state, resource information, and quantity (Example: in JSON format {"item":"iPad Pro", "quantity":1, "userEmotion":"hopeful"})

[0981] Step 8:

[0982] The server receives this request and reconnects to the external database to check the inventory data. It executes the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and determines whether it is available for borrowing based on the results. For example, if there is sufficient stock, the server will determine that it is "available for borrowing".

[0983] Input: Request data from the terminal

[0984] Data processing: Queries to external databases (execution of SQL queries)

[0985] Output: Reconfirmed inventory data and loan eligibility determination

[0986] Step 9:

[0987] Based on the inventory data reconfirmed by the server, an optimized message is generated using an emotion engine. For example, a message such as "One iPad Pro is available for loan" is generated and sent to the device.

[0988] Input: Reconfirmed inventory data and sentiment analysis data

[0989] Data processing: Message generation and emotion-based optimization

[0990] Output: Optimized message (e.g., "One iPad Pro is available for loan")

[0991] Step 10:

[0992] The terminal displays this message to the user, and the user performs the "Confirm Loan" operation.

[0993] Input: Optimized message from the server

[0994] Output: Display to the user and user interaction

[0995] Step 11:

[0996] The terminal receives the "Confirm Borrowing" operation, analyzes it again using the emotion engine, and sends the borrowing confirmation request to the server along with the results.

[0997] Input: User's "Confirm Loan" operation

[0998] Data processing: Re-analysis and request generation using an emotion engine.

[0999] Output: Request to the server (Example: in JSON format {"action":"confirmLoan", "item":"iPad Pro", "quantity":1, "userEmotion":"relieved"})

[1000] Step 12:

[1001] The server receives this request and performs a borrowing operation against the external database. It executes the SQL query `UPDATE inventory SET stock = stock - 1 WHERE item = 'iPad Pro';` and returns the result to the device. For example, it generates a message such as "Borrowing complete," optimizes it with the sentiment engine, and sends it to the device.

[1002] Input: Request data from the terminal

[1003] Data processing: Update queries to external databases (execution of SQL queries)

[1004] Output: Borrowing result and optimized message (e.g., "Borrowing complete")

[1005] Step 13:

[1006] The device displays this message to the user, providing them with a sense of security.

[1007] Input: Optimized message from the server

[1008] Output: Display to the user

[1009] This allows the system to take user emotions into consideration and perform efficient and accurate inventory checks and borrowing processes.

[1010] (Application Example 2)

[1011] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1012] Traditional inventory management and lending systems often failed to flexibly adapt to user emotions and usage patterns, resulting in a uniform processing approach that sometimes compromised the user experience. Furthermore, while there was a need for methods to process inventory information and lending procedures quickly and accurately, there was a lack of ingenuity in improving user satisfaction.

[1013] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1014] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for using an emotion engine to analyze the user's emotions and generating an optimized feedback message based on the emotion analysis results; means for checking inventory based on the user's loan request and determining whether or not to lend the item; means for requesting processing from the external database to confirm the loan of items that have become available for loan; and means for returning the loan processing results to the user terminal and displaying an optimized feedback message based on the emotion analysis results. This makes it possible to provide optimal feedback that reflects the user's emotions, improve the user experience, and realize efficient and accurate inventory management and loan procedures.

[1015] - An "external database" is a database accessible via the internet or a company's internal network, where inventory information and other related data are stored. In most cases, data is retrieved and updated via APIs.

[1016] "Inventory status" refers to the current stock quantity of a particular item and related information. For example, it includes information such as how many units are in stock, which warehouse they are in, and whether they are out of stock.

[1017] A "user terminal" is a device used by a user to operate the system, and includes personal computers, smartphones, tablets, and smart glasses. Through these terminals, users access the system and perform operations.

[1018] "Items requested for loan" refers to items that a user wishes to borrow for a specific period. This includes all items available for loan, such as books, electronic devices, and tools.

[1019] An "emotion engine" is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions. This allows it to recognize the user's current emotional state, such as joy, sadness, or anxiety.

[1020] A "feedback message" is information or a notification that the system provides to the user, and it is an optimized message based on the results of sentiment analysis. For example, it may include information on the availability of an item or the possibility of it being available for loan.

[1021] The "means for determining lending eligibility" refer to a system that receives a user's lending request and checks whether it is feasible. The decision is made considering factors such as inventory status, the user's lending history, and other lending requests.

[1022] "Methods for requesting processing from an external database" refer to methods in which the server calls the API of an external database to perform tasks such as updating inventory or recording loans.

[1023] "Loan processing result" refers to the result of the system's processing in response to a user's loan request, and includes information such as whether the loan was completed and whether the inventory was updated.

[1024] This invention is a system that combines an emotion engine that analyzes user emotions to efficiently and user-friendly manage inventory and lending procedures. The following describes in detail specific embodiments of this invention.

[1025] Hardware and software configuration

[1026] This system includes user terminals, a server, and an external database. It also incorporates an emotion engine for analyzing user emotions. User terminals are devices such as smartphones and smart glasses, which allow users to access and operate the system.

[1027] The role of the emotional engine

[1028] An emotion engine is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions, recognizing the emotional state the user is currently experiencing, such as joy, sadness, or anxiety. Specifically, it uses cameras and microphones built into smart glasses to collect and analyze the user's emotional data in real time.

[1029] Processing flow

[1030] 1. When the user terminal inputs the item whose inventory status they wish to check, the terminal uses an emotion engine to analyze the user's emotions. At this point, it sends an inventory status inquiry request to the server based on the user's input.

[1031] 2. The server connects to an external database to retrieve the inventory status of items. The retrieved inventory data is analyzed by the server, and an optimized feedback message is generated based on the analysis results of the emotion engine.

[1032] 3. The inventory status is returned to the user's terminal, and a feedback message is displayed. For example, if the user is anxious, a message such as "We have plenty of stock, so please rest assured" will be displayed.

[1033] Loan procedure

[1034] 1. When a user enters the item they wish to borrow, the user terminal uses the emotion engine again to analyze the user's emotions and sends a borrowing request to the server based on that information.

[1035] 2. The server reconfirms the inventory status and determines whether or not to lend the item. If there is sufficient inventory, a feedback message such as "Available for loan" is optimized based on the analysis results of the emotion engine and sent to the user's terminal.

[1036] 3. Once the user confirms the loan, the server updates the loan information in the external database and returns the loan processing result to the user's terminal. Here again, the emotion engine generates the most appropriate feedback message according to the user's emotional state.

[1037] Specific example

[1038] As a concrete example, consider a scenario where a user is wearing smart glasses and types, "Please tell me the availability of iPad Pros." In this case, the emotion engine detects the user's state of tension from their facial expression and displays a message such as, "We have 10 units in stock, so please don't worry." Similarly, if the user types, "I would like to borrow an iPad Pro," the emotion engine will provide optimal feedback based on its analysis results.

[1039] Example of a prompt

[1040] "When a user asks about the availability of an item, generate a feedback message that reflects their emotional state. For example, if they are feeling stressed, use a message that will ease their tension."

[1041] As described above, the system of the present invention uses an emotion engine to provide optimal feedback in response to the user's emotions, thereby improving the user experience and achieving efficient inventory management and lending procedures.

[1042] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1043] Step 1:

[1044] The user inputs the items whose inventory status they wish to check using voice or an input device on a smart glasses or smartphone. The device recognizes the user's input and analyzes the user's emotions using an emotion engine. This process retrieves both the user's input and the emotion analysis results.

[1045] Input: The name of the item the user wants to check and sentiment data from the sentiment engine.

[1046] Output: User input and sentiment analysis results

[1047] Step 2:

[1048] The terminal sends an inventory status inquiry request to the server based on the acquired data. The server connects to an external database and sends an API request to retrieve the inventory status of the items.

[1049] Input: User input and sentiment analysis results

[1050] Output: Inventory status query request to external database

[1051] Step 3:

[1052] The server analyzes inventory data retrieved from an external database and returns it to the user's terminal. At this time, it generates an optimized feedback message based on the analysis results of the emotion engine.

[1053] Input: Inventory data retrieved from an external database

[1054] Data processing: Combining inventory data with sentiment analysis results for analysis.

[1055] Output: Feedback message to send to the user's terminal

[1056] Step 4:

[1057] The user receives a feedback message and re-enters the items they wish to borrow. The terminal uses the emotion engine again to analyze the user's emotions and sends the borrowing request to the server.

[1058] Input: User's loan preferences and sentiment data

[1059] Output: Loan request to send to the server

[1060] Step 5:

[1061] The server receives the loan request and re-checks the inventory status. If there is sufficient inventory, it determines whether to grant the loan and generates an optimized feedback message based on the analysis results of the emotion engine.

[1062] Input: User loan requests and sentiment data

[1063] Data processing: Reconfirming inventory data and determining whether items are available for loan.

[1064] Output: Feedback message regarding loan availability.

[1065] Step 6:

[1066] Once the user confirms the loan, the server sends an API request to an external database to update the loan information. The result of the loan process is returned to the server, and a feedback message optimized by the emotion engine is sent again to the user's device.

[1067] Input: User loan confirmation operation and sentiment data

[1068] Output: Loan information update request to external database and feedback message of loan processing result.

[1069] Step 7:

[1070] The user receives a final feedback message, and the lending process is completed. The emotion engine is used to re-analyze the user's emotions and support them in confidently moving on to the next step.

[1071] Input: Loan processing results and sentiment data

[1072] Output: Final feedback message to the user

[1073] Through each of the above steps, the system of the present invention provides optimal feedback based on the user's emotions, improving the user experience and achieving efficient inventory management and lending procedures.

[1074] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1075] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1076] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1077] [Fourth Embodiment]

[1078] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1079] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1080] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1081] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1082] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1083] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1084] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1085] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1086] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1087] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1088] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1089] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1090] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1091] The system of the present invention allows users to easily check the inventory status of items and make loans by performing the following processes.

[1092] 1. The user operates the terminal and enters the name of the item whose stock status they wish to check. This input triggers the terminal to send a request to the server to inquire about the stock status.

[1093] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. Specifically, the server calls the external database's API to retrieve inventory data.

[1094] 3. The server analyzes the inventory data it has acquired and returns the results to the user's terminal. For example, it might notify the user that "there are 10 iPad Pros in stock."

[1095] 4. The user operates the terminal and enters the items and quantities they wish to borrow. This input triggers the terminal to send a borrowing request to the server.

[1096] 5. The server checks the inventory status again and determines whether the loan request can be fulfilled. If there is sufficient inventory, the server notifies the user that the loan is available.

[1097] 6. The user confirms the loan on the terminal. The terminal sends a loan confirmation request to the server.

[1098] 7. The server receives the loan confirmation request and requests the external database to process the loan. The server uses the external database's API to update the inventory information and record that the loan has been made.

[1099] 8. Finally, the server returns the loan processing result to the user's terminal, and the user confirms that the loan is complete.

[1100] Specific example:

[1101] Example 1:

[1102] The user types "I want to check the availability of iPad Pro" on their device. The device sends a request to the server. The server connects to an external database, retrieves the information that "there are 10 iPad Pros in stock," parses it, and returns it to the device. The user then types "I want to borrow one iPad Pro." The device sends a request to the server. The server checks the inventory, determines that it is "available," and notifies the device. The user clicks "Confirm Loan." The device sends a request to the server. The server connects to an external database, updates the inventory, and confirms the loan process. The server notifies the device that "the loan is complete," and the user confirms.

[1103] This system allows users to efficiently and accurately check the inventory status of items and proceed with the lending process.

[1104] The following describes the processing flow.

[1105] Step 1:

[1106] The user operates the device and enters the item whose stock status they want to check (e.g., "iPad Pro"). The device then sends a request to the server to inquire about the stock status based on the entered information.

[1107] Step 2:

[1108] The device sends an API request to the server with the content "Item: Please tell me the stock status of iPad Pro".

[1109] Step 3:

[1110] The server receives the request and connects to the external database's API. At this time, the server sends an API request to the external database to "query the availability of iPad Pro."

[1111] Step 4:

[1112] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[1113] Step 5:

[1114] The server analyzes the received data and converts it into a user-friendly format. Specifically, it generates a message such as, "We have 10 iPad Pros in stock."

[1115] Step 6:

[1116] The server returns a response to the terminal containing the analysis results. It also sends data to the terminal stating, "We have 10 iPad Pros in stock."

[1117] Step 7:

[1118] The terminal displays the inventory status received from the server to the user. The user operates the terminal and enters, "I would like to borrow one iPad Pro."

[1119] Step 8:

[1120] The device sends a "request to lend one iPad Pro" to the server based on the user's input.

[1121] Step 9:

[1122] The server receives the request and checks the inventory data again. The server checks whether there are 10 iPad Pros in stock and available for loan.

[1123] Step 10:

[1124] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan."

[1125] Step 11:

[1126] The user operates the device and enters "Confirm Loan". The device sends a request to the server saying "Confirm loan of 1 iPad Pro".

[1127] Step 12:

[1128] The server receives the request and sends an API request to the external database to perform the lending process.

[1129] Step 13:

[1130] The external database executes the lending process and returns a "lending successful" response to the server. The server receives this response.

[1131] Step 14:

[1132] The server returns the loan success result to the user's device. It sends a message to the device saying, "iPad Pro loan complete."

[1133] Step 15:

[1134] The user checks the loan completion status on their device. The user understands that "the iPad Pro loan has been completed."

[1135] (Example 1)

[1136] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1137] Conventional inventory management and lending systems have made it difficult for users to quickly and accurately check inventory status and to complete lending procedures for multiple items. Furthermore, the process of determining lending eligibility and updating inventory information is time-consuming and inefficient. This invention aims to solve these problems and provide a system that allows users to efficiently and accurately check the inventory status of items and complete lending procedures.

[1138] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1139] In this invention, the server includes means for querying the inventory status of items entered from a user terminal, means for obtaining the inventory status of specified items from an external database, means for analyzing the obtained inventory data and returning the results to the user terminal, means for identifying the items and quantities of items requested for loan from the user terminal, means for reconfirming the inventory status based on the loan request and determining whether or not to loan the items, means for updating inventory information in the external database for items whose loan has been confirmed and recording the loan information, and means for returning the results of the loan process to the user terminal. This enables the user to efficiently and accurately check the inventory status of items and carry out loan procedures.

[1140] A "user terminal" is a device that a user operates to input information and that can access a server via a network.

[1141] An "external database" is an information management system that a server connects to to retrieve and update inventory status and loan information.

[1142] "Inventory status" refers to information indicating the quantity of a particular item that is stored.

[1143] "Method of inquiry" refers to the process by which a user's terminal sends a request to a server to retrieve information.

[1144] "Means of acquisition" refers to the process by which a server retrieves necessary data from an external database.

[1145] "Means of analysis" refers to the process by which a server processes acquired data and extracts the necessary information.

[1146] "Items requested for loan" refers to specific items that the user wishes to borrow.

[1147] "Quantity" refers to the specific number of items you wish to borrow.

[1148] The "means of determining eligibility" refers to the process by which the server checks for availability based on a rental request and decides whether or not it is possible to rent it out.

[1149] "Confirmation method" refers to the process by which the server formally records information about items that have been determined to be available for loan.

[1150] "Loan information" refers to detailed data about the items that have been borrowed and their quantities.

[1151] "Means of notification" refers to the process by which the server communicates the processing results to the user's terminal.

[1152] This invention provides a system that allows users to easily check the inventory status of items and efficiently carry out lending procedures. This system operates by coordinating a user terminal, a server, and an external database.

[1153] The user operates their device (e.g., computer, tablet, smartphone) to input the item whose inventory status they want to check. Based on this input, the device sends an inventory status inquiry request to the server. The server parses the received request, extracts the item name, calls an API to an external database, and retrieves the inventory status of the specified item.

[1154] For example, a user enters "Check iPad Pro stock availability" into their device and clicks the submit button. The device sends this input as an HTTP request to the server. The server retrieves the iPad Pro stock availability from an external database, parses the response "Stock Quantity: 10", converts it to JSON format, and returns it to the user's device.

[1155] Next, the user operates their terminal to enter the items they wish to borrow and the quantity. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The terminal then sends a loan request to the server based on this input. The server checks the inventory status again and determines whether the loan request is possible.

[1156] If the server determines that the device is available for loan, the user confirms the loan on their device. The user's action sends a loan confirmation request to the server. The server connects to an external database and sends an API request, " / update_inventory?item=ipad-pro&quantity=-1", to update the inventory information. This updates the inventory count from 10 to 9.

[1157] After the loan information update is complete, the server returns the loan processing result to the user's terminal. Finally, the user receives and confirms a "loan completed" notification on their terminal screen.

[1158] The entire system is efficiently designed, allowing users to complete everything from checking inventory status to loan procedures in a short amount of time. For example, a user might type "I want to check the inventory status of iPad Pros," and the device sends a request to the server. The server retrieves information from an external database, stating "There are 10 iPad Pros in stock," analyzes it, and returns it to the device. Then, the user might type "I want to borrow one iPad Pro," and the server checks the inventory and notifies the user that it is "available." The user confirms the loan, the server connects to the external database to update the inventory, and confirms the loan process. Finally, the server notifies the device that "the loan is complete," and the user confirms it.

[1159] As described above, the present invention provides a system that allows users to efficiently and accurately check the inventory status of items and carry out lending procedures.

[1160] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1161] Step 1:

[1162] The user operates the device and enters the item whose stock status they want to check. Specifically, the user enters "Check iPad Pro stock status" into the device's interface (e.g., a form) and clicks the submit button. The input data is the item name "iPad Pro". As output, the device sends this input content to the server as an HTTP request.

[1163] Step 2:

[1164] The server parses the request received from the terminal. Specifically, the server extracts the item name (e.g., "iPad Pro"). The input data is the HTTP request sent from the terminal, and the output data is the extracted item name. The server then calls an API of an external database to retrieve the item's inventory status. The API call format is " / inventory?item=ipad-pro". The output is the inventory count, which is "10".

[1165] Step 3:

[1166] The server analyzes the acquired inventory data and generates data to be returned to the user's terminal. Specifically, the server converts information such as "There are 10 iPad Pros in stock" into JSON format (e.g., "{ 'item': 'iPad Pro', 'stock': 10}"). The input data is inventory information acquired from an external database, and the output data is the JSON formatted data after analysis. This data is sent to the user's terminal as an HTTP response.

[1167] Step 4:

[1168] The user terminal displays the received inventory information to the user. Specifically, the terminal screen will display "10 iPad Pro units in stock." The input data is inventory information in JSON format sent from the server, and the output data is the inventory information displayed to the user.

[1169] Step 5:

[1170] The user operates the terminal and enters the item and quantity they wish to borrow. For example, they might enter "I would like to borrow one iPad Pro" and click the submit button. The input data consists of the item name and quantity, and the terminal sends this as a loan request to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1}".

[1171] Step 6:

[1172] The server analyzes the loan request received from the terminal and reconnects to the external database to check the inventory status. The input data is the loan request (item name and quantity), and the output data is the inventory information retrieved again. Specifically, the server confirms that there are 10 iPad Pro units in stock and determines that it is possible to loan the iPad Pro because the requested loan quantity (1 unit) is within the available stock.

[1173] Step 7:

[1174] The server notifies the user terminal of the result of its determination that the item is available for loan. Specifically, it generates a "available for loan" message in JSON format (e.g., "{ 'status': 'possible'}") and sends it as an HTTP response. The input data is the determination result that the item is available for loan, and the output data is the notification message sent to the user terminal.

[1175] Step 8:

[1176] The user confirms the loan on the device. Specifically, the user clicks the "Confirm Loan" button. The input data is the user's confirmation action, and the output is a loan confirmation request sent to the server. The HTTP request sent is "{ 'item': 'iPad Pro', 'quantity': 1, 'action': 'confirm'}".

[1177] Step 9:

[1178] The server receives a loan confirmation request, updates the inventory information in an external database, and records the loan information. Specifically, it executes the API call " / update_inventory?item=ipad-pro&quantity=-1" to update the inventory count from 10 to 9. The input data is the loan confirmation request and the current inventory information, and the output data is the updated inventory information.

[1179] Step 10:

[1180] The server returns the result of the loan process to the user's terminal. Specifically, it generates a message indicating "loan completed" in JSON format (e.g., "{ 'status': 'completed'}") and sends it as an HTTP response. The input data is the result of the loan process, and the output data is the notification message sent to the user's terminal.

[1181] Step 11:

[1182] The user terminal displays the results of the loan process received from the server to the user. The user confirms the message "Loan complete" on the screen. The input data is a notification message in JSON format sent from the server, and the output data is the message displayed to the user.

[1183] (Application Example 1)

[1184] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1185] In logistics centers and inventory management systems, the process of checking inventory status and lending items was cumbersome, leading to decreased work efficiency. In particular, manual inventory checks and lending procedures were time-consuming and prone to human error. Furthermore, the inability of on-site workers to quickly search for and lend items resulted in overall reduced work efficiency.

[1186] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1187] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for checking inventory based on the user's loan request and determining whether or not to lend the items; means for requesting processing from the external database to confirm the loan of items that have become available for loan; means for returning the loan processing results to the user terminal; a terminal equipped with a reader for scanning the barcodes of the items; and means for transmitting the information acquired by the reader to the server. This makes it possible for field workers to efficiently check inventory and perform loan procedures via a smartphone application.

[1188] An "external database" is a data storage location located outside the system, where inventory information about goods is stored and provided.

[1189] "Means for obtaining inventory status" refers to a device or method for a server to access an external database and retrieve inventory data of stored items.

[1190] A "user terminal" is a device used by a user to operate, and can take the form of a smartphone, personal computer, or other similar device.

[1191] "Items requested for loan" refers to items in stock that a user wishes to borrow.

[1192] "Means of inquiry" refers to a device or method that transmits information such as inventory checks or loan requests from a user terminal to a server.

[1193] "Means for analyzing inventory data" refers to a device or method for processing and interpreting acquired inventory information and deriving the necessary results.

[1194] "Means for determining whether an item can be lent" refers to a device or method for determining whether an item can be lent based on inventory information and the user's lending request.

[1195] "Means for confirming a loan" refers to a device or method for updating an external database for items whose loan has been approved.

[1196] "Means for returning the loan processing results" refers to a device or method for notifying the user terminal of the final loan status.

[1197] A "barcode reader for scanning items" is a device that reads barcodes attached to items and electronically acquires that information.

[1198] "Means for sending to the server" refers to a device or method for sending information acquired by a reading device to a server.

[1199] The system for implementing this invention is designed to improve the efficiency of inventory checking and item lending in logistics centers. The entire system consists of an external database, a server, user terminals (e.g., smartphones), and barcode readers.

[1200] This system is used by users to check the inventory status of items at the logistics center and to proceed with lending procedures as needed. The system includes the following methods:

[1201] 1. User Terminal: A user terminal is a portable information device such as a smartphone, equipped with an interface for the user to operate the system. The terminal is equipped with a reader for scanning barcodes of items. On this terminal, the user can input the items they wish to borrow and their quantities.

[1202] 2. Server: The server receives requests sent from user terminals and mediates access to external databases. Specifically, it performs the following functions:

[1203] Retrieving inventory status from an external database: The server accesses an external database via an API to retrieve inventory data for items.

[1204] Data Analysis: The acquired inventory data is analyzed and returned to the user's terminal. This analysis includes inventory quantity and loan availability.

[1205] Loan Decision and Confirmation: Based on the user's loan request, inventory is reconfirmed and a decision is made regarding loan eligibility. Then, the external database is updated to record that the loan has been confirmed. This result is also returned to the user's terminal.

[1206] Let's explain the operation of this system using an example. For instance, if a field worker wants to check the inventory status of an "iPad Pro," they open the app on their smartphone, type "iPad Pro," and scan the product with a barcode reader. This information is sent to the server, which retrieves the necessary inventory data from an external database and returns the analysis results to the terminal. If the user wants to borrow one of those products, they enter this into the app and send another request to the server. The server checks the inventory and notifies the user that it is available for loan. After the user confirms the loan, the server updates the external database and returns the processing results to the user's terminal.

[1207] This system will enable on-site workers at logistics centers to efficiently check inventory and process loans.

[1208] Examples of prompts to input into a generative AI model:

[1209] Prompt: Develop an inventory management system application for a logistics center. The following conditions must be met:

[1210] Check the inventory status of items

[1211] Convenient lending procedures

[1212] Improve the work efficiency of on-site workers

[1213] This prompt can provide guidance for building a system that allows field workers to efficiently check inventory and complete lending procedures via a smartphone app.

[1214] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1215] Step 1:

[1216] The user enters the item(s) whose stock status they want to check on their smartphone and scans the item's barcode. The input data includes the item name and barcode information, which is then sent to the server.

[1217] Step 2:

[1218] The server receives item name and barcode information sent from the user terminal and sends a request for inventory status to an external database. The input data includes item name and barcode information, which is used to call the external database API.

[1219] Step 3:

[1220] An external database receives requests from the server and returns inventory data for the specified item. The input data includes the item name, and the output data is the inventory quantity of that item.

[1221] Step 4:

[1222] The server analyzes inventory data retrieved from an external database and returns the results to the user's terminal. The input data is inventory quantity, which the server analyzes and returns in a user-friendly format. The output data contains information related to inventory quantity.

[1223] Step 5:

[1224] The user enters the items they wish to borrow and the quantity via their smartphone. This input data, including the item name and the desired quantity, is also sent to the server.

[1225] Step 6:

[1226] The server receives the user's loan request data and checks the inventory status again against an external database. The input data includes the item name and the requested quantity, and the server calls the external database API to check the inventory.

[1227] Step 7:

[1228] The server reconfirms the inventory status and determines whether the item is available for loan. The input data includes the item name, the desired loan quantity, and the latest inventory quantity. Based on this data, the server determines whether the item is available for loan and outputs this information as output data.

[1229] Step 8:

[1230] The system notifies the user terminal that the server is available for use. At this time, it returns information indicating that the server is available for use as notification data to the user terminal.

[1231] Step 9:

[1232] The user confirms the loan using their smartphone. This input data includes information confirming the loan and is sent to the server.

[1233] Step 10:

[1234] The server receives a user's loan confirmation request and requests an external database to update the loan information. The input data is the item name and loan quantity, and an API is called to update the external database and reduce the inventory quantity.

[1235] Step 11:

[1236] The server returns the loan processing result to the user terminal. The final output data is information indicating that the loan has been completed, and this is notified to the user terminal.

[1237] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1238] The system of this invention combines a user emotion recognition engine to further enhance conventional inventory management and lending procedures. The specific flow of this process is described below.

[1239] 1. The user operates the terminal and enters the item whose inventory status they want to check. The terminal uses an emotion engine to analyze the user's emotions and sends an inventory status inquiry request to the server based on the user's input.

[1240] 2. Upon receiving a request from the terminal, the server connects to an external database and retrieves the inventory status of the items. The server calls the external database's API to retrieve the inventory data.

[1241] 3. When the server analyzes the inventory data it has acquired and returns the results to the user's terminal, it generates a customized message based on the analysis results of the sentiment engine. For example, it notifies the user of the information "There are 10 iPad Pros in stock" in a tone optimized based on sentiment analysis.

[1242] 4. The user operates the terminal and enters the items they wish to borrow and their quantities. The terminal also runs an emotion engine to analyze the user's emotional state. Based on the user's input, the terminal sends a "loan request" to the server.

[1243] 5. When the server receives a loan request, it uses feedback from the emotion engine to optimize the loan approval process. For example, if the user is in a state of impatience, the system will provide quick and easy-to-understand feedback.

[1244] 6. The server reconfirms the inventory status and determines whether the loan request is feasible. If there is sufficient inventory, the server determines that it is "available" and sends a message optimized by the emotion engine to the terminal.

[1245] 7. When the user confirms the loan on the device, the emotion engine is used to display the most appropriate confirmation message. The device sends a "loan confirmation request" to the server.

[1246] 8. The server receives the request and sends an API request to the external database to perform the lending process. The processing result is returned to the terminal, and an optimized feedback message is conveyed to the user based on the analysis results of the emotion engine.

[1247] 9. Finally, when the user checks the loan completion status on their device, the emotion engine optimizes the displayed content to support the user in proceeding with confidence.

[1248] Specific example:

[1249] Example 1:

[1250] The user types "I want to check the availability of iPad Pro" on their device. The device uses an emotion engine to recognize the user's emotional state and sends a request to the server saying, "Yes, you are looking for an iPad Pro. We currently have 10 in stock." The server connects to an external database and retrieves the inventory data. After confirming that there are 10 in stock, the server sends an emotion-optimized message to the device.

[1251] The user types, "I'd like to borrow one iPad Pro." The device uses an emotion engine to recognize the user's emotional state and confirms, "So you'd like to borrow one iPad Pro, is that correct?" The device sends a request to the server. The server checks its inventory, determines that there is sufficient stock and that it is available for loan, and sends an optimized message to the device saying, "One iPad Pro is available for loan."

[1252] The user performs the "Confirm Loan" action. The device sends a request to the server. The server connects to an external database, confirms the loan process, and sends a "Loan Complete" message. The emotion engine analyzes this result and provides appropriate feedback to the user.

[1253] Thus, the system of the present invention recognizes the user's emotions and provides optimal feedback based on them, thereby improving the user experience and enabling efficient and accurate inventory management and lending procedures.

[1254] The following describes the processing flow.

[1255] Step 1:

[1256] The user operates the device and enters the item whose inventory status they want to check (e.g., "iPad Pro"). The device prepares to send an inventory status inquiry request to the server based on the entered information. Simultaneously, it activates an emotion engine to analyze the user's emotional state from their facial expressions and voice.

[1257] Step 2:

[1258] The device sends an inventory status inquiry request to the server based on the emotion engine's analysis results. This request includes reassuring wording for the user. For example, if the system detects the user is anxious, a message such as "We'll check immediately, please wait a moment" will be displayed.

[1259] Step 3:

[1260] The server receives the request, connects to an external database API, and sends a request asking, "Please tell me the availability of iPad Pros."

[1261] Step 4:

[1262] An external database returns a response to the server stating that "there are 10 iPad Pro units in stock." The server receives this response.

[1263] Step 5:

[1264] The server analyzes the received data and converts it into a user-friendly format. During this process, it considers the results of the emotion engine's analysis and generates a message with an appropriate tone. For example, "Don't worry, we have 10 iPad Pros in stock."

[1265] Step 6:

[1266] The server returns a response to the device containing the analysis results. Based on the data received by the device, it displays to the user, "We have 10 iPad Pros in stock." An emotion engine is used to optimize the display method and tone.

[1267] Step 7:

[1268] The user operates the device and enters "I would like to borrow one iPad Pro." The device then sends a "loan request" to the server based on this input and the user's sentiment analysis results.

[1269] Step 8:

[1270] The server receives the request and re-checks the inventory data. The server checks whether "there are 10 iPad Pros in stock and they are available for loan."

[1271] Step 9:

[1272] If the server determines that an iPad Pro is available for loan, it sends a message to the user's device stating, "An iPad Pro is available for loan." At this point, the emotion engine is used again to provide feedback tailored to the user's emotional state.

[1273] Step 10:

[1274] The user operates the terminal and enters "Confirm Loan". The terminal displays a message based on the results of the emotion engine's analysis. For example, "Please wait with peace of mind. We are confirming the loan process."

[1275] Step 11:

[1276] The device sends a request to the server stating, "I confirm the loan of one iPad Pro."

[1277] Step 12:

[1278] The server receives the request and sends an API request to the external database to execute the lending process. If the process is successful, the external database returns a "lending successful" response to the server.

[1279] Step 13:

[1280] The server returns a "loan successful" result to the device. At this time, the emotion engine generates an appropriate feedback message based on the analysis results. For example, "Your iPad Pro loan is complete. Please use it."

[1281] Step 14:

[1282] The user confirms the loan completion status on their device. The emotion engine analyzes the results and supports the user so that they can confidently proceed to the next step.

[1283] (Example 2)

[1284] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1285] In modern resource management systems, efficient and accurate inventory checks and lending procedures are crucial. However, traditional systems often fail to adequately improve the user experience because they do not consider user emotions. Furthermore, they may not accurately reflect the actual status during inventory checks and lending processes. This can result in user dissatisfaction and confusion.

[1286] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring the inventory status of multiple resources from an external database, means for identifying the resource requested for borrowing from the user terminal and querying its inventory status, means for analyzing the acquired inventory data and returning the analysis results to the user terminal, means for checking inventory based on the borrowing request from the user and determining whether borrowing is possible, means for requesting processing from the external database to confirm the borrowing of the resource that has become available for borrowing, means for returning the borrowing processing results to the user terminal, and means for analyzing the user's emotions and optimizing the message based on the analysis results. This makes it possible to perform efficient and accurate inventory confirmation and lending processing while taking the user's emotions into consideration.

[1287] An "external database" is a data storage system located remotely that holds and manages information about specific resources.

[1288] "Resources" refer to items or services managed by the system that users wish to access or borrow.

[1289] "Inventory status" refers to data that shows the current number and condition of resources, and represents information about how much of those resources are available.

[1290] A "user terminal" is a device, such as a computer or smartphone, that a user uses to access a system and perform input or output.

[1291] "Borrowing request" refers to a user requesting the system to use a specific resource for a certain period of time.

[1292] An "emotion engine" is a software module that analyzes a user's emotional state and optimizes messages based on the analysis results.

[1293] "Optimizing a message" means adjusting the tone and content of a message to be appropriate and effective based on the user's emotional state.

[1294] "Borrowing process" refers to a series of operations in which the system accepts a borrowing request from a user, updates an external database, and confirms the borrowing.

[1295] The system of the present invention incorporates an emotion engine to provide optimal feedback based on the user's emotions in order to streamline resource management and borrowing procedures. The following describes how the system of the present invention is specifically implemented.

[1296] This system consists of user terminals, servers, and an external database. The user terminals incorporate an interface for receiving user input and an emotion engine for analyzing emotions.

[1297] For the emotion engine, generally available emotion analysis software, such as "IBM Watson Emotion Analysis," can be used. For the external database, database servers such as "AWS RDS" or "MySQL" can be used to manage inventory and borrowing data.

[1298] The device receives input from the user and analyzes its contents. When the user enters information about a resource they want to check, the emotion engine analyzes the user's emotions and sends the results to the server. An example of a prompt message in this case might be, "I want to check the availability of iPad Pros."

[1299] The server receives this request, connects to an external database, and retrieves inventory data. For example, if the retrieved inventory data shows "10 iPad Pros in stock," it analyzes this information, generates a message optimized by the emotion engine, and returns it to the device. This message is returned in a tone based on the user's emotional state.

[1300] For example, if a user enters "I want to check the stock status of iPad Pro" and the emotion engine analyzes the emotion as "certainty," the server will send a message to the device saying "There are currently 10 iPad Pros in stock" based on the data it has acquired.

[1301] Next, when the user types "I'd like to borrow an iPad Pro," the emotion engine similarly analyzes the user's emotions and generates a confirmation message such as "So you'd like to borrow an iPad Pro?". The borrowing request is then sent to the server. The server re-checks the inventory and uses the emotion engine to provide the user with the most appropriate feedback.

[1302] For example, if there is sufficient stock, the server generates a message saying "One iPad Pro is available for loan" and sends it to the device. When the user confirms the loan, the request is sent to the server, which connects to the external database again and performs the loan process. A message saying "Loan complete" is generated in the appropriate tone and returned to the user.

[1303] This ensures users always receive optimal feedback, and streamlines resource management and borrowing procedures.

[1304] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1305] Step 1:

[1306] The user operates the device and enters information about the resource they want to check (e.g., "iPad Pro"). When the user clicks the "Inventory Search" button and enters "iPad Pro" into the input form, this input data becomes the input data for the next processing step on the device.

[1307] Step 2:

[1308] When the terminal receives user input, it analyzes the user's emotions using its built-in emotion engine (e.g., "IBM Watson Emotion Analysis"). As a result of this analysis, an emotional state (e.g., "confident") is output. Next, the terminal generates a request containing this emotion analysis result and the resource information entered by the user, and sends it to the server.

[1309] Input: Resource information entered by the user: "iPad Pro"

[1310] Data processing: Emotional analysis using an emotion engine

[1311] Output: Request containing "confident" status and resource information (e.g., in JSON format {"item":"iPad Pro", "userEmotion":"confident"})

[1312] Step 3:

[1313] The server receives the request sent from the terminal. Next, it connects to an external database (e.g., "AWS RDS" or "MySQL") and retrieves inventory data for the specified resource. For example, it executes the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and retrieves data indicating that there are 10 units in stock.

[1314] Input: Request data from the terminal

[1315] Data processing: Queries to external databases (execution of SQL queries)

[1316] Output: Inventory data for "iPad Pro" (e.g., "10 units in stock")

[1317] Step 4:

[1318] The server analyzes the inventory data it acquires and uses this data to generate an optimized message using an emotion engine. The tone of this message is adjusted based on the user's emotional state (e.g., "confident"). For example, it might generate a message saying, "We currently have 10 iPad Pros in stock," and send it to the device.

[1319] Input: Inventory data and sentiment analysis data

[1320] Data processing: Message generation and emotion-based tone optimization

[1321] Output: Optimized message (e.g., "We currently have 10 iPad Pros in stock")

[1322] Step 5:

[1323] The terminal receives a message from the server and displays it to the user. The user reviews it and prepares to perform the next action.

[1324] Input: Optimized message from the server

[1325] Output: Display to the user

[1326] Step 6:

[1327] The user operates the device and enters the resource they wish to borrow (e.g., "iPad Pro") and the quantity (e.g., "1 unit"). The user clicks the "Borrow" button and enters "1" as the quantity.

[1328] Step 7:

[1329] The device uses the emotion engine again to analyze the user's emotions. It then sends a request to the server containing this analysis result (e.g., "expectation") and the user's input data.

[1330] Input: Resource information and quantity entered by the user.

[1331] Data processing: Reanalysis using an emotion engine

[1332] Output: Request including emotion state, resource information, and quantity (Example: in JSON format {"item":"iPad Pro", "quantity":1, "userEmotion":"hopeful"})

[1333] Step 8:

[1334] The server receives this request and reconnects to the external database to check the inventory data. It executes the SQL query SELECT stock FROM inventory WHERE item = 'iPad Pro'; and determines whether it is available for borrowing based on the results. For example, if there is sufficient stock, the server will determine that it is "available for borrowing".

[1335] Input: Request data from the terminal

[1336] Data processing: Queries to external databases (execution of SQL queries)

[1337] Output: Reconfirmed inventory data and loan eligibility determination

[1338] Step 9:

[1339] Based on the inventory data reconfirmed by the server, an optimized message is generated using an emotion engine. For example, a message such as "One iPad Pro is available for loan" is generated and sent to the device.

[1340] Input: Reconfirmed inventory data and sentiment analysis data

[1341] Data processing: Message generation and emotion-based optimization

[1342] Output: Optimized message (e.g., "One iPad Pro is available for loan")

[1343] Step 10:

[1344] The terminal displays this message to the user, and the user performs the "Confirm Loan" operation.

[1345] Input: Optimized message from the server

[1346] Output: Display to the user and user interaction

[1347] Step 11:

[1348] The terminal receives the "Confirm Borrowing" operation, analyzes it again using the emotion engine, and sends the borrowing confirmation request to the server along with the results.

[1349] Input: User's "Confirm Loan" operation

[1350] Data processing: Re-analysis and request generation using an emotion engine.

[1351] Output: Request to the server (Example: in JSON format {"action":"confirmLoan", "item":"iPad Pro", "quantity":1, "userEmotion":"relieved"})

[1352] Step 12:

[1353] The server receives this request and performs a borrowing operation against the external database. It executes the SQL query `UPDATE inventory SET stock = stock - 1 WHERE item = 'iPad Pro';` and returns the result to the device. For example, it generates a message such as "Borrowing complete," optimizes it with the sentiment engine, and sends it to the device.

[1354] Input: Request data from the terminal

[1355] Data processing: Update queries to external databases (execution of SQL queries)

[1356] Output: Borrowing result and optimized message (e.g., "Borrowing complete")

[1357] Step 13:

[1358] The device displays this message to the user, providing them with a sense of security.

[1359] Input: Optimized message from the server

[1360] Output: Display to the user

[1361] This allows the system to take user emotions into consideration and perform efficient and accurate inventory checks and borrowing processes.

[1362] (Application Example 2)

[1363] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1364] Traditional inventory management and lending systems often failed to flexibly adapt to user emotions and usage patterns, resulting in a uniform processing approach that sometimes compromised the user experience. Furthermore, while there was a need for methods to process inventory information and lending procedures quickly and accurately, there was a lack of ingenuity in improving user satisfaction.

[1365] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1366] In this invention, the server includes means for obtaining the inventory status of multiple items from an external database; means for identifying items requested for loan from a user terminal and querying their inventory status; means for analyzing the acquired inventory data and returning the analysis results to the user terminal; means for using an emotion engine to analyze the user's emotions and generating an optimized feedback message based on the emotion analysis results; means for checking inventory based on the user's loan request and determining whether or not to lend the item; means for requesting processing from the external database to confirm the loan of items that have become available for loan; and means for returning the loan processing results to the user terminal and displaying an optimized feedback message based on the emotion analysis results. This makes it possible to provide optimal feedback that reflects the user's emotions, improve the user experience, and realize efficient and accurate inventory management and loan procedures.

[1367] - An "external database" is a database accessible via the internet or a company's internal network, where inventory information and other related data are stored. In most cases, data is retrieved and updated via APIs.

[1368] "Inventory status" refers to the current stock quantity of a particular item and related information. For example, it includes information such as how many units are in stock, which warehouse they are in, and whether they are out of stock.

[1369] A "user terminal" is a device used by a user to operate the system, and includes personal computers, smartphones, tablets, and smart glasses. Through these terminals, users access the system and perform operations.

[1370] "Items requested for loan" refers to items that a user wishes to borrow for a specific period. This includes all items available for loan, such as books, electronic devices, and tools.

[1371] An "emotion engine" is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions. This allows it to recognize the user's current emotional state, such as joy, sadness, or anxiety.

[1372] A "feedback message" is information or a notification that the system provides to the user, and it is an optimized message based on the results of sentiment analysis. For example, it may include information on the availability of an item or the possibility of it being available for loan.

[1373] The "means for determining lending eligibility" refer to a system that receives a user's lending request and checks whether it is feasible. The decision is made considering factors such as inventory status, the user's lending history, and other lending requests.

[1374] "Methods for requesting processing from an external database" refer to methods in which the server calls the API of an external database to perform tasks such as updating inventory or recording loans.

[1375] "Loan processing result" refers to the result of the system's processing in response to a user's loan request, and includes information such as whether the loan was completed and whether the inventory was updated.

[1376] This invention is a system that combines an emotion engine that analyzes user emotions to efficiently and user-friendly manage inventory and lending procedures. The following describes in detail specific embodiments of this invention.

[1377] Hardware and software configuration

[1378] This system includes user terminals, a server, and an external database. It also incorporates an emotion engine for analyzing user emotions. User terminals are devices such as smartphones and smart glasses, which allow users to access and operate the system.

[1379] The role of the emotional engine

[1380] An emotion engine is a software or hardware system that analyzes a user's emotions from their facial expressions, voice, and actions, recognizing the emotional state the user is currently experiencing, such as joy, sadness, or anxiety. Specifically, it uses cameras and microphones built into smart glasses to collect and analyze the user's emotional data in real time.

[1381] Processing flow

[1382] 1. When the user terminal inputs the item whose inventory status they wish to check, the terminal uses an emotion engine to analyze the user's emotions. At this point, it sends an inventory status inquiry request to the server based on the user's input.

[1383] 2. The server connects to an external database to retrieve the inventory status of items. The retrieved inventory data is analyzed by the server, and an optimized feedback message is generated based on the analysis results of the emotion engine.

[1384] 3. The inventory status is returned to the user's terminal, and a feedback message is displayed. For example, if the user is anxious, a message such as "We have plenty of stock, so please rest assured" will be displayed.

[1385] Loan procedure

[1386] 1. When a user enters the item they wish to borrow, the user terminal uses the emotion engine again to analyze the user's emotions and sends a borrowing request to the server based on that information.

[1387] 2. The server reconfirms the inventory status and determines whether or not to lend the item. If there is sufficient inventory, a feedback message such as "Available for loan" is optimized based on the analysis results of the emotion engine and sent to the user's terminal.

[1388] 3. Once the user confirms the loan, the server updates the loan information in the external database and returns the loan processing result to the user's terminal. Here again, the emotion engine generates the most appropriate feedback message according to the user's emotional state.

[1389] Specific example

[1390] As a concrete example, consider a scenario where a user is wearing smart glasses and types, "Please tell me the availability of iPad Pros." In this case, the emotion engine detects the user's state of tension from their facial expression and displays a message such as, "We have 10 units in stock, so please don't worry." Similarly, if the user types, "I would like to borrow an iPad Pro," the emotion engine will provide optimal feedback based on its analysis results.

[1391] Example of a prompt

[1392] "When a user asks about the availability of an item, generate a feedback message that reflects their emotional state. For example, if they are feeling stressed, use a message that will ease their tension."

[1393] As described above, the system of the present invention uses an emotion engine to provide optimal feedback in response to the user's emotions, thereby improving the user experience and achieving efficient inventory management and lending procedures.

[1394] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1395] Step 1:

[1396] The user inputs the items whose inventory status they wish to check using voice or an input device on a smart glasses or smartphone. The device recognizes the user's input and analyzes the user's emotions using an emotion engine. This process retrieves both the user's input and the emotion analysis results.

[1397] Input: The name of the item the user wants to check and sentiment data from the sentiment engine.

[1398] Output: User input and sentiment analysis results

[1399] Step 2:

[1400] The terminal sends an inventory status inquiry request to the server based on the acquired data. The server connects to an external database and sends an API request to retrieve the inventory status of the items.

[1401] Input: User input and sentiment analysis results

[1402] Output: Inventory status query request to external database

[1403] Step 3:

[1404] The server analyzes inventory data retrieved from an external database and returns it to the user's terminal. At this time, it generates an optimized feedback message based on the analysis results of the emotion engine.

[1405] Input: Inventory data retrieved from an external database

[1406] Data processing: Combining inventory data with sentiment analysis results for analysis.

[1407] Output: Feedback message to send to the user's terminal

[1408] Step 4:

[1409] The user receives a feedback message and re-enters the items they wish to borrow. The terminal uses the emotion engine again to analyze the user's emotions and sends the borrowing request to the server.

[1410] Input: User's loan preferences and sentiment data

[1411] Output: Loan request to send to the server

[1412] Step 5:

[1413] The server receives the loan request and re-checks the inventory status. If there is sufficient inventory, it determines whether to grant the loan and generates an optimized feedback message based on the analysis results of the emotion engine.

[1414] Input: User loan requests and sentiment data

[1415] Data processing: Reconfirming inventory data and determining whether items are available for loan.

[1416] Output: Feedback message regarding loan availability.

[1417] Step 6:

[1418] Once the user confirms the loan, the server sends an API request to an external database to update the loan information. The result of the loan process is returned to the server, and a feedback message optimized by the emotion engine is sent again to the user's device.

[1419] Input: User loan confirmation operation and sentiment data

[1420] Output: Loan information update request to external database and feedback message of loan processing result.

[1421] Step 7:

[1422] The user receives a final feedback message, and the lending process is completed. The emotion engine is used to re-analyze the user's emotions and support them in confidently moving on to the next step.

[1423] Input: Loan processing results and sentiment data

[1424] Output: Final feedback message to the user

[1425] Through each of the above steps, the system of the present invention provides optimal feedback based on the user's emotions, improving the user experience and achieving efficient inventory management and lending procedures.

[1426] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1427] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1428] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1429] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1430] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1431] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1432] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1433] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1434] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1435] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1436] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1437] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1438] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1439] 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.

[1440] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1441] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1442] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1443] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1444] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1445] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1446] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1447] The following is further disclosed regarding the embodiments described above.

[1448] (Claim 1)

[1449] A means of obtaining the inventory status of multiple items from an external database,

[1450] A means to identify the item requested for loan from the user's terminal and to inquire about its availability,

[1451] A means of analyzing acquired inventory data and returning the analysis results to the user terminal,

[1452] A means of checking inventory based on user loan requests and determining whether or not to lend the item,

[1453] A means of requesting processing from an external database to confirm the loan of items that have become available for loan,

[1454] A means of returning the loan processing results to the user terminal,

[1455] A system that includes this.

[1456] (Claim 2)

[1457] The system according to claim 1, wherein the user terminal has an interface for inputting the items to be borrowed and their quantities.

[1458] (Claim 3)

[1459] The system according to claim 1, wherein, in the loan confirmation process, the available inventory quantity is reconfirmed and the loan information is updated in an external database.

[1460] "Example 1"

[1461] (Claim 1)

[1462] A means of inquiring about the inventory status of items entered from a user terminal,

[1463] A means of obtaining the inventory status of a specified item from an external database,

[1464] A means of analyzing acquired inventory data and returning the results to the user terminal,

[1465] A means for identifying the items requested for loan and their quantities entered from the user terminal,

[1466] A means of reconfirming inventory status based on loan requests and determining whether or not to lend the item,

[1467] A means of updating inventory information in an external database for items whose loan has been confirmed, and recording loan information,

[1468] A means of returning the results of the lending process to the user terminal,

[1469] A system that includes this.

[1470] (Claim 2)

[1471] The system according to claim 1, wherein the user terminal has an interface for inputting the items to be borrowed and their quantities.

[1472] (Claim 3)

[1473] The system according to claim 1, which, in the loan confirmation process, reconfirms the available inventory quantity and updates the loan information in an external database.

[1474] "Application Example 1"

[1475] (Claim 1)

[1476] A means of obtaining the inventory status of multiple items from an external database,

[1477] A means to identify the item requested for loan from the user's terminal and to inquire about its availability,

[1478] A means of analyzing acquired inventory data and returning the analysis results to the user terminal,

[1479] A means of checking inventory based on user loan requests and determining whether or not to lend the item,

[1480] A means of requesting processing from an external database to confirm the loan of items that have become available for loan,

[1481] A means of returning the loan processing results to the user terminal,

[1482] A terminal equipped with a reader for scanning barcodes on items,

[1483] Means for transmitting the information acquired by the aforementioned reading device to a server,

[1484] A system that includes this.

[1485] (Claim 2)

[1486] The system according to claim 1, wherein the user terminal has an interface for inputting the items to be borrowed and their quantities.

[1487] (Claim 3)

[1488] The system according to claim 1, wherein, in the loan confirmation process, the available inventory quantity is reconfirmed and the loan information is updated in an external database.

[1489] "Example 2 of combining an emotion engine"

[1490] (Claim 1)

[1491] A means of obtaining the inventory status of multiple resources from an external database,

[1492] A means for identifying the resource requested for borrowing from the user terminal and inquiring about its inventory status,

[1493] A means of analyzing acquired inventory data and returning the analysis results to the user terminal,

[1494] A means of checking inventory based on a user's loan request and determining whether or not the loan is possible,

[1495] A means of requesting processing from an external database to confirm the borrowing of resources that have become available for borrowing,

[1496] A means of returning the borrowing processing result to the user terminal,

[1497] A means of analyzing user emotions and optimizing messages based on the analysis results,

[1498] A system that includes this.

[1499] (Claim 2)

[1500] The system according to claim 1, wherein the user terminal has an interface for inputting the resources to be borrowed and their quantities.

[1501] (Claim 3)

[1502] The system according to claim 1, wherein, in the borrowing confirmation process, the available inventory quantity is reconfirmed and the borrowing information is updated in an external database.

[1503] "Application example 2 when combining with an emotional engine"

[1504] (Claim 1)

[1505] A means of obtaining the inventory status of multiple items from an external database,

[1506] A means to identify the item requested for loan from the user's terminal and to inquire about its availability,

[1507] A means of analyzing acquired inventory data and returning the analysis results to the user terminal,

[1508] A means for generating an optimized feedback message based on the results of an emotion analysis, using an emotion engine that analyzes the user's emotions,

[1509] A means of checking inventory based on user loan requests and determining whether or not to lend the item,

[1510] A means of requesting processing from an external database to confirm the loan of items that have become available for loan,

[1511] A means for returning the loan processing results to the user terminal and displaying an optimized feedback message based on the sentiment analysis results,

[1512] A system that includes this.

[1513] (Claim 2)

[1514] The system according to claim 1, wherein the user terminal has an interface for inputting the items to be borrowed and their quantities, and an emotion engine is used to analyze the user's emotional state.

[1515] (Claim 3)

[1516] The system according to claim 1, in the loan confirmation process, the available inventory quantity is reconfirmed, the loan information is updated in an external database, and a confirmation message optimized using an emotion engine is displayed. [Explanation of Symbols]

[1517] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining the inventory status of multiple items from an external database, A means to identify the item requested for loan from the user's terminal and to inquire about its availability, A means of analyzing acquired inventory data and returning the analysis results to the user terminal, A means of checking inventory based on user loan requests and determining whether or not to lend the item, A means of requesting processing from an external database to confirm the loan of items that have become available for loan, A means of returning the loan processing results to the user terminal, A system that includes this.

2. The system according to claim 1, wherein the user terminal has an interface for inputting the items to be borrowed and their quantities.

3. The system according to claim 1, wherein, in the loan confirmation process, the available inventory quantity is reconfirmed and the loan information is updated in an external database.

Images