system

Abstract

We provide the system. [Solution] A means of obtaining the product information desired by the user terminal, The terminal acquires location information and transmits it to the server along with the product information, A means for the server to obtain information about stores that handle the product, The server uses generated AI to acquire inventory information for the store, The server provides a means for displaying the nearest store with available stock to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, when consumers search for products they want in stores, they need to visit multiple stores to check the inventory status, which is a great deal of trouble for consumers. In particular, although the need to easily and quickly grasp the inventory status using a mobile terminal is increasing, there are not enough systems to realize this. It is required to solve this problem.

Means for Solving the Problems

[0005] This invention provides a means for a user to use their mobile device to send information about the product they want and their location to a server, and then use a generating AI to check the inventory status of nearby stores that carry the product. Based on the acquired inventory information, the server can identify the nearest store with the product in stock and present it to the user. Furthermore, the server can rank the stores based on the inventory information to provide the user with the most optimal information. This system allows users to check inventory information in real time before visiting a store, enabling efficient purchasing activities.

[0006] A "user terminal" is a computing device operated by a user, used for acquiring and transmitting product information and location information.

[0007] "Product information" refers to identifying information about a specific product that a user wishes to purchase.

[0008] "Location information" refers to geographical information that indicates the current location of the user's device.

[0009] A "server" is a computer system that processes information received from user terminals, aggregates related data, and provides it to users.

[0010] "Generative AI" is an artificial intelligence system used to efficiently acquire and determine the inventory status of a store.

[0011] "Inventory information" refers to information about whether a particular product is available in a store.

[0012] The "nearest store" is the store closest to the user's current location that has confirmed stock availability for the desired product.

[0013] "Presentation" refers to the act of displaying or notifying information to a user.

[0014] "Ranking" refers to the act of determining the priority of stores based on specific criteria.

Brief Description of the Drawings

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention is a system that enables users to efficiently search for specific products via communication between their mobile device and a server. First, the user uses their device to input information about the product they wish to purchase, and then the device acquires their current location information. The device then transmits this product information and location information to the server.

[0037] Based on the information received, the server consults a database to identify nearby stores that may carry the product. Furthermore, the server utilizes generated AI to check the inventory status of the identified stores. The AI ​​uses technology to access the stores' inventory management systems and retrieve the inventory status of the specified product.

[0038] The server then ranks the stores that have been determined to have the item in stock. The ranking takes into account several criteria, including the distance from the user's current location to the store, the store's opening status, and whether the product is immediately available. This ensures that information on the most accessible stores is provided to the user first.

[0039] This information is visually displayed on a map on the user's device, allowing them to check the nearest store with the item in stock. Based on this information, the user can either visit the store or arrange for delivery of the product through the app. For example, if a user is looking for a specific drink, the device will show the nearest store with the item in stock, allowing the user to efficiently choose to purchase the product based on that information.

[0040] This system aims to improve the consumer experience by reducing user effort, providing an environment where products can be found quickly, and enabling users to easily find what they're looking for.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user launches their mobile device, enters the information of the desired product into the app's search bar, and begins the search.

[0044] Step 2:

[0045] The device receives input from the user and obtains the current location information via GPS. The device then structures the obtained product information and location information and prepares to send it to the server.

[0046] Step 3:

[0047] The device transmits product information and location information to the server.

[0048] Step 4:

[0049] The server analyzes the received information and retrieves a list of stores that may carry the product from the database.

[0050] Step 5:

[0051] The server uses a generated AI model to query the inventory status of identified stores. The AI ​​model connects to each store and checks whether the specified product is in stock.

[0052] Step 6:

[0053] The generating AI model sends information about inventory status back to the server.

[0054] Step 7:

[0055] The server identifies stores with stock and ranks them based on factors such as distance from the user's current location, opening hours, and delivery and pickup options.

[0056] Step 8:

[0057] The server sends optimized store information to the terminal, which is then integrated with map data for a visual representation.

[0058] Step 9:

[0059] The terminal displays the received information to the user, showing the nearest store with stock on a map. The user then has the option to visit the store or order online.

[0060] Step 10:

[0061] Based on the information provided, users can either visit a retailer or proceed with the product delivery process via the app.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] Traditionally, a problem has been that users cannot quickly find specific items, leading to decreased purchasing efficiency. Furthermore, there was no easy way to obtain inventory information from nearby facilities and present users with the best purchasing options. Therefore, improving the consumer purchasing experience is a key challenge.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for acquiring facility information that handles goods, means for acquiring inventory information of facilities using a generating AI, means for presenting facilities in order of priority, and means for ranking facilities considering the user's geographical location. This makes it possible for users to efficiently find goods and visually understand the nearest facility with inventory.

[0067] A "user information terminal" refers to an electronic device used by users to input information, and includes smartphones and tablets.

[0068] "Item information" refers to information about the name and category of the product that the user wishes to purchase.

[0069] "Geographic location information" refers to latitude and longitude data indicating the current location of the user's information terminal.

[0070] A "server" refers to a central computer system that receives and processes information from user information terminals.

[0071] "Facility information" refers to information about stores and warehouses that may handle goods.

[0072] "Inventory information" refers to data that shows the inventory status of goods at a specific facility.

[0073] "Generative AI" refers to technology that uses artificial intelligence to generate new information and data.

[0074] "Presenting in order of priority" refers to displaying multiple options in a rearranged order based on their importance and convenience, according to specific criteria.

[0075] "Ranking" refers to assigning positions based on evaluation criteria.

[0076] To implement this invention, a system is constructed in which the user, terminal, and server work in cooperation. The user uses a user information terminal such as a smartphone or tablet to input information about the items they wish to purchase into a dedicated application. For example, if the user inputs "I want to buy 500ml of green tea" into the app, this information is acquired.

[0077] The device obtains the user's geographical location information using its built-in GPS function or location services. The user's device combines item information and geographical location information and transmits it to the server via the internet. HTTP or HTTPS protocols are commonly used for this communication.

[0078] The server analyzes the received information and extracts information about facilities that may handle the items from the database based on the item information. In this process, relational database management systems such as MySQL® or PostgreSQL may be used as the database.

[0079] Next, the server uses a generative AI model to retrieve inventory information for each facility. The AI ​​model utilizes pre-trained natural language processing techniques. As an example of a prompt, the text used is, "Please tell me the inventory status of 500ml green tea at store A."

[0080] After retrieving facility inventory information, the server sorts the facilities in order of priority, taking into account the user's current location and other factors. This ranking method allows the facility to be presented to the user in order of its convenience.

[0081] Ultimately, the server sends ranking information to the terminal. The terminal visually displays facility information using map APIs and other tools, prompting the user to take concrete purchasing action. Based on this information, the user can choose to visit the desired facility or place an order online.

[0082] In this way, users can efficiently find items and improve their consumer experience.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users use information terminals such as smartphones and tablets to input information about the items they wish to purchase. Specifically, they launch a dedicated app and enter a specific prompt in text format, such as "I want to buy 500ml of green tea." This input information is sent to the terminal as data indicating the name and type of item.

[0086] Step 2:

[0087] The device stores the item information entered by the user and retrieves the current geographical location information by calling its internal location information service. Using the GPS sensor, it outputs data as latitude and longitude. As a result, the device contains both the user's item information and geographical location information as input data.

[0088] Step 3:

[0089] The terminal combines acquired item information and geographical location information and sends it to the server as a data structure such as JSON. The HTTP protocol is used for this transmission over the internet. The terminal's operation involves converting the input data into a format that the server can process and sending it as a request.

[0090] Step 4:

[0091] The server parses the JSON data received from the terminal, analyzes the item information, and extracts the corresponding facility information from the database. This process uses SQL queries to output a list of relevant facilities. The output data includes basic facility information such as the facility name and address.

[0092] Step 5:

[0093] The server uses a generative AI model to check the inventory information of each extracted facility. It generates specific questions as prompts, such as "Please tell me the inventory status of 500ml green tea at store A," and queries the inventory management systems of each facility. The AI ​​model analyzes this and outputs data indicating whether or not the item is in stock.

[0094] Step 6:

[0095] The server uses multiple facility information and inventory data to create a ranking that takes into account factors such as distance from the user's current location and opening status. It then executes a ranking algorithm to determine the priority of each facility. This results in the output of the optimal facility ranking to present to the user.

[0096] Step 7:

[0097] The server sends optimized facility ranking information to the terminal. The terminal analyzes the received information and visualizes it on a map using Google Maps API, etc. By highlighting the most easily accessible facilities on the map, it becomes possible to take concrete actions that encourage purchasing behavior.

[0098] Step 8:

[0099] Users can view information displayed on a map and choose to visit the nearest facility with stock or place an order online directly through the application. This allows users to make efficient purchasing decisions.

[0100] (Application Example 1)

[0101] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0102] Users may have difficulty efficiently finding the products they want to buy in physical stores. In particular, they may not be able to quickly check whether nearby stores have the product in stock, leading to wasted travel time and effort. Even when they find the optimal store, they may face challenges such as difficulty figuring out the route to the store or reserving the product.

[0103] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0104] In this invention, the server includes means for acquiring desired product information, means for acquiring location information and transmitting it to an information processing device along with the product information, means for acquiring information about the facilities that handle the products, means for acquiring inventory information of the facilities using generation AI technology, means for presenting the nearest facility with stock to the user, and means for providing a route to the presented facility. This enables the user to quickly acquire information about the nearest store with stock and visit it via an efficient route.

[0105] An "information processing device" is a terminal device operated by a user that has the function of acquiring location information and product information, and communicating with other devices.

[0106] "Generative AI technology" is a technology that uses artificial intelligence to analyze inventory and store information and provide users with useful information.

[0107] "Location information" refers to data that indicates the user's current geographical location, and is information obtained through the user's device.

[0108] A "facility" refers to a physical store or warehouse where products are handled, and the inventory information for that facility is provided to the user.

[0109] "Inventory information" refers to information about the quantity of a particular product currently held at a facility and its immediate availability for purchase.

[0110] A "route" is geographical guidance information that suggests the optimal mode of transportation to the facility selected by the user.

[0111] "Presentation" refers to the act of providing information that is displayed on a user's device, serving as a guide for the user to take action based on that information.

[0112] This invention is a system that enables users to efficiently find products by transmitting product information and location information to a server via an information processing device. The information processing device consists of a terminal such as a smartphone or tablet, which acquires location information using GPS functionality and allows users to input desired product information.

[0113] The server is built as a server-side application using Node.js and interacts with the Firebase database to retrieve information about nearby facilities. The server also utilizes OpenAI® GPT-3®, a generative AI technology, to provide optimal facility information, including route information to the facility, based on the acquired facility inventory information.

[0114] Users can view displayed facility information on a map via their device and receive route guidance to the nearest facility. They can also choose to purchase products online based on the facility information. This system provides an efficient shopping experience through real-time inventory checks.

[0115] For example, if a user is looking for cosmetics of a specific brand, they can enter "Brand X lotion" into the terminal, which will then display the nearest store with the product in stock. The user can then use this information to efficiently visit a store or place an online order.

[0116] An example of a prompt used in a generative AI model is: "Check the nearby stock availability of a specific product and recommend the best facility. Product: Brand X lotion, Location: (35.6895, 139.6917)."

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The user enters product information for the product they wish to purchase on their device. The entered information, such as product name and category, is stored on the device. The device also uses its GPS function to obtain its current location. This location information, along with the product information, is then prepared for input to the server.

[0120] Step 2:

[0121] The device sends acquired product information and location data to the server. The server receives this information and uses it directly as a starting point for queries to the database. This information forms the basis for the data processed in the next step.

[0122] Step 3:

[0123] The server uses the received product information and the user's location to search the Firebase database. The database returns a list of facilities that may carry the relevant product. Through this process, the server obtains information about relevant facilities within a certain range of the user's current location.

[0124] Step 4:

[0125] The server utilizes OpenAI GPT-3, a generative AI technology, to check the inventory status of each facility based on the acquired facility information. Specifically, it queries the facility's inventory management system to obtain the availability of specified products. At this stage, the server aggregates the inventory information for each facility.

[0126] Step 5:

[0127] The server evaluates and ranks facilities based on aggregated inventory information, considering factors such as distance and the immediate availability of inventory. The highest priority facilities are those located close to the user's location and possessing the specified product in stock. Once the evaluation is complete, ranking information for each facility is generated.

[0128] Step 6:

[0129] The server sends facility information, along with map data, to the terminal. The terminal receives this information and displays it visually to the user. This allows the user to easily identify the nearest suitable facility and then use the map to begin directions to the store.

[0130] Step 7:

[0131] Based on the provided facility information, users can either visit a physical store or order products online via the application. Depending on the user's choice, additional options and services (such as product reservation) may also be offered.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention is a system that uses a user terminal and a server to acquire product information and combines this with an emotion engine that analyzes the user's emotions. First, the user uses a mobile terminal to input information about the product they wish to purchase. At this time, the terminal uses the device's camera and microphone to collect the user's facial expressions and voice, and acquire emotion data.

[0134] The device sends acquired product information, emotion information, and location information to the server. The server analyzes this information and consults a database to identify nearby stores that carry the product. The server uses a generative AI to check the inventory status of the identified stores and, at the same time, adjusts the recommendations for stores and products based on the emotion data acquired by the emotion engine, according to the user's current mood.

[0135] The emotion engine uses technology that identifies various emotional states by utilizing the user's voice and facial expression data. For example, if the user is detected as excited, the emotion engine can prioritize suggesting trending or new products to the user. The server also sorts and presents stores with confirmed inventory in an order that is optimal for the user's emotional state.

[0136] Users can check the nearest stores with stock on a map displayed on their device and choose to visit or order online. For example, if the system recognizes the user's mood when they are looking for a "specific drink," it can suggest other products that would go well with that drink.

[0137] This system aims to more accurately understand user needs, improve individual experiences, and provide a highly satisfying purchasing experience for consumers.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] The user activates their mobile device, opens the app, and enters information about the product they wish to purchase. The device simultaneously captures the user's facial expressions and voice data using its camera and microphone.

[0141] Step 2:

[0142] The device gathers product information, emotion data, and location information and prepares to send it to the server.

[0143] Step 3:

[0144] The device sends the above information to the server. The data is encrypted as needed before being sent.

[0145] Step 4:

[0146] The server analyzes the received information and retrieves information about nearby stores that may carry the product from the database.

[0147] Step 5:

[0148] The server uses generated AI to contact the listed stores and check the stock status of the specified product.

[0149] Step 6:

[0150] The server utilizes an emotion engine to analyze user emotional data. This allows it to adjust product and store recommendations to match the user's mood and emotions.

[0151] Step 7:

[0152] The server ranks stores with available stock and then sorts them in an order optimized for the user's emotional state. This ensures that the most relevant information is provided to the user first.

[0153] Step 8:

[0154] The server sends ranked store information back to the terminal and presents it to the user as a map or list.

[0155] Step 9:

[0156] Based on the information received by the device, the system displays the nearest stores with stock on a map and suggests options for visiting a store or ordering online.

[0157] Step 10:

[0158] Users select a store based on the information presented and either visit it in person or complete the purchase process through the app. Additional suggestions based on the user's emotions can also be useful here.

[0159] (Example 2)

[0160] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0161] Conventional sales information systems simply presented product and inventory information without considering the user's emotions. Therefore, it was difficult to maximize user purchasing intent and satisfaction. Furthermore, while inventory information could be checked, suggestions combining other products and optimal store selections were lacking. This invention aims to improve the user experience by providing more appropriate product and store suggestions based on the user's emotional state.

[0162] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0163] In this invention, the server includes means for acquiring the user's facial expressions and voice and generating emotion data, means for adjusting store and product suggestions based on the emotion data, and means for ranking sales locations based on inventory information and the user's emotion data. This makes it possible to optimize product suggestions and sales locations according to the user's emotions.

[0164] A "user terminal" is a computing device used by users to input product information and acquire emotional data.

[0165] "Product information" refers to data such as the name, category, and barcode of the product that the user wishes to purchase.

[0166] "Location data" refers to information that indicates the geographical location of the user's device.

[0167] "Emotional data" refers to information that indicates the emotional state of a user, analyzed from their facial expressions and voice.

[0168] A "server" is a central processing unit that receives and processes information sent from user terminals and provides optimal store and product recommendations.

[0169] A "place of sale" refers to a physical or online store that sells the product.

[0170] "Generative AI" is an artificial intelligence technology that operates on a server and supports the acquisition of inventory information and the adjustment of suggestions.

[0171] "Inventory information" refers to data that shows the availability of a product at a specific sales location.

[0172] "Adjusting suggestions" means optimizing the selection of products and stores suggested based on user sentiment data.

[0173] "Ranking" means evaluating and assigning a ranking to sales locations based on specific criteria.

[0174] This invention is a system consisting of a user terminal and a server that combines the acquisition of product information with the analysis of the user's emotions to provide appropriate product recommendations. The user inputs information about the products they wish to purchase using their mobile device. During this process, the terminal utilizes input devices such as a camera and microphone to collect the user's facial expressions and voice, generating emotion data. This makes it possible to analyze the user's emotional state in real time.

[0175] Product information, emotion information, and location information acquired by the device are transmitted to a server via the internet. The server processes this information and, by referring to its own database, identifies nearby sales locations that carry the product. This process utilizes generative AI models to obtain real-time inventory information for each sales location. The server also adjusts and optimizes store and product suggestions based on the user's emotion data obtained by the emotion engine. This enables more personalized suggestions that match the user's current emotional state.

[0176] For example, when a user is searching for a "new smartphone," if the emotion engine recognizes that the user is excited, the system can focus on suggesting the latest models and highly-rated products, and can also introduce related accessories.

[0177] Examples of prompts for the generative AI model include: "When a user is searching for new products, suggest appropriate product combinations, taking into account their current emotional state," and "Develop a strategy to encourage purchases of specific desired products by making suggestions based on the user's emotions."

[0178] By using this system, users will be able to obtain product information that more accurately matches their needs, aiming to provide a more fulfilling shopping experience.

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The user enters information about the product they wish to purchase using a mobile device. Specifically, the user launches an application on their device and enters the product name and category in text format, or scans the product barcode with the camera. The input data (product information) obtained includes the product name and barcode. This data is temporarily stored on the device.

[0182] Step 2:

[0183] The device uses its camera and microphone to collect the user's facial expressions and voice, generating emotion data in real time. Emotion analysis software analyzes the user's facial muscle movements and voice tone to determine their emotional state (e.g., joy, excitement, relaxation). This process yields the output as emotion data.

[0184] Step 3:

[0185] The device transmits acquired product information, emotion data, and location data to a server. Using a communication module within the device, this data is encrypted and transmitted to the server via the internet. The server receives this data as input.

[0186] Step 4:

[0187] The server, based on the received product information, consults a database to identify nearby retail locations that carry the product. Specifically, it uses a database search algorithm to extract store information that matches the entered product information. As output of this process, a list of identified retail locations is generated.

[0188] Step 5:

[0189] The server uses a generated AI model to retrieve inventory information for identified sales locations. The AI ​​model queries the database to check the real-time inventory status of each sales location. This step yields inventory information for each sales location as output.

[0190] Step 6:

[0191] The server adjusts its recommendations to suggest the most suitable stores and products to the user based on emotional data. It utilizes an emotional data analysis engine to prepare suggestions tailored to the user's current emotional state. This adjustment results in personalized recommendations for each individual user.

[0192] Step 7:

[0193] The server sends information to the user's terminal, including the nearest sales location with the item in stock, as the final recommendation. Here, the optimized recommendation data is encrypted again and sent back to the terminal. The user's terminal receives this information and displays it on the screen.

[0194] (Application Example 2)

[0195] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0196] In today's commercial environment, consumers demand quick and accurate information and suggestions when making purchases, but systems capable of addressing individual, emotion-based needs are limited. Current systems fail to adequately provide optimal product recommendations tailored to consumers' emotional states, nor do they adequately suggest nearby retail locations based on those emotional factors. Therefore, improving the personalized purchasing experience for each individual consumer is a key challenge.

[0197] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0198] In this invention, the server includes means for suggesting products or sales locations based on user sentiment data, means for ranking sales locations based on inventory information, and means for displaying the nearest location with available stock. This enables optimal purchase suggestions tailored to the user's emotional state and provides a customized purchasing experience that meets individual needs.

[0199] A "user terminal" is a computing device that has the function of acquiring product information and sentiment data and sending it to a server.

[0200] "Emotional data" refers to information that represents a user's emotional state, and is digital data obtained through the analysis of voice and facial expressions.

[0201] "Location information" refers to information indicating the geographical location of a user's device, and is data obtained using GPS or similar methods.

[0202] A "server" is a central computing system that analyzes data received from user terminals and provides information on sales locations and product suggestions.

[0203] A "sales outlet" is a physical or online facility that handles products.

[0204] "Generative artificial intelligence" is a computational technology that can make human-like decisions based on large amounts of data.

[0205] "Inventory information" refers to data that shows the inventory status of products at sales locations.

[0206] A "suggestion" is information that presents the most suitable products and sales locations based on the user's emotional state and desired purchases.

[0207] The system for implementing this invention consists of a user terminal, a server, and a communication network. The user first uses a mobile terminal to input the products they wish to purchase. The terminal is equipped with a camera and a microphone, and acquires emotional data by analyzing the user's facial expressions and voice. This allows the terminal to identify the user's emotional state.

[0208] Emotional data, product information, and location information are transmitted from the terminal to the server. The server analyzes this data and uses a database of sales locations to check inventory at each location that handles the product. Generative artificial intelligence technology is used to suggest the most suitable products and recommend sales locations based on the user's emotional state.

[0209] As a concrete example, consider a case where a user is looking for a specific drink. If the server recognizes that the user is in a cheerful mood, it can suggest snacks or other products that would pair well with that drink. For example, a prompt such as "Tell me some desserts I can enjoy today" might be generated. Based on this prompt, the server provides suggestions that are appropriate for the user.

[0210] The server provides users with the optimal ordering method: direct purchase at a designated sales location or online ordering. It also prioritizes locations with confirmed stock and presents users with the best options, thereby improving the user experience. This system personalizes the purchasing experience by taking into account the user's emotional state, resulting in a highly satisfying shopping experience for consumers.

[0211] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0212] Step 1:

[0213] The user enters the product they wish to purchase using a mobile device. This input includes information such as the product name and category. The device receives the product information and simultaneously records the user's facial expressions and voice using its camera and microphone. The Emotion API is used to analyze and retrieve the user's emotional data from the recorded data.

[0214] Step 2:

[0215] The device transmits acquired product information, sentiment data, and location information to the server. During transmission, all information is packetized and delivered to the designated server address via the communication network. This process allows the server to gain a multifaceted understanding of the client's current situation and needs.

[0216] Step 3:

[0217] The server analyzes the received information and searches for locations that handle the relevant product by referring to the sales location database. Using generative artificial intelligence (generative AI), it generates product recommendations that take into account the user's emotional state. As a result, a list of recommended products is created.

[0218] Step 4:

[0219] Based on the generated recommended product list, the server checks the inventory of sales locations and lists them in order of priority. It executes a database query to retrieve inventory data for each sales location and selects the nearest location based on the user's location information.

[0220] Step 5:

[0221] The server replies to the terminal with the nearest sales location whose inventory has been checked, along with recommended products determined using AI generation. This reply is designed to provide the user with the best possible purchasing options. As a result, the user can decide whether to visit a store or place an online order based on the information displayed.

[0222] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0223] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0224] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0228] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0229] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0230] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0231] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0232] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0233] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0234] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0235] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0236] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0237] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0238] This invention is a system that enables users to efficiently search for specific products via communication between their mobile device and a server. First, the user uses their device to input information about the product they wish to purchase, and then the device acquires their current location information. The device then transmits this product information and location information to the server.

[0239] Based on the information received, the server consults a database to identify nearby stores that may carry the product. Furthermore, the server utilizes generated AI to check the inventory status of the identified stores. The AI ​​uses technology to access the stores' inventory management systems and retrieve the inventory status of the specified product.

[0240] The server then ranks the stores that have been determined to have the item in stock. The ranking takes into account several criteria, including the distance from the user's current location to the store, the store's opening status, and whether the product is immediately available. This ensures that information on the most accessible stores is provided to the user first.

[0241] This information is visually displayed on a map on the user's device, allowing them to check the nearest store with the item in stock. Based on this information, the user can either visit the store or arrange for delivery of the product through the app. For example, if a user is looking for a specific drink, the device will show the nearest store with the item in stock, allowing the user to efficiently choose to purchase the product based on that information.

[0242] This system aims to improve the consumer experience by reducing user effort, providing an environment where products can be found quickly, and enabling users to easily find what they're looking for.

[0243] The following describes the processing flow.

[0244] Step 1:

[0245] The user launches their mobile device, enters the information of the desired product into the app's search bar, and begins the search.

[0246] Step 2:

[0247] The device receives input from the user and obtains the current location information via GPS. The device then structures the obtained product information and location information and prepares to send it to the server.

[0248] Step 3:

[0249] The device transmits product information and location information to the server.

[0250] Step 4:

[0251] The server analyzes the received information and retrieves a list of stores that may carry the product from the database.

[0252] Step 5:

[0253] The server uses a generated AI model to query the inventory status of identified stores. The AI ​​model connects to each store and checks whether the specified product is in stock.

[0254] Step 6:

[0255] The generating AI model sends information about inventory status back to the server.

[0256] Step 7:

[0257] The server identifies stores with stock and ranks them based on factors such as distance from the user's current location, opening hours, and delivery and pickup options.

[0258] Step 8:

[0259] The server sends optimized store information to the terminal, which is then integrated with map data for a visual representation.

[0260] Step 9:

[0261] The terminal displays the received information to the user, showing the nearest store with stock on a map. The user then has the option to visit the store or order online.

[0262] Step 10:

[0263] Based on the information provided, users can either visit a retailer or proceed with the product delivery process via the app.

[0264] (Example 1)

[0265] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0266] Traditionally, a problem has been that users cannot quickly find specific items, leading to decreased purchasing efficiency. Furthermore, there was no easy way to obtain inventory information from nearby facilities and present users with the best purchasing options. Therefore, improving the consumer purchasing experience is a key challenge.

[0267] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0268] In this invention, the server includes means for acquiring facility information that handles goods, means for acquiring inventory information of facilities using a generating AI, means for presenting facilities in order of priority, and means for ranking facilities considering the user's geographical location. This makes it possible for users to efficiently find goods and visually understand the nearest facility with inventory.

[0269] A "user information terminal" refers to an electronic device used by users to input information, and includes smartphones and tablets.

[0270] "Item information" refers to information about the name and category of the product that the user wishes to purchase.

[0271] "Geographic location information" refers to latitude and longitude data indicating the current location of the user's information terminal.

[0272] A "server" refers to a central computer system that receives and processes information from user information terminals.

[0273] "Facility information" refers to information about stores and warehouses that may handle goods.

[0274] "Inventory information" refers to data that shows the inventory status of goods at a specific facility.

[0275] "Generative AI" refers to technology that uses artificial intelligence to generate new information and data.

[0276] "Presenting in order of priority" refers to displaying multiple options in a rearranged order based on their importance and convenience, according to specific criteria.

[0277] "Ranking" refers to assigning positions based on evaluation criteria.

[0278] To implement this invention, a system is constructed in which the user, terminal, and server work in cooperation. The user uses a user information terminal such as a smartphone or tablet to input information about the items they wish to purchase into a dedicated application. For example, if the user inputs "I want to buy 500ml of green tea" into the app, this information is acquired.

[0279] The device obtains the user's geographical location information using its built-in GPS function or location services. The user's device combines item information and geographical location information and transmits it to the server via the internet. HTTP or HTTPS protocols are commonly used for this communication.

[0280] The server analyzes the received information and extracts information about facilities that may handle the items from the database based on the item information. In this process, relational database management systems such as MySQL or PostgreSQL may be used as the database.

[0281] Next, the server uses the generative AI model to obtain the inventory information of each facility. The AI model utilizes pre-trained natural language processing technology. As an example of the prompt text, the text "Please tell me the inventory status of 500ml green tea in Store A" is used.

[0282] After obtaining the inventory information of the facilities, the server sorts the facilities in order of priority while considering the user's current location information, etc. With this ranking method, it can be presented to the user in order from the most convenient facility.

[0283] Finally, the server sends the ranking information to the terminal. The terminal visually displays the facility information by utilizing a map API, etc., and prompts the user to take specific purchase actions. Based on this information, the user can choose to visit the target facility or place an online order.

[0284] In this way, the user can efficiently find items and improve the experience as a consumer.

[0285] The flow of the specific process in Example 1 will be described using FIG. 11.

[0286] Step 1:

[0287] The user uses an information terminal such as a smartphone or tablet to input information about the item they wish to purchase. Specifically, a dedicated app is launched, and a specific prompt text such as "I want to buy 500ml green tea" is input in text form. This input information is sent to the terminal as data indicating the item name and type.

[0288] Step 2:

[0289] The terminal holds the item information input by the user and calls the internal location information service to obtain the geographical location information of the current location. It is output as data of latitude and longitude using a GPS sensor. As a result, the user's item information and geographical location information exist as input data in the terminal.

[0290] Step 3:

[0291] The terminal combines acquired item information and geographical location information and sends it to the server as a data structure such as JSON. The HTTP protocol is used for this transmission over the internet. The terminal's operation involves converting the input data into a format that the server can process and sending it as a request.

[0292] Step 4:

[0293] The server parses the JSON data received from the terminal, analyzes the item information, and extracts the corresponding facility information from the database. This process uses SQL queries to output a list of relevant facilities. The output data includes basic facility information such as the facility name and address.

[0294] Step 5:

[0295] The server uses a generative AI model to check the inventory information of each extracted facility. It generates specific questions as prompts, such as "Please tell me the inventory status of 500ml green tea at store A," and queries the inventory management systems of each facility. The AI ​​model analyzes this and outputs data indicating whether or not the item is in stock.

[0296] Step 6:

[0297] The server uses multiple facility information and inventory data to create a ranking that takes into account factors such as distance from the user's current location and opening status. It then executes a ranking algorithm to determine the priority of each facility. This results in the output of the optimal facility ranking to present to the user.

[0298] Step 7:

[0299] The server sends optimized facility ranking information to the terminal. The terminal analyzes the received information and visualizes it on a map using the Google Maps API, etc. By highlighting the most easily accessible facilities on the map, it becomes possible to take concrete actions that encourage purchasing behavior.

[0300] Step 8:

[0301] Users can view information displayed on a map and choose to visit the nearest facility with stock or place an order online directly through the application. This allows users to make efficient purchasing decisions.

[0302] (Application Example 1)

[0303] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0304] Users may have difficulty efficiently finding the products they want to buy in physical stores. In particular, they may not be able to quickly check whether nearby stores have the product in stock, leading to wasted travel time and effort. Even when they find the optimal store, they may face challenges such as difficulty figuring out the route to the store or reserving the product.

[0305] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0306] In this invention, the server includes means for acquiring desired product information, means for acquiring location information and transmitting it to an information processing device along with the product information, means for acquiring information about the facilities that handle the products, means for acquiring inventory information of the facilities using generation AI technology, means for presenting the nearest facility with stock to the user, and means for providing a route to the presented facility. This enables the user to quickly acquire information about the nearest store with stock and visit it via an efficient route.

[0307] An "information processing device" is a terminal device operated by a user, which is a device having functions of acquiring location information and product information and communicating with other devices.

[0308] "Generative AI technology" is a technology that uses artificial intelligence to analyze inventory information and store information and provide useful information to users.

[0309] "Location information" is data indicating the current geographical location of a user, which is information acquired through the user's terminal.

[0310] "Facility" refers to places such as physical stores and warehouses where goods are handled, and is the target for which its inventory information is provided to users.

[0311] "Inventory information" is information regarding the quantity currently held by a facility for a specific product and its immediate purchase availability.

[0312] "Route" is geographical guidance information for presenting the optimal means of movement to a facility selected by a user.

[0313] "Presentation" is an act of providing information that displays information on a user's terminal and serves as a guideline for the user to act based on it.

[0314] This invention is a system realized by transmitting product information and location information to a server via an information processing device so that a user can efficiently find a product. The information processing device is composed of a terminal such as a smartphone or a tablet, acquires location information by a GPS function, and enables input of product information desired by a user.

[0315] The server is constructed with a server-side application using Node.js, acquires information on neighboring facilities in cooperation with a Firebase database. The server further utilizes OpenAI GPT-3, which is generative AI technology, and provides optimal facility information including route information to a facility based on the acquired inventory information of the facility.

[0316] Users can view displayed facility information on a map via their device and receive route guidance to the nearest facility. They can also choose to purchase products online based on the facility information. This system provides an efficient shopping experience through real-time inventory checks.

[0317] For example, if a user is looking for cosmetics of a specific brand, they can enter "Brand X lotion" into the terminal, which will then display the nearest store with the product in stock. The user can then use this information to efficiently visit a store or place an online order.

[0318] An example of a prompt used in a generative AI model is: "Check the nearby stock availability of a specific product and recommend the best facility. Product: Brand X lotion, Location: (35.6895, 139.6917)."

[0319] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0320] Step 1:

[0321] The user enters product information for the product they wish to purchase on their device. The entered information, such as product name and category, is stored on the device. The device also uses its GPS function to obtain its current location. This location information, along with the product information, is then prepared for input to the server.

[0322] Step 2:

[0323] The device sends acquired product information and location data to the server. The server receives this information and uses it directly as a starting point for queries to the database. This information forms the basis for the data processed in the next step.

[0324] Step 3:

[0325] The server uses the received product information and the user's location to search the Firebase database. The database returns a list of facilities that may carry the relevant product. Through this process, the server obtains information about relevant facilities within a certain range of the user's current location.

[0326] Step 4:

[0327] The server utilizes OpenAI GPT-3, a generative AI technology, to check the inventory status of each facility based on the acquired facility information. Specifically, it queries the facility's inventory management system to obtain the availability of specified products. At this stage, the server aggregates the inventory information for each facility.

[0328] Step 5:

[0329] The server evaluates and ranks facilities based on aggregated inventory information, considering factors such as distance and the immediate availability of inventory. The highest priority facilities are those located close to the user's location and possessing the specified product in stock. Once the evaluation is complete, ranking information for each facility is generated.

[0330] Step 6:

[0331] The server sends facility information, along with map data, to the terminal. The terminal receives this information and displays it visually to the user. This allows the user to easily identify the nearest suitable facility and then use the map to begin directions to the store.

[0332] Step 7:

[0333] Based on the provided facility information, users can either visit a physical store or order products online via the application. Depending on the user's choice, additional options and services (such as product reservation) may also be offered.

[0334] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0335] This invention is a system that uses a user terminal and a server to acquire product information and combines this with an emotion engine that analyzes the user's emotions. First, the user uses a mobile terminal to input information about the product they wish to purchase. At this time, the terminal uses the device's camera and microphone to collect the user's facial expressions and voice, and acquire emotion data.

[0336] The device sends acquired product information, emotion information, and location information to the server. The server analyzes this information and consults a database to identify nearby stores that carry the product. The server uses a generative AI to check the inventory status of the identified stores and, at the same time, adjusts the recommendations for stores and products based on the emotion data acquired by the emotion engine, according to the user's current mood.

[0337] The emotion engine uses technology that identifies various emotional states by utilizing the user's voice and facial expression data. For example, if the user is detected as excited, the emotion engine can prioritize suggesting trending or new products to the user. The server also sorts and presents stores with confirmed inventory in an order that is optimal for the user's emotional state.

[0338] Users can check the nearest stores with stock on a map displayed on their device and choose to visit or order online. For example, if the system recognizes the user's mood when they are looking for a "specific drink," it can suggest other products that would go well with that drink.

[0339] This system aims to more accurately understand user needs, improve individual experiences, and provide a highly satisfying purchasing experience for consumers.

[0340] The following describes the processing flow.

[0341] Step 1:

[0342] The user activates their mobile device, opens the app, and enters information about the product they wish to purchase. The device simultaneously captures the user's facial expressions and voice data using its camera and microphone.

[0343] Step 2:

[0344] The device gathers product information, emotion data, and location information and prepares to send it to the server.

[0345] Step 3:

[0346] The device sends the above information to the server. The data is encrypted as needed before being sent.

[0347] Step 4:

[0348] The server analyzes the received information and retrieves information about nearby stores that may carry the product from the database.

[0349] Step 5:

[0350] The server uses generated AI to contact the listed stores and check the stock status of the specified product.

[0351] Step 6:

[0352] The server utilizes an emotion engine to analyze user emotional data. This allows it to adjust product and store recommendations to match the user's mood and emotions.

[0353] Step 7:

[0354] The server ranks stores with available stock and then sorts them in an order optimized for the user's emotional state. This ensures that the most relevant information is provided to the user first.

[0355] Step 8:

[0356] The server sends ranked store information back to the terminal and presents it to the user as a map or list.

[0357] Step 9:

[0358] Based on the information received by the device, the system displays the nearest stores with stock on a map and suggests options for visiting a store or ordering online.

[0359] Step 10:

[0360] Users select a store based on the information presented and either visit it in person or complete the purchase process through the app. Additional suggestions based on the user's emotions can also be useful here.

[0361] (Example 2)

[0362] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0363] Conventional sales information systems simply presented product and inventory information without considering the user's emotions. Therefore, it was difficult to maximize user purchasing intent and satisfaction. Furthermore, while inventory information could be checked, suggestions combining other products and optimal store selections were lacking. This invention aims to improve the user experience by providing more appropriate product and store suggestions based on the user's emotional state.

[0364] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0365] In this invention, the server includes means for acquiring the user's facial expressions and voice and generating emotion data, means for adjusting store and product suggestions based on the emotion data, and means for ranking sales locations based on inventory information and the user's emotion data. This makes it possible to optimize product suggestions and sales locations according to the user's emotions.

[0366] A "user terminal" is a computing device used by users to input product information and acquire emotional data.

[0367] "Product information" refers to data such as the name, category, and barcode of the product that the user wishes to purchase.

[0368] "Location data" refers to information that indicates the geographical location of the user's device.

[0369] "Emotional data" refers to information that indicates the emotional state of a user, analyzed from their facial expressions and voice.

[0370] A "server" is a central processing unit that receives and processes information sent from user terminals and provides optimal store and product recommendations.

[0371] A "place of sale" refers to a physical or online store that sells the product.

[0372] "Generative AI" is an artificial intelligence technology that operates on a server and supports the acquisition of inventory information and the adjustment of suggestions.

[0373] "Inventory information" refers to data that shows the availability of a product at a specific sales location.

[0374] "Adjusting suggestions" means optimizing the selection of products and stores suggested based on user sentiment data.

[0375] "Ranking" means evaluating and assigning a ranking to sales locations based on specific criteria.

[0376] This invention is a system consisting of a user terminal and a server that combines the acquisition of product information with the analysis of the user's emotions to provide appropriate product recommendations. The user inputs information about the products they wish to purchase using their mobile device. During this process, the terminal utilizes input devices such as a camera and microphone to collect the user's facial expressions and voice, generating emotion data. This makes it possible to analyze the user's emotional state in real time.

[0377] Product information, emotion information, and location information acquired by the device are transmitted to a server via the internet. The server processes this information and, by referring to its own database, identifies nearby sales locations that carry the product. This process utilizes generative AI models to obtain real-time inventory information for each sales location. The server also adjusts and optimizes store and product suggestions based on the user's emotion data obtained by the emotion engine. This enables more personalized suggestions that match the user's current emotional state.

[0378] For example, when a user is searching for a "new smartphone," if the emotion engine recognizes that the user is excited, the system can focus on suggesting the latest models and highly-rated products, and can also introduce related accessories.

[0379] Examples of prompts for the generative AI model include: "When a user is searching for new products, suggest appropriate product combinations, taking into account their current emotional state," and "Develop a strategy to encourage purchases of specific desired products by making suggestions based on the user's emotions."

[0380] By using this system, users will be able to obtain product information that more accurately matches their needs, aiming to provide a more fulfilling shopping experience.

[0381] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0382] Step 1:

[0383] The user enters information about the product they wish to purchase using a mobile device. Specifically, the user launches an application on their device and enters the product name and category in text format, or scans the product barcode with the camera. The input data (product information) obtained includes the product name and barcode. This data is temporarily stored on the device.

[0384] Step 2:

[0385] The device uses its camera and microphone to collect the user's facial expressions and voice, generating emotion data in real time. Emotion analysis software analyzes the user's facial muscle movements and voice tone to determine their emotional state (e.g., joy, excitement, relaxation). This process yields the output as emotion data.

[0386] Step 3:

[0387] The device transmits acquired product information, emotion data, and location data to a server. Using a communication module within the device, this data is encrypted and transmitted to the server via the internet. The server receives this data as input.

[0388] Step 4:

[0389] The server, based on the received product information, consults a database to identify nearby retail locations that carry the product. Specifically, it uses a database search algorithm to extract store information that matches the entered product information. As output of this process, a list of identified retail locations is generated.

[0390] Step 5:

[0391] The server uses a generated AI model to retrieve inventory information for identified sales locations. The AI ​​model queries the database to check the real-time inventory status of each sales location. This step yields inventory information for each sales location as output.

[0392] Step 6:

[0393] The server adjusts its recommendations to suggest the most suitable stores and products to the user based on emotional data. It utilizes an emotional data analysis engine to prepare suggestions tailored to the user's current emotional state. This adjustment results in personalized recommendations for each individual user.

[0394] Step 7:

[0395] The server sends information to the user's terminal, including the nearest sales location with the item in stock, as the final recommendation. Here, the optimized recommendation data is encrypted again and sent back to the terminal. The user's terminal receives this information and displays it on the screen.

[0396] (Application Example 2)

[0397] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0398] In today's commercial environment, consumers demand quick and accurate information and suggestions when making purchases, but systems capable of addressing individual, emotion-based needs are limited. Current systems fail to adequately provide optimal product recommendations tailored to consumers' emotional states, nor do they adequately suggest nearby retail locations based on those emotional factors. Therefore, improving the personalized purchasing experience for each individual consumer is a key challenge.

[0399] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0400] In this invention, the server includes means for suggesting products or sales locations based on user sentiment data, means for ranking sales locations based on inventory information, and means for displaying the nearest location with available stock. This enables optimal purchase suggestions tailored to the user's emotional state and provides a customized purchasing experience that meets individual needs.

[0401] A "user terminal" is a computing device that has the function of acquiring product information and sentiment data and sending it to a server.

[0402] "Emotional data" refers to information that represents a user's emotional state, and is digital data obtained through the analysis of voice and facial expressions.

[0403] "Location information" refers to information indicating the geographical location of a user's device, and is data obtained using GPS or similar methods.

[0404] A "server" is a central computing system that analyzes data received from user terminals and provides information on sales locations and product suggestions.

[0405] A "sales outlet" is a physical or online facility that handles products.

[0406] "Generative artificial intelligence" is a computational technology that can make human-like decisions based on large amounts of data.

[0407] "Inventory information" refers to data that shows the inventory status of products at sales locations.

[0408] A "suggestion" is information that presents the most suitable products and sales locations based on the user's emotional state and desired purchases.

[0409] The system for implementing this invention consists of a user terminal, a server, and a communication network. The user first uses a mobile terminal to input the products they wish to purchase. The terminal is equipped with a camera and a microphone, and acquires emotional data by analyzing the user's facial expressions and voice. This allows the terminal to identify the user's emotional state.

[0410] Emotional data, product information, and location information are transmitted from the terminal to the server. The server analyzes this data and uses a database of sales locations to check inventory at each location that handles the product. Generative artificial intelligence technology is used to suggest the most suitable products and recommend sales locations based on the user's emotional state.

[0411] As a concrete example, consider a case where a user is looking for a specific drink. If the server recognizes that the user is in a cheerful mood, it can suggest snacks or other products that would pair well with that drink. For example, a prompt such as "Tell me some desserts I can enjoy today" might be generated. Based on this prompt, the server provides suggestions that are appropriate for the user.

[0412] The server provides users with the optimal ordering method: direct purchase at a designated sales location or online ordering. It also prioritizes locations with confirmed stock and presents users with the best options, thereby improving the user experience. This system personalizes the purchasing experience by taking into account the user's emotional state, resulting in a highly satisfying shopping experience for consumers.

[0413] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0414] Step 1:

[0415] The user enters the product they wish to purchase using a mobile device. This input includes information such as the product name and category. The device receives the product information and simultaneously records the user's facial expressions and voice using its camera and microphone. The Emotion API is used to analyze and retrieve the user's emotional data from the recorded data.

[0416] Step 2:

[0417] The device transmits acquired product information, sentiment data, and location information to the server. During transmission, all information is packetized and delivered to the designated server address via the communication network. This process allows the server to gain a multifaceted understanding of the client's current situation and needs.

[0418] Step 3:

[0419] The server analyzes the received information and searches for locations that handle the relevant product by referring to the sales location database. Using generative artificial intelligence (generative AI), it generates product recommendations that take into account the user's emotional state. As a result, a list of recommended products is created.

[0420] Step 4:

[0421] Based on the generated recommended product list, the server checks the inventory of sales locations and lists them in order of priority. It executes a database query to retrieve inventory data for each sales location and selects the nearest location based on the user's location information.

[0422] Step 5:

[0423] The server replies to the terminal with the nearest sales location whose inventory has been checked, along with recommended products determined using AI generation. This reply is designed to provide the user with the best possible purchasing options. As a result, the user can decide whether to visit a store or place an online order based on the information displayed.

[0424] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0425] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0426] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0427] [Third Embodiment]

[0428] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0429] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0430] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0431] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0432] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0433] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0434] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0435] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0436] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0437] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0438] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0439] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0440] This invention is a system that enables users to efficiently search for specific products via communication between their mobile device and a server. First, the user uses their device to input information about the product they wish to purchase, and then the device acquires their current location information. The device then transmits this product information and location information to the server.

[0441] Based on the information received, the server consults a database to identify nearby stores that may carry the product. Furthermore, the server utilizes generated AI to check the inventory status of the identified stores. The AI ​​uses technology to access the stores' inventory management systems and retrieve the inventory status of the specified product.

[0442] The server then ranks the stores that have been determined to have the item in stock. The ranking takes into account several criteria, including the distance from the user's current location to the store, the store's opening status, and whether the product is immediately available. This ensures that information on the most accessible stores is provided to the user first.

[0443] This information is visually displayed on a map on the user's device, allowing them to check the nearest store with the item in stock. Based on this information, the user can either visit the store or arrange for delivery of the product through the app. For example, if a user is looking for a specific drink, the device will show the nearest store with the item in stock, allowing the user to efficiently choose to purchase the product based on that information.

[0444] This system aims to improve the consumer experience by reducing user effort, providing an environment where products can be found quickly, and enabling users to easily find what they're looking for.

[0445] The following describes the processing flow.

[0446] Step 1:

[0447] The user launches their mobile device, enters the information of the desired product into the app's search bar, and begins the search.

[0448] Step 2:

[0449] The device receives input from the user and obtains the current location information via GPS. The device then structures the obtained product information and location information and prepares to send it to the server.

[0450] Step 3:

[0451] The device transmits product information and location information to the server.

[0452] Step 4:

[0453] The server analyzes the received information and retrieves a list of stores that may carry the product from the database.

[0454] Step 5:

[0455] The server uses a generated AI model to query the inventory status of identified stores. The AI ​​model connects to each store and checks whether the specified product is in stock.

[0456] Step 6:

[0457] The generating AI model sends information about inventory status back to the server.

[0458] Step 7:

[0459] The server identifies stores with stock and ranks them based on factors such as distance from the user's current location, opening hours, and delivery and pickup options.

[0460] Step 8:

[0461] The server sends optimized store information to the terminal, which is then integrated with map data for a visual representation.

[0462] Step 9:

[0463] The terminal displays the received information to the user, showing the nearest store with stock on a map. The user then has the option to visit the store or order online.

[0464] Step 10:

[0465] Based on the information provided, users can either visit a retailer or proceed with the product delivery process via the app.

[0466] (Example 1)

[0467] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0468] Traditionally, a problem has been that users cannot quickly find specific items, leading to decreased purchasing efficiency. Furthermore, there was no easy way to obtain inventory information from nearby facilities and present users with the best purchasing options. Therefore, improving the consumer purchasing experience is a key challenge.

[0469] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0470] In this invention, the server includes means for acquiring facility information that handles goods, means for acquiring inventory information of facilities using a generating AI, means for presenting facilities in order of priority, and means for ranking facilities considering the user's geographical location. This makes it possible for users to efficiently find goods and visually understand the nearest facility with inventory.

[0471] A "user information terminal" refers to an electronic device used by users to input information, and includes smartphones and tablets.

[0472] "Item information" refers to information about the name and category of the product that the user wishes to purchase.

[0473] "Geographic location information" refers to latitude and longitude data indicating the current location of the user's information terminal.

[0474] A "server" refers to a central computer system that receives and processes information from user information terminals.

[0475] "Facility information" refers to information about stores and warehouses that may handle goods.

[0476] "Inventory information" refers to data that shows the inventory status of goods at a specific facility.

[0477] "Generative AI" refers to technology that uses artificial intelligence to generate new information and data.

[0478] "Presenting in order of priority" refers to displaying multiple options in a rearranged order based on their importance and convenience, according to specific criteria.

[0479] "Ranking" refers to assigning positions based on evaluation criteria.

[0480] To implement this invention, a system is constructed in which the user, terminal, and server work in cooperation. The user uses a user information terminal such as a smartphone or tablet to input information about the items they wish to purchase into a dedicated application. For example, if the user inputs "I want to buy 500ml of green tea" into the app, this information is acquired.

[0481] The device obtains the user's geographical location information using its built-in GPS function or location services. The user's device combines item information and geographical location information and transmits it to the server via the internet. HTTP or HTTPS protocols are commonly used for this communication.

[0482] The server analyzes the received information and extracts information about facilities that may handle the items from the database based on the item information. In this process, relational database management systems such as MySQL or PostgreSQL may be used as the database.

[0483] Next, the server uses a generative AI model to retrieve inventory information for each facility. The AI ​​model utilizes pre-trained natural language processing techniques. As an example of a prompt, the text used is, "Please tell me the inventory status of 500ml green tea at store A."

[0484] After retrieving facility inventory information, the server sorts the facilities in order of priority, taking into account the user's current location and other factors. This ranking method allows the facility to be presented to the user in order of its convenience.

[0485] Ultimately, the server sends ranking information to the terminal. The terminal visually displays facility information using map APIs and other tools, prompting the user to take concrete purchasing action. Based on this information, the user can choose to visit the desired facility or place an order online.

[0486] In this way, users can efficiently find items and improve their consumer experience.

[0487] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0488] Step 1:

[0489] Users use information terminals such as smartphones and tablets to input information about the items they wish to purchase. Specifically, they launch a dedicated app and enter a specific prompt in text format, such as "I want to buy 500ml of green tea." This input information is sent to the terminal as data indicating the name and type of item.

[0490] Step 2:

[0491] The device stores the item information entered by the user and retrieves the current geographical location information by calling its internal location information service. Using the GPS sensor, it outputs data as latitude and longitude. As a result, the device contains both the user's item information and geographical location information as input data.

[0492] Step 3:

[0493] The terminal combines acquired item information and geographical location information and sends it to the server as a data structure such as JSON. The HTTP protocol is used for this transmission over the internet. The terminal's operation involves converting the input data into a format that the server can process and sending it as a request.

[0494] Step 4:

[0495] The server parses the JSON data received from the terminal, analyzes the item information, and extracts the corresponding facility information from the database. This process uses SQL queries to output a list of relevant facilities. The output data includes basic facility information such as the facility name and address.

[0496] Step 5:

[0497] The server uses a generative AI model to check the inventory information of each extracted facility. It generates specific questions as prompts, such as "Please tell me the inventory status of 500ml green tea at store A," and queries the inventory management systems of each facility. The AI ​​model analyzes this and outputs data indicating whether or not the item is in stock.

[0498] Step 6:

[0499] The server uses multiple facility information and inventory data to create a ranking that takes into account factors such as distance from the user's current location and opening status. It then executes a ranking algorithm to determine the priority of each facility. This results in the output of the optimal facility ranking to present to the user.

[0500] Step 7:

[0501] The server sends optimized facility ranking information to the terminal. The terminal analyzes the received information and visualizes it on a map using the Google Maps API, etc. By highlighting the most easily accessible facilities on the map, it becomes possible to take concrete actions that encourage purchasing behavior.

[0502] Step 8:

[0503] Users can view information displayed on a map and choose to visit the nearest facility with stock or place an order online directly through the application. This allows users to make efficient purchasing decisions.

[0504] (Application Example 1)

[0505] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0506] Users may have difficulty efficiently finding the products they want to buy in physical stores. In particular, they may not be able to quickly check whether nearby stores have the product in stock, leading to wasted travel time and effort. Even when they find the optimal store, they may face challenges such as difficulty figuring out the route to the store or reserving the product.

[0507] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0508] In this invention, the server includes means for acquiring desired product information, means for acquiring location information and transmitting it to an information processing device along with the product information, means for acquiring information about the facilities that handle the products, means for acquiring inventory information of the facilities using generation AI technology, means for presenting the nearest facility with stock to the user, and means for providing a route to the presented facility. This enables the user to quickly acquire information about the nearest store with stock and visit it via an efficient route.

[0509] An "information processing device" is a terminal device operated by a user that has the function of acquiring location information and product information, and communicating with other devices.

[0510] "Generative AI technology" is a technology that uses artificial intelligence to analyze inventory and store information and provide users with useful information.

[0511] "Location information" refers to data that indicates the user's current geographical location, and is information obtained through the user's device.

[0512] A "facility" refers to a physical store or warehouse where products are handled, and the inventory information for that facility is provided to the user.

[0513] "Inventory information" refers to information about the quantity of a particular product currently held at a facility and its immediate availability for purchase.

[0514] A "route" is geographical guidance information that suggests the optimal mode of transportation to the facility selected by the user.

[0515] "Presentation" refers to the act of providing information that is displayed on a user's device, serving as a guide for the user to take action based on that information.

[0516] This invention is a system that enables users to efficiently find products by transmitting product information and location information to a server via an information processing device. The information processing device consists of a terminal such as a smartphone or tablet, which acquires location information using GPS functionality and allows users to input desired product information.

[0517] The server is built as a server-side application using Node.js and interacts with the Firebase database to retrieve information about nearby facilities. The server also utilizes OpenAI GPT-3, a generative AI technology, to provide optimal facility information, including route information to the facility, based on the acquired facility inventory information.

[0518] Users can view displayed facility information on a map via their device and receive route guidance to the nearest facility. They can also choose to purchase products online based on the facility information. This system provides an efficient shopping experience through real-time inventory checks.

[0519] For example, if a user is looking for cosmetics of a specific brand, they can enter "Brand X lotion" into the terminal, which will then display the nearest store with the product in stock. The user can then use this information to efficiently visit a store or place an online order.

[0520] An example of a prompt used in a generative AI model is: "Check the nearby stock availability of a specific product and recommend the best facility. Product: Brand X lotion, Location: (35.6895, 139.6917)."

[0521] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0522] Step 1:

[0523] The user enters product information for the product they wish to purchase on their device. The entered information, such as product name and category, is stored on the device. The device also uses its GPS function to obtain its current location. This location information, along with the product information, is then prepared for input to the server.

[0524] Step 2:

[0525] The device sends acquired product information and location data to the server. The server receives this information and uses it directly as a starting point for queries to the database. This information forms the basis for the data processed in the next step.

[0526] Step 3:

[0527] The server uses the received product information and the user's location to search the Firebase database. The database returns a list of facilities that may carry the relevant product. Through this process, the server obtains information about relevant facilities within a certain range of the user's current location.

[0528] Step 4:

[0529] The server utilizes OpenAI GPT-3, a generative AI technology, to check the inventory status of each facility based on the acquired facility information. Specifically, it queries the facility's inventory management system to obtain the availability of specified products. At this stage, the server aggregates the inventory information for each facility.

[0530] Step 5:

[0531] The server evaluates and ranks facilities based on aggregated inventory information, considering factors such as distance and the immediate availability of inventory. The highest priority facilities are those located close to the user's location and possessing the specified product in stock. Once the evaluation is complete, ranking information for each facility is generated.

[0532] Step 6:

[0533] The server sends facility information, along with map data, to the terminal. The terminal receives this information and displays it visually to the user. This allows the user to easily identify the nearest suitable facility and then use the map to begin directions to the store.

[0534] Step 7:

[0535] Based on the provided facility information, users can either visit a physical store or order products online via the application. Depending on the user's choice, additional options and services (such as product reservation) may also be offered.

[0536] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0537] This invention is a system that uses a user terminal and a server to acquire product information and combines this with an emotion engine that analyzes the user's emotions. First, the user uses a mobile terminal to input information about the product they wish to purchase. At this time, the terminal uses the device's camera and microphone to collect the user's facial expressions and voice, and acquire emotion data.

[0538] The device sends acquired product information, emotion information, and location information to the server. The server analyzes this information and consults a database to identify nearby stores that carry the product. The server uses a generative AI to check the inventory status of the identified stores and, at the same time, adjusts the recommendations for stores and products based on the emotion data acquired by the emotion engine, according to the user's current mood.

[0539] The emotion engine uses technology that identifies various emotional states by utilizing the user's voice and facial expression data. For example, if the user is detected as excited, the emotion engine can prioritize suggesting trending or new products to the user. The server also sorts and presents stores with confirmed inventory in an order that is optimal for the user's emotional state.

[0540] Users can check the nearest stores with stock on a map displayed on their device and choose to visit or order online. For example, if the system recognizes the user's mood when they are looking for a "specific drink," it can suggest other products that would go well with that drink.

[0541] This system aims to more accurately understand user needs, improve individual experiences, and provide a highly satisfying purchasing experience for consumers.

[0542] The following describes the processing flow.

[0543] Step 1:

[0544] The user activates their mobile device, opens the app, and enters information about the product they wish to purchase. The device simultaneously captures the user's facial expressions and voice data using its camera and microphone.

[0545] Step 2:

[0546] The device gathers product information, emotion data, and location information and prepares to send it to the server.

[0547] Step 3:

[0548] The device sends the above information to the server. The data is encrypted as needed before being sent.

[0549] Step 4:

[0550] The server analyzes the received information and retrieves information about nearby stores that may carry the product from the database.

[0551] Step 5:

[0552] The server uses generated AI to contact the listed stores and check the stock status of the specified product.

[0553] Step 6:

[0554] The server utilizes an emotion engine to analyze user emotional data. This allows it to adjust product and store recommendations to match the user's mood and emotions.

[0555] Step 7:

[0556] The server ranks stores with available stock and then sorts them in an order optimized for the user's emotional state. This ensures that the most relevant information is provided to the user first.

[0557] Step 8:

[0558] The server sends ranked store information back to the terminal and presents it to the user as a map or list.

[0559] Step 9:

[0560] Based on the information received by the device, the system displays the nearest stores with stock on a map and suggests options for visiting a store or ordering online.

[0561] Step 10:

[0562] Users select a store based on the information presented and either visit it in person or complete the purchase process through the app. Additional suggestions based on the user's emotions can also be useful here.

[0563] (Example 2)

[0564] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0565] Conventional sales information systems simply presented product and inventory information without considering the user's emotions. Therefore, it was difficult to maximize user purchasing intent and satisfaction. Furthermore, while inventory information could be checked, suggestions combining other products and optimal store selections were lacking. This invention aims to improve the user experience by providing more appropriate product and store suggestions based on the user's emotional state.

[0566] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0567] In this invention, the server includes means for acquiring the user's facial expressions and voice and generating emotion data, means for adjusting store and product suggestions based on the emotion data, and means for ranking sales locations based on inventory information and the user's emotion data. This makes it possible to optimize product suggestions and sales locations according to the user's emotions.

[0568] A "user terminal" is a computing device used by users to input product information and acquire emotional data.

[0569] "Product information" refers to data such as the name, category, and barcode of the product that the user wishes to purchase.

[0570] "Location data" refers to information that indicates the geographical location of the user's device.

[0571] "Emotional data" refers to information that indicates the emotional state of a user, analyzed from their facial expressions and voice.

[0572] A "server" is a central processing unit that receives and processes information sent from user terminals and provides optimal store and product recommendations.

[0573] A "place of sale" refers to a physical or online store that sells the product.

[0574] "Generative AI" is an artificial intelligence technology that operates on a server and supports the acquisition of inventory information and the adjustment of suggestions.

[0575] "Inventory information" refers to data that shows the availability of a product at a specific sales location.

[0576] "Adjusting suggestions" means optimizing the selection of products and stores suggested based on user sentiment data.

[0577] "Ranking" means evaluating and assigning a ranking to sales locations based on specific criteria.

[0578] This invention is a system consisting of a user terminal and a server that combines the acquisition of product information with the analysis of the user's emotions to provide appropriate product recommendations. The user inputs information about the products they wish to purchase using their mobile device. During this process, the terminal utilizes input devices such as a camera and microphone to collect the user's facial expressions and voice, generating emotion data. This makes it possible to analyze the user's emotional state in real time.

[0579] Product information, emotion information, and location information acquired by the device are transmitted to a server via the internet. The server processes this information and, by referring to its own database, identifies nearby sales locations that carry the product. This process utilizes generative AI models to obtain real-time inventory information for each sales location. The server also adjusts and optimizes store and product suggestions based on the user's emotion data obtained by the emotion engine. This enables more personalized suggestions that match the user's current emotional state.

[0580] For example, when a user is searching for a "new smartphone," if the emotion engine recognizes that the user is excited, the system can focus on suggesting the latest models and highly-rated products, and can also introduce related accessories.

[0581] Examples of prompts for the generative AI model include: "When a user is searching for new products, suggest appropriate product combinations, taking into account their current emotional state," and "Develop a strategy to encourage purchases of specific desired products by making suggestions based on the user's emotions."

[0582] By using this system, users will be able to obtain product information that more accurately matches their needs, aiming to provide a more fulfilling shopping experience.

[0583] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0584] Step 1:

[0585] The user enters information about the product they wish to purchase using a mobile device. Specifically, the user launches an application on their device and enters the product name and category in text format, or scans the product barcode with the camera. The input data (product information) obtained includes the product name and barcode. This data is temporarily stored on the device.

[0586] Step 2:

[0587] The device uses its camera and microphone to collect the user's facial expressions and voice, generating emotion data in real time. Emotion analysis software analyzes the user's facial muscle movements and voice tone to determine their emotional state (e.g., joy, excitement, relaxation). This process yields the output as emotion data.

[0588] Step 3:

[0589] The device transmits acquired product information, emotion data, and location data to a server. Using a communication module within the device, this data is encrypted and transmitted to the server via the internet. The server receives this data as input.

[0590] Step 4:

[0591] The server, based on the received product information, consults a database to identify nearby retail locations that carry the product. Specifically, it uses a database search algorithm to extract store information that matches the entered product information. As output of this process, a list of identified retail locations is generated.

[0592] Step 5:

[0593] The server uses a generated AI model to retrieve inventory information for identified sales locations. The AI ​​model queries the database to check the real-time inventory status of each sales location. This step yields inventory information for each sales location as output.

[0594] Step 6:

[0595] The server adjusts its recommendations to suggest the most suitable stores and products to the user based on emotional data. It utilizes an emotional data analysis engine to prepare suggestions tailored to the user's current emotional state. This adjustment results in personalized recommendations for each individual user.

[0596] Step 7:

[0597] The server sends information to the user's terminal, including the nearest sales location with the item in stock, as the final recommendation. Here, the optimized recommendation data is encrypted again and sent back to the terminal. The user's terminal receives this information and displays it on the screen.

[0598] (Application Example 2)

[0599] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0600] In today's commercial environment, consumers demand quick and accurate information and suggestions when making purchases, but systems capable of addressing individual, emotion-based needs are limited. Current systems fail to adequately provide optimal product recommendations tailored to consumers' emotional states, nor do they adequately suggest nearby retail locations based on those emotional factors. Therefore, improving the personalized purchasing experience for each individual consumer is a key challenge.

[0601] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0602] In this invention, the server includes means for suggesting products or sales locations based on user sentiment data, means for ranking sales locations based on inventory information, and means for displaying the nearest location with available stock. This enables optimal purchase suggestions tailored to the user's emotional state and provides a customized purchasing experience that meets individual needs.

[0603] A "user terminal" is a computing device that has the function of acquiring product information and sentiment data and sending it to a server.

[0604] "Emotional data" refers to information that represents a user's emotional state, and is digital data obtained through the analysis of voice and facial expressions.

[0605] "Location information" refers to information indicating the geographical location of a user's device, and is data obtained using GPS or similar methods.

[0606] A "server" is a central computing system that analyzes data received from user terminals and provides information on sales locations and product suggestions.

[0607] A "sales outlet" is a physical or online facility that handles products.

[0608] "Generative artificial intelligence" is a computational technology that can make human-like decisions based on large amounts of data.

[0609] "Inventory information" refers to data that shows the inventory status of products at sales locations.

[0610] A "suggestion" is information that presents the most suitable products and sales locations based on the user's emotional state and desired purchases.

[0611] The system for implementing this invention consists of a user terminal, a server, and a communication network. The user first uses a mobile terminal to input the products they wish to purchase. The terminal is equipped with a camera and a microphone, and acquires emotional data by analyzing the user's facial expressions and voice. This allows the terminal to identify the user's emotional state.

[0612] Emotional data, product information, and location information are transmitted from the terminal to the server. The server analyzes this data and uses a database of sales locations to check inventory at each location that handles the product. Generative artificial intelligence technology is used to suggest the most suitable products and recommend sales locations based on the user's emotional state.

[0613] As a concrete example, consider a case where a user is looking for a specific drink. If the server recognizes that the user is in a cheerful mood, it can suggest snacks or other products that would pair well with that drink. For example, a prompt such as "Tell me some desserts I can enjoy today" might be generated. Based on this prompt, the server provides suggestions that are appropriate for the user.

[0614] The server provides users with the optimal ordering method: direct purchase at a designated sales location or online ordering. It also prioritizes locations with confirmed stock and presents users with the best options, thereby improving the user experience. This system personalizes the purchasing experience by taking into account the user's emotional state, resulting in a highly satisfying shopping experience for consumers.

[0615] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0616] Step 1:

[0617] The user enters the product they wish to purchase using a mobile device. This input includes information such as the product name and category. The device receives the product information and simultaneously records the user's facial expressions and voice using its camera and microphone. The Emotion API is used to analyze and retrieve the user's emotional data from the recorded data.

[0618] Step 2:

[0619] The device transmits acquired product information, sentiment data, and location information to the server. During transmission, all information is packetized and delivered to the designated server address via the communication network. This process allows the server to gain a multifaceted understanding of the client's current situation and needs.

[0620] Step 3:

[0621] The server analyzes the received information and searches for locations that handle the relevant product by referring to the sales location database. Using generative artificial intelligence (generative AI), it generates product recommendations that take into account the user's emotional state. As a result, a list of recommended products is created.

[0622] Step 4:

[0623] Based on the generated recommended product list, the server checks the inventory of sales locations and lists them in order of priority. It executes a database query to retrieve inventory data for each sales location and selects the nearest location based on the user's location information.

[0624] Step 5:

[0625] The server replies to the terminal with the nearest sales location whose inventory has been checked, along with recommended products determined using AI generation. This reply is designed to provide the user with the best possible purchasing options. As a result, the user can decide whether to visit a store or place an online order based on the information displayed.

[0626] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0627] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0628] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0629] [Fourth Embodiment]

[0630] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0631] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0632] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0633] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0634] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0635] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0636] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0637] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0638] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0639] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0640] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0641] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0642] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0643] This invention is a system that enables users to efficiently search for specific products via communication between their mobile device and a server. First, the user uses their device to input information about the product they wish to purchase, and then the device acquires their current location information. The device then transmits this product information and location information to the server.

[0644] Based on the information received, the server consults a database to identify nearby stores that may carry the product. Furthermore, the server utilizes generated AI to check the inventory status of the identified stores. The AI ​​uses technology to access the stores' inventory management systems and retrieve the inventory status of the specified product.

[0645] The server then ranks the stores that have been determined to have the item in stock. The ranking takes into account several criteria, including the distance from the user's current location to the store, the store's opening status, and whether the product is immediately available. This ensures that information on the most accessible stores is provided to the user first.

[0646] This information is visually displayed on a map on the user's device, allowing them to check the nearest store with the item in stock. Based on this information, the user can either visit the store or arrange for delivery of the product through the app. For example, if a user is looking for a specific drink, the device will show the nearest store with the item in stock, allowing the user to efficiently choose to purchase the product based on that information.

[0647] This system aims to improve the consumer experience by reducing user effort, providing an environment where products can be found quickly, and enabling users to easily find what they're looking for.

[0648] The following describes the processing flow.

[0649] Step 1:

[0650] The user launches their mobile device, enters the information of the desired product into the app's search bar, and begins the search.

[0651] Step 2:

[0652] The device receives input from the user and obtains the current location information via GPS. The device then structures the obtained product information and location information and prepares to send it to the server.

[0653] Step 3:

[0654] The device transmits product information and location information to the server.

[0655] Step 4:

[0656] The server analyzes the received information and retrieves a list of stores that may carry the product from the database.

[0657] Step 5:

[0658] The server uses a generated AI model to query the inventory status of identified stores. The AI ​​model connects to each store and checks whether the specified product is in stock.

[0659] Step 6:

[0660] The generating AI model sends information about inventory status back to the server.

[0661] Step 7:

[0662] The server identifies stores with stock and ranks them based on factors such as distance from the user's current location, opening hours, and delivery and pickup options.

[0663] Step 8:

[0664] The server sends optimized store information to the terminal, which is then integrated with map data for a visual representation.

[0665] Step 9:

[0666] The terminal displays the received information to the user, showing the nearest store with stock on a map. The user then has the option to visit the store or order online.

[0667] Step 10:

[0668] Based on the information provided, users can either visit a retailer or proceed with the product delivery process via the app.

[0669] (Example 1)

[0670] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0671] Traditionally, a problem has been that users cannot quickly find specific items, leading to decreased purchasing efficiency. Furthermore, there was no easy way to obtain inventory information from nearby facilities and present users with the best purchasing options. Therefore, improving the consumer purchasing experience is a key challenge.

[0672] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0673] In this invention, the server includes means for acquiring facility information that handles goods, means for acquiring inventory information of facilities using a generating AI, means for presenting facilities in order of priority, and means for ranking facilities considering the user's geographical location. This makes it possible for users to efficiently find goods and visually understand the nearest facility with inventory.

[0674] A "user information terminal" refers to an electronic device used by users to input information, and includes smartphones and tablets.

[0675] "Item information" refers to information about the name and category of the product that the user wishes to purchase.

[0676] "Geographic location information" refers to latitude and longitude data indicating the current location of the user's information terminal.

[0677] A "server" refers to a central computer system that receives and processes information from user information terminals.

[0678] "Facility information" refers to information about stores and warehouses that may handle goods.

[0679] "Inventory information" refers to data that shows the inventory status of goods at a specific facility.

[0680] "Generative AI" refers to technology that uses artificial intelligence to generate new information and data.

[0681] "Presenting in order of priority" refers to displaying multiple options in a rearranged order based on their importance and convenience, according to specific criteria.

[0682] "Ranking" refers to assigning positions based on evaluation criteria.

[0683] To implement this invention, a system is constructed in which the user, terminal, and server work in cooperation. The user uses a user information terminal such as a smartphone or tablet to input information about the items they wish to purchase into a dedicated application. For example, if the user inputs "I want to buy 500ml of green tea" into the app, this information is acquired.

[0684] The device obtains the user's geographical location information using its built-in GPS function or location services. The user's device combines item information and geographical location information and transmits it to the server via the internet. HTTP or HTTPS protocols are commonly used for this communication.

[0685] The server analyzes the received information and extracts information about facilities that may handle the items from the database based on the item information. In this process, relational database management systems such as MySQL or PostgreSQL may be used as the database.

[0686] Next, the server uses a generative AI model to retrieve inventory information for each facility. The AI ​​model utilizes pre-trained natural language processing techniques. As an example of a prompt, the text used is, "Please tell me the inventory status of 500ml green tea at store A."

[0687] After retrieving facility inventory information, the server sorts the facilities in order of priority, taking into account the user's current location and other factors. This ranking method allows the facility to be presented to the user in order of its convenience.

[0688] Ultimately, the server sends ranking information to the terminal. The terminal visually displays facility information using map APIs and other tools, prompting the user to take concrete purchasing action. Based on this information, the user can choose to visit the desired facility or place an order online.

[0689] In this way, users can efficiently find items and improve their consumer experience.

[0690] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0691] Step 1:

[0692] Users use information terminals such as smartphones and tablets to input information about the items they wish to purchase. Specifically, they launch a dedicated app and enter a specific prompt in text format, such as "I want to buy 500ml of green tea." This input information is sent to the terminal as data indicating the name and type of item.

[0693] Step 2:

[0694] The device stores the item information entered by the user and retrieves the current geographical location information by calling its internal location information service. Using the GPS sensor, it outputs data as latitude and longitude. As a result, the device contains both the user's item information and geographical location information as input data.

[0695] Step 3:

[0696] The terminal combines acquired item information and geographical location information and sends it to the server as a data structure such as JSON. The HTTP protocol is used for this transmission over the internet. The terminal's operation involves converting the input data into a format that the server can process and sending it as a request.

[0697] Step 4:

[0698] The server parses the JSON data received from the terminal, analyzes the item information, and extracts the corresponding facility information from the database. This process uses SQL queries to output a list of relevant facilities. The output data includes basic facility information such as the facility name and address.

[0699] Step 5:

[0700] The server uses a generative AI model to check the inventory information of each extracted facility. It generates specific questions as prompts, such as "Please tell me the inventory status of 500ml green tea at store A," and queries the inventory management systems of each facility. The AI ​​model analyzes this and outputs data indicating whether or not the item is in stock.

[0701] Step 6:

[0702] The server uses multiple facility information and inventory data to create a ranking that takes into account factors such as distance from the user's current location and opening status. It then executes a ranking algorithm to determine the priority of each facility. This results in the output of the optimal facility ranking to present to the user.

[0703] Step 7:

[0704] The server sends optimized facility ranking information to the terminal. The terminal analyzes the received information and visualizes it on a map using the Google Maps API, etc. By highlighting the most easily accessible facilities on the map, it becomes possible to take concrete actions that encourage purchasing behavior.

[0705] Step 8:

[0706] Users can view information displayed on a map and choose to visit the nearest facility with stock or place an order online directly through the application. This allows users to make efficient purchasing decisions.

[0707] (Application Example 1)

[0708] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0709] Users may have difficulty efficiently finding the products they want to buy in physical stores. In particular, they may not be able to quickly check whether nearby stores have the product in stock, leading to wasted travel time and effort. Even when they find the optimal store, they may face challenges such as difficulty figuring out the route to the store or reserving the product.

[0710] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0711] In this invention, the server includes means for acquiring desired product information, means for acquiring location information and transmitting it to an information processing device along with the product information, means for acquiring information about the facilities that handle the products, means for acquiring inventory information of the facilities using generation AI technology, means for presenting the nearest facility with stock to the user, and means for providing a route to the presented facility. This enables the user to quickly acquire information about the nearest store with stock and visit it via an efficient route.

[0712] An "information processing device" is a terminal device operated by a user that has the function of acquiring location information and product information, and communicating with other devices.

[0713] "Generative AI technology" is a technology that uses artificial intelligence to analyze inventory and store information and provide users with useful information.

[0714] "Location information" refers to data that indicates the user's current geographical location, and is information obtained through the user's device.

[0715] A "facility" refers to a physical store or warehouse where products are handled, and the inventory information for that facility is provided to the user.

[0716] "Inventory information" refers to information about the quantity of a particular product currently held at a facility and its immediate availability for purchase.

[0717] A "route" is geographical guidance information that suggests the optimal mode of transportation to the facility selected by the user.

[0718] "Presentation" refers to the act of providing information that is displayed on a user's device, serving as a guide for the user to take action based on that information.

[0719] This invention is a system that enables users to efficiently find products by transmitting product information and location information to a server via an information processing device. The information processing device consists of a terminal such as a smartphone or tablet, which acquires location information using GPS functionality and allows users to input desired product information.

[0720] The server is built as a server-side application using Node.js and interacts with the Firebase database to retrieve information about nearby facilities. The server also utilizes OpenAI GPT-3, a generative AI technology, to provide optimal facility information, including route information to the facility, based on the acquired facility inventory information.

[0721] Users can view displayed facility information on a map via their device and receive route guidance to the nearest facility. They can also choose to purchase products online based on the facility information. This system provides an efficient shopping experience through real-time inventory checks.

[0722] For example, if a user is looking for cosmetics of a specific brand, they can enter "Brand X lotion" into the terminal, which will then display the nearest store with the product in stock. The user can then use this information to efficiently visit a store or place an online order.

[0723] An example of a prompt used in a generative AI model is: "Check the nearby stock availability of a specific product and recommend the best facility. Product: Brand X lotion, Location: (35.6895, 139.6917)."

[0724] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0725] Step 1:

[0726] The user enters product information for the product they wish to purchase on their device. The entered information, such as product name and category, is stored on the device. The device also uses its GPS function to obtain its current location. This location information, along with the product information, is then prepared for input to the server.

[0727] Step 2:

[0728] The device sends acquired product information and location data to the server. The server receives this information and uses it directly as a starting point for queries to the database. This information forms the basis for the data processed in the next step.

[0729] Step 3:

[0730] The server uses the received product information and the user's location to search the Firebase database. The database returns a list of facilities that may carry the relevant product. Through this process, the server obtains information about relevant facilities within a certain range of the user's current location.

[0731] Step 4:

[0732] The server utilizes OpenAI GPT-3, a generative AI technology, to check the inventory status of each facility based on the acquired facility information. Specifically, it queries the facility's inventory management system to obtain the availability of specified products. At this stage, the server aggregates the inventory information for each facility.

[0733] Step 5:

[0734] The server evaluates and ranks facilities based on aggregated inventory information, considering factors such as distance and the immediate availability of inventory. The highest priority facilities are those located close to the user's location and possessing the specified product in stock. Once the evaluation is complete, ranking information for each facility is generated.

[0735] Step 6:

[0736] The server sends facility information, along with map data, to the terminal. The terminal receives this information and displays it visually to the user. This allows the user to easily identify the nearest suitable facility and then use the map to begin directions to the store.

[0737] Step 7:

[0738] Based on the provided facility information, users can either visit a physical store or order products online via the application. Depending on the user's choice, additional options and services (such as product reservation) may also be offered.

[0739] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0740] This invention is a system that uses a user terminal and a server to acquire product information and combines this with an emotion engine that analyzes the user's emotions. First, the user uses a mobile terminal to input information about the product they wish to purchase. At this time, the terminal uses the device's camera and microphone to collect the user's facial expressions and voice, and acquire emotion data.

[0741] The device sends acquired product information, emotion information, and location information to the server. The server analyzes this information and consults a database to identify nearby stores that carry the product. The server uses a generative AI to check the inventory status of the identified stores and, at the same time, adjusts the recommendations for stores and products based on the emotion data acquired by the emotion engine, according to the user's current mood.

[0742] The emotion engine uses technology that identifies various emotional states by utilizing the user's voice and facial expression data. For example, if the user is detected as excited, the emotion engine can prioritize suggesting trending or new products to the user. The server also sorts and presents stores with confirmed inventory in an order that is optimal for the user's emotional state.

[0743] Users can check the nearest stores with stock on a map displayed on their device and choose to visit or order online. For example, if the system recognizes the user's mood when they are looking for a "specific drink," it can suggest other products that would go well with that drink.

[0744] This system aims to more accurately understand user needs, improve individual experiences, and provide a highly satisfying purchasing experience for consumers.

[0745] The following describes the processing flow.

[0746] Step 1:

[0747] The user activates their mobile device, opens the app, and enters information about the product they wish to purchase. The device simultaneously captures the user's facial expressions and voice data using its camera and microphone.

[0748] Step 2:

[0749] The device gathers product information, emotion data, and location information and prepares to send it to the server.

[0750] Step 3:

[0751] The device sends the above information to the server. The data is encrypted as needed before being sent.

[0752] Step 4:

[0753] The server analyzes the received information and retrieves information about nearby stores that may carry the product from the database.

[0754] Step 5:

[0755] The server uses generated AI to contact the listed stores and check the stock status of the specified product.

[0756] Step 6:

[0757] The server utilizes an emotion engine to analyze user emotional data. This allows it to adjust product and store recommendations to match the user's mood and emotions.

[0758] Step 7:

[0759] The server ranks stores with available stock and then sorts them in an order optimized for the user's emotional state. This ensures that the most relevant information is provided to the user first.

[0760] Step 8:

[0761] The server sends ranked store information back to the terminal and presents it to the user as a map or list.

[0762] Step 9:

[0763] Based on the information received by the device, the system displays the nearest stores with stock on a map and suggests options for visiting a store or ordering online.

[0764] Step 10:

[0765] Users select a store based on the information presented and either visit it in person or complete the purchase process through the app. Additional suggestions based on the user's emotions can also be useful here.

[0766] (Example 2)

[0767] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0768] Conventional sales information systems simply presented product and inventory information without considering the user's emotions. Therefore, it was difficult to maximize user purchasing intent and satisfaction. Furthermore, while inventory information could be checked, suggestions combining other products and optimal store selections were lacking. This invention aims to improve the user experience by providing more appropriate product and store suggestions based on the user's emotional state.

[0769] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0770] In this invention, the server includes means for acquiring the user's facial expressions and voice and generating emotion data, means for adjusting store and product suggestions based on the emotion data, and means for ranking sales locations based on inventory information and the user's emotion data. This makes it possible to optimize product suggestions and sales locations according to the user's emotions.

[0771] A "user terminal" is a computing device used by users to input product information and acquire emotional data.

[0772] "Product information" refers to data such as the name, category, and barcode of the product that the user wishes to purchase.

[0773] "Location data" refers to information that indicates the geographical location of the user's device.

[0774] "Emotional data" refers to information that indicates the emotional state of a user, analyzed from their facial expressions and voice.

[0775] A "server" is a central processing unit that receives and processes information sent from user terminals and provides optimal store and product recommendations.

[0776] A "place of sale" refers to a physical or online store that sells the product.

[0777] "Generative AI" is an artificial intelligence technology that operates on a server and supports the acquisition of inventory information and the adjustment of suggestions.

[0778] "Inventory information" refers to data that shows the availability of a product at a specific sales location.

[0779] "Adjusting suggestions" means optimizing the selection of products and stores suggested based on user sentiment data.

[0780] "Ranking" means evaluating and assigning a ranking to sales locations based on specific criteria.

[0781] This invention is a system consisting of a user terminal and a server that combines the acquisition of product information with the analysis of the user's emotions to provide appropriate product recommendations. The user inputs information about the products they wish to purchase using their mobile device. During this process, the terminal utilizes input devices such as a camera and microphone to collect the user's facial expressions and voice, generating emotion data. This makes it possible to analyze the user's emotional state in real time.

[0782] Product information, emotion information, and location information acquired by the device are transmitted to a server via the internet. The server processes this information and, by referring to its own database, identifies nearby sales locations that carry the product. This process utilizes generative AI models to obtain real-time inventory information for each sales location. The server also adjusts and optimizes store and product suggestions based on the user's emotion data obtained by the emotion engine. This enables more personalized suggestions that match the user's current emotional state.

[0783] For example, when a user is searching for a "new smartphone," if the emotion engine recognizes that the user is excited, the system can focus on suggesting the latest models and highly-rated products, and can also introduce related accessories.

[0784] Examples of prompts for the generative AI model include: "When a user is searching for new products, suggest appropriate product combinations, taking into account their current emotional state," and "Develop a strategy to encourage purchases of specific desired products by making suggestions based on the user's emotions."

[0785] By using this system, users will be able to obtain product information that more accurately matches their needs, aiming to provide a more fulfilling shopping experience.

[0786] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0787] Step 1:

[0788] The user enters information about the product they wish to purchase using a mobile device. Specifically, the user launches an application on their device and enters the product name and category in text format, or scans the product barcode with the camera. The input data (product information) obtained includes the product name and barcode. This data is temporarily stored on the device.

[0789] Step 2:

[0790] The device uses its camera and microphone to collect the user's facial expressions and voice, generating emotion data in real time. Emotion analysis software analyzes the user's facial muscle movements and voice tone to determine their emotional state (e.g., joy, excitement, relaxation). This process yields the output as emotion data.

[0791] Step 3:

[0792] The device transmits acquired product information, emotion data, and location data to a server. Using a communication module within the device, this data is encrypted and transmitted to the server via the internet. The server receives this data as input.

[0793] Step 4:

[0794] The server, based on the received product information, consults a database to identify nearby retail locations that carry the product. Specifically, it uses a database search algorithm to extract store information that matches the entered product information. As output of this process, a list of identified retail locations is generated.

[0795] Step 5:

[0796] The server uses a generated AI model to retrieve inventory information for identified sales locations. The AI ​​model queries the database to check the real-time inventory status of each sales location. This step yields inventory information for each sales location as output.

[0797] Step 6:

[0798] The server adjusts its recommendations to suggest the most suitable stores and products to the user based on emotional data. It utilizes an emotional data analysis engine to prepare suggestions tailored to the user's current emotional state. This adjustment results in personalized recommendations for each individual user.

[0799] Step 7:

[0800] The server sends information to the user's terminal, including the nearest sales location with the item in stock, as the final recommendation. Here, the optimized recommendation data is encrypted again and sent back to the terminal. The user's terminal receives this information and displays it on the screen.

[0801] (Application Example 2)

[0802] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0803] In today's commercial environment, consumers demand quick and accurate information and suggestions when making purchases, but systems capable of addressing individual, emotion-based needs are limited. Current systems fail to adequately provide optimal product recommendations tailored to consumers' emotional states, nor do they adequately suggest nearby retail locations based on those emotional factors. Therefore, improving the personalized purchasing experience for each individual consumer is a key challenge.

[0804] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0805] In this invention, the server includes means for suggesting products or sales locations based on user sentiment data, means for ranking sales locations based on inventory information, and means for displaying the nearest location with available stock. This enables optimal purchase suggestions tailored to the user's emotional state and provides a customized purchasing experience that meets individual needs.

[0806] A "user terminal" is a computing device that has the function of acquiring product information and sentiment data and sending it to a server.

[0807] "Emotional data" refers to information that represents a user's emotional state, and is digital data obtained through the analysis of voice and facial expressions.

[0808] "Location information" refers to information indicating the geographical location of a user's device, and is data obtained using GPS or similar methods.

[0809] A "server" is a central computing system that analyzes data received from user terminals and provides information on sales locations and product suggestions.

[0810] A "sales outlet" is a physical or online facility that handles products.

[0811] "Generative artificial intelligence" is a computational technology that can make human-like decisions based on large amounts of data.

[0812] "Inventory information" refers to data that shows the inventory status of products at sales locations.

[0813] A "suggestion" is information that presents the most suitable products and sales locations based on the user's emotional state and desired purchases.

[0814] The system for implementing this invention consists of a user terminal, a server, and a communication network. The user first uses a mobile terminal to input the products they wish to purchase. The terminal is equipped with a camera and a microphone, and acquires emotional data by analyzing the user's facial expressions and voice. This allows the terminal to identify the user's emotional state.

[0815] Emotional data, product information, and location information are transmitted from the terminal to the server. The server analyzes this data and uses a database of sales locations to check inventory at each location that handles the product. Generative artificial intelligence technology is used to suggest the most suitable products and recommend sales locations based on the user's emotional state.

[0816] As a concrete example, consider a case where a user is looking for a specific drink. If the server recognizes that the user is in a cheerful mood, it can suggest snacks or other products that would pair well with that drink. For example, a prompt such as "Tell me some desserts I can enjoy today" might be generated. Based on this prompt, the server provides suggestions that are appropriate for the user.

[0817] The server provides users with the optimal ordering method: direct purchase at a designated sales location or online ordering. It also prioritizes locations with confirmed stock and presents users with the best options, thereby improving the user experience. This system personalizes the purchasing experience by taking into account the user's emotional state, resulting in a highly satisfying shopping experience for consumers.

[0818] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0819] Step 1:

[0820] The user enters the product they wish to purchase using a mobile device. This input includes information such as the product name and category. The device receives the product information and simultaneously records the user's facial expressions and voice using its camera and microphone. The Emotion API is used to analyze and retrieve the user's emotional data from the recorded data.

[0821] Step 2:

[0822] The device transmits acquired product information, sentiment data, and location information to the server. During transmission, all information is packetized and delivered to the designated server address via the communication network. This process allows the server to gain a multifaceted understanding of the client's current situation and needs.

[0823] Step 3:

[0824] The server analyzes the received information and searches for locations that handle the relevant product by referring to the sales location database. Using generative artificial intelligence (generative AI), it generates product recommendations that take into account the user's emotional state. As a result, a list of recommended products is created.

[0825] Step 4:

[0826] Based on the generated recommended product list, the server checks the inventory of sales locations and lists them in order of priority. It executes a database query to retrieve inventory data for each sales location and selects the nearest location based on the user's location information.

[0827] Step 5:

[0828] The server replies to the terminal with the nearest sales location whose inventory has been checked, along with recommended products determined using AI generation. This reply is designed to provide the user with the best possible purchasing options. As a result, the user can decide whether to visit a store or place an online order based on the information displayed.

[0829] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0830] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0831] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0832] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0833] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0834] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0835] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0836] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0837] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0838] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0839] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0840] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0841] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0842] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0843] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0844] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0845] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0846] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0847] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0848] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0849] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0850] The following is further disclosed regarding the embodiments described above.

[0851] (Claim 1)

[0852] A means of obtaining the product information desired by the user terminal,

[0853] The terminal acquires location information and transmits it to the server along with the product information,

[0854] A means for the server to obtain information about stores that handle the product,

[0855] The server uses generated AI to acquire inventory information for the store,

[0856] The server provides a means for displaying the nearest store with available stock to the user,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, wherein the server includes means for ranking stores based on inventory information.

[0860] (Claim 3)

[0861] The system according to claim 1, comprising means for a user to order products online based on the presented store information.

[0862] "Example 1"

[0863] (Claim 1)

[0864] A means of obtaining the item information desired by the user information terminal,

[0865] The information terminal acquires geographic location information and transmits it to the server along with the item information,

[0866] The server has means for acquiring facility information that handles the item,

[0867] The server provides a means for acquiring inventory information of the facility using generated AI,

[0868] The server provides a means for displaying facilities in order of priority based on inventory information,

[0869] The server has means for ranking facilities while taking into account the user's geographical location,

[0870] The information terminal includes means for visually displaying facility information on a map,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, comprising means for a user to order goods online based on the facility information presented.

[0874] (Claim 3)

[0875] The system according to claim 1, comprising means for prompting a user to make a decision to visit a facility based on information on the map.

[0876] "Application Example 1"

[0877] (Claim 1)

[0878] A means by which an information processing device obtains desired product information,

[0879] The information processing device acquires location information and transmits it to the information processing device along with the product information,

[0880] The information processing device provides means for acquiring information about the facility that handles the product,

[0881] The information processing device includes means for acquiring inventory information of the facility using AI generation technology,

[0882] The information processing device provides a means for displaying to the user the nearest facility with available stock,

[0883] The information processing device provides means for providing a route to the presented facility,

[0884] A system that includes this.

[0885] (Claim 2)

[0886] The system according to claim 1, wherein the information processing device includes means for evaluating a facility based on inventory information.

[0887] (Claim 3)

[0888] The system according to claim 1, which includes means for a user to purchase a product online based on the facility information presented.

[0889] "Example 2 of combining an emotion engine"

[0890] (Claim 1)

[0891] A means of obtaining information about the product desired by the user terminal,

[0892] The terminal acquires location data and transmits it to the server along with the product information,

[0893] The terminal includes means for acquiring the user's facial expressions and voice and generating emotion data,

[0894] A means for the server to obtain information about the sales locations that handle the product,

[0895] The server uses generated AI to obtain inventory information for the sales location,

[0896] The server provides means for adjusting store and product suggestions based on sentiment data,

[0897] The server provides a means for displaying to the user the nearest sales location with available stock,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, wherein the server includes means for ranking sales locations based on inventory information and user sentiment data.

[0901] (Claim 3)

[0902] The system according to claim 1, comprising means for a user to order goods online based on the presented sales location.

[0903] "Application example 2 when combining with an emotional engine"

[0904] (Claim 1)

[0905] A means of obtaining the product information desired by the user terminal,

[0906] The terminal has means for acquiring user emotion data,

[0907] The terminal acquires location information and transmits it to the server along with the product information and emotional information,

[0908] A means for the server to obtain information on sales locations that handle the product,

[0909] The server provides a means for acquiring inventory information of the sales base using artificial intelligence,

[0910] A means for suggesting products or sales locations that match the user's current mood based on sentiment data acquired by the server,

[0911] The server provides a means for the user to find the nearest location with available stock,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, which includes means for ranking locations based on inventory information.

[0915] (Claim 3)

[0916] The system according to claim 1, which includes means for a user to order products online based on the provided location information. [Explanation of Symbols]

[0917] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining the product information desired by the user terminal, The terminal acquires location information and transmits it to the server along with the product information, A means for the server to obtain information about stores that handle the product, The server uses generated AI to acquire inventory information for the store, The server provides a means for displaying the nearest store with available stock to the user, A system that includes this.

2. The system according to claim 1, wherein the server includes means for ranking stores based on inventory information.

3. The system according to claim 1, comprising means for a user to order products online based on the store information provided.

Images