System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting product information, inventory information, and price information from a store management system; means for analyzing the collected information and identifying products whose inventory is below a specified amount or whose price needs to be changed; means for generating and transmitting price change information and replenishment instructions to a terminal in the store; means for generating and transmitting the generated announcement content as a voice announcement; and a terminal for displaying the generated price change information and playing the voice announcement.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern supermarkets and retail stores, holding limited-time sales and special sale events is an important task that increases store revenue and stimulates consumer purchasing desire. However, current announcement methods are mainly done manually, which is inefficient and requires time and effort. Furthermore, if inventory management is not carried out properly, excess inventory and immobile inventory can occur, putting pressure on management. To address these issues, it is necessary to implement efficient and effective limited-time sales and special sale events and optimize inventory management to improve consumer experience and increase store operational efficiency. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means: a system including means for collecting product information, inventory information, and price information from a store management system, means for analyzing the collected information and identifying products whose inventory falls below a certain level or whose prices need to be changed, means for generating price change information and replenishment instructions and sending them to in-store terminals, means for generating and sending the generated announcement content as audio announcements, and a terminal for displaying the generated price change information and playing the audio announcements. Furthermore, by using multimodal AI technology to monitor consumer behavior in the store and optimize announcements in real time, and means for notifying store staff of replenishment instructions and displaying those instructions on the terminals, the system achieves efficient inventory management and limited-time sale operation, improving the consumer experience and streamlining store operations.

[0006] A "store management system" is an information system for managing inventory information, price information, product buying and selling information, etc. within a store.

[0007] "Product information" refers to detailed information such as product name, product number, category, specifications, and price.

[0008] "Inventory information" refers to information such as current inventory levels, inventory locations, and inventory receipt and delivery history.

[0009] "Price information" refers to information related to prices, such as the current price of a product, discount information, and special sale prices.

[0010] "Analysis" refers to the process of analyzing collected data to extract useful information and identify problems.

[0011] "Price change information" refers to information indicating a change from a current price to a new price.

[0012] "Replenishment instructions" refer to instructions to replenish additional stock for products that are out of stock.

[0013] "Terminal" refers to an electronic device used to display price information, provide replenishment instructions, and receive and play voice announcements.

[0014] "Voice announcement" refers to an audio message used to convey information to consumers and staff within a store.

[0015] "Multimodal AI technology" refers to artificial intelligence technology that analyzes multiple data sources, such as audio, video, and text, and makes comprehensive judgments.

[0016] "Consumer behavior" refers to behavioral patterns such as which products consumers look at in a store, the route they take, and which products they pick up.

[0017] "Real time" refers to processing or responses being carried out in accordance with actual time.

[0018] A "system" refers to a set of mechanisms in which multiple devices and programs work together to perform a specific function. [Brief explanation of the drawings]

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

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

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

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] Server-side processing

[0041] Data collection

[0042] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, the server obtains information that there are 10 or fewer units of product A in stock and that the price is discounted.

[0043] Data analysis

[0044] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[0045] instruction generation

[0046] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[0047] Generate a voice announcement

[0048] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[0049] Terminal side processing

[0050] View pricing information

[0051] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives information that product B is 10% off and displays the new price on the price tag.

[0052] Broadcast announcements

[0053] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[0054] Staff Notification

[0055] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[0056] User processing

[0057] Staff behavior

[0058] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[0059] Consumer behavior

[0060] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. Specifically, the user checks the new price of the sale item B, picks it up, and purchases it.

[0061] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, thereby improving consumer experience and streamlining store operations.

[0062] The processing flow will be explained below.

[0063] Server-side processing steps

[0064] Data collection

[0065] Step 1:

[0066] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[0067] Step 2:

[0068] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[0069] Data analysis

[0070] Step 3:

[0071] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[0072] Step 4:

[0073] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[0074] Step 5:

[0075] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[0076] instruction generation

[0077] Step 6:

[0078] The server generates price change information for the identified product in JSON format, including the new price.

[0079] Step 7:

[0080] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[0081] Generate a voice announcement

[0082] Step 8:

[0083] The server generates announcement content as text based on information about special sale events and time sales.

[0084] Step 9:

[0085] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[0086] Step 10:

[0087] The server prepares to send the generated audio file to the in-store terminal.

[0088] Terminal processing steps

[0089] View pricing information

[0090] Step 1:

[0091] The terminal receives price information in JSON format sent from the server.

[0092] Step 2:

[0093] The terminal parses the received JSON data and extracts the product ID and new price.

[0094] Step 3:

[0095] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[0096] Broadcast announcements

[0097] Step 4:

[0098] The terminal receives the audio file sent from the server.

[0099] Step 5:

[0100] The terminal stores the received audio file in local storage.

[0101] Step 6:

[0102] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[0103] Staff Notification

[0104] Step 7:

[0105] The terminal receives a replenishment instruction from the server.

[0106] Step 8:

[0107] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[0108] Step 9:

[0109] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[0110] User processing steps

[0111] Staff behavior

[0112] Step 1:

[0113] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[0114] Step 2:

[0115] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[0116] Consumer behavior

[0117] Step 3:

[0118] Users (consumers) check digital price tags and voice announcements in the store to find out about special sales.

[0119] Step 4:

[0120] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[0121] Through the above processing steps, the server, terminals, and users work together to realize efficient and effective time sales and special sale events, as well as inventory management.

[0122] Example 1

[0123] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0124] There is a need for automated inventory management, price updates, and voice announcements regarding special sale events. However, current systems make it difficult to perform these tasks efficiently and effectively. In particular, there are limited ways to respond quickly when inventory is low or prices need to be changed, making it difficult to improve the consumer experience and streamline store operations.

[0125] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0126] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating and transmitting price change information and replenishment instructions to terminals in the store, means for generating and transmitting the generated announcement content as voice announcements, a terminal for displaying the generated price change information and playing the voice announcements, means for notifying store staff terminals of replenishment instructions, and means for generating voice announcements using a generative AI model. This enables inventory management, price information updates, and the effective implementation of special sale events.

[0127] A "store management system" is an integrated system of software and hardware for managing product information, inventory information, and price information within a store.

[0128] The "server" is a computer system that analyzes and processes information collected from the store management system and sends generated instructions and voice announcements to terminals within the store.

[0129] "Product information" refers to basic product data such as product name, product category, and product code.

[0130] "Inventory information" refers to information such as the current inventory quantity and inventory location of each product.

[0131] "Price information" is data including the current selling price and discount information for each product.

[0132] "API Request" means a message requesting data from another system via an Application Programming Interface.

[0133] "JSON format" is an abbreviation for JavaScript Object Notation, a data representation format, and a text format with a structure that is easy for both humans and machines to read and write.

[0134] "Multimodal AI technology" is an artificial intelligence technology that processes multiple types of data (such as text, audio, and images) in an integrated manner.

[0135] A "terminal" is a device that displays and plays instructions and information received from the server and enables interaction with store staff and consumers.

[0136] "Generative AI models" are algorithms and models that use artificial intelligence to generate appropriate data and responses for specific tasks.

[0137] "Price change information" is data indicating how the selling price of a product should be changed.

[0138] "Voice announcements" are announcements that convey information about special sales events, time sales, etc. to consumers and staff via voice.

[0139] "Replenishment instruction" is a message to instruct the replenishment of products that are out of stock.

[0140] The present invention provides a system that improves the efficiency of product inventory management, price information updates, and sales events through cooperation between a store management system, a server, terminals, and users. Specific embodiments for carrying out the invention are described below.

[0141] Server-side processing

[0142] Data collection

[0143] The server periodically collects product information, inventory information, and price information from the store management system. This collection process uses API requests and receives data in JSON format. For example, the server obtains information such as "there are 10 or fewer units of product A in stock and the price is discounted."

[0144] Data analysis

[0145] The server analyzes the received data and identifies products that are out of stock or need a price change. The analysis involves parsing the data and making conditional decisions, such as listing products with less than 10 units in stock. It then determines whether a price change is necessary based on discount campaign information.

[0146] instruction generation

[0147] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[0148] Generate a voice announcement

[0149] The server uses the generative AI model to generate a voice announcement, such as "Time sale starts at 3 PM. All items are 30% off," and sends it to the device.

[0150] Terminal side processing

[0151] View pricing information

[0152] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[0153] Broadcast announcements

[0154] The device receives the voice announcement file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time. Specifically, it announces, "The limited-time sale has begun at 3 PM."

[0155] Staff Notification

[0156] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[0157] User processing

[0158] Staff behavior

[0159] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[0160] Consumer behavior

[0161] The user (consumer) checks the latest sale information through digital price tags or voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[0162] Examples of prompt statements

[0163] Below are some specific examples of prompt sentences to input into the generative AI model.

[0164] You are an expert in store management systems. In this system, the store server collects product information, analyzes the data, and generates instructions for inventory shortages and price changes. It also creates voice announcements and sends them to terminals. The terminals then display price information, play voice announcements, and notify staff of replenishment instructions. Please explain this process in detail.

[0165] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0166] Server-side processing

[0167] Step 1: Start collecting data

[0168] The server sends an API request to the store management system. This request includes parameters to retrieve product information, inventory information, and price information. The server executes this process according to a regular schedule.

[0169] Input: API request parameters

[0170] Output: Response data in JSON format

[0171] Step 2: Receiving data

[0172] The server receives JSON format data as a response from the store management system, which includes the stock quantity, price information, discount information, etc. for each product.

[0173] Input: Response data in JSON format

[0174] Output: A parsable JSON data object

[0175] Step 3: Begin data analysis

[0176] The server parses the received JSON data to analyze it. Specifically, it extracts the stock quantity and price for each product and prepares the data for analysis.

[0177] Input: JSON data object

[0178] Output: Extracted inventory quantity and price information

[0179] Step 4: Identifying defects and important information

[0180] The server uses the extracted data to identify products whose inventory has fallen below a certain number (for example, 10 units) or whose prices have changed. This information serves as the basis for generating new instruction data.

[0181] Input: Extracted inventory quantity, price information

[0182] Output: Stock shortage list, price change list

[0183] Step 5: Start generating instructions

[0184] The server generates price change information and replenishment instructions based on the identified information, such as "issue a replenishment instruction because product A is out of stock" or "reflect the price of product B on the digital price tag."

[0185] Input: Stock shortage list, price change list

[0186] Output: Price change instructions, replenishment instructions

[0187] Step 6: Sending instruction data

[0188] The server sends the generated instruction data in JSON format to the device, allowing the device to perform appropriate updates based on the received data.

[0189] Input: Price change instructions, replenishment instructions

[0190] Output: JSON data sent to the terminal

[0191] Step 7: Start generating voice announcements

[0192] The server uses a generative AI model to generate voice announcements, such as "A limited-time sale starts at 3 p.m. All items are 30% off" based on information about special sales events and limited-time sales.

[0193] Input: Special sale event information, limited time sale information

[0194] Output: Voice announcement data

[0195] Step 8: Send a voice announcement

[0196] The server sends the generated voice announcement file to the terminal, allowing each terminal to play the announcement at the appropriate time.

[0197] Input: Voice announcement data

[0198] Output: Audio file sent to the device

[0199] Terminal side processing

[0200] Step 1: Receiving price information

[0201] The terminal receives price information in JSON format from the server, which includes specific price change instructions.

[0202] Input: Price change information in JSON format

[0203] Output: Price change instruction data

[0204] Step 2: Parse the price information

[0205] The terminal analyzes the received data and identifies which items require price changes, for example, identifying that item B is on a 10% discount.

[0206] Input: Price change instruction data

[0207] Output: Updated pricing information

[0208] Step 3: Update your digital price tags

[0209] Based on the analysis, the terminal will display the new price on a digital price tag for consumer verification.

[0210] Input: Updated pricing information

[0211] Output: New price displayed on the digital price tag

[0212] Step 4: Receive a voice announcement

[0213] The device retrieves the voice announcement file received from the server and stores it in local storage.

[0214] Input: Audio file sent to the device

[0215] Output: Saved audio file

[0216] Step 5: Play an announcement

[0217] The device then plays the stored audio announcement over the in-store speakers at the appropriate time, for example, announcing, "The 3 PM limited-time sale has begun."

[0218] Input: Saved audio file

[0219] Output: Played audio announcement

[0220] Step 6: Receiving replenishment orders

[0221] The terminal receives a replenishment instruction from the server, which is then sent to the terminal of the store staff member.

[0222] Input: Refill order sent to terminal

[0223] Output: Replenishment message sent to store staff

[0224] User processing

[0225] Step 1: Confirm replenishment instructions

[0226] The user (store staff) checks the replenishment instruction from the terminal. Specifically, a message is displayed saying, "Product A is low in stock. Please replenish from the warehouse."

[0227] Input: Replenishment instructions notified

[0228] Output: Confirmed replenishment order

[0229] Step 2: Replenish inventory

[0230] The user promptly replenishes inventory based on the confirmed instructions, for example, by taking product A from the warehouse and stocking it in the store.

[0231] Input: Confirmed replenishment order

[0232] Output: Replenished products

[0233] Step 3: Check for special offers

[0234] Users (consumers) check the latest sales information through digital price tags or voice announcements in the store. For example, they check the new price of product B on sale.

[0235] Input: Digital price tag, voice announcement

[0236] Output: Confirmed sale information

[0237] Step 4: Shop the sale items

[0238] The user purchases a product based on the sale information they have checked. For example, they pick up and purchase product B, which is on sale.

[0239] Input: Confirmed sale information

[0240] Output: Purchased items

[0241] Through these steps, the system can efficiently and effectively manage inventory, update price information, and automate sales events.

[0242] (Application example 1)

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

[0244] Conventional store management systems did not sufficiently streamline inventory management and price changes, and notifications of special sales and limited-time sales were often done manually. It was also difficult for store staff to share information in real time when replenishing inventory. Furthermore, effective sales information was not provided to consumers, resulting in lost sales opportunities. Therefore, there is a need for a system that automates inventory management, price changes, and sales information notifications, and provides appropriate information to consumers and store staff in real time.

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

[0246] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for providing consumers with real-time sales information and limited-time sale start notifications using smartphones or tablet devices, means for providing store staff with real-time inventory status confirmation and replenishment instruction notification functions, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management, price change and sale information notifications, and real-time information provision to consumers and store staff.

[0247] Key Word Definitions

[0248] A "store management system" is an integrated information system for managing products, inventory, prices, etc. within a store.

[0249] "Product information" means data containing detailed information about each product, typically including the name, price, category, and availability.

[0250] "Inventory information" is data that indicates the current quantity of each product in the store and in the warehouse.

[0251] "Price information" is data that includes the current selling price and discount information for each product.

[0252] "Analysis" refers to the process of extracting and determining information for a specific purpose from collected data.

[0253] "Special sale information" is information indicating special sales conditions and discount details for products that will be offered within a certain period of time.

[0254] A "time sale" is a promotional event where products are sold at a discounted price for a specific time frame.

[0255] "Server" refers to a computer system that collects, analyzes, and distributes data over a network.

[0256] A "terminal" is a device for displaying and operating information, and includes smartphones and tablet devices.

[0257] "Multimodal AI technology" is an artificial intelligence technology that integrates multiple data modalities (e.g., voice, text, images) to perform analysis and decision-making.

[0258] A "voice announcement" is a means of conveying specific information using voice data.

[0259] "Real-time" refers to the generation and processing of data occurring immediately, without delay.

[0260] "Push notifications" are a technology that sends information to mobile devices in real time.

[0261] MODE FOR CARRYING OUT THE INVENTION

[0262] Server-side processing

[0263] Data collection

[0264] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information such as when there are 10 or fewer units of a specific product A in stock or when the price is discounted can be obtained.

[0265] Data analysis

[0266] The server analyzes the acquired data and identifies products that are low in stock or products subject to price changes. For example, it lists products with less than 10 units in stock or products for which discount campaigns are applied. This identifies products subject to special sales or limited-time sales.

[0267] instruction generation

[0268] The server generates price change information and replenishment instructions based on the analysis results. The generated data is sent to the terminal in JSON format. For example, it may contain specific instructions such as "issue a replenishment order because product A is out of stock" or "reflect the price change of product B on the digital price tag."

[0269] Generate a voice announcement

[0270] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[0271] Terminal side processing

[0272] View pricing information

[0273] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives discount information for product B and displays the new price on the price tag.

[0274] Broadcast announcements

[0275] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[0276] Staff Notification

[0277] The terminal notifies the store staff terminal of the replenishment instruction from the server. For example, a message such as "Product A is low in stock. Please replenish from the warehouse" is displayed.

[0278] User processing

[0279] Staff behavior

[0280] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. For example, they take product A from the warehouse and replenish it on the storefront.

[0281] Consumer behavior

[0282] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[0283] Hardware and software used

[0284] Server: A high-performance server is used, and a web framework such as Flask is used.

[0285] Devices: Smartphones, tablets, digital price tags, etc.

[0286] Software: Python, REST API, React Native, text-to-speech API, multimodal AI, etc.

[0287] Examples and prompts

[0288] For example, if you want to automatically issue replenishment instructions for specific products and update price change information in real time, the following prompt sentence is effective:

[0289] "Write a program that generates replenishment orders for low-stock items and updates digital price tags based on price change information. Also, add the ability to generate audio announcements about special sales and send them to a smartphone app."

[0290] The above is a specific embodiment for carrying out the present invention.

[0291] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0292] Program processing flow

[0293] Step 1:

[0294] Data collection

[0295] The server periodically collects product information, inventory information, and price information in JSON format from the store management system through an API. The API endpoint and authentication information are required as input. The data collection process involves sending an HTTP GET request and parsing the JSON data received as a response to extract fields such as product name, inventory quantity, price, and discount information. The output is parseable JSON data.

[0296] Step 2:

[0297] Data analysis

[0298] The server parses the collected JSON data. The JSON data to be parsed is used as input. The data parsing process filters based on specific conditions (for example, items with less than 10 units in stock, items with discount campaigns applied, etc.). Specifically, it lists items that are low in stock and items that need to be repriced. The output is a list of low-stock items and items that need to be repriced.

[0299] Step 3:

[0300] instruction generation

[0301] The server generates price change information and replenishment instructions based on the analysis results. As input, it requires a list of low-stock items and a list of items subject to price changes. In the instruction generation process, it generates JSON data containing stock replenishment instructions and new price information for each item. The generated data is sent to the terminal in the store via API. The output is replenishment instructions and price change information in JSON format, which are sent to the terminal.

[0302] Step 4:

[0303] Generate a voice announcement

[0304] The server generates a voice announcement using multimodal AI technology. The generated instruction content is used as input. The voice announcement generation process generates voice data using a text-to-speech API, which converts text content into an audio file. Specifically, it creates an announcement such as, "A limited-time sale starts at 3:00 PM. All items are 30% off." The output is the URL of the audio file.

[0305] Step 5:

[0306] View pricing information

[0307] The terminal parses the price change information received from the server and displays it on the digital price tag. The received price change information in JSON format is used as input. The price information display process immediately reflects the new price on the digital price tag. Specifically, it updates the display content of the price tag and applies the information to the product in the store. The output is the updated price tag display.

[0308] Step 6:

[0309] Broadcast announcements

[0310] The terminal stores the voice announcement file received from the server in local storage and plays it through the in-store speakers at the specified time. The URL of the voice file and playback timing information are used as input. The voice announcement broadcast process downloads the voice file and plays it on the playback device at the appropriate time. The output is the announcement broadcast in the store.

[0311] Step 7:

[0312] Staff Notification

[0313] The terminal notifies the store staff terminal of the replenishment instruction from the server. JSON data containing the replenishment instruction is used as input. The notification process sends a push notification to the store staff device and displays information about the products that need to be replenished. Specifically, it displays a message on the smartphone or tablet saying, "Product A is low in stock. Please replenish it from the warehouse." The output is a notification of the replenishment instruction to the staff.

[0314] Step 8:

[0315] Staff behavior

[0316] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes inventory. The replenishment instruction information displayed on the terminal is used as input. The behavioral process executes specific steps to retrieve the specified products from the warehouse and replenish them in the store. The output is the replenishment of products in the store and an inventory update.

[0317] Step 9:

[0318] Consumer behavior

[0319] Users (consumers) check the latest sale information through digital price tags and voice announcements in the store. The sale information obtained from the price tags and announcements is used as input. In the behavioral process, the user picks up a sale item and takes action to actually purchase it. The output is the sales record resulting from the purchase of the item.

[0320] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0321] Server-side processing

[0322] Data collection

[0323] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information is obtained that product A has 10 or fewer units in stock and is eligible for a discount.

[0324] Data analysis

[0325] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[0326] Use of emotion engine

[0327] The server uses an emotion engine to collect and analyze in real time the emotional data of consumers in the store. This emotional data is acquired from cameras and sensors, and emotions are inferred from the consumers' facial expressions and behavior.

[0328] instruction generation

[0329] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. For example, it may include instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[0330] Generate a voice announcement

[0331] The server optimizes the announcement content based on information about special sales events and limited-time sales, as well as consumer sentiment data. For example, it creates a voice message such as, "Our limited-time sale starts at 3 p.m. All items are 30% off," and sends it to the device.

[0332] Terminal side processing

[0333] View pricing information

[0334] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[0335] Broadcast announcements

[0336] The device receives the audio file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time, for example announcing, "The limited-time sale has begun at 3 PM."

[0337] Staff Notification

[0338] The terminal notifies the store staff terminal of the replenishment instruction from the server. The notification content includes specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[0339] User processing

[0340] Staff behavior

[0341] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[0342] Consumer behavior

[0343] The user (consumer) checks the digital price tag, voice announcements, and emotion-based optimization information in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[0344] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and further improves the consumer experience by utilizing an emotion engine.

[0345] The processing flow will be explained below.

[0346] Server-side processing steps

[0347] Data collection

[0348] Step 1:

[0349] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[0350] Step 2:

[0351] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[0352] Data analysis

[0353] Step 3:

[0354] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[0355] Step 4:

[0356] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[0357] Step 5:

[0358] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[0359] Use of emotion engine

[0360] Step 6:

[0361] The server collects consumer facial expression and behavioral data obtained from cameras and sensors within the store.

[0362] Step 7:

[0363] The server uses an emotion engine to analyze the consumer's emotions in real time from the collected data, inferring, for example, whether the consumer is excited or bored.

[0364] instruction generation

[0365] Step 8:

[0366] Based on the analysis results, the server generates price change information and replenishment instructions, and the generated data is sent to the terminal in JSON format.

[0367] Step 9:

[0368] The server generates price change information for the identified product in JSON format, including the new price.

[0369] Step 10:

[0370] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[0371] Generate a voice announcement

[0372] Step 11:

[0373] The server optimizes the content of announcements based on information about special sales events and limited-time sales, as well as consumer sentiment data.

[0374] Step 12:

[0375] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[0376] Step 13:

[0377] The server prepares to send the generated audio file to the in-store terminal.

[0378] Terminal processing steps

[0379] View pricing information

[0380] Step 1:

[0381] The terminal receives price information in JSON format sent from the server.

[0382] Step 2:

[0383] The terminal parses the received JSON data and extracts the product ID and new price.

[0384] Step 3:

[0385] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[0386] Broadcast announcements

[0387] Step 4:

[0388] The terminal receives the audio file sent from the server.

[0389] Step 5:

[0390] The terminal stores the received audio file in local storage.

[0391] Step 6:

[0392] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[0393] Staff Notification

[0394] Step 7:

[0395] The terminal receives a replenishment instruction from the server.

[0396] Step 8:

[0397] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[0398] Step 9:

[0399] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[0400] User processing steps

[0401] Staff behavior

[0402] Step 1:

[0403] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[0404] Step 2:

[0405] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[0406] Consumer behavior

[0407] Step 3:

[0408] Users (consumers) see digital price tags, voice announcements, and sentiment-based optimization information in the store.

[0409] Step 4:

[0410] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[0411] Example 2

[0412] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0413] In today's retail industry, efficient and effective inventory management, price updates, and even marketing activities are extremely important. However, traditional store management systems face challenges in that they are unable to provide real-time data and optimally timed information based on consumer behavior and emotions. Furthermore, inventory shortages and missed price changes frequently occur, resulting in reduced store operational efficiency.

[0414] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for collecting consumer emotion data in the store and analyzing it in real time using emotion analysis technology, means for generating price change information and replenishment instructions and transmitting them to terminals in the store, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management and price updates to be performed more efficiently and effectively than before, and enables information to be provided at the optimal time based on consumer emotions and behavior. Furthermore, it enables quick notification of replenishment instructions to store staff and real-time announcements to consumers, thereby improving the efficiency of store operations and customer satisfaction.

[0415] A "store management system" is a system for comprehensively managing a store's inventory, sales, pricing, etc.

[0416] "Product information" refers to basic information about a product, such as product name, product code, classification, and description.

[0417] "Inventory information" refers to data regarding the inventory quantity of each product, inventory history, inventory location, etc.

[0418] "Price information" refers to data including the current price of each product, past price change history, discount information, etc.

[0419] "Analysis" refers to the process of determining whether collected data meets certain conditions and extracting relevant information.

[0420] "Emotion analysis technology" refers to technology that uses data obtained from cameras and sensors to infer emotions from consumers' facial expressions and behavior.

[0421] "Price change information" refers to information for updating an existing price to a new price.

[0422] "Replenishment Instructions" refers to specific instructions to notify store staff to replenish items that are low in stock.

[0423] "Announcement content" refers to announcements made in stores, including information about special sales and limited-time sales.

[0424] "Voice announcement" refers to broadcasting the generated announcement content in audio format within the store.

[0425] "Terminal" refers to a device that communicates with a server to receive information and display or play audio.

[0426] The present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and also improves consumer experience by utilizing emotion analysis technology.

[0427] Server Processing

[0428] Data collection

[0429] The server periodically sends requests to the API endpoint of the store management system and receives product information, inventory information, and price information in JSON format. This process can be done using, for example, the curl library or an HTTP client. The received data is then stored in a database, for example, MongoDB.

[0430] Data analysis

[0431] The server reads the latest data from the database and identifies products whose inventory has dropped below a certain level or whose prices need to be adjusted. This analysis is done using SQL or NoSQL queries. For example, it retrieves a list of products with less than 10 units in stock and determines whether a price change is necessary based on current promotions.

[0432] Use of emotion analysis technology

[0433] The server acquires video data from cameras and sensors in the store and performs facial recognition using, for example, the OpenCV library. It then analyzes consumer emotions in real time using an emotion analysis engine (for example, Microsoft Azure Face API). The analysis results are stored in a database.

[0434] instruction generation

[0435] Based on the results of data and sentiment analysis, the server generates stock replenishment instructions and price change information in JSON format and sends it to the terminal. For example, specific instructions such as "Inventory of product A is low, so issue an instruction to replenish it" or "Update the price of product B on the digital price tag" can be included.

[0436] Generate a voice announcement

[0437] The server collects information about special sales events and limited-time sales, and generates optimal announcement content while referring to consumer sentiment data. The generated text is converted into an audio file using Google Text-to-Speech API or similar and sent to the device. For example, a voice announcement such as "Our limited-time sale starts at 3 p.m. All items are 30% off" may be created.

[0438] Terminal handling

[0439] View pricing information

[0440] The terminal parses the JSON data received from the server and displays the new price on the digital price tag. For example, if product B is 10% off, the terminal displays this information on the E-ink display.

[0441] Broadcast announcements

[0442] The device receives the audio file from the server, stores it in local storage, and plays it from the in-store speakers at the specified time. As a specific example of operation, the audio file is downloaded using the wget command and played based on a pre-set schedule.

[0443] Staff Notification

[0444] The device extracts replenishment instructions from the server using JSON data and sends notifications to store staff members' smartphones using the Firebase Cloud Messaging service. The notifications include specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[0445] User Behavior

[0446] Staff behavior

[0447] The user, a store staff member, receives the notification from the device and replenishes the products according to the instructions. For example, the staff member checks the notification on their smartphone, quickly retrieves product A from the warehouse, and replenishes it on the storefront.

[0448] Consumer behavior

[0449] The consumer user is encouraged to make a purchase by checking the new price on the digital price tag or the voice announcement over the in-store speaker. For example, the user checks the new price of a special sale item B, picks up the item, and purchases it.

[0450] Prompt Sentence Examples

[0451] "Please explain the process of a program that analyzes product information obtained from the store management system, generates replenishment instructions for items that are low on stock, and notifies store staff."

[0452] In this way, the present invention is a system that realizes more efficient and effective store operations and an improved customer experience through close cooperation between the server, terminals, and users.

[0453] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0454] Server Processing

[0455] Data collection

[0456] Step 1:

[0457] The server prepares an API client and accesses the API endpoint of the store management system. This is achieved by issuing an HTTP request using, for example, the curl library. The input is the API endpoint URL, and the output is a JSON-formatted response containing product information, inventory information, and price information.

[0458] Step 2:

[0459] The server parses the received JSON format data and extracts the necessary information. Specifically, it uses a JSON parser to convert the data into an object and extracts information such as product name, stock quantity, and price. The input is JSON data, and the output is the parsed data object.

[0460] Step 3:

[0461] The server stores the parsed data in a database. For example, it uses the MongoDB insertOne method to insert each product's information into the database. The input is the parsed data object, and the output is the result stored in the database.

[0462] Data analysis

[0463] Step 1:

[0464] The server retrieves the latest inventory and pricing information from the database by issuing a query with specific criteria, for example using the MongoDB find method. The input is the query criteria, and the output is the data object that is the query result.

[0465] Step 2:

[0466] The server identifies products whose inventory has fallen below a certain level or whose prices need to be changed by filtering the data it retrieves to create a list of products with inventory levels of 10 or less or that are on a discount. The input is the query results from the database, and the output is the list of identified products.

[0467] Step 3:

[0468] The server generates replenishment instructions and price change information based on the information of the identified products. For example, if there are 10 or fewer products in stock, it creates a specific instruction such as "Replenish product A." The input is a list of identified products, and the output is the generated instructions and price change information.

[0469] Use of emotion analysis technology

[0470] Step 1:

[0471] The server collects video data obtained from cameras and sensors. This is done, for example, by using the camera's API to acquire video in real time. The input is video data from the camera, and the output is image data for each frame.

[0472] Step 2:

[0473] The server sends the video data to an emotion analysis engine to analyze consumer emotions. Specifically, it uses OpenCV to perform facial recognition and sends the results to an emotion analysis engine (for example, Microsoft Azure Face API). The input is image data for each frame, and the output is emotional data as the analysis result.

[0474] Step 3:

[0475] The server saves the analysis results in a database and updates the results in real time. The input is emotion data as the analysis result, and the output is the result saved in the database.

[0476] instruction generation

[0477] Step 1:

[0478] The server combines the results of data analysis and sentiment analysis to generate replenishment instructions and price change information. Specifically, it generates replenishment instructions for low-stock items based on the data analysis results and optimizes the timing of price changes based on the sentiment analysis results. The input is the analysis results, and the output is the generated instructions and price change information.

[0479] Step 2:

[0480] The server converts the generated instructions and price change information into JSON format and sends it to the terminal. The input is the generated instructions and price change information, and the output is JSON format data.

[0481] Generate a voice announcement

[0482] Step 1:

[0483] The server collects information about special sales events and limited-time sales, and determines the content of announcements. Specifically, it creates announcement content based on a pre-set schedule and the results of sentiment analysis. The input is schedule information and sentiment analysis results, and the output is announcement text.

[0484] Step 2:

[0485] The server converts the generated announcement text into an audio file. Specifically, it uses the Google Text-to-Speech API to convert text to audio. The input is the announcement text, and the output is an audio file.

[0486] Step 3:

[0487] The server sends the generated audio file to the terminal. The input is the audio file, and the output is the transmission result to the terminal.

[0488] Terminal handling

[0489] View pricing information

[0490] Step 1:

[0491] The terminal parses the JSON data received from the server and extracts new price information. The input is the received JSON data and the output is the extracted price information.

[0492] Step 2:

[0493] The terminal displays the extracted price information on a digital price tag, specifically by updating the new price on the E-ink display. The input is the extracted price information and the output is the displayed price.

[0494] Broadcast announcements

[0495] Step 1:

[0496] The device saves the audio file received from the server in local storage. The input is the audio file, and the output is the result saved in local storage.

[0497] Step 2:

[0498] The terminal plays the stored audio file at the appropriate time. Specifically, it plays the audio through the store's speakers. The input is the stored audio file, and the output is the played audio.

[0499] Staff Notification

[0500] Step 1:

[0501] The terminal parses the replenishment order received from the server and extracts the necessary information. The input is the received JSON data, and the output is the extracted replenishment order.

[0502] Step 2:

[0503] The terminal notifies the extracted replenishment instructions to the store staff's smartphones. Specifically, it sends notifications using the Firebase Cloud Messaging service. The input is the extracted replenishment instructions, and the output is the sent notification.

[0504] User Behavior

[0505] Staff behavior

[0506] Step 1:

[0507] The user (store staff) receives a replenishment instruction notification on their smartphone. The input is the smartphone, and the output is the received notification.

[0508] Step 2:

[0509] The user replenishes the products according to the notification. Specifically, the staff retrieves the specified products from the warehouse and replenishes them in the store. The input is the received notification, and the output is the replenished products.

[0510] Consumer behavior

[0511] Step 1:

[0512] The user (consumer) checks the new price information displayed on the digital price tag. The input is the digital price tag, and the output is the checked price information.

[0513] Step 2:

[0514] Users listen to audio announcements from in-store speakers, which stimulates their desire to make a purchase. Specifically, they pick up and purchase products based on information about special sales and time-limited sales. The input is the audio announcement, and the output is the purchased product.

[0515] (Application example 2)

[0516] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0517] With conventional store management systems, inventory management and pricing are time-consuming and place a heavy burden on store staff. Furthermore, it is not possible to grasp consumer sentiment and behavior in real time, making it difficult to provide optimal services. Therefore, there is a need for efficient and accurate inventory management, price changes, and flexible service provision in response to consumer behavior.

[0518] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for generating and sending the generated announcement content as a voice announcement, and a terminal for displaying the generated price change information and playing the voice announcement. In this system, the server includes means for generating and optimizing the voice announcement using a generative AI model, and means for inputting prompt sentences into the generative AI model to create the voice announcement. This enables efficient and accurate inventory management and price changes, as well as the provision of optimal services based on consumer emotions and behavior.

[0519] A "store management system" is a system that manages product information, inventory information, and price information within a store.

[0520] "Product information" is attribute data such as the name, model number, and description of each product.

[0521] "Stock information" is data that indicates the current stock quantity of a particular product.

[0522] "Price information" is data indicating the selling price and discount information of each product.

[0523] "Means of collection" refers to the methods and functions for periodically obtaining necessary information from the store management system.

[0524] "Means for analyzing" refers to methods or functions for analyzing collected data and identifying products whose inventory is below a certain level or products that require price changes.

[0525] "Price change information" is data indicating an instruction to change the price of a specific product.

[0526] A "replenishment instruction" is an instruction indicating that a product that is low in stock needs to be replenished.

[0527] "Terminal" refers to a device (e.g., tablet, smartphone) used in a store to display information, receive instructions, etc.

[0528] A "generative AI model" is a model that uses artificial intelligence technology to generate voice announcements and other information.

[0529] A "prompt" is a textual instruction that is input to a generative AI model.

[0530] First, the server periodically collects product information, inventory information, and price information from the store management system via API and receives this data in JSON format. For example, it obtains information such as whether there are 10 or fewer units of product A in stock and whether the price is subject to a discount.

[0531] The server then analyzes the collected data to identify products that are out of stock or that need to be repriced. During the analysis process, the server lists products with inventory levels below 10 and determines whether a price change is necessary based on discount campaign information.

[0532] The server uses a generative AI model to collect emotional data from consumers in the store and analyze it in real time. This emotional data is obtained from cameras and sensors, and emotions are inferred from the consumer's facial expressions and behavior. Based on the results of this analysis, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Reflect the price change for product B on the digital price tag."

[0533] Furthermore, the server uses a generative AI model to generate announcement content based on information about special sales events and limited-time sales, as well as consumer sentiment data. For example, it creates a voice message such as, "Limited-time sales start at 3 p.m. All items are 30% off," and sends it to the device.

[0534] The terminal analyzes the price information received from the server and displays it on the digital price tag in the store. For example, if it receives information that product B is 10% off, it displays the new price on the price tag. It also saves the received audio file in local storage and plays it on the in-store speaker at the appropriate time. For example, it announces, "The 3 PM limited-time sale has begun."

[0535] Furthermore, replenishment instructions from the server are sent to the store staff's terminals. The notification content includes specific instructions such as "Product A is low in stock. Please replenish from the warehouse."

[0536] The main hardware used includes smartphones and tablets, while the software uses requests for API communication, pyttsx3 for speech synthesis, and playsound for audio file playback.

[0537] As a specific example, when a time sale starts at 3 p.m., the app will send a notification to store staff saying, "Product A is out of stock. Please replenish it from the warehouse," and at the same time, it will play an audio announcement over the in-store speakers saying, "The time sale starts at 3 p.m. All items are 30% off."

[0538] An example of a prompt for a generative AI model is as follows:

[0539] "Generate a voice announcement for a limited-time sale starting at 3 PM with a 30% discount."

[0540] "Generate replenishment orders for items that are low on stock."

[0541] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0542] Step 1:

[0543] The server periodically collects product information, inventory information, and price information from the store management system via API. Specifically, the server sends a request to the API endpoint and receives product information, inventory information, and price information data in JSON format. For example, obtain information that the inventory quantity of product A is 10 or less. The input for this step is an API request, and the output is JSON format data.

[0544] Step 2:

[0545] The server analyzes the collected JSON data and identifies products whose inventory is below a certain level or whose prices need to be changed. Specifically, it lists products with inventory quantities of less than 10 units and extracts products whose prices need to be changed due to discount campaign information. The input for this step is the collected JSON data, and the output is a list of products with low inventory and products whose prices need to be changed.

[0546] Step 3:

[0547] The server uses the emotion engine to collect emotional data from in-store consumers via cameras and sensors and analyze it in real time. Specifically, it analyzes the video data from the cameras and infers emotions from the consumers' facial expressions and behavior. The input for this step is the video data, and the output is the analyzed emotional data of the consumers.

[0548] Step 4:

[0549] The server generates price change information and replenishment instructions based on the analysis results. Specifically, it generates JSON data containing instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Reflect the price change for product B on the digital price tag." The input for this step is a list of products with low stock and a list of products that need price changes, and the output is JSON data containing price change information and replenishment instructions.

[0550] Step 5:

[0551] The server uses the generative AI model to generate a voice announcement based on information about special sales events and limited-time sales, as well as consumer emotional data. Specifically, it generates a voice message such as, "Our limited-time sale starts at 3 PM. All items are 30% off." The input for this step is a prompt and emotional data, and the output is the generated voice file.

[0552] Step 6:

[0553] The terminal analyzes the price information received from the server and displays the new price on the digital price tag. Specifically, if it receives information that product B is 10% off, it displays the new price on the price tag. The input to this step is JSON data containing the price change information, and the output is the updated digital price tag.

[0554] Step 7:

[0555] The device stores the audio file received from the server in local storage and plays it on the in-store speakers at the appropriate time. For example, play a voice announcement such as "A limited-time sale has started at 3 PM." The input of this step is the generated audio file, and the output is a voice announcement played over the in-store speakers.

[0556] Step 8:

[0557] A replenishment instruction is sent to the store staff's terminal. The notification includes specific instructions such as "Product A is low in stock. Please replenish it from the warehouse." Specifically, a push notification is sent to the terminal so that the staff can confirm the instructions. The input to this step is JSON data containing the replenishment instruction, and the output is a notification on the store staff's terminal.

[0558] Step 9:

[0559] The store staff member who receives the replenishment instruction at the terminal follows the instruction and retrieves product A from the warehouse to replenish the stock. Specifically, the staff member goes to the warehouse, retrieves the products that need to be replenished, and displays them on the shelves. The input for this step is the replenishment instruction received by the staff member, and the output is the replenished products.

[0560] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0561] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0562] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0563] [Second embodiment]

[0564] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0565] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0566] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0567] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0568] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0569] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0570] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0571] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0572] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0573] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0574] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0575] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0576] Server-side processing

[0577] Data collection

[0578] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, the server obtains information that there are 10 or fewer units of product A in stock and that the price is discounted.

[0579] Data analysis

[0580] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[0581] instruction generation

[0582] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[0583] Generate a voice announcement

[0584] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[0585] Terminal side processing

[0586] View pricing information

[0587] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives information that product B is 10% off and displays the new price on the price tag.

[0588] Broadcast announcements

[0589] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[0590] Staff Notification

[0591] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[0592] User processing

[0593] Staff behavior

[0594] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[0595] Consumer behavior

[0596] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. Specifically, the user checks the new price of the sale item B, picks it up, and purchases it.

[0597] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, thereby improving consumer experience and streamlining store operations.

[0598] The processing flow will be explained below.

[0599] Server-side processing steps

[0600] Data collection

[0601] Step 1:

[0602] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[0603] Step 2:

[0604] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[0605] Data analysis

[0606] Step 3:

[0607] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[0608] Step 4:

[0609] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[0610] Step 5:

[0611] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[0612] instruction generation

[0613] Step 6:

[0614] The server generates price change information for the identified product in JSON format, including the new price.

[0615] Step 7:

[0616] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[0617] Generate a voice announcement

[0618] Step 8:

[0619] The server generates announcement content as text based on information about special sale events and time sales.

[0620] Step 9:

[0621] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[0622] Step 10:

[0623] The server prepares to send the generated audio file to the in-store terminal.

[0624] Terminal processing steps

[0625] View pricing information

[0626] Step 1:

[0627] The terminal receives price information in JSON format sent from the server.

[0628] Step 2:

[0629] The terminal parses the received JSON data and extracts the product ID and new price.

[0630] Step 3:

[0631] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[0632] Broadcast announcements

[0633] Step 4:

[0634] The terminal receives the audio file sent from the server.

[0635] Step 5:

[0636] The terminal stores the received audio file in local storage.

[0637] Step 6:

[0638] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[0639] Staff Notification

[0640] Step 7:

[0641] The terminal receives a replenishment instruction from the server.

[0642] Step 8:

[0643] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[0644] Step 9:

[0645] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[0646] User processing steps

[0647] Staff behavior

[0648] Step 1:

[0649] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[0650] Step 2:

[0651] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[0652] Consumer behavior

[0653] Step 3:

[0654] Users (consumers) check digital price tags and voice announcements in the store to find out about special sales.

[0655] Step 4:

[0656] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[0657] Through the above processing steps, the server, terminals, and users work together to realize efficient and effective time sales and special sale events, as well as inventory management.

[0658] Example 1

[0659] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0660] There is a need for automated inventory management, price updates, and voice announcements regarding special sale events. However, current systems make it difficult to perform these tasks efficiently and effectively. In particular, there are limited ways to respond quickly when inventory is low or prices need to be changed, making it difficult to improve the consumer experience and streamline store operations.

[0661] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0662] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating and transmitting price change information and replenishment instructions to terminals in the store, means for generating and transmitting the generated announcement content as voice announcements, a terminal for displaying the generated price change information and playing the voice announcements, means for notifying store staff terminals of replenishment instructions, and means for generating voice announcements using a generative AI model. This enables inventory management, price information updates, and the effective implementation of special sale events.

[0663] A "store management system" is an integrated system of software and hardware for managing product information, inventory information, and price information within a store.

[0664] The "server" is a computer system that analyzes and processes information collected from the store management system and sends generated instructions and voice announcements to terminals within the store.

[0665] "Product information" refers to basic product data such as product name, product category, and product code.

[0666] "Inventory information" refers to information such as the current inventory quantity and inventory location of each product.

[0667] "Price information" is data including the current selling price and discount information for each product.

[0668] "API Request" means a message requesting data from another system via an Application Programming Interface.

[0669] "JSON format" is an abbreviation for JavaScript Object Notation, a data representation format, and a text format with a structure that is easy for both humans and machines to read and write.

[0670] "Multimodal AI technology" is an artificial intelligence technology that processes multiple types of data (such as text, audio, and images) in an integrated manner.

[0671] A "terminal" is a device that displays and plays instructions and information received from the server and enables interaction with store staff and consumers.

[0672] "Generative AI models" are algorithms and models that use artificial intelligence to generate appropriate data and responses for specific tasks.

[0673] "Price change information" is data indicating how the selling price of a product should be changed.

[0674] "Voice announcements" are announcements that convey information about special sales events, time sales, etc. to consumers and staff via voice.

[0675] "Replenishment instruction" is a message to instruct the replenishment of products that are out of stock.

[0676] The present invention provides a system that improves the efficiency of product inventory management, price information updates, and sales events through cooperation between a store management system, a server, terminals, and users. Specific embodiments for carrying out the invention are described below.

[0677] Server-side processing

[0678] Data collection

[0679] The server periodically collects product information, inventory information, and price information from the store management system. This collection process uses API requests and receives data in JSON format. For example, the server obtains information such as "there are 10 or fewer units of product A in stock and the price is discounted."

[0680] Data analysis

[0681] The server analyzes the received data and identifies products that are out of stock or need a price change. The analysis involves parsing the data and making conditional decisions, such as listing products with less than 10 units in stock. It then determines whether a price change is necessary based on discount campaign information.

[0682] instruction generation

[0683] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[0684] Generate a voice announcement

[0685] The server uses the generative AI model to generate a voice announcement, such as "Time sale starts at 3 PM. All items are 30% off," and sends it to the device.

[0686] Terminal side processing

[0687] View pricing information

[0688] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[0689] Broadcast announcements

[0690] The device receives the voice announcement file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time. Specifically, it announces, "The limited-time sale has begun at 3 PM."

[0691] Staff Notification

[0692] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[0693] User processing

[0694] Staff behavior

[0695] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[0696] Consumer behavior

[0697] The user (consumer) checks the latest sale information through digital price tags or voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[0698] Examples of prompt statements

[0699] Below are some specific examples of prompt sentences to input into the generative AI model.

[0700] You are an expert in store management systems. In this system, the store server collects product information, analyzes the data, and generates instructions for inventory shortages and price changes. It also creates voice announcements and sends them to terminals. The terminals then display price information, play voice announcements, and notify staff of replenishment instructions. Please explain this process in detail.

[0701] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0702] Server-side processing

[0703] Step 1: Start collecting data

[0704] The server sends an API request to the store management system. This request includes parameters to retrieve product information, inventory information, and price information. The server executes this process according to a regular schedule.

[0705] Input: API request parameters

[0706] Output: Response data in JSON format

[0707] Step 2: Receiving data

[0708] The server receives JSON format data as a response from the store management system, which includes the stock quantity, price information, discount information, etc. for each product.

[0709] Input: Response data in JSON format

[0710] Output: A parsable JSON data object

[0711] Step 3: Begin data analysis

[0712] The server parses the received JSON data to analyze it. Specifically, it extracts the stock quantity and price for each product and prepares the data for analysis.

[0713] Input: JSON data object

[0714] Output: Extracted inventory quantity and price information

[0715] Step 4: Identifying defects and important information

[0716] The server uses the extracted data to identify products whose inventory has fallen below a certain number (for example, 10 units) or whose prices have changed. This information serves as the basis for generating new instruction data.

[0717] Input: Extracted inventory quantity, price information

[0718] Output: Stock shortage list, price change list

[0719] Step 5: Start generating instructions

[0720] The server generates price change information and replenishment instructions based on the identified information, such as "issue a replenishment instruction because product A is out of stock" or "reflect the price of product B on the digital price tag."

[0721] Input: Stock shortage list, price change list

[0722] Output: Price change instructions, replenishment instructions

[0723] Step 6: Sending instruction data

[0724] The server sends the generated instruction data in JSON format to the device, allowing the device to perform appropriate updates based on the received data.

[0725] Input: Price change instructions, replenishment instructions

[0726] Output: JSON data sent to the terminal

[0727] Step 7: Start generating voice announcements

[0728] The server uses a generative AI model to generate voice announcements, such as "A limited-time sale starts at 3 p.m. All items are 30% off" based on information about special sales events and limited-time sales.

[0729] Input: Special sale event information, limited time sale information

[0730] Output: Voice announcement data

[0731] Step 8: Send a voice announcement

[0732] The server sends the generated voice announcement file to the terminal, allowing each terminal to play the announcement at the appropriate time.

[0733] Input: Voice announcement data

[0734] Output: Audio file sent to the device

[0735] Terminal side processing

[0736] Step 1: Receiving price information

[0737] The terminal receives price information in JSON format from the server, which includes specific price change instructions.

[0738] Input: Price change information in JSON format

[0739] Output: Price change instruction data

[0740] Step 2: Parse the price information

[0741] The terminal analyzes the received data and identifies which items require price changes, for example, identifying that item B is on a 10% discount.

[0742] Input: Price change instruction data

[0743] Output: Updated pricing information

[0744] Step 3: Update your digital price tags

[0745] Based on the analysis, the terminal will display the new price on a digital price tag for consumer verification.

[0746] Input: Updated pricing information

[0747] Output: New price displayed on the digital price tag

[0748] Step 4: Receive a voice announcement

[0749] The device retrieves the voice announcement file received from the server and stores it in local storage.

[0750] Input: Audio file sent to the device

[0751] Output: Saved audio file

[0752] Step 5: Play an announcement

[0753] The device then plays the stored audio announcement over the in-store speakers at the appropriate time, for example, announcing, "The 3 PM limited-time sale has begun."

[0754] Input: Saved audio file

[0755] Output: Played audio announcement

[0756] Step 6: Receiving replenishment orders

[0757] The terminal receives a replenishment instruction from the server, which is then sent to the terminal of the store staff member.

[0758] Input: Refill order sent to terminal

[0759] Output: Replenishment message sent to store staff

[0760] User processing

[0761] Step 1: Confirm replenishment instructions

[0762] The user (store staff) checks the replenishment instruction from the terminal. Specifically, a message is displayed saying, "Product A is low in stock. Please replenish from the warehouse."

[0763] Input: Replenishment instructions notified

[0764] Output: Confirmed replenishment order

[0765] Step 2: Replenish inventory

[0766] The user promptly replenishes inventory based on the confirmed instructions, for example, by taking product A from the warehouse and stocking it in the store.

[0767] Input: Confirmed replenishment order

[0768] Output: Replenished products

[0769] Step 3: Check for special offers

[0770] Users (consumers) check the latest sales information through digital price tags or voice announcements in the store. For example, they check the new price of product B on sale.

[0771] Input: Digital price tag, voice announcement

[0772] Output: Confirmed sale information

[0773] Step 4: Shop the sale items

[0774] The user purchases a product based on the sale information they have checked. For example, they pick up and purchase product B, which is on sale.

[0775] Input: Confirmed sale information

[0776] Output: Purchased items

[0777] Through these steps, the system can efficiently and effectively manage inventory, update price information, and automate sales events.

[0778] (Application example 1)

[0779] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0780] Conventional store management systems did not sufficiently streamline inventory management and price changes, and notifications of special sales and limited-time sales were often done manually. It was also difficult for store staff to share information in real time when replenishing inventory. Furthermore, effective sales information was not provided to consumers, resulting in lost sales opportunities. Therefore, there is a need for a system that automates inventory management, price changes, and sales information notifications, and provides appropriate information to consumers and store staff in real time.

[0781] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0782] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for providing consumers with real-time sales information and limited-time sale start notifications using smartphones or tablet devices, means for providing store staff with real-time inventory status confirmation and replenishment instruction notification functions, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management, price change and sale information notifications, and real-time information provision to consumers and store staff.

[0783] Key Word Definitions

[0784] A "store management system" is an integrated information system for managing products, inventory, prices, etc. within a store.

[0785] "Product information" means data containing detailed information about each product, typically including the name, price, category, and availability.

[0786] "Inventory information" is data that indicates the current quantity of each product in the store and in the warehouse.

[0787] "Price information" is data that includes the current selling price and discount information for each product.

[0788] "Analysis" refers to the process of extracting and determining information for a specific purpose from collected data.

[0789] "Special sale information" is information indicating special sales conditions and discount details for products that will be offered within a certain period of time.

[0790] A "time sale" is a promotional event where products are sold at a discounted price for a specific time frame.

[0791] "Server" refers to a computer system that collects, analyzes, and distributes data over a network.

[0792] A "terminal" is a device for displaying and operating information, and includes smartphones and tablet devices.

[0793] "Multimodal AI technology" is an artificial intelligence technology that integrates multiple data modalities (e.g., voice, text, images) to perform analysis and decision-making.

[0794] A "voice announcement" is a means of conveying specific information using voice data.

[0795] "Real-time" refers to the generation and processing of data occurring immediately, without delay.

[0796] "Push notifications" are a technology that sends information to mobile devices in real time.

[0797] MODE FOR CARRYING OUT THE INVENTION

[0798] Server-side processing

[0799] Data collection

[0800] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information such as when there are 10 or fewer units of a specific product A in stock or when the price is discounted can be obtained.

[0801] Data analysis

[0802] The server analyzes the acquired data and identifies products that are low in stock or products subject to price changes. For example, it lists products with less than 10 units in stock or products for which discount campaigns are applied. This identifies products subject to special sales or limited-time sales.

[0803] instruction generation

[0804] The server generates price change information and replenishment instructions based on the analysis results. The generated data is sent to the terminal in JSON format. For example, it may contain specific instructions such as "issue a replenishment order because product A is out of stock" or "reflect the price change of product B on the digital price tag."

[0805] Generate a voice announcement

[0806] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[0807] Terminal side processing

[0808] View pricing information

[0809] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives discount information for product B and displays the new price on the price tag.

[0810] Broadcast announcements

[0811] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[0812] Staff Notification

[0813] The terminal notifies the store staff terminal of the replenishment instruction from the server. For example, a message such as "Product A is low in stock. Please replenish from the warehouse" is displayed.

[0814] User processing

[0815] Staff behavior

[0816] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. For example, they take product A from the warehouse and replenish it on the storefront.

[0817] Consumer behavior

[0818] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[0819] Hardware and software used

[0820] Server: A high-performance server is used, and a web framework such as Flask is used.

[0821] Devices: Smartphones, tablets, digital price tags, etc.

[0822] Software: Python, REST API, React Native, text-to-speech API, multimodal AI, etc.

[0823] Examples and prompts

[0824] For example, if you want to automatically issue replenishment instructions for specific products and update price change information in real time, the following prompt sentence is effective:

[0825] "Write a program that generates replenishment orders for low-stock items and updates digital price tags based on price change information. Also, add the ability to generate audio announcements about special sales and send them to a smartphone app."

[0826] The above is a specific embodiment for carrying out the present invention.

[0827] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0828] Program processing flow

[0829] Step 1:

[0830] Data collection

[0831] The server periodically collects product information, inventory information, and price information in JSON format from the store management system through an API. The API endpoint and authentication information are required as input. The data collection process involves sending an HTTP GET request and parsing the JSON data received as a response to extract fields such as product name, inventory quantity, price, and discount information. The output is parseable JSON data.

[0832] Step 2:

[0833] Data analysis

[0834] The server parses the collected JSON data. The JSON data to be parsed is used as input. The data parsing process filters based on specific conditions (for example, items with less than 10 units in stock, items with discount campaigns applied, etc.). Specifically, it lists items that are low in stock and items that need to be repriced. The output is a list of low-stock items and items that need to be repriced.

[0835] Step 3:

[0836] instruction generation

[0837] The server generates price change information and replenishment instructions based on the analysis results. As input, it requires a list of low-stock items and a list of items subject to price changes. In the instruction generation process, it generates JSON data containing stock replenishment instructions and new price information for each item. The generated data is sent to the terminal in the store via API. The output is replenishment instructions and price change information in JSON format, which are sent to the terminal.

[0838] Step 4:

[0839] Generate a voice announcement

[0840] The server generates a voice announcement using multimodal AI technology. The generated instruction content is used as input. The voice announcement generation process generates voice data using a text-to-speech API, which converts text content into an audio file. Specifically, it creates an announcement such as, "A limited-time sale starts at 3:00 PM. All items are 30% off." The output is the URL of the audio file.

[0841] Step 5:

[0842] View pricing information

[0843] The terminal parses the price change information received from the server and displays it on the digital price tag. The received price change information in JSON format is used as input. The price information display process immediately reflects the new price on the digital price tag. Specifically, it updates the display content of the price tag and applies the information to the product in the store. The output is the updated price tag display.

[0844] Step 6:

[0845] Broadcast announcements

[0846] The terminal stores the voice announcement file received from the server in local storage and plays it through the in-store speakers at the specified time. The URL of the voice file and playback timing information are used as input. The voice announcement broadcast process downloads the voice file and plays it on the playback device at the appropriate time. The output is the announcement broadcast in the store.

[0847] Step 7:

[0848] Staff Notification

[0849] The terminal notifies the store staff terminal of the replenishment instruction from the server. JSON data containing the replenishment instruction is used as input. The notification process sends a push notification to the store staff device and displays information about the products that need to be replenished. Specifically, it displays a message on the smartphone or tablet saying, "Product A is low in stock. Please replenish it from the warehouse." The output is a notification of the replenishment instruction to the staff.

[0850] Step 8:

[0851] Staff behavior

[0852] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes inventory. The replenishment instruction information displayed on the terminal is used as input. The behavioral process executes specific steps to retrieve the specified products from the warehouse and replenish them in the store. The output is the replenishment of products in the store and an inventory update.

[0853] Step 9:

[0854] Consumer behavior

[0855] Users (consumers) check the latest sale information through digital price tags and voice announcements in the store. The sale information obtained from the price tags and announcements is used as input. In the behavioral process, the user picks up a sale item and takes action to actually purchase it. The output is the sales record resulting from the purchase of the item.

[0856] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0857] Server-side processing

[0858] Data collection

[0859] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information is obtained that product A has 10 or fewer units in stock and is eligible for a discount.

[0860] Data analysis

[0861] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[0862] Use of emotion engine

[0863] The server uses an emotion engine to collect and analyze in real time the emotional data of consumers in the store. This emotional data is acquired from cameras and sensors, and emotions are inferred from the consumers' facial expressions and behavior.

[0864] instruction generation

[0865] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. For example, it may include instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[0866] Generate a voice announcement

[0867] The server optimizes the announcement content based on information about special sales events and limited-time sales, as well as consumer sentiment data. For example, it creates a voice message such as, "Our limited-time sale starts at 3 p.m. All items are 30% off," and sends it to the device.

[0868] Terminal side processing

[0869] View pricing information

[0870] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[0871] Broadcast announcements

[0872] The device receives the audio file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time, for example announcing, "The limited-time sale has begun at 3 PM."

[0873] Staff Notification

[0874] The terminal notifies the store staff terminal of the replenishment instruction from the server. The notification content includes specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[0875] User processing

[0876] Staff behavior

[0877] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[0878] Consumer behavior

[0879] The user (consumer) checks the digital price tag, voice announcements, and emotion-based optimization information in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[0880] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and further improves the consumer experience by utilizing an emotion engine.

[0881] The processing flow will be explained below.

[0882] Server-side processing steps

[0883] Data collection

[0884] Step 1:

[0885] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[0886] Step 2:

[0887] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[0888] Data analysis

[0889] Step 3:

[0890] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[0891] Step 4:

[0892] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[0893] Step 5:

[0894] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[0895] Use of emotion engine

[0896] Step 6:

[0897] The server collects consumer facial expression and behavioral data obtained from cameras and sensors within the store.

[0898] Step 7:

[0899] The server uses an emotion engine to analyze the consumer's emotions in real time from the collected data, inferring, for example, whether the consumer is excited or bored.

[0900] instruction generation

[0901] Step 8:

[0902] Based on the analysis results, the server generates price change information and replenishment instructions, and the generated data is sent to the terminal in JSON format.

[0903] Step 9:

[0904] The server generates price change information for the identified product in JSON format, including the new price.

[0905] Step 10:

[0906] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[0907] Generate a voice announcement

[0908] Step 11:

[0909] The server optimizes the content of announcements based on information about special sales events and limited-time sales, as well as consumer sentiment data.

[0910] Step 12:

[0911] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[0912] Step 13:

[0913] The server prepares to send the generated audio file to the in-store terminal.

[0914] Terminal processing steps

[0915] View pricing information

[0916] Step 1:

[0917] The terminal receives price information in JSON format sent from the server.

[0918] Step 2:

[0919] The terminal parses the received JSON data and extracts the product ID and new price.

[0920] Step 3:

[0921] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[0922] Broadcast announcements

[0923] Step 4:

[0924] The terminal receives the audio file sent from the server.

[0925] Step 5:

[0926] The terminal stores the received audio file in local storage.

[0927] Step 6:

[0928] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[0929] Staff Notification

[0930] Step 7:

[0931] The terminal receives a replenishment instruction from the server.

[0932] Step 8:

[0933] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[0934] Step 9:

[0935] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[0936] User processing steps

[0937] Staff behavior

[0938] Step 1:

[0939] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[0940] Step 2:

[0941] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[0942] Consumer behavior

[0943] Step 3:

[0944] Users (consumers) see digital price tags, voice announcements, and sentiment-based optimization information in the store.

[0945] Step 4:

[0946] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[0947] Example 2

[0948] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0949] In today's retail industry, efficient and effective inventory management, price updates, and even marketing activities are extremely important. However, traditional store management systems face challenges in that they are unable to provide real-time data and optimally timed information based on consumer behavior and emotions. Furthermore, inventory shortages and missed price changes frequently occur, resulting in reduced store operational efficiency.

[0950] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for collecting consumer emotion data in the store and analyzing it in real time using emotion analysis technology, means for generating price change information and replenishment instructions and transmitting them to terminals in the store, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management and price updates to be performed more efficiently and effectively than before, and enables information to be provided at the optimal time based on consumer emotions and behavior. Furthermore, it enables quick notification of replenishment instructions to store staff and real-time announcements to consumers, thereby improving the efficiency of store operations and customer satisfaction.

[0951] A "store management system" is a system for comprehensively managing a store's inventory, sales, pricing, etc.

[0952] "Product information" refers to basic information about a product, such as product name, product code, classification, and description.

[0953] "Inventory information" refers to data regarding the inventory quantity of each product, inventory history, inventory location, etc.

[0954] "Price information" refers to data including the current price of each product, past price change history, discount information, etc.

[0955] "Analysis" refers to the process of determining whether collected data meets certain conditions and extracting relevant information.

[0956] "Emotion analysis technology" refers to technology that uses data obtained from cameras and sensors to infer emotions from consumers' facial expressions and behavior.

[0957] "Price change information" refers to information for updating an existing price to a new price.

[0958] "Replenishment Instructions" refers to specific instructions to notify store staff to replenish items that are low in stock.

[0959] "Announcement content" refers to announcements made in stores, including information about special sales and limited-time sales.

[0960] "Voice announcement" refers to broadcasting the generated announcement content in audio format within the store.

[0961] "Terminal" refers to a device that communicates with a server to receive information and display or play audio.

[0962] The present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and also improves consumer experience by utilizing emotion analysis technology.

[0963] Server Processing

[0964] Data collection

[0965] The server periodically sends requests to the API endpoint of the store management system and receives product information, inventory information, and price information in JSON format. This process can be done using, for example, the curl library or an HTTP client. The received data is then stored in a database, for example, MongoDB.

[0966] Data analysis

[0967] The server reads the latest data from the database and identifies products whose inventory has dropped below a certain level or whose prices need to be adjusted. This analysis is done using SQL or NoSQL queries. For example, it retrieves a list of products with less than 10 units in stock and determines whether a price change is necessary based on current promotions.

[0968] Use of emotion analysis technology

[0969] The server acquires video data from cameras and sensors in the store and performs facial recognition using, for example, the OpenCV library. It then analyzes consumer emotions in real time using an emotion analysis engine (for example, Microsoft Azure Face API). The analysis results are stored in a database.

[0970] instruction generation

[0971] Based on the results of data and sentiment analysis, the server generates stock replenishment instructions and price change information in JSON format and sends it to the terminal. For example, specific instructions such as "Inventory of product A is low, so issue an instruction to replenish it" or "Update the price of product B on the digital price tag" can be included.

[0972] Generate a voice announcement

[0973] The server collects information about special sales events and limited-time sales, and generates optimal announcement content while referring to consumer sentiment data. The generated text is converted into an audio file using Google Text-to-Speech API or similar and sent to the device. For example, a voice announcement such as "Our limited-time sale starts at 3 p.m. All items are 30% off" may be created.

[0974] Terminal handling

[0975] View pricing information

[0976] The terminal parses the JSON data received from the server and displays the new price on the digital price tag. For example, if product B is 10% off, the terminal displays this information on the E-ink display.

[0977] Broadcast announcements

[0978] The device receives the audio file from the server, stores it in local storage, and plays it from the in-store speakers at the specified time. As a specific example of operation, the audio file is downloaded using the wget command and played based on a pre-set schedule.

[0979] Staff Notification

[0980] The device extracts replenishment instructions from the server using JSON data and sends notifications to store staff members' smartphones using the Firebase Cloud Messaging service. The notifications include specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[0981] User Behavior

[0982] Staff behavior

[0983] The user, a store staff member, receives the notification from the device and replenishes the products according to the instructions. For example, the staff member checks the notification on their smartphone, quickly retrieves product A from the warehouse, and replenishes it on the storefront.

[0984] Consumer behavior

[0985] The consumer user is encouraged to make a purchase by checking the new price on the digital price tag or the voice announcement over the in-store speaker. For example, the user checks the new price of a special sale item B, picks up the item, and purchases it.

[0986] Prompt Sentence Examples

[0987] "Please explain the process of a program that analyzes product information obtained from the store management system, generates replenishment instructions for items that are low on stock, and notifies store staff."

[0988] In this way, the present invention is a system that realizes more efficient and effective store operations and an improved customer experience through close cooperation between the server, terminals, and users.

[0989] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0990] Server Processing

[0991] Data collection

[0992] Step 1:

[0993] The server prepares an API client and accesses the API endpoint of the store management system. This is achieved by issuing an HTTP request using, for example, the curl library. The input is the API endpoint URL, and the output is a JSON-formatted response containing product information, inventory information, and price information.

[0994] Step 2:

[0995] The server parses the received JSON format data and extracts the necessary information. Specifically, it uses a JSON parser to convert the data into an object and extracts information such as product name, stock quantity, and price. The input is JSON data, and the output is the parsed data object.

[0996] Step 3:

[0997] The server stores the parsed data in a database. For example, it uses the MongoDB insertOne method to insert each product's information into the database. The input is the parsed data object, and the output is the result stored in the database.

[0998] Data analysis

[0999] Step 1:

[1000] The server retrieves the latest inventory and pricing information from the database by issuing a query with specific criteria, for example using the MongoDB find method. The input is the query criteria, and the output is the data object that is the query result.

[1001] Step 2:

[1002] The server identifies products whose inventory has fallen below a certain level or whose prices need to be changed by filtering the data it retrieves to create a list of products with inventory levels of 10 or less or that are on a discount. The input is the query results from the database, and the output is the list of identified products.

[1003] Step 3:

[1004] The server generates replenishment instructions and price change information based on the information of the identified products. For example, if there are 10 or fewer products in stock, it creates a specific instruction such as "Replenish product A." The input is a list of identified products, and the output is the generated instructions and price change information.

[1005] Use of emotion analysis technology

[1006] Step 1:

[1007] The server collects video data obtained from cameras and sensors. This is done, for example, by using the camera's API to acquire video in real time. The input is video data from the camera, and the output is image data for each frame.

[1008] Step 2:

[1009] The server sends the video data to an emotion analysis engine to analyze consumer emotions. Specifically, it uses OpenCV to perform facial recognition and sends the results to an emotion analysis engine (for example, Microsoft Azure Face API). The input is image data for each frame, and the output is emotional data as the analysis result.

[1010] Step 3:

[1011] The server saves the analysis results in a database and updates the results in real time. The input is emotion data as the analysis result, and the output is the result saved in the database.

[1012] instruction generation

[1013] Step 1:

[1014] The server combines the results of data analysis and sentiment analysis to generate replenishment instructions and price change information. Specifically, it generates replenishment instructions for low-stock items based on the data analysis results and optimizes the timing of price changes based on the sentiment analysis results. The input is the analysis results, and the output is the generated instructions and price change information.

[1015] Step 2:

[1016] The server converts the generated instructions and price change information into JSON format and sends it to the terminal. The input is the generated instructions and price change information, and the output is JSON format data.

[1017] Generate a voice announcement

[1018] Step 1:

[1019] The server collects information about special sales events and limited-time sales, and determines the content of announcements. Specifically, it creates announcement content based on a pre-set schedule and the results of sentiment analysis. The input is schedule information and sentiment analysis results, and the output is announcement text.

[1020] Step 2:

[1021] The server converts the generated announcement text into an audio file. Specifically, it uses the Google Text-to-Speech API to convert text to audio. The input is the announcement text, and the output is an audio file.

[1022] Step 3:

[1023] The server sends the generated audio file to the terminal. The input is the audio file, and the output is the transmission result to the terminal.

[1024] Terminal handling

[1025] View pricing information

[1026] Step 1:

[1027] The terminal parses the JSON data received from the server and extracts new price information. The input is the received JSON data and the output is the extracted price information.

[1028] Step 2:

[1029] The terminal displays the extracted price information on a digital price tag, specifically by updating the new price on the E-ink display. The input is the extracted price information and the output is the displayed price.

[1030] Broadcast announcements

[1031] Step 1:

[1032] The device saves the audio file received from the server in local storage. The input is the audio file, and the output is the result saved in local storage.

[1033] Step 2:

[1034] The terminal plays the stored audio file at the appropriate time. Specifically, it plays the audio through the store's speakers. The input is the stored audio file, and the output is the played audio.

[1035] Staff Notification

[1036] Step 1:

[1037] The terminal parses the replenishment order received from the server and extracts the necessary information. The input is the received JSON data, and the output is the extracted replenishment order.

[1038] Step 2:

[1039] The terminal notifies the extracted replenishment instructions to the store staff's smartphones. Specifically, it sends notifications using the Firebase Cloud Messaging service. The input is the extracted replenishment instructions, and the output is the sent notification.

[1040] User Behavior

[1041] Staff behavior

[1042] Step 1:

[1043] The user (store staff) receives a replenishment instruction notification on their smartphone. The input is the smartphone, and the output is the received notification.

[1044] Step 2:

[1045] The user replenishes the products according to the notification. Specifically, the staff retrieves the specified products from the warehouse and replenishes them in the store. The input is the received notification, and the output is the replenished products.

[1046] Consumer behavior

[1047] Step 1:

[1048] The user (consumer) checks the new price information displayed on the digital price tag. The input is the digital price tag, and the output is the checked price information.

[1049] Step 2:

[1050] Users listen to audio announcements from in-store speakers, which stimulates their desire to make a purchase. Specifically, they pick up and purchase products based on information about special sales and time-limited sales. The input is the audio announcement, and the output is the purchased product.

[1051] (Application example 2)

[1052] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1053] With conventional store management systems, inventory management and pricing are time-consuming and place a heavy burden on store staff. Furthermore, it is not possible to grasp consumer sentiment and behavior in real time, making it difficult to provide optimal services. Therefore, there is a need for efficient and accurate inventory management, price changes, and flexible service provision in response to consumer behavior.

[1054] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for generating and sending the generated announcement content as a voice announcement, and a terminal for displaying the generated price change information and playing the voice announcement. In this system, the server includes means for generating and optimizing the voice announcement using a generative AI model, and means for inputting prompt sentences into the generative AI model to create the voice announcement. This enables efficient and accurate inventory management and price changes, as well as the provision of optimal services based on consumer emotions and behavior.

[1055] A "store management system" is a system that manages product information, inventory information, and price information within a store.

[1056] "Product information" is attribute data such as the name, model number, and description of each product.

[1057] "Stock information" is data that indicates the current stock quantity of a particular product.

[1058] "Price information" is data indicating the selling price and discount information of each product.

[1059] "Means of collection" refers to the methods and functions for periodically obtaining necessary information from the store management system.

[1060] "Means for analyzing" refers to methods or functions for analyzing collected data and identifying products whose inventory is below a certain level or products that require price changes.

[1061] "Price change information" is data indicating an instruction to change the price of a specific product.

[1062] A "replenishment instruction" is an instruction indicating that a product that is low in stock needs to be replenished.

[1063] "Terminal" refers to a device (e.g., tablet, smartphone) used in a store to display information, receive instructions, etc.

[1064] A "generative AI model" is a model that uses artificial intelligence technology to generate voice announcements and other information.

[1065] A "prompt" is a textual instruction that is input to a generative AI model.

[1066] First, the server periodically collects product information, inventory information, and price information from the store management system via API and receives this data in JSON format. For example, it obtains information such as whether there are 10 or fewer units of product A in stock and whether the price is subject to a discount.

[1067] The server then analyzes the collected data to identify products that are out of stock or that need to be repriced. During the analysis process, the server lists products with inventory levels below 10 and determines whether a price change is necessary based on discount campaign information.

[1068] The server uses a generative AI model to collect emotional data from consumers in the store and analyze it in real time. This emotional data is obtained from cameras and sensors, and emotions are inferred from the consumer's facial expressions and behavior. Based on the results of this analysis, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Reflect the price change for product B on the digital price tag."

[1069] Furthermore, the server uses a generative AI model to generate announcement content based on information about special sales events and limited-time sales, as well as consumer sentiment data. For example, it creates a voice message such as, "Limited-time sales start at 3 p.m. All items are 30% off," and sends it to the device.

[1070] The terminal analyzes the price information received from the server and displays it on the digital price tag in the store. For example, if it receives information that product B is 10% off, it displays the new price on the price tag. It also saves the received audio file in local storage and plays it on the in-store speaker at the appropriate time. For example, it announces, "The 3 PM limited-time sale has begun."

[1071] Furthermore, replenishment instructions from the server are sent to the store staff's terminals. The notification content includes specific instructions such as "Product A is low in stock. Please replenish from the warehouse."

[1072] The main hardware used includes smartphones and tablets, while the software uses requests for API communication, pyttsx3 for speech synthesis, and playsound for audio file playback.

[1073] As a specific example, when a time sale starts at 3 p.m., the app will send a notification to store staff saying, "Product A is out of stock. Please replenish it from the warehouse," and at the same time, it will play an audio announcement over the in-store speakers saying, "The time sale starts at 3 p.m. All items are 30% off."

[1074] An example of a prompt for a generative AI model is as follows:

[1075] "Generate a voice announcement for a limited-time sale starting at 3 PM with a 30% discount."

[1076] "Generate replenishment orders for items that are low on stock."

[1077] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1078] Step 1:

[1079] The server periodically collects product information, inventory information, and price information from the store management system via API. Specifically, the server sends a request to the API endpoint and receives product information, inventory information, and price information data in JSON format. For example, obtain information that the inventory quantity of product A is 10 or less. The input for this step is an API request, and the output is JSON format data.

[1080] Step 2:

[1081] The server analyzes the collected JSON data and identifies products whose inventory is below a certain level or whose prices need to be changed. Specifically, it lists products with inventory quantities of less than 10 units and extracts products whose prices need to be changed due to discount campaign information. The input for this step is the collected JSON data, and the output is a list of products with low inventory and products whose prices need to be changed.

[1082] Step 3:

[1083] The server uses the emotion engine to collect emotional data from in-store consumers via cameras and sensors and analyze it in real time. Specifically, it analyzes the video data from the cameras and infers emotions from the consumers' facial expressions and behavior. The input for this step is the video data, and the output is the analyzed emotional data of the consumers.

[1084] Step 4:

[1085] The server generates price change information and replenishment instructions based on the analysis results. Specifically, it generates JSON data containing instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Reflect the price change for product B on the digital price tag." The input for this step is a list of products with low stock and a list of products that need price changes, and the output is JSON data containing price change information and replenishment instructions.

[1086] Step 5:

[1087] The server uses the generative AI model to generate a voice announcement based on information about special sales events and limited-time sales, as well as consumer emotional data. Specifically, it generates a voice message such as, "Our limited-time sale starts at 3 PM. All items are 30% off." The input for this step is a prompt and emotional data, and the output is the generated voice file.

[1088] Step 6:

[1089] The terminal analyzes the price information received from the server and displays the new price on the digital price tag. Specifically, if it receives information that product B is 10% off, it displays the new price on the price tag. The input to this step is JSON data containing the price change information, and the output is the updated digital price tag.

[1090] Step 7:

[1091] The device stores the audio file received from the server in local storage and plays it on the in-store speakers at the appropriate time. For example, play a voice announcement such as "A limited-time sale has started at 3 PM." The input of this step is the generated audio file, and the output is a voice announcement played over the in-store speakers.

[1092] Step 8:

[1093] A replenishment instruction is sent to the store staff's terminal. The notification includes specific instructions such as "Product A is low in stock. Please replenish it from the warehouse." Specifically, a push notification is sent to the terminal so that the staff can confirm the instructions. The input to this step is JSON data containing the replenishment instruction, and the output is a notification on the store staff's terminal.

[1094] Step 9:

[1095] The store staff member who receives the replenishment instruction at the terminal follows the instruction and retrieves product A from the warehouse to replenish the stock. Specifically, the staff member goes to the warehouse, retrieves the products that need to be replenished, and displays them on the shelves. The input for this step is the replenishment instruction received by the staff member, and the output is the replenished products.

[1096] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1097] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1098] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1099] [Third embodiment]

[1100] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1101] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1102] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1103] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1104] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1105] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1106] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1107] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1108] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1109] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1110] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1111] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1112] Server-side processing

[1113] Data collection

[1114] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, the server obtains information that there are 10 or fewer units of product A in stock and that the price is discounted.

[1115] Data analysis

[1116] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[1117] instruction generation

[1118] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[1119] Generate a voice announcement

[1120] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[1121] Terminal side processing

[1122] View pricing information

[1123] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives information that product B is 10% off and displays the new price on the price tag.

[1124] Broadcast announcements

[1125] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[1126] Staff Notification

[1127] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[1128] User processing

[1129] Staff behavior

[1130] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[1131] Consumer behavior

[1132] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. Specifically, the user checks the new price of the sale item B, picks it up, and purchases it.

[1133] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, thereby improving consumer experience and streamlining store operations.

[1134] The processing flow will be explained below.

[1135] Server-side processing steps

[1136] Data collection

[1137] Step 1:

[1138] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[1139] Step 2:

[1140] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[1141] Data analysis

[1142] Step 3:

[1143] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[1144] Step 4:

[1145] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[1146] Step 5:

[1147] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[1148] instruction generation

[1149] Step 6:

[1150] The server generates price change information for the identified product in JSON format, including the new price.

[1151] Step 7:

[1152] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[1153] Generate a voice announcement

[1154] Step 8:

[1155] The server generates announcement content as text based on information about special sale events and time sales.

[1156] Step 9:

[1157] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[1158] Step 10:

[1159] The server prepares to send the generated audio file to the in-store terminal.

[1160] Terminal processing steps

[1161] View pricing information

[1162] Step 1:

[1163] The terminal receives price information in JSON format sent from the server.

[1164] Step 2:

[1165] The terminal parses the received JSON data and extracts the product ID and new price.

[1166] Step 3:

[1167] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[1168] Broadcast announcements

[1169] Step 4:

[1170] The terminal receives the audio file sent from the server.

[1171] Step 5:

[1172] The terminal stores the received audio file in local storage.

[1173] Step 6:

[1174] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[1175] Staff Notification

[1176] Step 7:

[1177] The terminal receives a replenishment instruction from the server.

[1178] Step 8:

[1179] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[1180] Step 9:

[1181] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[1182] User processing steps

[1183] Staff behavior

[1184] Step 1:

[1185] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[1186] Step 2:

[1187] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[1188] Consumer behavior

[1189] Step 3:

[1190] Users (consumers) check digital price tags and voice announcements in the store to find out about special sales.

[1191] Step 4:

[1192] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[1193] Through the above processing steps, the server, terminals, and users work together to realize efficient and effective time sales and special sale events, as well as inventory management.

[1194] Example 1

[1195] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1196] There is a need for automated inventory management, price updates, and voice announcements regarding special sale events. However, current systems make it difficult to perform these tasks efficiently and effectively. In particular, there are limited ways to respond quickly when inventory is low or prices need to be changed, making it difficult to improve the consumer experience and streamline store operations.

[1197] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1198] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating and transmitting price change information and replenishment instructions to terminals in the store, means for generating and transmitting the generated announcement content as voice announcements, a terminal for displaying the generated price change information and playing the voice announcements, means for notifying store staff terminals of replenishment instructions, and means for generating voice announcements using a generative AI model. This enables inventory management, price information updates, and the effective implementation of special sale events.

[1199] A "store management system" is an integrated system of software and hardware for managing product information, inventory information, and price information within a store.

[1200] The "server" is a computer system that analyzes and processes information collected from the store management system and sends generated instructions and voice announcements to terminals within the store.

[1201] "Product information" refers to basic product data such as product name, product category, and product code.

[1202] "Inventory information" refers to information such as the current inventory quantity and inventory location of each product.

[1203] "Price information" is data including the current selling price and discount information for each product.

[1204] "API Request" means a message requesting data from another system via an Application Programming Interface.

[1205] "JSON format" is an abbreviation for JavaScript Object Notation, a data representation format, and a text format with a structure that is easy for both humans and machines to read and write.

[1206] "Multimodal AI technology" is an artificial intelligence technology that processes multiple types of data (such as text, audio, and images) in an integrated manner.

[1207] A "terminal" is a device that displays and plays instructions and information received from the server and enables interaction with store staff and consumers.

[1208] "Generative AI models" are algorithms and models that use artificial intelligence to generate appropriate data and responses for specific tasks.

[1209] "Price change information" is data indicating how the selling price of a product should be changed.

[1210] "Voice announcements" are announcements that convey information about special sales events, time sales, etc. to consumers and staff via voice.

[1211] "Replenishment instruction" is a message to instruct the replenishment of products that are out of stock.

[1212] The present invention provides a system that improves the efficiency of product inventory management, price information updates, and sales events through cooperation between a store management system, a server, terminals, and users. Specific embodiments for carrying out the invention are described below.

[1213] Server-side processing

[1214] Data collection

[1215] The server periodically collects product information, inventory information, and price information from the store management system. This collection process uses API requests and receives data in JSON format. For example, the server obtains information such as "there are 10 or fewer units of product A in stock and the price is discounted."

[1216] Data analysis

[1217] The server analyzes the received data and identifies products that are out of stock or need a price change. The analysis involves parsing the data and making conditional decisions, such as listing products with less than 10 units in stock. It then determines whether a price change is necessary based on discount campaign information.

[1218] instruction generation

[1219] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[1220] Generate a voice announcement

[1221] The server uses the generative AI model to generate a voice announcement, such as "Time sale starts at 3 PM. All items are 30% off," and sends it to the device.

[1222] Terminal side processing

[1223] View pricing information

[1224] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[1225] Broadcast announcements

[1226] The device receives the voice announcement file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time. Specifically, it announces, "The limited-time sale has begun at 3 PM."

[1227] Staff Notification

[1228] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[1229] User processing

[1230] Staff behavior

[1231] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[1232] Consumer behavior

[1233] The user (consumer) checks the latest sale information through digital price tags or voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[1234] Examples of prompt statements

[1235] Below are some specific examples of prompt sentences to input into the generative AI model.

[1236] You are an expert in store management systems. In this system, the store server collects product information, analyzes the data, and generates instructions for inventory shortages and price changes. It also creates voice announcements and sends them to terminals. The terminals then display price information, play voice announcements, and notify staff of replenishment instructions. Please explain this process in detail.

[1237] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1238] Server-side processing

[1239] Step 1: Start collecting data

[1240] The server sends an API request to the store management system. This request includes parameters to retrieve product information, inventory information, and price information. The server executes this process according to a regular schedule.

[1241] Input: API request parameters

[1242] Output: Response data in JSON format

[1243] Step 2: Receiving data

[1244] The server receives JSON format data as a response from the store management system, which includes the stock quantity, price information, discount information, etc. for each product.

[1245] Input: Response data in JSON format

[1246] Output: A parsable JSON data object

[1247] Step 3: Begin data analysis

[1248] The server parses the received JSON data to analyze it. Specifically, it extracts the stock quantity and price for each product and prepares the data for analysis.

[1249] Input: JSON data object

[1250] Output: Extracted inventory quantity and price information

[1251] Step 4: Identifying defects and important information

[1252] The server uses the extracted data to identify products whose inventory has fallen below a certain number (for example, 10 units) or whose prices have changed. This information serves as the basis for generating new instruction data.

[1253] Input: Extracted inventory quantity, price information

[1254] Output: Stock shortage list, price change list

[1255] Step 5: Start generating instructions

[1256] The server generates price change information and replenishment instructions based on the identified information, such as "issue a replenishment instruction because product A is out of stock" or "reflect the price of product B on the digital price tag."

[1257] Input: Stock shortage list, price change list

[1258] Output: Price change instructions, replenishment instructions

[1259] Step 6: Sending instruction data

[1260] The server sends the generated instruction data in JSON format to the device, allowing the device to perform appropriate updates based on the received data.

[1261] Input: Price change instructions, replenishment instructions

[1262] Output: JSON data sent to the terminal

[1263] Step 7: Start generating voice announcements

[1264] The server uses a generative AI model to generate voice announcements, such as "A limited-time sale starts at 3 p.m. All items are 30% off" based on information about special sales events and limited-time sales.

[1265] Input: Special sale event information, limited time sale information

[1266] Output: Voice announcement data

[1267] Step 8: Send a voice announcement

[1268] The server sends the generated voice announcement file to the terminal, allowing each terminal to play the announcement at the appropriate time.

[1269] Input: Voice announcement data

[1270] Output: Audio file sent to the device

[1271] Terminal side processing

[1272] Step 1: Receiving price information

[1273] The terminal receives price information in JSON format from the server, which includes specific price change instructions.

[1274] Input: Price change information in JSON format

[1275] Output: Price change instruction data

[1276] Step 2: Parse the price information

[1277] The terminal analyzes the received data and identifies which items require price changes, for example, identifying that item B is on a 10% discount.

[1278] Input: Price change instruction data

[1279] Output: Updated pricing information

[1280] Step 3: Update your digital price tags

[1281] Based on the analysis, the terminal will display the new price on a digital price tag for consumer verification.

[1282] Input: Updated pricing information

[1283] Output: New price displayed on the digital price tag

[1284] Step 4: Receive a voice announcement

[1285] The device retrieves the voice announcement file received from the server and stores it in local storage.

[1286] Input: Audio file sent to the device

[1287] Output: Saved audio file

[1288] Step 5: Play an announcement

[1289] The device then plays the stored audio announcement over the in-store speakers at the appropriate time, for example, announcing, "The 3 PM limited-time sale has begun."

[1290] Input: Saved audio file

[1291] Output: Played audio announcement

[1292] Step 6: Receiving replenishment orders

[1293] The terminal receives a replenishment instruction from the server, which is then sent to the terminal of the store staff member.

[1294] Input: Refill order sent to terminal

[1295] Output: Replenishment message sent to store staff

[1296] User processing

[1297] Step 1: Confirm replenishment instructions

[1298] The user (store staff) checks the replenishment instruction from the terminal. Specifically, a message is displayed saying, "Product A is low in stock. Please replenish from the warehouse."

[1299] Input: Replenishment instructions notified

[1300] Output: Confirmed replenishment order

[1301] Step 2: Replenish inventory

[1302] The user promptly replenishes inventory based on the confirmed instructions, for example, by taking product A from the warehouse and stocking it in the store.

[1303] Input: Confirmed replenishment order

[1304] Output: Replenished products

[1305] Step 3: Check for special offers

[1306] Users (consumers) check the latest sales information through digital price tags or voice announcements in the store. For example, they check the new price of product B on sale.

[1307] Input: Digital price tag, voice announcement

[1308] Output: Confirmed sale information

[1309] Step 4: Shop the sale items

[1310] The user purchases a product based on the sale information they have checked. For example, they pick up and purchase product B, which is on sale.

[1311] Input: Confirmed sale information

[1312] Output: Purchased items

[1313] Through these steps, the system can efficiently and effectively manage inventory, update price information, and automate sales events.

[1314] (Application example 1)

[1315] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1316] Conventional store management systems did not sufficiently streamline inventory management and price changes, and notifications of special sales and limited-time sales were often done manually. It was also difficult for store staff to share information in real time when replenishing inventory. Furthermore, effective sales information was not provided to consumers, resulting in lost sales opportunities. Therefore, there is a need for a system that automates inventory management, price changes, and sales information notifications, and provides appropriate information to consumers and store staff in real time.

[1317] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1318] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for providing consumers with real-time sales information and limited-time sale start notifications using smartphones or tablet devices, means for providing store staff with real-time inventory status confirmation and replenishment instruction notification functions, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management, price change and sale information notifications, and real-time information provision to consumers and store staff.

[1319] Key Word Definitions

[1320] A "store management system" is an integrated information system for managing products, inventory, prices, etc. within a store.

[1321] "Product information" means data containing detailed information about each product, typically including the name, price, category, and availability.

[1322] "Inventory information" is data that indicates the current quantity of each product in the store and in the warehouse.

[1323] "Price information" is data that includes the current selling price and discount information for each product.

[1324] "Analysis" refers to the process of extracting and determining information for a specific purpose from collected data.

[1325] "Special sale information" is information indicating special sales conditions and discount details for products that will be offered within a certain period of time.

[1326] A "time sale" is a promotional event where products are sold at a discounted price for a specific time frame.

[1327] "Server" refers to a computer system that collects, analyzes, and distributes data over a network.

[1328] A "terminal" is a device for displaying and operating information, and includes smartphones and tablet devices.

[1329] "Multimodal AI technology" is an artificial intelligence technology that integrates multiple data modalities (e.g., voice, text, images) to perform analysis and decision-making.

[1330] A "voice announcement" is a means of conveying specific information using voice data.

[1331] "Real-time" refers to the generation and processing of data occurring immediately, without delay.

[1332] "Push notifications" are a technology that sends information to mobile devices in real time.

[1333] MODE FOR CARRYING OUT THE INVENTION

[1334] Server-side processing

[1335] Data collection

[1336] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information such as when there are 10 or fewer units of a specific product A in stock or when the price is discounted can be obtained.

[1337] Data analysis

[1338] The server analyzes the acquired data and identifies products that are low in stock or products subject to price changes. For example, it lists products with less than 10 units in stock or products for which discount campaigns are applied. This identifies products subject to special sales or limited-time sales.

[1339] instruction generation

[1340] The server generates price change information and replenishment instructions based on the analysis results. The generated data is sent to the terminal in JSON format. For example, it may contain specific instructions such as "issue a replenishment order because product A is out of stock" or "reflect the price change of product B on the digital price tag."

[1341] Generate a voice announcement

[1342] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[1343] Terminal side processing

[1344] View pricing information

[1345] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives discount information for product B and displays the new price on the price tag.

[1346] Broadcast announcements

[1347] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[1348] Staff Notification

[1349] The terminal notifies the store staff terminal of the replenishment instruction from the server. For example, a message such as "Product A is low in stock. Please replenish from the warehouse" is displayed.

[1350] User processing

[1351] Staff behavior

[1352] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. For example, they take product A from the warehouse and replenish it on the storefront.

[1353] Consumer behavior

[1354] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[1355] Hardware and software used

[1356] Server: A high-performance server is used, and a web framework such as Flask is used.

[1357] Devices: Smartphones, tablets, digital price tags, etc.

[1358] Software: Python, REST API, React Native, text-to-speech API, multimodal AI, etc.

[1359] Examples and prompts

[1360] For example, if you want to automatically issue replenishment instructions for specific products and update price change information in real time, the following prompt sentence is effective:

[1361] "Write a program that generates replenishment orders for low-stock items and updates digital price tags based on price change information. Also, add the ability to generate audio announcements about special sales and send them to a smartphone app."

[1362] The above is a specific embodiment for carrying out the present invention.

[1363] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1364] Program processing flow

[1365] Step 1:

[1366] Data collection

[1367] The server periodically collects product information, inventory information, and price information in JSON format from the store management system through an API. The API endpoint and authentication information are required as input. The data collection process involves sending an HTTP GET request and parsing the JSON data received as a response to extract fields such as product name, inventory quantity, price, and discount information. The output is parseable JSON data.

[1368] Step 2:

[1369] Data analysis

[1370] The server parses the collected JSON data. The JSON data to be parsed is used as input. The data parsing process filters based on specific conditions (for example, items with less than 10 units in stock, items with discount campaigns applied, etc.). Specifically, it lists items that are low in stock and items that need to be repriced. The output is a list of low-stock items and items that need to be repriced.

[1371] Step 3:

[1372] instruction generation

[1373] The server generates price change information and replenishment instructions based on the analysis results. As input, it requires a list of low-stock items and a list of items subject to price changes. In the instruction generation process, it generates JSON data containing stock replenishment instructions and new price information for each item. The generated data is sent to the terminal in the store via API. The output is replenishment instructions and price change information in JSON format, which are sent to the terminal.

[1374] Step 4:

[1375] Generate a voice announcement

[1376] The server generates a voice announcement using multimodal AI technology. The generated instruction content is used as input. The voice announcement generation process generates voice data using a text-to-speech API, which converts text content into an audio file. Specifically, it creates an announcement such as, "A limited-time sale starts at 3:00 PM. All items are 30% off." The output is the URL of the audio file.

[1377] Step 5:

[1378] View pricing information

[1379] The terminal parses the price change information received from the server and displays it on the digital price tag. The received price change information in JSON format is used as input. The price information display process immediately reflects the new price on the digital price tag. Specifically, it updates the display content of the price tag and applies the information to the product in the store. The output is the updated price tag display.

[1380] Step 6:

[1381] Broadcast announcements

[1382] The terminal stores the voice announcement file received from the server in local storage and plays it through the in-store speakers at the specified time. The URL of the voice file and playback timing information are used as input. The voice announcement broadcast process downloads the voice file and plays it on the playback device at the appropriate time. The output is the announcement broadcast in the store.

[1383] Step 7:

[1384] Staff Notification

[1385] The terminal notifies the store staff terminal of the replenishment instruction from the server. JSON data containing the replenishment instruction is used as input. The notification process sends a push notification to the store staff device and displays information about the products that need to be replenished. Specifically, it displays a message on the smartphone or tablet saying, "Product A is low in stock. Please replenish it from the warehouse." The output is a notification of the replenishment instruction to the staff.

[1386] Step 8:

[1387] Staff behavior

[1388] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes inventory. The replenishment instruction information displayed on the terminal is used as input. The behavioral process executes specific steps to retrieve the specified products from the warehouse and replenish them in the store. The output is the replenishment of products in the store and an inventory update.

[1389] Step 9:

[1390] Consumer behavior

[1391] Users (consumers) check the latest sale information through digital price tags and voice announcements in the store. The sale information obtained from the price tags and announcements is used as input. In the behavioral process, the user picks up a sale item and takes action to actually purchase it. The output is the sales record resulting from the purchase of the item.

[1392] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1393] Server-side processing

[1394] Data collection

[1395] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information is obtained that product A has 10 or fewer units in stock and is eligible for a discount.

[1396] Data analysis

[1397] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[1398] Use of emotion engine

[1399] The server uses an emotion engine to collect and analyze in real time the emotional data of consumers in the store. This emotional data is acquired from cameras and sensors, and emotions are inferred from the consumers' facial expressions and behavior.

[1400] instruction generation

[1401] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. For example, it may include instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[1402] Generate a voice announcement

[1403] The server optimizes the announcement content based on information about special sales events and limited-time sales, as well as consumer sentiment data. For example, it creates a voice message such as, "Our limited-time sale starts at 3 p.m. All items are 30% off," and sends it to the device.

[1404] Terminal side processing

[1405] View pricing information

[1406] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[1407] Broadcast announcements

[1408] The device receives the audio file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time, for example announcing, "The limited-time sale has begun at 3 PM."

[1409] Staff Notification

[1410] The terminal notifies the store staff terminal of the replenishment instruction from the server. The notification content includes specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[1411] User processing

[1412] Staff behavior

[1413] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[1414] Consumer behavior

[1415] The user (consumer) checks the digital price tag, voice announcements, and emotion-based optimization information in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[1416] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and further improves the consumer experience by utilizing an emotion engine.

[1417] The processing flow will be explained below.

[1418] Server-side processing steps

[1419] Data collection

[1420] Step 1:

[1421] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[1422] Step 2:

[1423] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[1424] Data analysis

[1425] Step 3:

[1426] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[1427] Step 4:

[1428] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[1429] Step 5:

[1430] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[1431] Use of emotion engine

[1432] Step 6:

[1433] The server collects consumer facial expression and behavioral data obtained from cameras and sensors within the store.

[1434] Step 7:

[1435] The server uses an emotion engine to analyze the consumer's emotions in real time from the collected data, inferring, for example, whether the consumer is excited or bored.

[1436] instruction generation

[1437] Step 8:

[1438] Based on the analysis results, the server generates price change information and replenishment instructions, and the generated data is sent to the terminal in JSON format.

[1439] Step 9:

[1440] The server generates price change information for the identified product in JSON format, including the new price.

[1441] Step 10:

[1442] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[1443] Generate a voice announcement

[1444] Step 11:

[1445] The server optimizes the content of announcements based on information about special sales events and limited-time sales, as well as consumer sentiment data.

[1446] Step 12:

[1447] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[1448] Step 13:

[1449] The server prepares to send the generated audio file to the in-store terminal.

[1450] Terminal processing steps

[1451] View pricing information

[1452] Step 1:

[1453] The terminal receives price information in JSON format sent from the server.

[1454] Step 2:

[1455] The terminal parses the received JSON data and extracts the product ID and new price.

[1456] Step 3:

[1457] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[1458] Broadcast announcements

[1459] Step 4:

[1460] The terminal receives the audio file sent from the server.

[1461] Step 5:

[1462] The terminal stores the received audio file in local storage.

[1463] Step 6:

[1464] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[1465] Staff Notification

[1466] Step 7:

[1467] The terminal receives a replenishment instruction from the server.

[1468] Step 8:

[1469] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[1470] Step 9:

[1471] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[1472] User processing steps

[1473] Staff behavior

[1474] Step 1:

[1475] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[1476] Step 2:

[1477] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[1478] Consumer behavior

[1479] Step 3:

[1480] Users (consumers) see digital price tags, voice announcements, and sentiment-based optimization information in the store.

[1481] Step 4:

[1482] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[1483] Example 2

[1484] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1485] In today's retail industry, efficient and effective inventory management, price updates, and even marketing activities are extremely important. However, traditional store management systems face challenges in that they are unable to provide real-time data and optimally timed information based on consumer behavior and emotions. Furthermore, inventory shortages and missed price changes frequently occur, resulting in reduced store operational efficiency.

[1486] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for collecting consumer emotion data in the store and analyzing it in real time using emotion analysis technology, means for generating price change information and replenishment instructions and transmitting them to terminals in the store, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management and price updates to be performed more efficiently and effectively than before, and enables information to be provided at the optimal time based on consumer emotions and behavior. Furthermore, it enables quick notification of replenishment instructions to store staff and real-time announcements to consumers, thereby improving the efficiency of store operations and customer satisfaction.

[1487] A "store management system" is a system for comprehensively managing a store's inventory, sales, pricing, etc.

[1488] "Product information" refers to basic information about a product, such as product name, product code, classification, and description.

[1489] "Inventory information" refers to data regarding the inventory quantity of each product, inventory history, inventory location, etc.

[1490] "Price information" refers to data including the current price of each product, past price change history, discount information, etc.

[1491] "Analysis" refers to the process of determining whether collected data meets certain conditions and extracting relevant information.

[1492] "Emotion analysis technology" refers to technology that uses data obtained from cameras and sensors to infer emotions from consumers' facial expressions and behavior.

[1493] "Price change information" refers to information for updating an existing price to a new price.

[1494] "Replenishment Instructions" refers to specific instructions to notify store staff to replenish items that are low in stock.

[1495] "Announcement content" refers to announcements made in stores, including information about special sales and limited-time sales.

[1496] "Voice announcement" refers to broadcasting the generated announcement content in audio format within the store.

[1497] "Terminal" refers to a device that communicates with a server to receive information and display or play audio.

[1498] The present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and also improves consumer experience by utilizing emotion analysis technology.

[1499] Server Processing

[1500] Data collection

[1501] The server periodically sends requests to the API endpoint of the store management system and receives product information, inventory information, and price information in JSON format. This process can be done using, for example, the curl library or an HTTP client. The received data is then stored in a database, for example, MongoDB.

[1502] Data analysis

[1503] The server reads the latest data from the database and identifies products whose inventory has dropped below a certain level or whose prices need to be adjusted. This analysis is done using SQL or NoSQL queries. For example, it retrieves a list of products with less than 10 units in stock and determines whether a price change is necessary based on current promotions.

[1504] Use of emotion analysis technology

[1505] The server acquires video data from cameras and sensors in the store and performs facial recognition using, for example, the OpenCV library. It then analyzes consumer emotions in real time using an emotion analysis engine (for example, Microsoft Azure Face API). The analysis results are stored in a database.

[1506] instruction generation

[1507] Based on the results of data and sentiment analysis, the server generates stock replenishment instructions and price change information in JSON format and sends it to the terminal. For example, specific instructions such as "Inventory of product A is low, so issue an instruction to replenish it" or "Update the price of product B on the digital price tag" can be included.

[1508] Generate a voice announcement

[1509] The server collects information about special sales events and limited-time sales, and generates optimal announcement content while referring to consumer sentiment data. The generated text is converted into an audio file using Google Text-to-Speech API or similar and sent to the device. For example, a voice announcement such as "Our limited-time sale starts at 3 p.m. All items are 30% off" may be created.

[1510] Terminal handling

[1511] View pricing information

[1512] The terminal parses the JSON data received from the server and displays the new price on the digital price tag. For example, if product B is 10% off, the terminal displays this information on the E-ink display.

[1513] Broadcast announcements

[1514] The device receives the audio file from the server, stores it in local storage, and plays it from the in-store speakers at the specified time. As a specific example of operation, the audio file is downloaded using the wget command and played based on a pre-set schedule.

[1515] Staff Notification

[1516] The device extracts replenishment instructions from the server using JSON data and sends notifications to store staff members' smartphones using the Firebase Cloud Messaging service. The notifications include specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[1517] User Behavior

[1518] Staff behavior

[1519] The user, a store staff member, receives the notification from the device and replenishes the products according to the instructions. For example, the staff member checks the notification on their smartphone, quickly retrieves product A from the warehouse, and replenishes it on the storefront.

[1520] Consumer behavior

[1521] The consumer user is encouraged to make a purchase by checking the new price on the digital price tag or the voice announcement over the in-store speaker. For example, the user checks the new price of a special sale item B, picks up the item, and purchases it.

[1522] Prompt Sentence Examples

[1523] "Please explain the process of a program that analyzes product information obtained from the store management system, generates replenishment instructions for items that are low on stock, and notifies store staff."

[1524] In this way, the present invention is a system that realizes more efficient and effective store operations and an improved customer experience through close cooperation between the server, terminals, and users.

[1525] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1526] Server Processing

[1527] Data collection

[1528] Step 1:

[1529] The server prepares an API client and accesses the API endpoint of the store management system. This is achieved by issuing an HTTP request using, for example, the curl library. The input is the API endpoint URL, and the output is a JSON-formatted response containing product information, inventory information, and price information.

[1530] Step 2:

[1531] The server parses the received JSON format data and extracts the necessary information. Specifically, it uses a JSON parser to convert the data into an object and extracts information such as product name, stock quantity, and price. The input is JSON data, and the output is the parsed data object.

[1532] Step 3:

[1533] The server stores the parsed data in a database. For example, it uses the MongoDB insertOne method to insert each product's information into the database. The input is the parsed data object, and the output is the result stored in the database.

[1534] Data analysis

[1535] Step 1:

[1536] The server retrieves the latest inventory and pricing information from the database by issuing a query with specific criteria, for example using the MongoDB find method. The input is the query criteria, and the output is the data object that is the query result.

[1537] Step 2:

[1538] The server identifies products whose inventory has fallen below a certain level or whose prices need to be changed by filtering the data it retrieves to create a list of products with inventory levels of 10 or less or that are on a discount. The input is the query results from the database, and the output is the list of identified products.

[1539] Step 3:

[1540] The server generates replenishment instructions and price change information based on the information of the identified products. For example, if there are 10 or fewer products in stock, it creates a specific instruction such as "Replenish product A." The input is a list of identified products, and the output is the generated instructions and price change information.

[1541] Use of emotion analysis technology

[1542] Step 1:

[1543] The server collects video data obtained from cameras and sensors. This is done, for example, by using the camera's API to acquire video in real time. The input is video data from the camera, and the output is image data for each frame.

[1544] Step 2:

[1545] The server sends the video data to an emotion analysis engine to analyze consumer emotions. Specifically, it uses OpenCV to perform facial recognition and sends the results to an emotion analysis engine (for example, Microsoft Azure Face API). The input is image data for each frame, and the output is emotional data as the analysis result.

[1546] Step 3:

[1547] The server saves the analysis results in a database and updates the results in real time. The input is emotion data as the analysis result, and the output is the result saved in the database.

[1548] instruction generation

[1549] Step 1:

[1550] The server combines the results of data analysis and sentiment analysis to generate replenishment instructions and price change information. Specifically, it generates replenishment instructions for low-stock items based on the data analysis results and optimizes the timing of price changes based on the sentiment analysis results. The input is the analysis results, and the output is the generated instructions and price change information.

[1551] Step 2:

[1552] The server converts the generated instructions and price change information into JSON format and sends it to the terminal. The input is the generated instructions and price change information, and the output is JSON format data.

[1553] Generate a voice announcement

[1554] Step 1:

[1555] The server collects information about special sales events and limited-time sales, and determines the content of announcements. Specifically, it creates announcement content based on a pre-set schedule and the results of sentiment analysis. The input is schedule information and sentiment analysis results, and the output is announcement text.

[1556] Step 2:

[1557] The server converts the generated announcement text into an audio file. Specifically, it uses the Google Text-to-Speech API to convert text to audio. The input is the announcement text, and the output is an audio file.

[1558] Step 3:

[1559] The server sends the generated audio file to the terminal. The input is the audio file, and the output is the transmission result to the terminal.

[1560] Terminal handling

[1561] View pricing information

[1562] Step 1:

[1563] The terminal parses the JSON data received from the server and extracts new price information. The input is the received JSON data and the output is the extracted price information.

[1564] Step 2:

[1565] The terminal displays the extracted price information on a digital price tag, specifically by updating the new price on the E-ink display. The input is the extracted price information and the output is the displayed price.

[1566] Broadcast announcements

[1567] Step 1:

[1568] The device saves the audio file received from the server in local storage. The input is the audio file, and the output is the result saved in local storage.

[1569] Step 2:

[1570] The terminal plays the stored audio file at the appropriate time. Specifically, it plays the audio through the store's speakers. The input is the stored audio file, and the output is the played audio.

[1571] Staff Notification

[1572] Step 1:

[1573] The terminal parses the replenishment order received from the server and extracts the necessary information. The input is the received JSON data, and the output is the extracted replenishment order.

[1574] Step 2:

[1575] The terminal notifies the extracted replenishment instructions to the store staff's smartphones. Specifically, it sends notifications using the Firebase Cloud Messaging service. The input is the extracted replenishment instructions, and the output is the sent notification.

[1576] User Behavior

[1577] Staff behavior

[1578] Step 1:

[1579] The user (store staff) receives a replenishment instruction notification on their smartphone. The input is the smartphone, and the output is the received notification.

[1580] Step 2:

[1581] The user replenishes the products according to the notification. Specifically, the staff retrieves the specified products from the warehouse and replenishes them in the store. The input is the received notification, and the output is the replenished products.

[1582] Consumer behavior

[1583] Step 1:

[1584] The user (consumer) checks the new price information displayed on the digital price tag. The input is the digital price tag, and the output is the checked price information.

[1585] Step 2:

[1586] Users listen to audio announcements from in-store speakers, which stimulates their desire to make a purchase. Specifically, they pick up and purchase products based on information about special sales and time-limited sales. The input is the audio announcement, and the output is the purchased product.

[1587] (Application example 2)

[1588] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1589] With conventional store management systems, inventory management and pricing are time-consuming and place a heavy burden on store staff. Furthermore, it is not possible to grasp consumer sentiment and behavior in real time, making it difficult to provide optimal services. Therefore, there is a need for efficient and accurate inventory management, price changes, and flexible service provision in response to consumer behavior.

[1590] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for generating and sending the generated announcement content as a voice announcement, and a terminal for displaying the generated price change information and playing the voice announcement. In this system, the server includes means for generating and optimizing the voice announcement using a generative AI model, and means for inputting prompt sentences into the generative AI model to create the voice announcement. This enables efficient and accurate inventory management and price changes, as well as the provision of optimal services based on consumer emotions and behavior.

[1591] A "store management system" is a system that manages product information, inventory information, and price information within a store.

[1592] "Product information" is attribute data such as the name, model number, and description of each product.

[1593] "Stock information" is data that indicates the current stock quantity of a particular product.

[1594] "Price information" is data indicating the selling price and discount information of each product.

[1595] "Means of collection" refers to the methods and functions for periodically obtaining necessary information from the store management system.

[1596] "Means for analyzing" refers to methods or functions for analyzing collected data and identifying products whose inventory is below a certain level or products that require price changes.

[1597] "Price change information" is data indicating an instruction to change the price of a specific product.

[1598] A "replenishment instruction" is an instruction indicating that a product that is low in stock needs to be replenished.

[1599] "Terminal" refers to a device (e.g., tablet, smartphone) used in a store to display information, receive instructions, etc.

[1600] A "generative AI model" is a model that uses artificial intelligence technology to generate voice announcements and other information.

[1601] A "prompt" is a textual instruction that is input to a generative AI model.

[1602] First, the server periodically collects product information, inventory information, and price information from the store management system via API and receives this data in JSON format. For example, it obtains information such as whether there are 10 or fewer units of product A in stock and whether the price is subject to a discount.

[1603] The server then analyzes the collected data to identify products that are out of stock or that need to be repriced. During the analysis process, the server lists products with inventory levels below 10 and determines whether a price change is necessary based on discount campaign information.

[1604] The server uses a generative AI model to collect emotional data from consumers in the store and analyze it in real time. This emotional data is obtained from cameras and sensors, and emotions are inferred from the consumer's facial expressions and behavior. Based on the results of this analysis, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Reflect the price change for product B on the digital price tag."

[1605] Furthermore, the server uses a generative AI model to generate announcement content based on information about special sales events and limited-time sales, as well as consumer sentiment data. For example, it creates a voice message such as, "Limited-time sales start at 3 p.m. All items are 30% off," and sends it to the device.

[1606] The terminal analyzes the price information received from the server and displays it on the digital price tag in the store. For example, if it receives information that product B is 10% off, it displays the new price on the price tag. It also saves the received audio file in local storage and plays it on the in-store speaker at the appropriate time. For example, it announces, "The 3 PM limited-time sale has begun."

[1607] Furthermore, replenishment instructions from the server are sent to the store staff's terminals. The notification content includes specific instructions such as "Product A is low in stock. Please replenish from the warehouse."

[1608] The main hardware used includes smartphones and tablets, while the software uses requests for API communication, pyttsx3 for speech synthesis, and playsound for audio file playback.

[1609] As a specific example, when a time sale starts at 3 p.m., the app will send a notification to store staff saying, "Product A is out of stock. Please replenish it from the warehouse," and at the same time, it will play an audio announcement over the in-store speakers saying, "The time sale starts at 3 p.m. All items are 30% off."

[1610] An example of a prompt for a generative AI model is as follows:

[1611] "Generate a voice announcement for a limited-time sale starting at 3 PM with a 30% discount."

[1612] "Generate replenishment orders for items that are low on stock."

[1613] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1614] Step 1:

[1615] The server periodically collects product information, inventory information, and price information from the store management system via API. Specifically, the server sends a request to the API endpoint and receives product information, inventory information, and price information data in JSON format. For example, obtain information that the inventory quantity of product A is 10 or less. The input for this step is an API request, and the output is JSON format data.

[1616] Step 2:

[1617] The server analyzes the collected JSON data and identifies products whose inventory is below a certain level or whose prices need to be changed. Specifically, it lists products with inventory quantities of less than 10 units and extracts products whose prices need to be changed due to discount campaign information. The input for this step is the collected JSON data, and the output is a list of products with low inventory and products whose prices need to be changed.

[1618] Step 3:

[1619] The server uses the emotion engine to collect emotional data from in-store consumers via cameras and sensors and analyze it in real time. Specifically, it analyzes the video data from the cameras and infers emotions from the consumers' facial expressions and behavior. The input for this step is the video data, and the output is the analyzed emotional data of the consumers.

[1620] Step 4:

[1621] The server generates price change information and replenishment instructions based on the analysis results. Specifically, it generates JSON data containing instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Reflect the price change for product B on the digital price tag." The input for this step is a list of products with low stock and a list of products that need price changes, and the output is JSON data containing price change information and replenishment instructions.

[1622] Step 5:

[1623] The server uses the generative AI model to generate a voice announcement based on information about special sales events and limited-time sales, as well as consumer emotional data. Specifically, it generates a voice message such as, "Our limited-time sale starts at 3 PM. All items are 30% off." The input for this step is a prompt and emotional data, and the output is the generated voice file.

[1624] Step 6:

[1625] The terminal analyzes the price information received from the server and displays the new price on the digital price tag. Specifically, if it receives information that product B is 10% off, it displays the new price on the price tag. The input to this step is JSON data containing the price change information, and the output is the updated digital price tag.

[1626] Step 7:

[1627] The device stores the audio file received from the server in local storage and plays it on the in-store speakers at the appropriate time. For example, play a voice announcement such as "A limited-time sale has started at 3 PM." The input of this step is the generated audio file, and the output is a voice announcement played over the in-store speakers.

[1628] Step 8:

[1629] A replenishment instruction is sent to the store staff's terminal. The notification includes specific instructions such as "Product A is low in stock. Please replenish it from the warehouse." Specifically, a push notification is sent to the terminal so that the staff can confirm the instructions. The input to this step is JSON data containing the replenishment instruction, and the output is a notification on the store staff's terminal.

[1630] Step 9:

[1631] The store staff member who receives the replenishment instruction at the terminal follows the instruction and retrieves product A from the warehouse to replenish the stock. Specifically, the staff member goes to the warehouse, retrieves the products that need to be replenished, and displays them on the shelves. The input for this step is the replenishment instruction received by the staff member, and the output is the replenished products.

[1632] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1633] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1634] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1635] [Fourth embodiment]

[1636] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1637] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1638] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1639] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1640] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1641] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1642] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1643] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1644] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1645] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1646] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1647] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1648] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1649] Server-side processing

[1650] Data collection

[1651] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, the server obtains information that there are 10 or fewer units of product A in stock and that the price is discounted.

[1652] Data analysis

[1653] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[1654] instruction generation

[1655] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[1656] Generate a voice announcement

[1657] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[1658] Terminal side processing

[1659] View pricing information

[1660] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives information that product B is 10% off and displays the new price on the price tag.

[1661] Broadcast announcements

[1662] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[1663] Staff Notification

[1664] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[1665] User processing

[1666] Staff behavior

[1667] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[1668] Consumer behavior

[1669] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. Specifically, the user checks the new price of the sale item B, picks it up, and purchases it.

[1670] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, thereby improving consumer experience and streamlining store operations.

[1671] The processing flow will be explained below.

[1672] Server-side processing steps

[1673] Data collection

[1674] Step 1:

[1675] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[1676] Step 2:

[1677] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[1678] Data analysis

[1679] Step 3:

[1680] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[1681] Step 4:

[1682] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[1683] Step 5:

[1684] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[1685] instruction generation

[1686] Step 6:

[1687] The server generates price change information for the identified product in JSON format, including the new price.

[1688] Step 7:

[1689] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[1690] Generate a voice announcement

[1691] Step 8:

[1692] The server generates announcement content as text based on information about special sale events and time sales.

[1693] Step 9:

[1694] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[1695] Step 10:

[1696] The server prepares to send the generated audio file to the in-store terminal.

[1697] Terminal processing steps

[1698] View pricing information

[1699] Step 1:

[1700] The terminal receives price information in JSON format sent from the server.

[1701] Step 2:

[1702] The terminal parses the received JSON data and extracts the product ID and new price.

[1703] Step 3:

[1704] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[1705] Broadcast announcements

[1706] Step 4:

[1707] The terminal receives the audio file sent from the server.

[1708] Step 5:

[1709] The terminal stores the received audio file in local storage.

[1710] Step 6:

[1711] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[1712] Staff Notification

[1713] Step 7:

[1714] The terminal receives a replenishment instruction from the server.

[1715] Step 8:

[1716] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[1717] Step 9:

[1718] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[1719] User processing steps

[1720] Staff behavior

[1721] Step 1:

[1722] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[1723] Step 2:

[1724] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[1725] Consumer behavior

[1726] Step 3:

[1727] Users (consumers) check digital price tags and voice announcements in the store to find out about special sales.

[1728] Step 4:

[1729] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[1730] Through the above processing steps, the server, terminals, and users work together to realize efficient and effective time sales and special sale events, as well as inventory management.

[1731] Example 1

[1732] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1733] There is a need for automated inventory management, price updates, and voice announcements regarding special sale events. However, current systems make it difficult to perform these tasks efficiently and effectively. In particular, there are limited ways to respond quickly when inventory is low or prices need to be changed, making it difficult to improve the consumer experience and streamline store operations.

[1734] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1735] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating and transmitting price change information and replenishment instructions to terminals in the store, means for generating and transmitting the generated announcement content as voice announcements, a terminal for displaying the generated price change information and playing the voice announcements, means for notifying store staff terminals of replenishment instructions, and means for generating voice announcements using a generative AI model. This enables inventory management, price information updates, and the effective implementation of special sale events.

[1736] A "store management system" is an integrated system of software and hardware for managing product information, inventory information, and price information within a store.

[1737] The "server" is a computer system that analyzes and processes information collected from the store management system and sends generated instructions and voice announcements to terminals within the store.

[1738] "Product information" refers to basic product data such as product name, product category, and product code.

[1739] "Inventory information" refers to information such as the current inventory quantity and inventory location of each product.

[1740] "Price information" is data including the current selling price and discount information for each product.

[1741] "API Request" means a message requesting data from another system via an Application Programming Interface.

[1742] "JSON format" is an abbreviation for JavaScript Object Notation, a data representation format, and a text format with a structure that is easy for both humans and machines to read and write.

[1743] "Multimodal AI technology" is an artificial intelligence technology that processes multiple types of data (such as text, audio, and images) in an integrated manner.

[1744] A "terminal" is a device that displays and plays instructions and information received from the server and enables interaction with store staff and consumers.

[1745] "Generative AI models" are algorithms and models that use artificial intelligence to generate appropriate data and responses for specific tasks.

[1746] "Price change information" is data indicating how the selling price of a product should be changed.

[1747] "Voice announcements" are announcements that convey information about special sales events, time sales, etc. to consumers and staff via voice.

[1748] "Replenishment instruction" is a message to instruct the replenishment of products that are out of stock.

[1749] The present invention provides a system that improves the efficiency of product inventory management, price information updates, and sales events through cooperation between a store management system, a server, terminals, and users. Specific embodiments for carrying out the invention are described below.

[1750] Server-side processing

[1751] Data collection

[1752] The server periodically collects product information, inventory information, and price information from the store management system. This collection process uses API requests and receives data in JSON format. For example, the server obtains information such as "there are 10 or fewer units of product A in stock and the price is discounted."

[1753] Data analysis

[1754] The server analyzes the received data and identifies products that are out of stock or need a price change. The analysis involves parsing the data and making conditional decisions, such as listing products with less than 10 units in stock. It then determines whether a price change is necessary based on discount campaign information.

[1755] instruction generation

[1756] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. Specifically, it includes instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[1757] Generate a voice announcement

[1758] The server uses the generative AI model to generate a voice announcement, such as "Time sale starts at 3 PM. All items are 30% off," and sends it to the device.

[1759] Terminal side processing

[1760] View pricing information

[1761] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[1762] Broadcast announcements

[1763] The device receives the voice announcement file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time. Specifically, it announces, "The limited-time sale has begun at 3 PM."

[1764] Staff Notification

[1765] The terminal notifies the store staff terminal of the replenishment instruction from the server. This notification is displayed as a message saying, "Product A is out of stock. Please replenish from the warehouse."

[1766] User processing

[1767] Staff behavior

[1768] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[1769] Consumer behavior

[1770] The user (consumer) checks the latest sale information through digital price tags or voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[1771] Examples of prompt statements

[1772] Below are some specific examples of prompt sentences to input into the generative AI model.

[1773] You are an expert in store management systems. In this system, the store server collects product information, analyzes the data, and generates instructions for inventory shortages and price changes. It also creates voice announcements and sends them to terminals. The terminals then display price information, play voice announcements, and notify staff of replenishment instructions. Please explain this process in detail.

[1774] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1775] Server-side processing

[1776] Step 1: Start collecting data

[1777] The server sends an API request to the store management system. This request includes parameters to retrieve product information, inventory information, and price information. The server executes this process according to a regular schedule.

[1778] Input: API request parameters

[1779] Output: Response data in JSON format

[1780] Step 2: Receiving data

[1781] The server receives JSON format data as a response from the store management system, which includes the stock quantity, price information, discount information, etc. for each product.

[1782] Input: Response data in JSON format

[1783] Output: A parsable JSON data object

[1784] Step 3: Begin data analysis

[1785] The server parses the received JSON data to analyze it. Specifically, it extracts the stock quantity and price for each product and prepares the data for analysis.

[1786] Input: JSON data object

[1787] Output: Extracted inventory quantity and price information

[1788] Step 4: Identifying defects and important information

[1789] The server uses the extracted data to identify products whose inventory has fallen below a certain number (for example, 10 units) or whose prices have changed. This information serves as the basis for generating new instruction data.

[1790] Input: Extracted inventory quantity, price information

[1791] Output: Stock shortage list, price change list

[1792] Step 5: Start generating instructions

[1793] The server generates price change information and replenishment instructions based on the identified information, such as "issue a replenishment instruction because product A is out of stock" or "reflect the price of product B on the digital price tag."

[1794] Input: Stock shortage list, price change list

[1795] Output: Price change instructions, replenishment instructions

[1796] Step 6: Sending instruction data

[1797] The server sends the generated instruction data in JSON format to the device, allowing the device to perform appropriate updates based on the received data.

[1798] Input: Price change instructions, replenishment instructions

[1799] Output: JSON data sent to the terminal

[1800] Step 7: Start generating voice announcements

[1801] The server uses a generative AI model to generate voice announcements, such as "A limited-time sale starts at 3 p.m. All items are 30% off" based on information about special sales events and limited-time sales.

[1802] Input: Special sale event information, limited time sale information

[1803] Output: Voice announcement data

[1804] Step 8: Send a voice announcement

[1805] The server sends the generated voice announcement file to the terminal, allowing each terminal to play the announcement at the appropriate time.

[1806] Input: Voice announcement data

[1807] Output: Audio file sent to the device

[1808] Terminal side processing

[1809] Step 1: Receiving price information

[1810] The terminal receives price information in JSON format from the server, which includes specific price change instructions.

[1811] Input: Price change information in JSON format

[1812] Output: Price change instruction data

[1813] Step 2: Parse the price information

[1814] The terminal analyzes the received data and identifies which items require price changes, for example, identifying that item B is on a 10% discount.

[1815] Input: Price change instruction data

[1816] Output: Updated pricing information

[1817] Step 3: Update your digital price tags

[1818] Based on the analysis, the terminal will display the new price on a digital price tag for consumer verification.

[1819] Input: Updated pricing information

[1820] Output: New price displayed on the digital price tag

[1821] Step 4: Receive a voice announcement

[1822] The device retrieves the voice announcement file received from the server and stores it in local storage.

[1823] Input: Audio file sent to the device

[1824] Output: Saved audio file

[1825] Step 5: Play an announcement

[1826] The device then plays the stored audio announcement over the in-store speakers at the appropriate time, for example, announcing, "The 3 PM limited-time sale has begun."

[1827] Input: Saved audio file

[1828] Output: Played audio announcement

[1829] Step 6: Receiving replenishment orders

[1830] The terminal receives a replenishment instruction from the server, which is then sent to the terminal of the store staff member.

[1831] Input: Refill order sent to terminal

[1832] Output: Replenishment message sent to store staff

[1833] User processing

[1834] Step 1: Confirm replenishment instructions

[1835] The user (store staff) checks the replenishment instruction from the terminal. Specifically, a message is displayed saying, "Product A is low in stock. Please replenish from the warehouse."

[1836] Input: Replenishment instructions notified

[1837] Output: Confirmed replenishment order

[1838] Step 2: Replenish inventory

[1839] The user promptly replenishes inventory based on the confirmed instructions, for example, by taking product A from the warehouse and stocking it in the store.

[1840] Input: Confirmed replenishment order

[1841] Output: Replenished products

[1842] Step 3: Check for special offers

[1843] Users (consumers) check the latest sales information through digital price tags or voice announcements in the store. For example, they check the new price of product B on sale.

[1844] Input: Digital price tag, voice announcement

[1845] Output: Confirmed sale information

[1846] Step 4: Shop the sale items

[1847] The user purchases a product based on the sale information they have checked. For example, they pick up and purchase product B, which is on sale.

[1848] Input: Confirmed sale information

[1849] Output: Purchased items

[1850] Through these steps, the system can efficiently and effectively manage inventory, update price information, and automate sales events.

[1851] (Application example 1)

[1852] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1853] Conventional store management systems did not sufficiently streamline inventory management and price changes, and notifications of special sales and limited-time sales were often done manually. It was also difficult for store staff to share information in real time when replenishing inventory. Furthermore, effective sales information was not provided to consumers, resulting in lost sales opportunities. Therefore, there is a need for a system that automates inventory management, price changes, and sales information notifications, and provides appropriate information to consumers and store staff in real time.

[1854] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1855] In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require price changes, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for providing consumers with real-time sales information and limited-time sale start notifications using smartphones or tablet devices, means for providing store staff with real-time inventory status confirmation and replenishment instruction notification functions, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management, price change and sale information notifications, and real-time information provision to consumers and store staff.

[1856] Key Word Definitions

[1857] A "store management system" is an integrated information system for managing products, inventory, prices, etc. within a store.

[1858] "Product information" means data containing detailed information about each product, typically including the name, price, category, and availability.

[1859] "Inventory information" is data that indicates the current quantity of each product in the store and in the warehouse.

[1860] "Price information" is data that includes the current selling price and discount information for each product.

[1861] "Analysis" refers to the process of extracting and determining information for a specific purpose from collected data.

[1862] "Special sale information" is information indicating special sales conditions and discount details for products that will be offered within a certain period of time.

[1863] A "time sale" is a promotional event where products are sold at a discounted price for a specific time frame.

[1864] "Server" refers to a computer system that collects, analyzes, and distributes data over a network.

[1865] A "terminal" is a device for displaying and operating information, and includes smartphones and tablet devices.

[1866] "Multimodal AI technology" is an artificial intelligence technology that integrates multiple data modalities (e.g., voice, text, images) to perform analysis and decision-making.

[1867] A "voice announcement" is a means of conveying specific information using voice data.

[1868] "Real-time" refers to the generation and processing of data occurring immediately, without delay.

[1869] "Push notifications" are a technology that sends information to mobile devices in real time.

[1870] MODE FOR CARRYING OUT THE INVENTION

[1871] Server-side processing

[1872] Data collection

[1873] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information such as when there are 10 or fewer units of a specific product A in stock or when the price is discounted can be obtained.

[1874] Data analysis

[1875] The server analyzes the acquired data and identifies products that are low in stock or products subject to price changes. For example, it lists products with less than 10 units in stock or products for which discount campaigns are applied. This identifies products subject to special sales or limited-time sales.

[1876] instruction generation

[1877] The server generates price change information and replenishment instructions based on the analysis results. The generated data is sent to the terminal in JSON format. For example, it may contain specific instructions such as "issue a replenishment order because product A is out of stock" or "reflect the price change of product B on the digital price tag."

[1878] Generate a voice announcement

[1879] The server generates voice announcements using multimodal AI technology, creating voice messages based on information about special sales events and time sales, such as "Time sales start at 3 p.m. All items are 30% off," and sending them to the device.

[1880] Terminal side processing

[1881] View pricing information

[1882] The terminal analyzes the price information received from the server and displays it on the digital price tag. Specifically, it receives discount information for product B and displays the new price on the price tag.

[1883] Broadcast announcements

[1884] The device stores the voice announcement file received from the server in local storage and plays it back on the in-store speakers at the appropriate time. For example, it could announce, "The limited-time sale has started at 3 PM."

[1885] Staff Notification

[1886] The terminal notifies the store staff terminal of the replenishment instruction from the server. For example, a message such as "Product A is low in stock. Please replenish from the warehouse" is displayed.

[1887] User processing

[1888] Staff behavior

[1889] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. For example, they take product A from the warehouse and replenish it on the storefront.

[1890] Consumer behavior

[1891] The user (consumer) checks the latest sale information through digital price tags and voice announcements in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[1892] Hardware and software used

[1893] Server: A high-performance server is used, and a web framework such as Flask is used.

[1894] Devices: Smartphones, tablets, digital price tags, etc.

[1895] Software: Python, REST API, React Native, text-to-speech API, multimodal AI, etc.

[1896] Examples and prompts

[1897] For example, if you want to automatically issue replenishment instructions for specific products and update price change information in real time, the following prompt sentence is effective:

[1898] "Write a program that generates replenishment orders for low-stock items and updates digital price tags based on price change information. Also, add the ability to generate audio announcements about special sales and send them to a smartphone app."

[1899] The above is a specific embodiment for carrying out the present invention.

[1900] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1901] Program processing flow

[1902] Step 1:

[1903] Data collection

[1904] The server periodically collects product information, inventory information, and price information in JSON format from the store management system through an API. The API endpoint and authentication information are required as input. The data collection process involves sending an HTTP GET request and parsing the JSON data received as a response to extract fields such as product name, inventory quantity, price, and discount information. The output is parseable JSON data.

[1905] Step 2:

[1906] Data analysis

[1907] The server parses the collected JSON data. The JSON data to be parsed is used as input. The data parsing process filters based on specific conditions (for example, items with less than 10 units in stock, items with discount campaigns applied, etc.). Specifically, it lists items that are low in stock and items that need to be repriced. The output is a list of low-stock items and items that need to be repriced.

[1908] Step 3:

[1909] instruction generation

[1910] The server generates price change information and replenishment instructions based on the analysis results. As input, it requires a list of low-stock items and a list of items subject to price changes. In the instruction generation process, it generates JSON data containing stock replenishment instructions and new price information for each item. The generated data is sent to the terminal in the store via API. The output is replenishment instructions and price change information in JSON format, which are sent to the terminal.

[1911] Step 4:

[1912] Generate a voice announcement

[1913] The server generates a voice announcement using multimodal AI technology. The generated instruction content is used as input. The voice announcement generation process generates voice data using a text-to-speech API, which converts text content into an audio file. Specifically, it creates an announcement such as, "A limited-time sale starts at 3:00 PM. All items are 30% off." The output is the URL of the audio file.

[1914] Step 5:

[1915] View pricing information

[1916] The terminal parses the price change information received from the server and displays it on the digital price tag. The received price change information in JSON format is used as input. The price information display process immediately reflects the new price on the digital price tag. Specifically, it updates the display content of the price tag and applies the information to the product in the store. The output is the updated price tag display.

[1917] Step 6:

[1918] Broadcast announcements

[1919] The terminal stores the voice announcement file received from the server in local storage and plays it through the in-store speakers at the specified time. The URL of the voice file and playback timing information are used as input. The voice announcement broadcast process downloads the voice file and plays it on the playback device at the appropriate time. The output is the announcement broadcast in the store.

[1920] Step 7:

[1921] Staff Notification

[1922] The terminal notifies the store staff terminal of the replenishment instruction from the server. JSON data containing the replenishment instruction is used as input. The notification process sends a push notification to the store staff device and displays information about the products that need to be replenished. Specifically, it displays a message on the smartphone or tablet saying, "Product A is low in stock. Please replenish it from the warehouse." The output is a notification of the replenishment instruction to the staff.

[1923] Step 8:

[1924] Staff behavior

[1925] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes inventory. The replenishment instruction information displayed on the terminal is used as input. The behavioral process executes specific steps to retrieve the specified products from the warehouse and replenish them in the store. The output is the replenishment of products in the store and an inventory update.

[1926] Step 9:

[1927] Consumer behavior

[1928] Users (consumers) check the latest sale information through digital price tags and voice announcements in the store. The sale information obtained from the price tags and announcements is used as input. In the behavioral process, the user picks up a sale item and takes action to actually purchase it. The output is the sales record resulting from the purchase of the item.

[1929] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1930] Server-side processing

[1931] Data collection

[1932] The server periodically collects product information, inventory information, and price information from the store management system. This collection process is carried out via API, and the information is received as JSON format data. For example, information is obtained that product A has 10 or fewer units in stock and is eligible for a discount.

[1933] Data analysis

[1934] The server analyzes the acquired data and identifies products that are out of stock or that need to be subject to price changes. For example, the analysis may list products with inventory levels below 10 units and determine whether a price change is necessary based on discount campaign information.

[1935] Use of emotion engine

[1936] The server uses an emotion engine to collect and analyze in real time the emotional data of consumers in the store. This emotional data is acquired from cameras and sensors, and emotions are inferred from the consumers' facial expressions and behavior.

[1937] instruction generation

[1938] Based on the analysis results, the server generates price change information and replenishment instructions. The generated data is sent to the terminal in JSON format. For example, it may include instructions such as "Product A is out of stock, so issue a replenishment instruction" or "Update the price of product B on the digital price tag."

[1939] Generate a voice announcement

[1940] The server optimizes the announcement content based on information about special sales events and limited-time sales, as well as consumer sentiment data. For example, it creates a voice message such as, "Our limited-time sale starts at 3 p.m. All items are 30% off," and sends it to the device.

[1941] Terminal side processing

[1942] View pricing information

[1943] The terminal analyzes the price information received from the server and displays it on the digital price tag. For example, it receives information that product B is 10% off and displays the new price on the price tag.

[1944] Broadcast announcements

[1945] The device receives the audio file from the server, stores it in local storage, and plays it back on the in-store speakers at the appropriate time, for example announcing, "The limited-time sale has begun at 3 PM."

[1946] Staff Notification

[1947] The terminal notifies the store staff terminal of the replenishment instruction from the server. The notification content includes specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[1948] User processing

[1949] Staff behavior

[1950] The user (store staff) checks the replenishment instructions from the terminal and promptly replenishes the inventory. Specifically, the user takes product A from the warehouse and replenishes it on the storefront.

[1951] Consumer behavior

[1952] The user (consumer) checks the digital price tag, voice announcements, and emotion-based optimization information in the store. For example, the user checks the new price of product B on sale, picks it up, and purchases it.

[1953] In this way, the present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and further improves the consumer experience by utilizing an emotion engine.

[1954] The processing flow will be explained below.

[1955] Server-side processing steps

[1956] Data collection

[1957] Step 1:

[1958] The server sends periodic requests to the store management system to API endpoints containing product, inventory, and pricing information.

[1959] Step 2:

[1960] The server receives JSON-formatted data as a response from the store management system, including the current inventory level and the latest pricing information.

[1961] Data analysis

[1962] Step 3:

[1963] The server parses the collected JSON data and stores product availability and pricing information in an internal database.

[1964] Step 4:

[1965] The server analyzes the inventory levels for each product and creates a list of products whose inventory has fallen below a certain threshold (for example, 10 units).

[1966] Step 5:

[1967] The server analyzes the pricing information to determine whether discounts or special offers are necessary, for example, determining price changes for items that qualify for a special promotion.

[1968] Use of emotion engine

[1969] Step 6:

[1970] The server collects consumer facial expression and behavioral data obtained from cameras and sensors within the store.

[1971] Step 7:

[1972] The server uses an emotion engine to analyze the consumer's emotions in real time from the collected data, inferring, for example, whether the consumer is excited or bored.

[1973] instruction generation

[1974] Step 8:

[1975] Based on the analysis results, the server generates price change information and replenishment instructions, and the generated data is sent to the terminal in JSON format.

[1976] Step 9:

[1977] The server generates price change information for the identified product in JSON format, including the new price.

[1978] Step 10:

[1979] The server generates a replenishment instruction and records a message in an internal database, such as "Product A is low in stock, please replenish."

[1980] Generate a voice announcement

[1981] Step 11:

[1982] The server optimizes the content of announcements based on information about special sales events and limited-time sales, as well as consumer sentiment data.

[1983] Step 12:

[1984] The server utilizes a text-to-speech (TTS) engine to convert the generated text announcement into an audio file.

[1985] Step 13:

[1986] The server prepares to send the generated audio file to the in-store terminal.

[1987] Terminal processing steps

[1988] View pricing information

[1989] Step 1:

[1990] The terminal receives price information in JSON format sent from the server.

[1991] Step 2:

[1992] The terminal parses the received JSON data and extracts the product ID and new price.

[1993] Step 3:

[1994] The terminal then processes the digital price tag to display the new price, specifically by updating the tag's display.

[1995] Broadcast announcements

[1996] Step 4:

[1997] The terminal receives the audio file sent from the server.

[1998] Step 5:

[1999] The terminal stores the received audio file in local storage.

[2000] Step 6:

[2001] The terminal sends the audio file to the in-store speaker at the specified time and plays the announcement.

[2002] Staff Notification

[2003] Step 7:

[2004] The terminal receives a replenishment instruction from the server.

[2005] Step 8:

[2006] The terminal parses the received replenishment instruction and extracts the products to be replenished and the specific quantities.

[2007] Step 9:

[2008] Based on the extracted information, the terminal displays a notification message on the store staff's terminal, displaying a pop-up message with specific instructions such as "Please replenish the stock of product A."

[2009] User processing steps

[2010] Staff behavior

[2011] Step 1:

[2012] The user (store staff member) checks the replenishment instructions from the terminal and understands the displayed content.

[2013] Step 2:

[2014] The user follows the instructions and replenishes the storefront with the stock of the specified product from the warehouse.

[2015] Consumer behavior

[2016] Step 3:

[2017] Users (consumers) see digital price tags, voice announcements, and sentiment-based optimization information in the store.

[2018] Step 4:

[2019] The user picks up the sale or discounted item and heads to the cash register to make the purchase.

[2020] Example 2

[2021] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2022] In today's retail industry, efficient and effective inventory management, price updates, and even marketing activities are extremely important. However, traditional store management systems face challenges in that they are unable to provide real-time data and optimally timed information based on consumer behavior and emotions. Furthermore, inventory shortages and missed price changes frequently occur, resulting in reduced store operational efficiency.

[2023] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for collecting consumer emotion data in the store and analyzing it in real time using emotion analysis technology, means for generating price change information and replenishment instructions and transmitting them to terminals in the store, means for generating and transmitting the generated announcement content as an audio announcement, and a terminal for displaying the generated price change information and playing the audio announcement. This enables inventory management and price updates to be performed more efficiently and effectively than before, and enables information to be provided at the optimal time based on consumer emotions and behavior. Furthermore, it enables quick notification of replenishment instructions to store staff and real-time announcements to consumers, thereby improving the efficiency of store operations and customer satisfaction.

[2024] A "store management system" is a system for comprehensively managing a store's inventory, sales, pricing, etc.

[2025] "Product information" refers to basic information about a product, such as product name, product code, classification, and description.

[2026] "Inventory information" refers to data regarding the inventory quantity of each product, inventory history, inventory location, etc.

[2027] "Price information" refers to data including the current price of each product, past price change history, discount information, etc.

[2028] "Analysis" refers to the process of determining whether collected data meets certain conditions and extracting relevant information.

[2029] "Emotion analysis technology" refers to technology that uses data obtained from cameras and sensors to infer emotions from consumers' facial expressions and behavior.

[2030] "Price change information" refers to information for updating an existing price to a new price.

[2031] "Replenishment Instructions" refers to specific instructions to notify store staff to replenish items that are low in stock.

[2032] "Announcement content" refers to announcements made in stores, including information about special sales and limited-time sales.

[2033] "Voice announcement" refers to broadcasting the generated announcement content in audio format within the store.

[2034] "Terminal" refers to a device that communicates with a server to receive information and display or play audio.

[2035] The present invention is a system that efficiently and effectively implements limited-time sales and special sale events through collaboration between store management systems, servers, terminals, and users, and also improves consumer experience by utilizing emotion analysis technology.

[2036] Server Processing

[2037] Data collection

[2038] The server periodically sends requests to the API endpoint of the store management system and receives product information, inventory information, and price information in JSON format. This process can be done using, for example, the curl library or an HTTP client. The received data is then stored in a database, for example, MongoDB.

[2039] Data analysis

[2040] The server reads the latest data from the database and identifies products whose inventory has dropped below a certain level or whose prices need to be adjusted. This analysis is done using SQL or NoSQL queries. For example, it retrieves a list of products with less than 10 units in stock and determines whether a price change is necessary based on current promotions.

[2041] Use of emotion analysis technology

[2042] The server acquires video data from cameras and sensors in the store and performs facial recognition using, for example, the OpenCV library. It then analyzes consumer emotions in real time using an emotion analysis engine (for example, Microsoft Azure Face API). The analysis results are stored in a database.

[2043] instruction generation

[2044] Based on the results of data and sentiment analysis, the server generates stock replenishment instructions and price change information in JSON format and sends it to the terminal. For example, specific instructions such as "Inventory of product A is low, so issue an instruction to replenish it" or "Update the price of product B on the digital price tag" can be included.

[2045] Generate a voice announcement

[2046] The server collects information about special sales events and limited-time sales, and generates optimal announcement content while referring to consumer sentiment data. The generated text is converted into an audio file using Google Text-to-Speech API or similar and sent to the device. For example, a voice announcement such as "Our limited-time sale starts at 3 p.m. All items are 30% off" may be created.

[2047] Terminal handling

[2048] View pricing information

[2049] The terminal parses the JSON data received from the server and displays the new price on the digital price tag. For example, if product B is 10% off, the terminal displays this information on the E-ink display.

[2050] Broadcast announcements

[2051] The device receives the audio file from the server, stores it in local storage, and plays it from the in-store speakers at the specified time. As a specific example of operation, the audio file is downloaded using the wget command and played based on a pre-set schedule.

[2052] Staff Notification

[2053] The device extracts replenishment instructions from the server using JSON data and sends notifications to store staff members' smartphones using the Firebase Cloud Messaging service. The notifications include specific instructions such as "Product A is low in stock. Please replenish it from the warehouse."

[2054] User Behavior

[2055] Staff behavior

[2056] The user, a store staff member, receives the notification from the device and replenishes the products according to the instructions. For example, the staff member checks the notification on their smartphone, quickly retrieves product A from the warehouse, and replenishes it on the storefront.

[2057] Consumer behavior

[2058] The consumer user is encouraged to make a purchase by checking the new price on the digital price tag or the voice announcement over the in-store speaker. For example, the user checks the new price of a special sale item B, picks up the item, and purchases it.

[2059] Prompt Sentence Examples

[2060] "Please explain the process of a program that analyzes product information obtained from the store management system, generates replenishment instructions for items that are low on stock, and notifies store staff."

[2061] In this way, the present invention is a system that realizes more efficient and effective store operations and an improved customer experience through close cooperation between the server, terminals, and users.

[2062] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2063] Server Processing

[2064] Data collection

[2065] Step 1:

[2066] The server prepares an API client and accesses the API endpoint of the store management system. This is achieved by issuing an HTTP request using, for example, the curl library. The input is the API endpoint URL, and the output is a JSON-formatted response containing product information, inventory information, and price information.

[2067] Step 2:

[2068] The server parses the received JSON format data and extracts the necessary information. Specifically, it uses a JSON parser to convert the data into an object and extracts information such as product name, stock quantity, and price. The input is JSON data, and the output is the parsed data object.

[2069] Step 3:

[2070] The server stores the parsed data in a database. For example, it uses the MongoDB insertOne method to insert each product's information into the database. The input is the parsed data object, and the output is the result stored in the database.

[2071] Data analysis

[2072] Step 1:

[2073] The server retrieves the latest inventory and pricing information from the database by issuing a query with specific criteria, for example using the MongoDB find method. The input is the query criteria, and the output is the data object that is the query result.

[2074] Step 2:

[2075] The server identifies products whose inventory has fallen below a certain level or whose prices need to be changed by filtering the data it retrieves to create a list of products with inventory levels of 10 or less or that are on a discount. The input is the query results from the database, and the output is the list of identified products.

[2076] Step 3:

[2077] The server generates replenishment instructions and price change information based on the information of the identified products. For example, if there are 10 or fewer products in stock, it creates a specific instruction such as "Replenish product A." The input is a list of identified products, and the output is the generated instructions and price change information.

[2078] Use of emotion analysis technology

[2079] Step 1:

[2080] The server collects video data obtained from cameras and sensors. This is done, for example, by using the camera's API to acquire video in real time. The input is video data from the camera, and the output is image data for each frame.

[2081] Step 2:

[2082] The server sends the video data to an emotion analysis engine to analyze consumer emotions. Specifically, it uses OpenCV to perform facial recognition and sends the results to an emotion analysis engine (for example, Microsoft Azure Face API). The input is image data for each frame, and the output is emotional data as the analysis result.

[2083] Step 3:

[2084] The server saves the analysis results in a database and updates the results in real time. The input is emotion data as the analysis result, and the output is the result saved in the database.

[2085] instruction generation

[2086] Step 1:

[2087] The server combines the results of data analysis and sentiment analysis to generate replenishment instructions and price change information. Specifically, it generates replenishment instructions for low-stock items based on the data analysis results and optimizes the timing of price changes based on the sentiment analysis results. The input is the analysis results, and the output is the generated instructions and price change information.

[2088] Step 2:

[2089] The server converts the generated instructions and price change information into JSON format and sends it to the terminal. The input is the generated instructions and price change information, and the output is JSON format data.

[2090] Generate a voice announcement

[2091] Step 1:

[2092] The server collects information about special sales events and limited-time sales, and determines the content of announcements. Specifically, it creates announcement content based on a pre-set schedule and the results of sentiment analysis. The input is schedule information and sentiment analysis results, and the output is announcement text.

[2093] Step 2:

[2094] The server converts the generated announcement text into an audio file. Specifically, it uses the Google Text-to-Speech API to convert text to audio. The input is the announcement text, and the output is an audio file.

[2095] Step 3:

[2096] The server sends the generated audio file to the terminal. The input is the audio file, and the output is the transmission result to the terminal.

[2097] Terminal handling

[2098] View pricing information

[2099] Step 1:

[2100] The terminal parses the JSON data received from the server and extracts new price information. The input is the received JSON data and the output is the extracted price information.

[2101] Step 2:

[2102] The terminal displays the extracted price information on a digital price tag, specifically by updating the new price on the E-ink display. The input is the extracted price information and the output is the displayed price.

[2103] Broadcast announcements

[2104] Step 1:

[2105] The device saves the audio file received from the server in local storage. The input is the audio file, and the output is the result saved in local storage.

[2106] Step 2:

[2107] The terminal plays the stored audio file at the appropriate time. Specifically, it plays the audio through the store's speakers. The input is the stored audio file, and the output is the played audio.

[2108] Staff Notification

[2109] Step 1:

[2110] The terminal parses the replenishment order received from the server and extracts the necessary information. The input is the received JSON data, and the output is the extracted replenishment order.

[2111] Step 2:

[2112] The terminal notifies the extracted replenishment instructions to the store staff's smartphones. Specifically, it sends notifications using the Firebase Cloud Messaging service. The input is the extracted replenishment instructions, and the output is the sent notification.

[2113] User Behavior

[2114] Staff behavior

[2115] Step 1:

[2116] The user (store staff) receives a replenishment instruction notification on their smartphone. The input is the smartphone, and the output is the received notification.

[2117] Step 2:

[2118] The user replenishes the products according to the notification. Specifically, the staff retrieves the specified products from the warehouse and replenishes them in the store. The input is the received notification, and the output is the replenished products.

[2119] Consumer behavior

[2120] Step 1:

[2121] The user (consumer) checks the new price information displayed on the digital price tag. The input is the digital price tag, and the output is the checked price information.

[2122] Step 2:

[2123] Users listen to audio announcements from in-store speakers, which stimulates their desire to make a purchase. Specifically, they pick up and purchase products based on information about special sales and time-limited sales. The input is the audio announcement, and the output is the purchased product.

[2124] (Application example 2)

[2125] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2126] With conventional store management systems, inventory management and pricing are time-consuming and place a heavy burden on store staff. Furthermore, it is not possible to grasp consumer sentiment and behavior in real time, making it difficult to provide optimal services. Therefore, there is a need for efficient and accurate inventory management, price changes, and flexible service provision in response to consumer behavior.

[2127] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting product information, inventory information, and price information from the store management system, means for analyzing the collected information and identifying products whose inventory is below a certain level or products that require a price change, means for generating price change information and replenishment instructions and sending them to terminals in the store, means for generating and sending the generated announcement content as a voice announcement, and a terminal for displaying the generated price change information and playing the voice announcement. In this system, the server includes means for generating and optimizing the voice announcement using a generative AI model, and means for inputting prompt sentences into the generative AI model to create the voice announcement. This enables efficient and accurate inventory management and price changes, as well as the provision of optimal services based...

Claims

1. A means for collecting product information, inventory information, and price information from a store management system; A means of analyzing the collected information to identify products that are below a certain level of inventory or require price changes; means for generating and transmitting price change information and replenishment instructions to in-store terminals; means for generating and transmitting the generated announcement content as a voice announcement; A system including a terminal that displays the generated price change information and plays an audio announcement.

2. 10. The system of claim 1, further comprising means for using multimodal AI techniques to monitor consumer behavior in the store and optimize announcements in real time.

3. 2. The system according to claim 1, further comprising means for notifying a store staff member of a replenishment instruction and means for displaying the instruction on a terminal of the store staff member.

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