system

Abstract

We provide a system that collects store congestion information in digital format and stores and processes the information on a central server. [Solution] A system comprising: means for acquiring store congestion information in digital format; means for transferring the acquired congestion information to a central server; means for storing and processing the acquired congestion information on the central server; means for displaying immediately available congestion information on a user terminal; means for providing special offer information related to a store selected by the user; means for generating an electronic coupon using the special offer information and displaying it on the user terminal; means for authenticating the electronic coupon at the store; means for providing the authenticated special offer information; and means for analyzing store and user usage data and generating a report.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In small and medium-sized stores in a region, there are problems such as visitors suffering from opportunity losses due to congestion and the lack of an effective customer attraction strategy. There is also a problem that it is difficult to formulate measures based on specific data for promoting regional activation. Furthermore, there is a need for a mechanism that allows users to conveniently use congestion situations and privilege information.

Means for Solving the Problems

[0005] This invention provides a system that collects store congestion information in digital format and stores and processes the information on a central server. Congestion status is displayed in real time via user terminals, allowing users to check the congestion level and benefits of their desired store before using electronic coupons. Furthermore, coupon authentication at the store enables the provision of benefits, encouraging store visits. This achieves visualization of congestion status and effective customer attraction. Additionally, by analyzing usage data and providing reports to stores and local governments, it supports the development of data-driven measures for regional revitalization.

[0006] "Store congestion information" refers to digital data that includes the current number of customers in a specific store, seat availability, and average stay time.

[0007] A "central server" is a digital information management device used to store and process data aggregated from multiple stores.

[0008] A "user terminal" is an electronic device that acquires information and displays it in a format usable by the user, and includes smartphones and tablets.

[0009] An "electronic coupon" is proof of receiving discounts or benefits offered in digital format, often presented as a QR code (registered trademark) or barcode.

[0010] "Authentication" refers to the process of verifying that the presented electronic coupon is valid and then providing the service or applying the discount.

[0011] "Usage data" refers to digital information about the service usage behavior of users and stores, and is data that is accumulated in an analyzable format.

[0012] "Generating a report" is the process of analyzing collected data and creating a report summarizing the results. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] 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.

[0017] 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.

[0018] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. 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.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention provides a system for collecting store congestion information in digital format and processing and storing it on a central server. The server receives congestion information transmitted from each store in real time and records it in a database. The congestion information includes the number of customers, seat availability, and average dwell time. This allows the server to quickly present congestion information to users when they access the site.

[0035] Users launch the application using their mobile devices or tablets and retrieve store information based on their current location and desired service category. The device communicates with the server to display a screen that visually shows the congestion levels and available benefits of nearby stores. Based on this information, users can view details of stores of interest and efficiently plan their visits.

[0036] As a concrete example, suppose a user is looking for lunch in a tourist area. The user launches the app and searches for nearby restaurants, and the app provides information on the congestion status of nearby establishments and any special offers. In this case, the user's device can present the information clearly using voice guidance and visual effects. For example, a notification might appear stating, "This restaurant is currently busy, but a table is expected to become available within 20 minutes."

[0037] When a user becomes interested in a particular store, they can check the special offers and select an electronic coupon within the app. The electronic coupon is displayed on the device as a QR code, which the user can then use at the store upon arrival.

[0038] At the store, staff scan the QR code from the user's device, verify that it is a valid coupon, and then provide the benefit or discount. The server integrates this usage data and analyzes store usage across the region to generate useful reports for local governments. These reports can be used to plan and measure the effectiveness of regional revitalization measures.

[0039] Therefore, this system efficiently manages store congestion information, enabling user convenience and contributing to increased customer traffic for stores. By utilizing this platform, economic activity among local small and medium-sized enterprises will be stimulated, and the attractiveness of the region will be enhanced.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The server receives congestion data from the stores. The server receives congestion information generated in real time from store sensors and staff input, and stores it in a database.

[0043] Step 2:

[0044] The user launches the app on their device. The device determines the user's current location and inputs the desired category and time slot.

[0045] Step 3:

[0046] The server filters nearby store information based on location data and criteria. It organizes information such as congestion levels, distance, and available benefits, and sends it to the user's terminal.

[0047] Step 4:

[0048] Users select a store they are interested in from the store information displayed on their device and check detailed congestion information and special offers.

[0049] Step 5:

[0050] Users select the electronic coupon they want to use and generate a QR code on their device. The coupon is saved within the app for easy redemption.

[0051] Step 6:

[0052] The user presents a QR code to store staff upon arrival. The store's terminal scans this QR code and verifies its validity.

[0053] Step 7:

[0054] The server aggregates coupon usage information and store usage data. Based on this, it analyzes usage trends and generates reports for each region.

[0055] Step 8:

[0056] Local governments will utilize the generated reports to help plan regional revitalization and tourism policies.

[0057] In this way, the entire system works in coordination, enhancing convenience for both users and stores, and contributing to the revitalization of the local economy.

[0058] (Example 1)

[0059] 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."

[0060] The challenge lies in improving store customer attraction while simultaneously providing users with highly convenient information by efficiently collecting and managing real-time store congestion information. Furthermore, it is necessary to effectively utilize related promotional information to stimulate local economic activity. Existing systems often provide inaccurate or delayed congestion information, leading to decreased user satisfaction.

[0061] 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.

[0062] In this invention, the server includes means for acquiring the occupancy status of people in a store as digital data, means for transferring the acquired occupancy status to a central information processing device, and means for storing and processing the acquired occupancy status in the central information processing device. This enables real-time management of store congestion information and rapid provision of information to users.

[0063] A "store" refers to a physical or virtual location where customers visit to use goods or services.

[0064] "Human presence status" refers to information indicating the number of people present in a specific location within a certain period of time, and how that number changes.

[0065] "Digital data" refers to information expressed in a format that can be processed by computers and electronic devices.

[0066] A "central information processing system" refers to a computer system that aggregates multiple data sets and manages them through calculations and recording.

[0067] "Benefit information" refers to information that promotes the use of a service, such as perks and discounts offered to users.

[0068] An "electronic discount voucher" refers to a digital coupon used to obtain discounts or benefits.

[0069] "User equipment" refers to electronic devices that users directly use to acquire, process, and display information.

[0070] A "report" refers to a document that summarizes the results of an analysis of specific data or activities.

[0071] "Voice guidance for terminology" refers to instructions and information provided through audio.

[0072] "Visual effects" refer to visual representations used to enhance the impression of information when it is seen.

[0073] This invention is a system for efficiently collecting store congestion information and providing users with that information quickly.

[0074] The server receives congestion information transmitted from stores in real time via web server software such as "Apache®" or "Nginx". This information is stored in a "MySQL®" database, where data such as the number of customers, availability, and average dwell time are recorded in a structured manner. This allows the server to analyze congestion levels through various calculations and prepare for rapid information provision.

[0075] The device obtains GPS location information when the user operates an application using a mobile communication terminal or tablet. Based on this location information, it requests store information, including recent congestion levels, from the server. The device uses development frameworks such as "Flutter®" or "React Native" to visually display store congestion levels and special offer information on the screen. Furthermore, this information may be provided as voice guidance using speech synthesis software.

[0076] As a concrete example, consider a user looking for a restaurant for lunch in a busy downtown area. The user launches the application and searches for nearby restaurants. The displayed app screen shows the congestion status and special offers for each restaurant. In this case, using a prompt such as "Search for cafes near my current location and let me know their congestion status" allows the user to efficiently receive the information they need.

[0077] When a user finally selects a specific store, an electronic coupon is displayed on their terminal and becomes available for use upon arrival. At the store, staff verify the coupon using a QR code reader. This system improves the store's ability to attract customers and provides a more user-friendly environment.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] Sending congestion information from stores

[0081] Store staff use a dedicated management system to input data such as the number of customers in the store, seating availability, and average dwell time. This information is transmitted to a server in real time via the internet. The input represents the actual congestion level of the store, while the output is digital congestion information sent to the server.

[0082] Step 2:

[0083] Data reception and recording on the server.

[0084] The server receives congestion information sent from the stores. Web server software such as "Apache" or "Nginx" enables this, and records the received data in a "MySQL" database. During the data recording process, the information is stored in an appropriate structure and indexes are added to speed up subsequent queries. The input is congestion information from the stores, and the output is structured information stored in the database.

[0085] Step 3:

[0086] Obtaining and requesting user information

[0087] The user launches the application on their device and uses GPS to obtain their current location. They also specify the service category they want to search for. The device uses this information to request nearby store information from the server. The input is the user's location and category information, and the output is the information request to the server.

[0088] Step 4:

[0089] Displaying store information on a terminal

[0090] The server queries the database for appropriate store information based on the user's request and sends it to the terminal. The terminal then uses tools such as Flutter or React Native to visually display store congestion status and special offers. The input is the store information sent from the server, and the output is the screen display on the user's terminal.

[0091] Step 5:

[0092] Selection of reward information and generation of electronic coupons

[0093] When a user selects a store they are interested in, they can check the special offers and choose an electronic coupon within the app. The device generates and displays the coupon as a QR code. The input is the user's selection of special offers, and the output is an electronic coupon in QR code format.

[0094] Step 6:

[0095] Use of electronic coupons at stores

[0096] Store staff scan the QR code displayed on the user's terminal with a dedicated reader to verify its validity. After verification, the benefits and discounts are applied. The input is the electronic coupon presented by the user, and the output is the sales information with the benefits applied.

[0097] (Application Example 1)

[0098] 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."

[0099] Modern consumers face challenges such as wasting time due to the inability to understand real-time congestion levels and the inability to check seating availability or special offers before visiting a facility. Furthermore, information related to the real world often lacks entertainment value and visual appeal. Additionally, providing data tailored to promoting customer acquisition for small and medium-sized enterprises in specific regions and revitalizing local markets is challenging.

[0100] 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.

[0101] In this invention, the server includes means for acquiring store congestion information in digital format, means for an information processing device to present congestion information using audio guidance and visual effects, and means for overlaying congestion information onto real-world visual information using augmented reality technology. This allows users to intuitively grasp the congestion status and special offers of facilities in real time, enabling them to plan efficient visits. Furthermore, it enables the provision of information that is effectively useful for attracting customers to a trade area and promoting regional development.

[0102] "Store congestion information" refers to real-time data such as the number of customers, seat availability, and average stay time within a specific facility.

[0103] An "information processing device" refers to a combination of hardware and software, such as servers and cloud systems, used for storing, processing, and analyzing data.

[0104] "Audio guide" refers to a system that provides users with information such as congestion levels and store information via audio.

[0105] "Visual effects" refers to display technologies and graphical effects used to visually highlight and display information such as congestion levels and special offers.

[0106] Augmented reality technology is a technique that overlays digital information onto real-world visual information, enabling users to obtain information while interacting with their surroundings.

[0107] An "electronic coupon" refers to a code or digital voucher provided in digital format that is used to receive benefits or discounts at participating establishments.

[0108] "Special offers" refers to information that presents discounts, services, and other promotions that users can receive when using a facility.

[0109] "Usage data" refers to data that includes facility and user behavior and records of store usage, and is collected for the purpose of creating value through analysis.

[0110] A "report" refers to a document that analyzes usage data and proposes improvement measures for an organization or region based on the results.

[0111] To implement this invention, first, an information processing device is used to place a central server on a cloud platform and receive congestion information from each store via the network. The data is obtained from sensors and camera systems within the stores and aggregated on the server in real time as customer count and seating availability information. In this case, it is appropriate to use a server such as Amazon Web Services or Google Cloud Platform.

[0112] The server uses machine learning libraries such as TENSORFLOW® to analyze the received data, predicting and analyzing congestion trends. The analysis results are immediately transferred to the user's smartphone app and presented as a visual and audio guide. The application should preferably be developed using cross-platform development tools such as React Native or Flutter. Through the app, users can check the congestion status of nearby stores, integrating it with the real world using AR (augmented reality) technology.

[0113] As an example, let's say a tourist uses their smartphone to check the congestion status of nearby restaurants. As the user scans the streetscape with their camera, the AR function overlays entertaining visual information, displaying it along with an audio guide saying, "This cafe is currently crowded, but a table is expected to become available within 15 minutes."

[0114] In addition, users can review digital reward information received within the app and generate and display electronic coupons on the screen as needed. Store staff then review these coupons and provide appropriate services or discounts. In particular, a generation AI model is used for coupon generation and reward information management.

[0115] An example of a prompt message is as follows:

[0116] "Users want to know how busy nearby cafes are. Please display the current availability and any available perks as information about that cafe."

[0117] "I'm looking for a restaurant for lunch in a tourist area. Please show me restaurants with seats available within 20 minutes and provide an electronic coupon."

[0118] This system allows users to efficiently plan their visits and contribute to revitalizing the use of local facilities.

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The server receives real-time congestion information transmitted from each store. This input includes customer counts and seating availability information obtained from sensors and cameras within the stores. The server collects this data via a streaming API and stores it in a database.

[0122] Step 2:

[0123] The server uses machine learning algorithms to predict customer flow and seat availability based on accumulated congestion information. Here, the TensorFlow library is used to perform future predictions based on historical data. The output includes estimated seat availability and peak visit times.

[0124] Step 3:

[0125] The server receives the user's current location and desired category. Based on this, it selects congestion predictions and special offer information for nearby stores and sends them to the user's terminal. The terminal uses this as input and displays the results on the application screen using React Native.

[0126] Step 4:

[0127] The device uses its camera function to scan the real environment and overlays congestion information onto the real image using augmented reality (AR) technology. It performs actions to make the information visually easy for the user to understand and obtain.

[0128] Step 5:

[0129] Users view special offers related to stores they are interested in and generate electronic coupons. The terminal performs this generation process via an AI model and displays the electronic coupon as a QR code on its screen.

[0130] Step 6:

[0131] When a user visits a store, store staff scan the QR code displayed on the user's device to authenticate the benefit information. At this point, the server performs the authentication process and transmits the result to the store.

[0132] Step 7:

[0133] The server aggregates store and user usage data, performs statistical analysis, and generates reports to create information useful for revitalizing local facilities. This output is provided to local government agencies and other organizations.

[0134] 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.

[0135] This invention aims to further improve the user experience by integrating an emotion engine into conventional store information management systems. The emotion engine analyzes the user's emotional state based on input data obtained from the user, such as facial recognition, input behavior, and voice.

[0136] The server receives this data and uses an emotion engine to determine the user's psychological state. For example, it analyzes the user's satisfaction level and expectations based on their typing speed and force when entering a food review, or their facial expressions while using the service.

[0137] When a user launches the app on their device, the emotion engine recommends the most suitable stores and offers based on the user's state. The server uses the user's current location information to select stores that are within a reasonable distance and require minimal effort, and also uses emotion data to suggest services that match the user's mood. For example, if the system determines that the user is tired, it will recommend stores with a more relaxing atmosphere or stores that offer stress-relieving offers.

[0138] As a concrete example, consider a busy business traveler using the app during lunchtime. If the device detects that fatigue is reflected in the user's facial expression, the server will recommend a restaurant with a quiet and comfortable atmosphere. Furthermore, the electronic coupons offer perks such as "drink service" or "use of relaxing aromatherapy" to further enhance user satisfaction.

[0139] After a user visits a store, the emotion engine re-evaluates whether the suggested effect was achieved. This feedback is analyzed by the server to help improve future services. Stores can also use this data to gain a detailed understanding of user emotional changes and to understand potential customer needs, thereby improving the quality of their services.

[0140] In this way, this system, which incorporates an emotion engine, strengthens the link between user emotions and service experience, enabling personalized store recommendations and rewards tailored to individual needs. This allows for effective customer acquisition focused on the local community, contributing to the revitalization of the local economy.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The user launches the app on their device, and emotional input data is collected along with location information. The device then uses its camera and microphone to send the user's facial expressions, voice tone, and other information to the emotion engine.

[0144] Step 2:

[0145] The emotion engine analyzes the user's emotions. Based on facial features and voice waveform data, the engine determines the user's current emotional state. This information is sent to the server as the user's psychological state.

[0146] Step 3:

[0147] The server combines location information and sentiment analysis results to recommend the most suitable stores and benefits. If the user wants to relax, stores with a quiet atmosphere or services that promote relaxation will be selected.

[0148] Step 4:

[0149] The terminal displays recommended store information and special offers to the user. The server also considers the store's congestion level and guides the user to the store with the shortest possible waiting time.

[0150] Step 5:

[0151] After the user selects a store and checks the benefits, an electronic coupon is generated based on the selected benefit information. The coupon is provided in the form of a QR code displayed on the terminal.

[0152] Step 6:

[0153] The user presents a QR code at their chosen store, which the store's terminal scans and verifies. The store then offers emotionally-driven rewards to improve user satisfaction.

[0154] Step 7:

[0155] After a user visits, feedback is sent to the server. The emotion engine then analyzes the user's emotions again, and their post-visit state is evaluated. This information is stored as data for service improvement.

[0156] Step 8:

[0157] The server collects all user data and analyzes regional usage trends. The analysis results are provided to stores and local governments and used to improve service quality and implement regional revitalization measures.

[0158] (Example 2)

[0159] 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".

[0160] Traditional store recommendation systems primarily rely on recommendations based on the user's physical location, which has the drawback of not adequately considering the emotional and psychological states of individual users. As a result, they tend to provide uniform promotional information, failing to adequately contribute to improving the user experience or revitalizing the local economy.

[0161] 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.

[0162] In this invention, the server includes means for analyzing the user's emotional state, means for providing personalized store recommendations based on the analyzed emotional state, and means for collecting user feedback and storing it in a database for future service improvements. This enables store recommendations and the provision of benefits that correspond to the user's emotional state, thereby improving the user experience and stimulating the local economy.

[0163] "Congestion information" refers to data that shows the level of people gathered at a particular store or location, the length of queues, and other information indicating the dwell time of users.

[0164] A "central server" is a centralized computer system for processing, storing, and managing data via the internet.

[0165] A "user terminal" is an electronic device used directly by the user, and includes devices such as smartphones and tablets.

[0166] "Benefit information" refers to additional value or discount information regarding products and services offered to users, and is provided in the form of electronic coupons, etc.

[0167] An "electronic coupon" is a digital coupon provided in digital format that grants the right to receive a discount or free provision of a specific service or product.

[0168] "Emotional state" refers to information that indicates the user's psychological and emotional state, and is analyzed based on digital data.

[0169] "Personalized store recommendations" refer to a personalized store selection and referral process based on the user's individual behavioral characteristics and emotional state.

[0170] "User feedback" refers to data that reflects users' impressions and opinions on the services and recommendations provided, and is used to improve those services.

[0171] This invention is a system that analyzes a user's emotional state and provides personalized store recommendations and special offers based on that analysis. The system primarily utilizes a user terminal, a central server, and an emotion analysis engine to achieve the functions described in the claims.

[0172] The user launches a dedicated application on a device such as a smartphone or tablet. The device uses its camera, microphone, and touch sensors to collect data such as the user's facial expressions, voice, and keyboard input patterns. This emotional data is temporarily stored on the device and securely transmitted to a central server using encryption technology.

[0173] The server passes the received data to the sentiment analysis engine. The sentiment analysis engine uses machine learning algorithms to quantify the user's emotional state. This analysis incorporates a generative AI model that leverages past data and learning to more accurately determine the emotional state.

[0174] The server then uses the analysis results to select the most suitable stores and offers for the user. This selection process takes into account the user's current location and emotional state, resulting in personalized recommendations. The selected store and offer information is sent to the device and displayed to the user in an immediately usable format.

[0175] For example, if a user on a business trip is using the app and facial analysis detects signs of fatigue, the server will recommend a quiet and relaxing restaurant. The perks offered may include services such as complimentary drinks or the use of relaxing aromatherapy.

[0176] This system collects user feedback and uses it to improve future services, thereby contributing to an enhanced user experience.

[0177] An example of a prompt message might be, "Based on the user's sentiment data, recommend the best store and benefits."

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The user launches the app on their device. The device uses its camera, microphone, and touch sensors to collect the user's facial expressions, voice, and keyboard input patterns. This data is temporarily stored on the device as input. Specifically, facial recognition software analyzes the user's image, and voice recognition software analyzes the tone and speed of their voice. The output is quantified data that suggests the user's emotions.

[0181] Step 2:

[0182] The terminal securely transmits the collected data to a central server using encryption technology. The input includes encrypted emotional data, which is securely sent to the server over the internet. This process utilizes specific data transfer protocols to ensure data integrity.

[0183] Step 3:

[0184] The server decrypts the received encrypted data and passes it to the sentiment analysis engine. This engine uses the input data to utilize a generative AI model to analyze the user's emotional state. Specifically, a machine learning algorithm quantifies the emotions, and an emotion score is generated as output.

[0185] Step 4:

[0186] The server combines sentiment scores with the user's current location information to select the most suitable stores and offers. This process uses the analysis results and geographic information systems to generate personalized recommendation lists. The output is a personalized list of stores and offers.

[0187] Step 5:

[0188] The server sends the generated store list and special offer information to the terminal. The terminal displays the data it has received as input to the user. Specifically, the user interface organizes the recommendation information and displays it on the screen. The output is a visual presentation for the user to take action.

[0189] Step 6:

[0190] After the user visits a recommended store, the terminal collects sentiment data again and sends feedback to the server. The input includes the newly collected sentiment data, which is then sent back to the server. This feedback is used to improve the accuracy of future analyses.

[0191] Step 7:

[0192] The server analyzes the collected feedback data and stores it in a database. This data is used for the continuous training of machine learning and helps improve recommendation algorithms. Specifically, the database management system detects certain patterns and trends and compiles them into reports.

[0193] (Application Example 2)

[0194] 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".

[0195] Conventional store information management systems were limited to providing congestion information and special offers, and were unable to personalize services that took into account the emotional state of the user. As a result, it was difficult to improve user satisfaction and propose the most suitable facilities and services. This invention aims to solve these problems and enable the provision of advanced services based on the emotions of the user.

[0196] 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.

[0197] In this invention, the server includes means for determining the user's emotional state using an emotion analysis engine, means for capturing the user's facial expressions using image recognition technology and linking this to emotion analysis, and means for recommending appropriate facilities based on the user's location information and emotional state. This makes it possible to recommend the optimal store, rest area, and service in real time according to the user's emotional state, thereby improving the quality of the user's experience.

[0198] A "device for acquiring congestion information in stores in digital format" is a device that electronically detects the congestion level within a facility and acquires that information as digital data.

[0199] A "centralized processing unit" is a central computer that receives information collected from multiple terminals in a unified manner, and stores and processes that information.

[0200] "User's device" refers to a mobile information device such as a smartphone or tablet that the user carries with them.

[0201] An "emotion analysis engine" is a software component that analyzes a user's psychological state based on data acquired from them.

[0202] A "device that captures a user's facial expressions using image recognition technology and uses that information for emotion analysis" is a device equipped with technology that uses cameras and sensors to identify a user's facial expressions and uses that information for emotion analysis.

[0203] A "device that recommends appropriate facilities based on the user's location information and emotional state" is a system that combines the user's current location with an analysis of their emotions to suggest the most suitable place or facility for the user.

[0204] A "digital coupon" is an electronic voucher containing discounts or special offers that is distributed electronically.

[0205] A "report generation device" is a device that analyzes facility and user usage information and uses that information to create detailed reports.

[0206] This invention is a system that personalizes facilities and services based on the user's emotional state. The server uses an emotion analysis engine to analyze the user's emotions from their facial expressions, keyboard typing speed, voice, etc. In this process, OpenCV is introduced as an image recognition technology to identify facial expressions and provide data for emotion analysis. In addition, location information is obtained from the user's terminal and used to select recommended facilities. Based on these analysis results, the server recommends appropriate cafes or rest areas where the user can relax.

[0207] Furthermore, the server uses an API to retrieve the latest congestion and special offer information from facilities and generates digital coupons based on that information. These digital coupons are sent to the user's device, and when the user presents them, the authentication process at the facility is completed. The results of the facility's service provision are re-evaluated, and user feedback is used to improve future services. A possible prompt for users might be: "Please recommend a relaxing store for a tired user."

[0208] As a concrete example, consider a scenario where a customer visiting a shopping mall is fatigued from prolonged shopping. The server can detect this state using facial recognition and location information, recommend a nearby comfortable cafe, and provide a digital coupon for a free drink. In this way, the present invention can provide information services based on emotional states and improve customer satisfaction.

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] The device captures the user's facial expressions with a camera and performs face detection using OpenCV. The input is image data from the camera, and the output is feature data related to facial expressions. This feature data serves as basic information to be sent to the emotion analysis engine.

[0212] Step 2:

[0213] The server receives facial feature data transmitted from the terminal and analyzes the user's emotions using an emotion analysis engine. The input is facial feature data, and the output is the user's emotional state (e.g., fatigue, satisfaction, stress). Based on this emotional state, the server prepares recommended services.

[0214] Step 3:

[0215] The server obtains location information from the terminal and determines the user's current location. The input is location data, and the output is information about the facility where the user is located and its surroundings. Based on this location information, the server selects the most suitable store.

[0216] Step 4:

[0217] The server recommends the most suitable facility for the user, taking into account both their emotional state and location. The input is the user's emotional state and location, and the output is a list of recommended facilities. For example, it might select and suggest a relaxing cafe or a comfortable rest area.

[0218] Step 5:

[0219] The server retrieves information about benefits related to selected facilities and services via an API and generates digital coupons based on that information. The input is information about recommended facilities and benefits, and the output is an electronically issued digital coupon. This coupon may include benefits such as free drinks or relaxation items.

[0220] Step 6:

[0221] The terminal displays digital coupons received from the server to the user. The input is digital coupon information, and the output is a display of coupon data in a format usable by the user. Users can use the displayed coupons to receive discounts and benefits at stores and services.

[0222] Step 7:

[0223] After a user visits a store, the terminal sends feedback to the server to evaluate the effectiveness of the suggested services and benefits. The input is user feedback data, and the output is analysis data for the server. Based on this feedback, the server makes improvements to future services.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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".

[0240] This invention provides a system for collecting store congestion information in digital format and processing and storing it on a central server. The server receives congestion information transmitted from each store in real time and records it in a database. The congestion information includes the number of customers, seat availability, and average dwell time. This allows the server to quickly present congestion information to users when they access the site.

[0241] Users launch the application using their mobile devices or tablets and retrieve store information based on their current location and desired service category. The device communicates with the server to display a screen that visually shows the congestion levels and available benefits of nearby stores. Based on this information, users can view details of stores of interest and efficiently plan their visits.

[0242] As a concrete example, suppose a user is looking for lunch in a tourist area. The user launches the app and searches for nearby restaurants, and the app provides information on the congestion status of nearby establishments and any special offers. In this case, the user's device can present the information clearly using voice guidance and visual effects. For example, a notification might appear stating, "This restaurant is currently busy, but a table is expected to become available within 20 minutes."

[0243] When a user becomes interested in a particular store, they can check the special offers and select an electronic coupon within the app. The electronic coupon is displayed on the device as a QR code, which the user can then use at the store upon arrival.

[0244] At the store, staff scan the QR code from the user's device, verify that it is a valid coupon, and then provide the benefit or discount. The server integrates this usage data and analyzes store usage across the region to generate useful reports for local governments. These reports can be used to plan and measure the effectiveness of regional revitalization measures.

[0245] Therefore, this system efficiently manages store congestion information, enabling user convenience and contributing to increased customer traffic for stores. By utilizing this platform, economic activity among local small and medium-sized enterprises will be stimulated, and the attractiveness of the region will be enhanced.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The server receives congestion data from the stores. The server receives congestion information generated in real time from store sensors and staff input, and stores it in a database.

[0249] Step 2:

[0250] The user launches the app on their device. The device determines the user's current location and inputs the desired category and time slot.

[0251] Step 3:

[0252] The server filters nearby store information based on location data and criteria. It organizes information such as congestion levels, distance, and available benefits, and sends it to the user's terminal.

[0253] Step 4:

[0254] Users select a store they are interested in from the store information displayed on their device and check detailed congestion information and special offers.

[0255] Step 5:

[0256] Users select the electronic coupon they want to use and generate a QR code on their device. The coupon is saved within the app for easy redemption.

[0257] Step 6:

[0258] The user presents a QR code to store staff upon arrival. The store's terminal scans this QR code and verifies its validity.

[0259] Step 7:

[0260] The server aggregates coupon usage information and store usage data. Based on this, it analyzes usage trends and generates reports for each region.

[0261] Step 8:

[0262] Local governments will utilize the generated reports to help plan regional revitalization and tourism policies.

[0263] In this way, the entire system works in coordination, enhancing convenience for both users and stores, and contributing to the revitalization of the local economy.

[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] The challenge lies in improving store customer attraction while simultaneously providing users with highly convenient information by efficiently collecting and managing real-time store congestion information. Furthermore, it is necessary to effectively utilize related promotional information to stimulate local economic activity. Existing systems often provide inaccurate or delayed congestion information, leading to decreased user satisfaction.

[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 the occupancy status of people in a store as digital data, means for transferring the acquired occupancy status to a central information processing device, and means for storing and processing the acquired occupancy status in the central information processing device. This enables real-time management of store congestion information and rapid provision of information to users.

[0269] A "store" refers to a physical or virtual location where customers visit to use goods or services.

[0270] "Human presence status" refers to information indicating the number of people present in a specific location within a certain period of time, and how that number changes.

[0271] "Digital data" refers to information expressed in a format that can be processed by computers and electronic devices.

[0272] A "central information processing system" refers to a computer system that aggregates multiple data sets and manages them through calculations and recording.

[0273] "Benefit information" refers to information that promotes the use of a service, such as perks and discounts offered to users.

[0274] An "electronic discount voucher" refers to a digital coupon used to obtain discounts or benefits.

[0275] "User equipment" refers to electronic devices that users directly use to acquire, process, and display information.

[0276] A "report" refers to a document that summarizes the results of an analysis of specific data or activities.

[0277] "Voice guidance for terminology" refers to instructions and information provided through audio.

[0278] "Visual effects" refer to visual representations used to enhance the impression of information when it is seen.

[0279] This invention is a system for efficiently collecting store congestion information and providing users with that information quickly.

[0280] The server receives congestion information sent from stores in real time via web server software such as Apache or Nginx. This information is stored in a MySQL database, where data such as the number of customers, availability, and average dwell time are recorded in a structured manner. This allows the server to analyze congestion levels through various calculations and prepare for rapid information provision.

[0281] The terminal obtains the GPS location information by the user operating an application using a mobile communication terminal or a tablet. Based on this location information, it requests store information including the latest congestion situation from the server. The terminal uses development frameworks such as "Flutter" or "React Native" to visually display the congestion level and privilege information of the store on the screen. Furthermore, the information may be provided as voice guidance using text-to-speech software.

[0282] As a specific example, consider the case where a user is looking for a store for lunch in a busy street. The user launches the application and searches for nearby restaurants, and the congestion situation and privilege information of each store are shown on the displayed application screen. At this time, if the prompt text "Search for cafes around the current location and inform me of the congestion situation" is used, the user can efficiently receive the desired information.

[0283] Finally, when the user selects a specific store, an electronic coupon is displayed on the terminal and can be used when visiting the store. At the store, the staff uses a QR code reader to check the coupon. With this system, the store's ability to attract customers is improved, and a more user-friendly environment is provided for users.

[0284] The flow of the specific process in Example 1 will be described using FIG. 11.

[0285] Step 1:

[0286] Transmission of congestion information from the store

[0287] The staff of the store uses a dedicated management system to input data such as the number of customers in the store, the vacancy situation, and the average stay time. This information is transmitted to the server in real time via the Internet. The input is the actual congestion situation of the store, and the output is the digital-form congestion information sent to the server.

[0288] Step 2:

[0289] Data reception and recording on the server.

[0290] The server receives congestion information sent from the stores. Web server software such as "Apache" or "Nginx" enables this, and records the received data in a "MySQL" database. During the data recording process, the information is stored in an appropriate structure and indexes are added to speed up subsequent queries. The input is congestion information from the stores, and the output is structured information stored in the database.

[0291] Step 3:

[0292] Obtaining and requesting user information

[0293] The user launches the application on their device and uses GPS to obtain their current location. They also specify the service category they want to search for. The device uses this information to request nearby store information from the server. The input is the user's location and category information, and the output is the information request to the server.

[0294] Step 4:

[0295] Displaying store information on a terminal

[0296] The server queries the database for appropriate store information based on the user's request and sends it to the terminal. The terminal then uses tools such as Flutter or React Native to visually display store congestion status and special offers. The input is the store information sent from the server, and the output is the screen display on the user's terminal.

[0297] Step 5:

[0298] Selection of reward information and generation of electronic coupons

[0299] When a user selects a store they are interested in, they can check the special offers and choose an electronic coupon within the app. The device generates and displays the coupon as a QR code. The input is the user's selection of special offers, and the output is an electronic coupon in QR code format.

[0300] Step 6:

[0301] Use of electronic coupons at stores

[0302] Store staff scan the QR code displayed on the user's terminal with a dedicated reader to verify its validity. After verification, the benefits and discounts are applied. The input is the electronic coupon presented by the user, and the output is the sales information with the benefits applied.

[0303] (Application Example 1)

[0304] 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."

[0305] Modern consumers face challenges such as wasting time due to the inability to understand real-time congestion levels and the inability to check seating availability or special offers before visiting a facility. Furthermore, information related to the real world often lacks entertainment value and visual appeal. Additionally, providing data tailored to promoting customer acquisition for small and medium-sized enterprises in specific regions and revitalizing local markets is challenging.

[0306] 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.

[0307] In this invention, the server includes means for acquiring the congestion information of a store in digital form, means for an information processing device to present the congestion information using voice guidance and visual effects, and means for superimposing and displaying the congestion information on the visual information of the real world using augmented reality technology. As a result, users can intuitively grasp the congestion status and privilege information of the facility in real time, and it becomes possible to make an efficient visit plan. In addition, it is possible to provide information that is effectively useful for attracting customers in the business district and promoting regional development.

[0308] The "congestion information of a store" refers to real-time data such as the number of customers in a specific facility, the availability of seats, and the average stay time.

[0309] The "information processing device" refers to a combination of hardware and software for storing, processing, and analyzing data, such as a server or a cloud system.

[0310] The "voice guidance" refers to a system that provides congestion information and store information to users by voice.

[0311] The "visual effects" refer to display technologies and graphical effects for visually emphasizing and displaying congestion information and privilege information.

[0312] The "augmented reality technology" is a technology for superimposing digital information on real visual information, enabling users to obtain information while interacting with the surrounding environment.

[0313] The "electronic coupon" refers to a code or digital voucher provided in digital form and used to receive privileges and discounts at the target facility.

[0314] The "privilege information" refers to information presenting discounts, services, and other promotions that users can receive when using the facility.

[0315] "Usage data" refers to data that includes facility and user behavior and records of store usage, and is collected for the purpose of creating value through analysis.

[0316] A "report" refers to a document that analyzes usage data and proposes improvement measures for an organization or region based on the results.

[0317] To implement this invention, first, an information processing system is used to place a central server on a cloud platform and receive congestion information from each store via the network. The data is obtained from sensors and camera systems within the stores and aggregated on the server in real time as customer count and seating availability information. In this case, it is appropriate to use a server such as Amazon Web Services or Google Cloud Platform.

[0318] The server uses machine learning libraries such as TensorFlow to analyze the received data, predicting and analyzing congestion trends. The analysis results are immediately transferred to the user's smartphone app and presented as a visual and audio guide. The application should ideally be developed using cross-platform development tools such as React Native or Flutter. Through the app, users can check the congestion status of nearby stores, integrating it with the real world using AR (augmented reality) technology.

[0319] As an example, let's say a tourist uses their smartphone to check the congestion status of nearby restaurants. As the user scans the streetscape with their camera, the AR function overlays entertaining visual information, displaying it along with an audio guide saying, "This cafe is currently crowded, but a table is expected to become available within 15 minutes."

[0320] In addition, users can review digital reward information received within the app and generate and display electronic coupons on the screen as needed. Store staff then review these coupons and provide appropriate services or discounts. In particular, a generation AI model is used for coupon generation and reward information management.

[0321] An example of a prompt message is as follows:

[0322] "Users want to know how busy nearby cafes are. Please display the current availability and any available perks as information about that cafe."

[0323] "I'm looking for a restaurant for lunch in a tourist area. Please show me restaurants with seats available within 20 minutes and provide an electronic coupon."

[0324] This system allows users to efficiently plan their visits and contribute to revitalizing the use of local facilities.

[0325] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0326] Step 1:

[0327] The server receives real-time congestion information transmitted from each store. This input includes customer counts and seating availability information obtained from sensors and cameras within the stores. The server collects this data via a streaming API and stores it in a database.

[0328] Step 2:

[0329] The server uses machine learning algorithms to predict customer flow and seat availability based on accumulated congestion information. Here, the TensorFlow library is used to perform future predictions based on historical data. The output includes estimated seat availability and peak visit times.

[0330] Step 3:

[0331] The server receives the user's current location and desired category. Based on this, it selects congestion predictions and special offer information for nearby stores and sends them to the user's terminal. The terminal uses this as input and displays the results on the application screen using React Native.

[0332] Step 4:

[0333] The device uses its camera function to scan the real environment and overlays congestion information onto the real image using augmented reality (AR) technology. It performs actions to make the information visually easy for the user to understand and obtain.

[0334] Step 5:

[0335] Users view special offers related to stores they are interested in and generate electronic coupons. The terminal performs this generation process via an AI model and displays the electronic coupon as a QR code on its screen.

[0336] Step 6:

[0337] When a user visits a store, store staff scan the QR code displayed on the user's device to authenticate the benefit information. At this point, the server performs the authentication process and transmits the result to the store.

[0338] Step 7:

[0339] The server aggregates store and user usage data, performs statistical analysis, and generates reports to create information useful for revitalizing local facilities. This output is provided to local government agencies and other organizations.

[0340] 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.

[0341] This invention aims to further improve the user experience by integrating an emotion engine into conventional store information management systems. The emotion engine analyzes the user's emotional state based on input data obtained from the user, such as facial recognition, input behavior, and voice.

[0342] The server receives this data and uses an emotion engine to determine the user's psychological state. For example, it analyzes the user's satisfaction level and expectations based on their typing speed and force when entering a food review, or their facial expressions while using the service.

[0343] When a user launches the app on their device, the emotion engine recommends the most suitable stores and offers based on the user's state. The server uses the user's current location information to select stores that are within a reasonable distance and require minimal effort, and also uses emotion data to suggest services that match the user's mood. For example, if the system determines that the user is tired, it will recommend stores with a more relaxing atmosphere or stores that offer stress-relieving offers.

[0344] As a concrete example, consider a busy business traveler using the app during lunchtime. If the device detects that fatigue is reflected in the user's facial expression, the server will recommend a restaurant with a quiet and comfortable atmosphere. Furthermore, the electronic coupons offer perks such as "drink service" or "use of relaxing aromatherapy" to further enhance user satisfaction.

[0345] After a user visits a store, the emotion engine re-evaluates whether the suggested effect was achieved. This feedback is analyzed by the server to help improve future services. Stores can also use this data to gain a detailed understanding of user emotional changes and to understand potential customer needs, thereby improving the quality of their services.

[0346] In this way, this system, which incorporates an emotion engine, strengthens the link between user emotions and service experience, enabling personalized store recommendations and rewards tailored to individual needs. This allows for effective customer acquisition focused on the local community, contributing to the revitalization of the local economy.

[0347] The following describes the processing flow.

[0348] Step 1:

[0349] The user launches the app on their device, and emotional input data is collected along with location information. The device then uses its camera and microphone to send the user's facial expressions, voice tone, and other information to the emotion engine.

[0350] Step 2:

[0351] The emotion engine analyzes the user's emotions. Based on facial features and voice waveform data, the engine determines the user's current emotional state. This information is sent to the server as the user's psychological state.

[0352] Step 3:

[0353] The server combines location information and sentiment analysis results to recommend the most suitable stores and benefits. If the user wants to relax, stores with a quiet atmosphere or services that promote relaxation will be selected.

[0354] Step 4:

[0355] The terminal displays recommended store information and special offers to the user. The server also considers the store's congestion level and guides the user to the store with the shortest possible waiting time.

[0356] Step 5:

[0357] After the user selects a store and checks the benefits, an electronic coupon is generated based on the selected benefit information. The coupon is provided in the form of a QR code displayed on the terminal.

[0358] Step 6:

[0359] The user presents a QR code at their chosen store, which the store's terminal scans and verifies. The store then offers emotionally-driven rewards to improve user satisfaction.

[0360] Step 7:

[0361] After a user visits, feedback is sent to the server. The emotion engine then analyzes the user's emotions again, and their post-visit state is evaluated. This information is stored as data for service improvement.

[0362] Step 8:

[0363] The server collects all user data and analyzes regional usage trends. The analysis results are provided to stores and local governments and used to improve service quality and implement regional revitalization measures.

[0364] (Example 2)

[0365] 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".

[0366] Traditional store recommendation systems primarily rely on recommendations based on the user's physical location, which has the drawback of not adequately considering the emotional and psychological states of individual users. As a result, they tend to provide uniform promotional information, failing to adequately contribute to improving the user experience or revitalizing the local economy.

[0367] 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.

[0368] In this invention, the server includes means for analyzing the user's emotional state, means for providing personalized store recommendations based on the analyzed emotional state, and means for collecting user feedback and storing it in a database for future service improvements. This enables store recommendations and the provision of benefits that correspond to the user's emotional state, thereby improving the user experience and stimulating the local economy.

[0369] "Congestion information" refers to data that shows the level of people gathered at a particular store or location, the length of queues, and other information indicating the dwell time of users.

[0370] A "central server" is a centralized computer system for processing, storing, and managing data via the internet.

[0371] A "user terminal" is an electronic device used directly by the user, and includes devices such as smartphones and tablets.

[0372] "Benefit information" refers to additional value or discount information regarding products and services offered to users, and is provided in the form of electronic coupons, etc.

[0373] An "electronic coupon" is a digital coupon provided in digital format that grants the right to receive a discount or free provision of a specific service or product.

[0374] "Emotional state" refers to information that indicates the user's psychological and emotional state, and is analyzed based on digital data.

[0375] "Personalized store recommendations" refer to a personalized store selection and referral process based on the user's individual behavioral characteristics and emotional state.

[0376] "User feedback" refers to data that reflects users' impressions and opinions on the services and recommendations provided, and is used to improve those services.

[0377] This invention is a system that analyzes a user's emotional state and provides personalized store recommendations and special offers based on that analysis. The system primarily utilizes a user terminal, a central server, and an emotion analysis engine to achieve the functions described in the claims.

[0378] The user launches a dedicated application on a device such as a smartphone or tablet. The device uses its camera, microphone, and touch sensors to collect data such as the user's facial expressions, voice, and keyboard input patterns. This emotional data is temporarily stored on the device and securely transmitted to a central server using encryption technology.

[0379] The server passes the received data to the sentiment analysis engine. The sentiment analysis engine uses machine learning algorithms to quantify the user's emotional state. This analysis incorporates a generative AI model that leverages past data and learning to more accurately determine the emotional state.

[0380] The server then uses the analysis results to select the most suitable stores and offers for the user. This selection process takes into account the user's current location and emotional state, resulting in personalized recommendations. The selected store and offer information is sent to the device and displayed to the user in an immediately usable format.

[0381] For example, if a user on a business trip is using the app and facial analysis detects signs of fatigue, the server will recommend a quiet and relaxing restaurant. The perks offered may include services such as complimentary drinks or the use of relaxing aromatherapy.

[0382] This system collects user feedback and uses it to improve future services, thereby contributing to an enhanced user experience.

[0383] An example of a prompt message might be, "Based on the user's sentiment data, recommend the best store and benefits."

[0384] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0385] Step 1:

[0386] The user launches the app on their device. The device uses its camera, microphone, and touch sensors to collect the user's facial expressions, voice, and keyboard input patterns. This data is temporarily stored on the device as input. Specifically, facial recognition software analyzes the user's image, and voice recognition software analyzes the tone and speed of their voice. The output is quantified data that suggests the user's emotions.

[0387] Step 2:

[0388] The terminal securely transmits the collected data to a central server using encryption technology. The input includes encrypted emotional data, which is securely sent to the server over the internet. This process utilizes specific data transfer protocols to ensure data integrity.

[0389] Step 3:

[0390] The server decrypts the received encrypted data and passes it to the sentiment analysis engine. This engine uses the input data to utilize a generative AI model to analyze the user's emotional state. Specifically, a machine learning algorithm quantifies the emotions, and an emotion score is generated as output.

[0391] Step 4:

[0392] The server combines sentiment scores with the user's current location information to select the most suitable stores and offers. This process uses the analysis results and geographic information systems to generate personalized recommendation lists. The output is a personalized list of stores and offers.

[0393] Step 5:

[0394] The server sends the generated store list and special offer information to the terminal. The terminal displays the data it has received as input to the user. Specifically, the user interface organizes the recommendation information and displays it on the screen. The output is a visual presentation for the user to take action.

[0395] Step 6:

[0396] After the user visits a recommended store, the terminal collects sentiment data again and sends feedback to the server. The input includes the newly collected sentiment data, which is then sent back to the server. This feedback is used to improve the accuracy of future analyses.

[0397] Step 7:

[0398] The server analyzes the collected feedback data and stores it in a database. This data is used for the continuous training of machine learning and helps improve recommendation algorithms. Specifically, the database management system detects certain patterns and trends and compiles them into reports.

[0399] (Application Example 2)

[0400] 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."

[0401] Conventional store information management systems were limited to providing congestion information and special offers, and were unable to personalize services that took into account the emotional state of the user. As a result, it was difficult to improve user satisfaction and propose the most suitable facilities and services. This invention aims to solve these problems and enable the provision of advanced services based on the emotions of the user.

[0402] 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.

[0403] In this invention, the server includes means for determining the user's emotional state using an emotion analysis engine, means for capturing the user's facial expressions using image recognition technology and linking this to emotion analysis, and means for recommending appropriate facilities based on the user's location information and emotional state. This makes it possible to recommend the optimal store, rest area, and service in real time according to the user's emotional state, thereby improving the quality of the user's experience.

[0404] A "device for acquiring congestion information in stores in digital format" is a device that electronically detects the congestion level within a facility and acquires that information as digital data.

[0405] A "centralized processing unit" is a central computer that receives information collected from multiple terminals in a unified manner, and stores and processes that information.

[0406] "User's device" refers to a mobile information device such as a smartphone or tablet that the user carries with them.

[0407] An "emotion analysis engine" is a software component that analyzes a user's psychological state based on data acquired from them.

[0408] A "device that captures a user's facial expressions using image recognition technology and uses that information for emotion analysis" is a device equipped with technology that uses cameras and sensors to identify a user's facial expressions and uses that information for emotion analysis.

[0409] A "device that recommends appropriate facilities based on the user's location information and emotional state" is a system that combines the user's current location with an analysis of their emotions to suggest the most suitable place or facility for the user.

[0410] A "digital coupon" is an electronic voucher containing discounts or special offers that is distributed electronically.

[0411] A "report generation device" is a device that analyzes facility and user usage information and uses that information to create detailed reports.

[0412] This invention is a system that personalizes facilities and services based on the user's emotional state. The server uses an emotion analysis engine to analyze the user's emotions from their facial expressions, keyboard typing speed, voice, etc. In this process, OpenCV is introduced as an image recognition technology to identify facial expressions and provide data for emotion analysis. In addition, location information is obtained from the user's terminal and used to select recommended facilities. Based on these analysis results, the server recommends appropriate cafes or rest areas where the user can relax.

[0413] Furthermore, the server uses an API to retrieve the latest congestion and special offer information from facilities and generates digital coupons based on that information. These digital coupons are sent to the user's device, and when the user presents them, the authentication process at the facility is completed. The results of the facility's service provision are re-evaluated, and user feedback is used to improve future services. A possible prompt for users might be: "Please recommend a relaxing store for a tired user."

[0414] As a concrete example, consider a scenario where a customer visiting a shopping mall is fatigued from prolonged shopping. The server can detect this state using facial recognition and location information, recommend a nearby comfortable cafe, and provide a digital coupon for a free drink. In this way, the present invention can provide information services based on emotional states and improve customer satisfaction.

[0415] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0416] Step 1:

[0417] The device captures the user's facial expressions with a camera and performs face detection using OpenCV. The input is image data from the camera, and the output is feature data related to facial expressions. This feature data serves as basic information to be sent to the emotion analysis engine.

[0418] Step 2:

[0419] The server receives facial feature data transmitted from the terminal and analyzes the user's emotions using an emotion analysis engine. The input is facial feature data, and the output is the user's emotional state (e.g., fatigue, satisfaction, stress). Based on this emotional state, the server prepares recommended services.

[0420] Step 3:

[0421] The server obtains location information from the terminal and determines the user's current location. The input is location data, and the output is information about the facility where the user is located and its surroundings. Based on this location information, the server selects the most suitable store.

[0422] Step 4:

[0423] The server recommends the most suitable facility for the user, taking into account both their emotional state and location. The input is the user's emotional state and location, and the output is a list of recommended facilities. For example, it might select and suggest a relaxing cafe or a comfortable rest area.

[0424] Step 5:

[0425] The server retrieves information about benefits related to selected facilities and services via an API and generates digital coupons based on that information. The input is information about recommended facilities and benefits, and the output is an electronically issued digital coupon. This coupon may include benefits such as free drinks or relaxation items.

[0426] Step 6:

[0427] The terminal displays digital coupons received from the server to the user. The input is digital coupon information, and the output is a display of coupon data in a format usable by the user. Users can use the displayed coupons to receive discounts and benefits at stores and services.

[0428] Step 7:

[0429] After a user visits a store, the terminal sends feedback to the server to evaluate the effectiveness of the suggested services and benefits. The input is user feedback data, and the output is analysis data for the server. Based on this feedback, the server makes improvements to future services.

[0430] 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.

[0431] 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.

[0432] 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.

[0433] [Third Embodiment]

[0434] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0435] 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.

[0436] 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).

[0437] 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.

[0438] 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.

[0439] 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).

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] 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.

[0445] 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".

[0446] This invention provides a system for collecting store congestion information in digital format and processing and storing it on a central server. The server receives congestion information transmitted from each store in real time and records it in a database. The congestion information includes the number of customers, seat availability, and average dwell time. This allows the server to quickly present congestion information to users when they access the site.

[0447] Users launch the application using their mobile devices or tablets and retrieve store information based on their current location and desired service category. The device communicates with the server to display a screen that visually shows the congestion levels and available benefits of nearby stores. Based on this information, users can view details of stores of interest and efficiently plan their visits.

[0448] As a concrete example, suppose a user is looking for lunch in a tourist area. The user launches the app and searches for nearby restaurants, and the app provides information on the congestion status of nearby establishments and any special offers. In this case, the user's device can present the information clearly using voice guidance and visual effects. For example, a notification might appear stating, "This restaurant is currently busy, but a table is expected to become available within 20 minutes."

[0449] When a user becomes interested in a particular store, they can check the special offers and select an electronic coupon within the app. The electronic coupon is displayed on the device as a QR code, which the user can then use at the store upon arrival.

[0450] At the store, staff scan the QR code from the user's device, verify that it is a valid coupon, and then provide the benefit or discount. The server integrates this usage data and analyzes store usage across the region to generate useful reports for local governments. These reports can be used to plan and measure the effectiveness of regional revitalization measures.

[0451] Therefore, this system efficiently manages store congestion information, enabling user convenience and contributing to increased customer traffic for stores. By utilizing this platform, economic activity among local small and medium-sized enterprises will be stimulated, and the attractiveness of the region will be enhanced.

[0452] The following describes the processing flow.

[0453] Step 1:

[0454] The server receives congestion data from the stores. The server receives congestion information generated in real time from store sensors and staff input, and stores it in a database.

[0455] Step 2:

[0456] The user launches the app on their device. The device determines the user's current location and inputs the desired category and time slot.

[0457] Step 3:

[0458] The server filters nearby store information based on location data and criteria. It organizes information such as congestion levels, distance, and available benefits, and sends it to the user's terminal.

[0459] Step 4:

[0460] Users select a store they are interested in from the store information displayed on their device and check detailed congestion information and special offers.

[0461] Step 5:

[0462] Users select the electronic coupon they want to use and generate a QR code on their device. The coupon is saved within the app for easy redemption.

[0463] Step 6:

[0464] The user presents a QR code to store staff upon arrival. The store's terminal scans this QR code and verifies its validity.

[0465] Step 7:

[0466] The server aggregates coupon usage information and store usage data. Based on this, it analyzes usage trends and generates reports for each region.

[0467] Step 8:

[0468] Local governments will utilize the generated reports to help plan regional revitalization and tourism policies.

[0469] In this way, the entire system works in coordination, enhancing convenience for both users and stores, and contributing to the revitalization of the local economy.

[0470] (Example 1)

[0471] 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."

[0472] The challenge lies in improving store customer attraction while simultaneously providing users with highly convenient information by efficiently collecting and managing real-time store congestion information. Furthermore, it is necessary to effectively utilize related promotional information to stimulate local economic activity. Existing systems often provide inaccurate or delayed congestion information, leading to decreased user satisfaction.

[0473] 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.

[0474] In this invention, the server includes means for acquiring the occupancy status of people in a store as digital data, means for transferring the acquired occupancy status to a central information processing device, and means for storing and processing the acquired occupancy status in the central information processing device. This enables real-time management of store congestion information and rapid provision of information to users.

[0475] A "store" refers to a physical or virtual location where customers visit to use goods or services.

[0476] "Human presence status" refers to information indicating the number of people present in a specific location within a certain period of time, and how that number changes.

[0477] "Digital data" refers to information expressed in a format that can be processed by computers and electronic devices.

[0478] A "central information processing system" refers to a computer system that aggregates multiple data sets and manages them through calculations and recording.

[0479] "Benefit information" refers to information that promotes the use of a service, such as perks and discounts offered to users.

[0480] An "electronic discount voucher" refers to a digital coupon used to obtain discounts or benefits.

[0481] "User equipment" refers to electronic devices that users directly use to acquire, process, and display information.

[0482] A "report" refers to a document that summarizes the results of an analysis of specific data or activities.

[0483] "Voice guidance for terminology" refers to instructions and information provided through audio.

[0484] "Visual effects" refer to visual representations used to enhance the impression of information when it is seen.

[0485] This invention is a system for efficiently collecting store congestion information and providing users with that information quickly.

[0486] The server receives congestion information sent from stores in real time via web server software such as Apache or Nginx. This information is stored in a MySQL database, where data such as the number of customers, availability, and average dwell time are recorded in a structured manner. This allows the server to analyze congestion levels through various calculations and prepare for rapid information provision.

[0487] The device obtains GPS location information when the user operates an application using a mobile communication terminal or tablet. Based on this location information, it requests store information, including recent congestion levels, from the server. The device uses development frameworks such as "Flutter" or "React Native" to visually display store congestion levels and special offers on the screen. Furthermore, this information may be provided as voice guidance using speech synthesis software.

[0488] As a concrete example, consider a user looking for a restaurant for lunch in a busy downtown area. The user launches the application and searches for nearby restaurants. The displayed app screen shows the congestion status and special offers for each restaurant. In this case, using a prompt such as "Search for cafes near my current location and let me know their congestion status" allows the user to efficiently receive the information they need.

[0489] When a user finally selects a specific store, an electronic coupon is displayed on their terminal and becomes available for use upon arrival. At the store, staff verify the coupon using a QR code reader. This system improves the store's ability to attract customers and provides a more user-friendly environment.

[0490] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0491] Step 1:

[0492] Sending congestion information from stores

[0493] Store staff use a dedicated management system to input data such as the number of customers in the store, seating availability, and average dwell time. This information is transmitted to a server in real time via the internet. The input represents the actual congestion level of the store, while the output is digital congestion information sent to the server.

[0494] Step 2:

[0495] Data reception and recording on the server.

[0496] The server receives congestion information sent from the stores. Web server software such as "Apache" or "Nginx" enables this, and records the received data in a "MySQL" database. During the data recording process, the information is stored in an appropriate structure and indexes are added to speed up subsequent queries. The input is congestion information from the stores, and the output is structured information stored in the database.

[0497] Step 3:

[0498] Obtaining and requesting user information

[0499] The user launches the application on their device and uses GPS to obtain their current location. They also specify the service category they want to search for. The device uses this information to request nearby store information from the server. The input is the user's location and category information, and the output is the information request to the server.

[0500] Step 4:

[0501] Displaying store information on a terminal

[0502] The server queries the database for appropriate store information based on the user's request and sends it to the terminal. The terminal then uses tools such as Flutter or React Native to visually display store congestion status and special offers. The input is the store information sent from the server, and the output is the screen display on the user's terminal.

[0503] Step 5:

[0504] Selection of reward information and generation of electronic coupons

[0505] When a user selects a store they are interested in, they can check the special offers and choose an electronic coupon within the app. The device generates and displays the coupon as a QR code. The input is the user's selection of special offers, and the output is an electronic coupon in QR code format.

[0506] Step 6:

[0507] Use of electronic coupons at stores

[0508] Store staff scan the QR code displayed on the user's terminal with a dedicated reader to verify its validity. After verification, the benefits and discounts are applied. The input is the electronic coupon presented by the user, and the output is the sales information with the benefits applied.

[0509] (Application Example 1)

[0510] 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."

[0511] Modern consumers face challenges such as wasting time due to the inability to understand real-time congestion levels and the inability to check seating availability or special offers before visiting a facility. Furthermore, information related to the real world often lacks entertainment value and visual appeal. Additionally, providing data tailored to promoting customer acquisition for small and medium-sized enterprises in specific regions and revitalizing local markets is challenging.

[0512] 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.

[0513] In this invention, the server includes means for acquiring store congestion information in digital format, means for an information processing device to present congestion information using audio guidance and visual effects, and means for overlaying congestion information onto real-world visual information using augmented reality technology. This allows users to intuitively grasp the congestion status and special offers of facilities in real time, enabling them to plan efficient visits. Furthermore, it enables the provision of information that is effectively useful for attracting customers to a trade area and promoting regional development.

[0514] "Store congestion information" refers to real-time data such as the number of customers, seat availability, and average stay time within a specific facility.

[0515] An "information processing device" refers to a combination of hardware and software, such as servers and cloud systems, used for storing, processing, and analyzing data.

[0516] "Audio guide" refers to a system that provides users with information such as congestion levels and store information via audio.

[0517] "Visual effects" refers to display technologies and graphical effects used to visually highlight and display information such as congestion levels and special offers.

[0518] Augmented reality technology is a technique that overlays digital information onto real-world visual information, enabling users to obtain information while interacting with their surroundings.

[0519] An "electronic coupon" refers to a code or digital voucher provided in digital format that is used to receive benefits or discounts at participating establishments.

[0520] "Special offers" refers to information that presents discounts, services, and other promotions that users can receive when using a facility.

[0521] "Usage data" refers to data that includes facility and user behavior and records of store usage, and is collected for the purpose of creating value through analysis.

[0522] A "report" refers to a document that analyzes usage data and proposes improvement measures for an organization or region based on the results.

[0523] To implement this invention, first, an information processing system is used to place a central server on a cloud platform and receive congestion information from each store via the network. The data is obtained from sensors and camera systems within the stores and aggregated on the server in real time as customer count and seating availability information. In this case, it is appropriate to use a server such as Amazon Web Services or Google Cloud Platform.

[0524] The server uses machine learning libraries such as TensorFlow to analyze the received data, predicting and analyzing congestion trends. The analysis results are immediately transferred to the user's smartphone app and presented as a visual and audio guide. The application should ideally be developed using cross-platform development tools such as React Native or Flutter. Through the app, users can check the congestion status of nearby stores, integrating it with the real world using AR (augmented reality) technology.

[0525] As an example, let's say a tourist uses their smartphone to check the congestion status of nearby restaurants. As the user scans the streetscape with their camera, the AR function overlays entertaining visual information, displaying it along with an audio guide saying, "This cafe is currently crowded, but a table is expected to become available within 15 minutes."

[0526] In addition, users can review digital reward information received within the app and generate and display electronic coupons on the screen as needed. Store staff then review these coupons and provide appropriate services or discounts. In particular, a generation AI model is used for coupon generation and reward information management.

[0527] An example of a prompt message is as follows:

[0528] "Users want to know how busy nearby cafes are. Please display the current availability and any available perks as information about that cafe."

[0529] "I'm looking for a restaurant for lunch in a tourist area. Please show me restaurants with seats available within 20 minutes and provide an electronic coupon."

[0530] This system allows users to efficiently plan their visits and contribute to revitalizing the use of local facilities.

[0531] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0532] Step 1:

[0533] The server receives real-time congestion information transmitted from each store. This input includes customer counts and seating availability information obtained from sensors and cameras within the stores. The server collects this data via a streaming API and stores it in a database.

[0534] Step 2:

[0535] The server uses machine learning algorithms to predict customer flow and seat availability based on accumulated congestion information. Here, the TensorFlow library is used to perform future predictions based on historical data. The output includes estimated seat availability and peak visit times.

[0536] Step 3:

[0537] The server receives the user's current location and desired category. Based on this, it selects congestion predictions and special offer information for nearby stores and sends them to the user's terminal. The terminal uses this as input and displays the results on the application screen using React Native.

[0538] Step 4:

[0539] The device uses its camera function to scan the real environment and overlays congestion information onto the real image using augmented reality (AR) technology. It performs actions to make the information visually easy for the user to understand and obtain.

[0540] Step 5:

[0541] Users view special offers related to stores they are interested in and generate electronic coupons. The terminal performs this generation process via an AI model and displays the electronic coupon as a QR code on its screen.

[0542] Step 6:

[0543] When a user visits a store, store staff scan the QR code displayed on the user's device to authenticate the benefit information. At this point, the server performs the authentication process and transmits the result to the store.

[0544] Step 7:

[0545] The server aggregates store and user usage data, performs statistical analysis, and generates reports to create information useful for revitalizing local facilities. This output is provided to local government agencies and other organizations.

[0546] 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.

[0547] This invention aims to further improve the user experience by integrating an emotion engine into conventional store information management systems. The emotion engine analyzes the user's emotional state based on input data obtained from the user, such as facial recognition, input behavior, and voice.

[0548] The server receives this data and uses an emotion engine to determine the user's psychological state. For example, it analyzes the user's satisfaction level and expectations based on their typing speed and force when entering a food review, or their facial expressions while using the service.

[0549] When a user launches the app on their device, the emotion engine recommends the most suitable stores and offers based on the user's state. The server uses the user's current location information to select stores that are within a reasonable distance and require minimal effort, and also uses emotion data to suggest services that match the user's mood. For example, if the system determines that the user is tired, it will recommend stores with a more relaxing atmosphere or stores that offer stress-relieving offers.

[0550] As a concrete example, consider a busy business traveler using the app during lunchtime. If the device detects that fatigue is reflected in the user's facial expression, the server will recommend a restaurant with a quiet and comfortable atmosphere. Furthermore, the electronic coupons offer perks such as "drink service" or "use of relaxing aromatherapy" to further enhance user satisfaction.

[0551] After a user visits a store, the emotion engine re-evaluates whether the suggested effect was achieved. This feedback is analyzed by the server to help improve future services. Stores can also use this data to gain a detailed understanding of user emotional changes and to understand potential customer needs, thereby improving the quality of their services.

[0552] In this way, this system, which incorporates an emotion engine, strengthens the link between user emotions and service experience, enabling personalized store recommendations and rewards tailored to individual needs. This allows for effective customer acquisition focused on the local community, contributing to the revitalization of the local economy.

[0553] The following describes the processing flow.

[0554] Step 1:

[0555] The user launches the app on their device, and emotional input data is collected along with location information. The device then uses its camera and microphone to send the user's facial expressions, voice tone, and other information to the emotion engine.

[0556] Step 2:

[0557] The emotion engine analyzes the user's emotions. Based on facial features and voice waveform data, the engine determines the user's current emotional state. This information is sent to the server as the user's psychological state.

[0558] Step 3:

[0559] The server combines location information and sentiment analysis results to recommend the most suitable stores and benefits. If the user wants to relax, stores with a quiet atmosphere or services that promote relaxation will be selected.

[0560] Step 4:

[0561] The terminal displays recommended store information and special offers to the user. The server also considers the store's congestion level and guides the user to the store with the shortest possible waiting time.

[0562] Step 5:

[0563] After the user selects a store and checks the benefits, an electronic coupon is generated based on the selected benefit information. The coupon is provided in the form of a QR code displayed on the terminal.

[0564] Step 6:

[0565] The user presents a QR code at their chosen store, which the store's terminal scans and verifies. The store then offers emotionally-driven rewards to improve user satisfaction.

[0566] Step 7:

[0567] After a user visits, feedback is sent to the server. The emotion engine then analyzes the user's emotions again, and their post-visit state is evaluated. This information is stored as data for service improvement.

[0568] Step 8:

[0569] The server collects all user data and analyzes regional usage trends. The analysis results are provided to stores and local governments and used to improve service quality and implement regional revitalization measures.

[0570] (Example 2)

[0571] 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."

[0572] Traditional store recommendation systems primarily rely on recommendations based on the user's physical location, which has the drawback of not adequately considering the emotional and psychological states of individual users. As a result, they tend to provide uniform promotional information, failing to adequately contribute to improving the user experience or revitalizing the local economy.

[0573] 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.

[0574] In this invention, the server includes means for analyzing the user's emotional state, means for providing personalized store recommendations based on the analyzed emotional state, and means for collecting user feedback and storing it in a database for future service improvements. This enables store recommendations and the provision of benefits that correspond to the user's emotional state, thereby improving the user experience and stimulating the local economy.

[0575] "Congestion information" refers to data that shows the level of people gathered at a particular store or location, the length of queues, and other information indicating the dwell time of users.

[0576] A "central server" is a centralized computer system for processing, storing, and managing data via the internet.

[0577] A "user terminal" is an electronic device used directly by the user, and includes devices such as smartphones and tablets.

[0578] "Benefit information" refers to additional value or discount information regarding products and services offered to users, and is provided in the form of electronic coupons, etc.

[0579] An "electronic coupon" is a digital coupon provided in digital format that grants the right to receive a discount or free provision of a specific service or product.

[0580] "Emotional state" refers to information that indicates the user's psychological and emotional state, and is analyzed based on digital data.

[0581] "Personalized store recommendations" refer to a personalized store selection and referral process based on the user's individual behavioral characteristics and emotional state.

[0582] "User feedback" refers to data that reflects users' impressions and opinions on the services and recommendations provided, and is used to improve those services.

[0583] This invention is a system that analyzes a user's emotional state and provides personalized store recommendations and special offers based on that analysis. The system primarily utilizes a user terminal, a central server, and an emotion analysis engine to achieve the functions described in the claims.

[0584] The user launches a dedicated application on a device such as a smartphone or tablet. The device uses its camera, microphone, and touch sensors to collect data such as the user's facial expressions, voice, and keyboard input patterns. This emotional data is temporarily stored on the device and securely transmitted to a central server using encryption technology.

[0585] The server passes the received data to the sentiment analysis engine. The sentiment analysis engine uses machine learning algorithms to quantify the user's emotional state. This analysis incorporates a generative AI model that leverages past data and learning to more accurately determine the emotional state.

[0586] The server then uses the analysis results to select the most suitable stores and offers for the user. This selection process takes into account the user's current location and emotional state, resulting in personalized recommendations. The selected store and offer information is sent to the device and displayed to the user in an immediately usable format.

[0587] For example, if a user on a business trip is using the app and facial analysis detects signs of fatigue, the server will recommend a quiet and relaxing restaurant. The perks offered may include services such as complimentary drinks or the use of relaxing aromatherapy.

[0588] This system collects user feedback and uses it to improve future services, thereby contributing to an enhanced user experience.

[0589] An example of a prompt message might be, "Based on the user's sentiment data, recommend the best store and benefits."

[0590] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0591] Step 1:

[0592] The user launches the app on their device. The device uses its camera, microphone, and touch sensors to collect the user's facial expressions, voice, and keyboard input patterns. This data is temporarily stored on the device as input. Specifically, facial recognition software analyzes the user's image, and voice recognition software analyzes the tone and speed of their voice. The output is quantified data that suggests the user's emotions.

[0593] Step 2:

[0594] The terminal securely transmits the collected data to a central server using encryption technology. The input includes encrypted emotional data, which is securely sent to the server over the internet. This process utilizes specific data transfer protocols to ensure data integrity.

[0595] Step 3:

[0596] The server decrypts the received encrypted data and passes it to the sentiment analysis engine. This engine uses the input data to utilize a generative AI model to analyze the user's emotional state. Specifically, a machine learning algorithm quantifies the emotions, and an emotion score is generated as output.

[0597] Step 4:

[0598] The server combines sentiment scores with the user's current location information to select the most suitable stores and offers. This process uses the analysis results and geographic information systems to generate personalized recommendation lists. The output is a personalized list of stores and offers.

[0599] Step 5:

[0600] The server sends the generated store list and special offer information to the terminal. The terminal displays the data it has received as input to the user. Specifically, the user interface organizes the recommendation information and displays it on the screen. The output is a visual presentation for the user to take action.

[0601] Step 6:

[0602] After the user visits a recommended store, the terminal collects sentiment data again and sends feedback to the server. The input includes the newly collected sentiment data, which is then sent back to the server. This feedback is used to improve the accuracy of future analyses.

[0603] Step 7:

[0604] The server analyzes the collected feedback data and stores it in a database. This data is used for the continuous training of machine learning and helps improve recommendation algorithms. Specifically, the database management system detects certain patterns and trends and compiles them into reports.

[0605] (Application Example 2)

[0606] 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."

[0607] Conventional store information management systems were limited to providing congestion information and special offers, and were unable to personalize services that took into account the emotional state of the user. As a result, it was difficult to improve user satisfaction and propose the most suitable facilities and services. This invention aims to solve these problems and enable the provision of advanced services based on the emotions of the user.

[0608] 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.

[0609] In this invention, the server includes means for determining the user's emotional state using an emotion analysis engine, means for capturing the user's facial expressions using image recognition technology and linking this to emotion analysis, and means for recommending appropriate facilities based on the user's location information and emotional state. This makes it possible to recommend the optimal store, rest area, and service in real time according to the user's emotional state, thereby improving the quality of the user's experience.

[0610] A "device for acquiring congestion information in stores in digital format" is a device that electronically detects the congestion level within a facility and acquires that information as digital data.

[0611] A "centralized processing unit" is a central computer that receives information collected from multiple terminals in a unified manner, and stores and processes that information.

[0612] "User's device" refers to a mobile information device such as a smartphone or tablet that the user carries with them.

[0613] An "emotion analysis engine" is a software component that analyzes a user's psychological state based on data acquired from them.

[0614] A "device that captures a user's facial expressions using image recognition technology and uses that information for emotion analysis" is a device equipped with technology that uses cameras and sensors to identify a user's facial expressions and uses that information for emotion analysis.

[0615] A "device that recommends appropriate facilities based on the user's location information and emotional state" is a system that combines the user's current location with an analysis of their emotions to suggest the most suitable place or facility for the user.

[0616] A "digital coupon" is an electronic voucher containing discounts or special offers that is distributed electronically.

[0617] A "report generation device" is a device that analyzes facility and user usage information and uses that information to create detailed reports.

[0618] This invention is a system that personalizes facilities and services based on the user's emotional state. The server uses an emotion analysis engine to analyze the user's emotions from their facial expressions, keyboard typing speed, voice, etc. In this process, OpenCV is introduced as an image recognition technology to identify facial expressions and provide data for emotion analysis. In addition, location information is obtained from the user's terminal and used to select recommended facilities. Based on these analysis results, the server recommends appropriate cafes or rest areas where the user can relax.

[0619] Furthermore, the server uses an API to retrieve the latest congestion and special offer information from facilities and generates digital coupons based on that information. These digital coupons are sent to the user's device, and when the user presents them, the authentication process at the facility is completed. The results of the facility's service provision are re-evaluated, and user feedback is used to improve future services. A possible prompt for users might be: "Please recommend a relaxing store for a tired user."

[0620] As a concrete example, consider a scenario where a customer visiting a shopping mall is fatigued from prolonged shopping. The server can detect this state using facial recognition and location information, recommend a nearby comfortable cafe, and provide a digital coupon for a free drink. In this way, the present invention can provide information services based on emotional states and improve customer satisfaction.

[0621] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0622] Step 1:

[0623] The device captures the user's facial expressions with a camera and performs face detection using OpenCV. The input is image data from the camera, and the output is feature data related to facial expressions. This feature data serves as basic information to be sent to the emotion analysis engine.

[0624] Step 2:

[0625] The server receives facial feature data transmitted from the terminal and analyzes the user's emotions using an emotion analysis engine. The input is facial feature data, and the output is the user's emotional state (e.g., fatigue, satisfaction, stress). Based on this emotional state, the server prepares recommended services.

[0626] Step 3:

[0627] The server obtains location information from the terminal and determines the user's current location. The input is location data, and the output is information about the facility where the user is located and its surroundings. Based on this location information, the server selects the most suitable store.

[0628] Step 4:

[0629] The server recommends the most suitable facility for the user, taking into account both their emotional state and location. The input is the user's emotional state and location, and the output is a list of recommended facilities. For example, it might select and suggest a relaxing cafe or a comfortable rest area.

[0630] Step 5:

[0631] The server retrieves information about benefits related to selected facilities and services via an API and generates digital coupons based on that information. The input is information about recommended facilities and benefits, and the output is an electronically issued digital coupon. This coupon may include benefits such as free drinks or relaxation items.

[0632] Step 6:

[0633] The terminal displays digital coupons received from the server to the user. The input is digital coupon information, and the output is a display of coupon data in a format usable by the user. Users can use the displayed coupons to receive discounts and benefits at stores and services.

[0634] Step 7:

[0635] After a user visits a store, the terminal sends feedback to the server to evaluate the effectiveness of the suggested services and benefits. The input is user feedback data, and the output is analysis data for the server. Based on this feedback, the server makes improvements to future services.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] [Fourth Embodiment]

[0640] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0641] 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.

[0642] 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).

[0643] 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.

[0644] 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.

[0645] 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).

[0646] 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.

[0647] 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.

[0648] 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.

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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".

[0653] This invention provides a system for collecting store congestion information in digital format and processing and storing it on a central server. The server receives congestion information transmitted from each store in real time and records it in a database. The congestion information includes the number of customers, seat availability, and average dwell time. This allows the server to quickly present congestion information to users when they access the site.

[0654] Users launch the application using their mobile devices or tablets and retrieve store information based on their current location and desired service category. The device communicates with the server to display a screen that visually shows the congestion levels and available benefits of nearby stores. Based on this information, users can view details of stores of interest and efficiently plan their visits.

[0655] As a concrete example, suppose a user is looking for lunch in a tourist area. The user launches the app and searches for nearby restaurants, and the app provides information on the congestion status of nearby establishments and any special offers. In this case, the user's device can present the information clearly using voice guidance and visual effects. For example, a notification might appear stating, "This restaurant is currently busy, but a table is expected to become available within 20 minutes."

[0656] When a user becomes interested in a particular store, they can check the special offers and select an electronic coupon within the app. The electronic coupon is displayed on the device as a QR code, which the user can then use at the store upon arrival.

[0657] At the store, staff scan the QR code from the user's device, verify that it is a valid coupon, and then provide the benefit or discount. The server integrates this usage data and analyzes store usage across the region to generate useful reports for local governments. These reports can be used to plan and measure the effectiveness of regional revitalization measures.

[0658] Therefore, this system efficiently manages store congestion information, enabling user convenience and contributing to increased customer traffic for stores. By utilizing this platform, economic activity among local small and medium-sized enterprises will be stimulated, and the attractiveness of the region will be enhanced.

[0659] The following describes the processing flow.

[0660] Step 1:

[0661] The server receives congestion data from the stores. The server receives congestion information generated in real time from store sensors and staff input, and stores it in a database.

[0662] Step 2:

[0663] The user launches the app on their device. The device determines the user's current location and inputs the desired category and time slot.

[0664] Step 3:

[0665] The server filters nearby store information based on location data and criteria. It organizes information such as congestion levels, distance, and available benefits, and sends it to the user's terminal.

[0666] Step 4:

[0667] Users select a store they are interested in from the store information displayed on their device and check detailed congestion information and special offers.

[0668] Step 5:

[0669] Users select the electronic coupon they want to use and generate a QR code on their device. The coupon is saved within the app for easy redemption.

[0670] Step 6:

[0671] The user presents a QR code to store staff upon arrival. The store's terminal scans this QR code and verifies its validity.

[0672] Step 7:

[0673] The server aggregates coupon usage information and store usage data. Based on this, it analyzes usage trends and generates reports for each region.

[0674] Step 8:

[0675] Local governments will utilize the generated reports to help plan regional revitalization and tourism policies.

[0676] In this way, the entire system works in coordination, enhancing convenience for both users and stores, and contributing to the revitalization of the local economy.

[0677] (Example 1)

[0678] 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".

[0679] The challenge lies in improving store customer attraction while simultaneously providing users with highly convenient information by efficiently collecting and managing real-time store congestion information. Furthermore, it is necessary to effectively utilize related promotional information to stimulate local economic activity. Existing systems often provide inaccurate or delayed congestion information, leading to decreased user satisfaction.

[0680] 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.

[0681] In this invention, the server includes means for acquiring the occupancy status of people in a store as digital data, means for transferring the acquired occupancy status to a central information processing device, and means for storing and processing the acquired occupancy status in the central information processing device. This enables real-time management of store congestion information and rapid provision of information to users.

[0682] A "store" refers to a physical or virtual location where customers visit to use goods or services.

[0683] "Human presence status" refers to information indicating the number of people present in a specific location within a certain period of time, and how that number changes.

[0684] "Digital data" refers to information expressed in a format that can be processed by computers and electronic devices.

[0685] A "central information processing system" refers to a computer system that aggregates multiple data sets and manages them through calculations and recording.

[0686] "Benefit information" refers to information that promotes the use of a service, such as perks and discounts offered to users.

[0687] An "electronic discount voucher" refers to a digital coupon used to obtain discounts or benefits.

[0688] "User equipment" refers to electronic devices that users directly use to acquire, process, and display information.

[0689] A "report" refers to a document that summarizes the results of an analysis of specific data or activities.

[0690] "Voice guidance for terminology" refers to instructions and information provided through audio.

[0691] "Visual effects" refer to visual representations used to enhance the impression of information when it is seen.

[0692] This invention is a system for efficiently collecting store congestion information and providing users with that information quickly.

[0693] The server receives congestion information sent from stores in real time via web server software such as Apache or Nginx. This information is stored in a MySQL database, where data such as the number of customers, availability, and average dwell time are recorded in a structured manner. This allows the server to analyze congestion levels through various calculations and prepare for rapid information provision.

[0694] The device obtains GPS location information when the user operates an application using a mobile communication terminal or tablet. Based on this location information, it requests store information, including recent congestion levels, from the server. The device uses development frameworks such as "Flutter" or "React Native" to visually display store congestion levels and special offers on the screen. Furthermore, this information may be provided as voice guidance using speech synthesis software.

[0695] As a concrete example, consider a user looking for a restaurant for lunch in a busy downtown area. The user launches the application and searches for nearby restaurants. The displayed app screen shows the congestion status and special offers for each restaurant. In this case, using a prompt such as "Search for cafes near my current location and let me know their congestion status" allows the user to efficiently receive the information they need.

[0696] When a user finally selects a specific store, an electronic coupon is displayed on their terminal and becomes available for use upon arrival. At the store, staff verify the coupon using a QR code reader. This system improves the store's ability to attract customers and provides a more user-friendly environment.

[0697] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0698] Step 1:

[0699] Sending congestion information from stores

[0700] Store staff use a dedicated management system to input data such as the number of customers in the store, seating availability, and average dwell time. This information is transmitted to a server in real time via the internet. The input represents the actual congestion level of the store, while the output is digital congestion information sent to the server.

[0701] Step 2:

[0702] Data reception and recording on the server.

[0703] The server receives congestion information sent from the stores. Web server software such as "Apache" or "Nginx" enables this, and records the received data in a "MySQL" database. During the data recording process, the information is stored in an appropriate structure and indexes are added to speed up subsequent queries. The input is congestion information from the stores, and the output is structured information stored in the database.

[0704] Step 3:

[0705] Obtaining and requesting user information

[0706] The user launches the application on their device and uses GPS to obtain their current location. They also specify the service category they want to search for. The device uses this information to request nearby store information from the server. The input is the user's location and category information, and the output is the information request to the server.

[0707] Step 4:

[0708] Displaying store information on a terminal

[0709] The server queries the database for appropriate store information based on the user's request and sends it to the terminal. The terminal then uses tools such as Flutter or React Native to visually display store congestion status and special offers. The input is the store information sent from the server, and the output is the screen display on the user's terminal.

[0710] Step 5:

[0711] Selection of reward information and generation of electronic coupons

[0712] When a user selects a store they are interested in, they can check the special offers and choose an electronic coupon within the app. The device generates and displays the coupon as a QR code. The input is the user's selection of special offers, and the output is an electronic coupon in QR code format.

[0713] Step 6:

[0714] Use of electronic coupons at stores

[0715] Store staff scan the QR code displayed on the user's terminal with a dedicated reader to verify its validity. After verification, the benefits and discounts are applied. The input is the electronic coupon presented by the user, and the output is the sales information with the benefits applied.

[0716] (Application Example 1)

[0717] 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".

[0718] Modern consumers face challenges such as wasting time due to the inability to understand real-time congestion levels and the inability to check seating availability or special offers before visiting a facility. Furthermore, information related to the real world often lacks entertainment value and visual appeal. Additionally, providing data tailored to promoting customer acquisition for small and medium-sized enterprises in specific regions and revitalizing local markets is challenging.

[0719] 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.

[0720] In this invention, the server includes means for acquiring store congestion information in digital format, means for an information processing device to present congestion information using audio guidance and visual effects, and means for overlaying congestion information onto real-world visual information using augmented reality technology. This allows users to intuitively grasp the congestion status and special offers of facilities in real time, enabling them to plan efficient visits. Furthermore, it enables the provision of information that is effectively useful for attracting customers to a trade area and promoting regional development.

[0721] "Store congestion information" refers to real-time data such as the number of customers, seat availability, and average stay time within a specific facility.

[0722] An "information processing device" refers to a combination of hardware and software, such as servers and cloud systems, used for storing, processing, and analyzing data.

[0723] "Audio guide" refers to a system that provides users with information such as congestion levels and store information via audio.

[0724] "Visual effects" refers to display technologies and graphical effects used to visually highlight and display information such as congestion levels and special offers.

[0725] Augmented reality technology is a technique that overlays digital information onto real-world visual information, enabling users to obtain information while interacting with their surroundings.

[0726] An "electronic coupon" refers to a code or digital voucher provided in digital format that is used to receive benefits or discounts at participating establishments.

[0727] "Special offers" refers to information that presents discounts, services, and other promotions that users can receive when using a facility.

[0728] "Usage data" refers to data that includes facility and user behavior and records of store usage, and is collected for the purpose of creating value through analysis.

[0729] A "report" refers to a document that analyzes usage data and proposes improvement measures for an organization or region based on the results.

[0730] To implement this invention, first, an information processing system is used to place a central server on a cloud platform and receive congestion information from each store via the network. The data is obtained from sensors and camera systems within the stores and aggregated on the server in real time as customer count and seating availability information. In this case, it is appropriate to use a server such as Amazon Web Services or Google Cloud Platform.

[0731] The server uses machine learning libraries such as TensorFlow to analyze the received data, predicting and analyzing congestion trends. The analysis results are immediately transferred to the user's smartphone app and presented as a visual and audio guide. The application should ideally be developed using cross-platform development tools such as React Native or Flutter. Through the app, users can check the congestion status of nearby stores, integrating it with the real world using AR (augmented reality) technology.

[0732] As an example, let's say a tourist uses their smartphone to check the congestion status of nearby restaurants. As the user scans the streetscape with their camera, the AR function overlays entertaining visual information, displaying it along with an audio guide saying, "This cafe is currently crowded, but a table is expected to become available within 15 minutes."

[0733] In addition, users can review digital reward information received within the app and generate and display electronic coupons on the screen as needed. Store staff then review these coupons and provide appropriate services or discounts. In particular, a generation AI model is used for coupon generation and reward information management.

[0734] An example of a prompt message is as follows:

[0735] "Users want to know how busy nearby cafes are. Please display the current availability and any available perks as information about that cafe."

[0736] "I'm looking for a restaurant for lunch in a tourist area. Please show me restaurants with seats available within 20 minutes and provide an electronic coupon."

[0737] This system allows users to efficiently plan their visits and contribute to revitalizing the use of local facilities.

[0738] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0739] Step 1:

[0740] The server receives real-time congestion information transmitted from each store. This input includes customer counts and seating availability information obtained from sensors and cameras within the stores. The server collects this data via a streaming API and stores it in a database.

[0741] Step 2:

[0742] The server uses machine learning algorithms to predict customer flow and seat availability based on accumulated congestion information. Here, the TensorFlow library is used to perform future predictions based on historical data. The output includes estimated seat availability and peak visit times.

[0743] Step 3:

[0744] The server receives the user's current location and desired category. Based on this, it selects congestion predictions and special offer information for nearby stores and sends them to the user's terminal. The terminal uses this as input and displays the results on the application screen using React Native.

[0745] Step 4:

[0746] The device uses its camera function to scan the real environment and overlays congestion information onto the real image using augmented reality (AR) technology. It performs actions to make the information visually easy for the user to understand and obtain.

[0747] Step 5:

[0748] Users view special offers related to stores they are interested in and generate electronic coupons. The terminal performs this generation process via an AI model and displays the electronic coupon as a QR code on its screen.

[0749] Step 6:

[0750] When a user visits a store, store staff scan the QR code displayed on the user's device to authenticate the benefit information. At this point, the server performs the authentication process and transmits the result to the store.

[0751] Step 7:

[0752] The server aggregates store and user usage data, performs statistical analysis, and generates reports to create information useful for revitalizing local facilities. This output is provided to local government agencies and other organizations.

[0753] 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.

[0754] This invention aims to further improve the user experience by integrating an emotion engine into conventional store information management systems. The emotion engine analyzes the user's emotional state based on input data obtained from the user, such as facial recognition, input behavior, and voice.

[0755] The server receives this data and uses an emotion engine to determine the user's psychological state. For example, it analyzes the user's satisfaction level and expectations based on their typing speed and force when entering a food review, or their facial expressions while using the service.

[0756] When a user launches the app on their device, the emotion engine recommends the most suitable stores and offers based on the user's state. The server uses the user's current location information to select stores that are within a reasonable distance and require minimal effort, and also uses emotion data to suggest services that match the user's mood. For example, if the system determines that the user is tired, it will recommend stores with a more relaxing atmosphere or stores that offer stress-relieving offers.

[0757] As a concrete example, consider a busy business traveler using the app during lunchtime. If the device detects that fatigue is reflected in the user's facial expression, the server will recommend a restaurant with a quiet and comfortable atmosphere. Furthermore, the electronic coupons offer perks such as "drink service" or "use of relaxing aromatherapy" to further enhance user satisfaction.

[0758] After a user visits a store, the emotion engine re-evaluates whether the suggested effect was achieved. This feedback is analyzed by the server to help improve future services. Stores can also use this data to gain a detailed understanding of user emotional changes and to understand potential customer needs, thereby improving the quality of their services.

[0759] In this way, this system, which incorporates an emotion engine, strengthens the link between user emotions and service experience, enabling personalized store recommendations and rewards tailored to individual needs. This allows for effective customer acquisition focused on the local community, contributing to the revitalization of the local economy.

[0760] The following describes the processing flow.

[0761] Step 1:

[0762] The user launches the app on their device, and emotional input data is collected along with location information. The device then uses its camera and microphone to send the user's facial expressions, voice tone, and other information to the emotion engine.

[0763] Step 2:

[0764] The emotion engine analyzes the user's emotions. Based on facial features and voice waveform data, the engine determines the user's current emotional state. This information is sent to the server as the user's psychological state.

[0765] Step 3:

[0766] The server combines location information and sentiment analysis results to recommend the most suitable stores and benefits. If the user wants to relax, stores with a quiet atmosphere or services that promote relaxation will be selected.

[0767] Step 4:

[0768] The terminal displays recommended store information and special offers to the user. The server also considers the store's congestion level and guides the user to the store with the shortest possible waiting time.

[0769] Step 5:

[0770] After the user selects a store and checks the benefits, an electronic coupon is generated based on the selected benefit information. The coupon is provided in the form of a QR code displayed on the terminal.

[0771] Step 6:

[0772] The user presents a QR code at their chosen store, which the store's terminal scans and verifies. The store then offers emotionally-driven rewards to improve user satisfaction.

[0773] Step 7:

[0774] After a user visits, feedback is sent to the server. The emotion engine then analyzes the user's emotions again, and their post-visit state is evaluated. This information is stored as data for service improvement.

[0775] Step 8:

[0776] The server collects all user data and analyzes regional usage trends. The analysis results are provided to stores and local governments and used to improve service quality and implement regional revitalization measures.

[0777] (Example 2)

[0778] 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".

[0779] Traditional store recommendation systems primarily rely on recommendations based on the user's physical location, which has the drawback of not adequately considering the emotional and psychological states of individual users. As a result, they tend to provide uniform promotional information, failing to adequately contribute to improving the user experience or revitalizing the local economy.

[0780] 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.

[0781] In this invention, the server includes means for analyzing the user's emotional state, means for providing personalized store recommendations based on the analyzed emotional state, and means for collecting user feedback and storing it in a database for future service improvements. This enables store recommendations and the provision of benefits that correspond to the user's emotional state, thereby improving the user experience and stimulating the local economy.

[0782] "Congestion information" refers to data that shows the level of people gathered at a particular store or location, the length of queues, and other information indicating the dwell time of users.

[0783] A "central server" is a centralized computer system for processing, storing, and managing data via the internet.

[0784] A "user terminal" is an electronic device used directly by the user, and includes devices such as smartphones and tablets.

[0785] "Benefit information" refers to additional value or discount information regarding products and services offered to users, and is provided in the form of electronic coupons, etc.

[0786] An "electronic coupon" is a digital coupon provided in digital format that grants the right to receive a discount or free provision of a specific service or product.

[0787] "Emotional state" refers to information that indicates the user's psychological and emotional state, and is analyzed based on digital data.

[0788] "Personalized store recommendations" refer to a personalized store selection and referral process based on the user's individual behavioral characteristics and emotional state.

[0789] "User feedback" refers to data that reflects users' impressions and opinions on the services and recommendations provided, and is used to improve those services.

[0790] This invention is a system that analyzes a user's emotional state and provides personalized store recommendations and special offers based on that analysis. The system primarily utilizes a user terminal, a central server, and an emotion analysis engine to achieve the functions described in the claims.

[0791] The user launches a dedicated application on a device such as a smartphone or tablet. The device uses its camera, microphone, and touch sensors to collect data such as the user's facial expressions, voice, and keyboard input patterns. This emotional data is temporarily stored on the device and securely transmitted to a central server using encryption technology.

[0792] The server passes the received data to the sentiment analysis engine. The sentiment analysis engine uses machine learning algorithms to quantify the user's emotional state. This analysis incorporates a generative AI model that leverages past data and learning to more accurately determine the emotional state.

[0793] The server then uses the analysis results to select the most suitable stores and offers for the user. This selection process takes into account the user's current location and emotional state, resulting in personalized recommendations. The selected store and offer information is sent to the device and displayed to the user in an immediately usable format.

[0794] For example, if a user on a business trip is using the app and facial analysis detects signs of fatigue, the server will recommend a quiet and relaxing restaurant. The perks offered may include services such as complimentary drinks or the use of relaxing aromatherapy.

[0795] This system collects user feedback and uses it to improve future services, thereby contributing to an enhanced user experience.

[0796] An example of a prompt message might be, "Based on the user's sentiment data, recommend the best store and benefits."

[0797] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0798] Step 1:

[0799] The user launches the app on their device. The device uses its camera, microphone, and touch sensors to collect the user's facial expressions, voice, and keyboard input patterns. This data is temporarily stored on the device as input. Specifically, facial recognition software analyzes the user's image, and voice recognition software analyzes the tone and speed of their voice. The output is quantified data that suggests the user's emotions.

[0800] Step 2:

[0801] The terminal securely transmits the collected data to a central server using encryption technology. The input includes encrypted emotional data, which is securely sent to the server over the internet. This process utilizes specific data transfer protocols to ensure data integrity.

[0802] Step 3:

[0803] The server decrypts the received encrypted data and passes it to the sentiment analysis engine. This engine uses the input data to utilize a generative AI model to analyze the user's emotional state. Specifically, a machine learning algorithm quantifies the emotions, and an emotion score is generated as output.

[0804] Step 4:

[0805] The server combines sentiment scores with the user's current location information to select the most suitable stores and offers. This process uses the analysis results and geographic information systems to generate personalized recommendation lists. The output is a personalized list of stores and offers.

[0806] Step 5:

[0807] The server sends the generated store list and special offer information to the terminal. The terminal displays the data it has received as input to the user. Specifically, the user interface organizes the recommendation information and displays it on the screen. The output is a visual presentation for the user to take action.

[0808] Step 6:

[0809] After the user visits a recommended store, the terminal collects sentiment data again and sends feedback to the server. The input includes the newly collected sentiment data, which is then sent back to the server. This feedback is used to improve the accuracy of future analyses.

[0810] Step 7:

[0811] The server analyzes the collected feedback data and stores it in a database. This data is used for the continuous training of machine learning and helps improve recommendation algorithms. Specifically, the database management system detects certain patterns and trends and compiles them into reports.

[0812] (Application Example 2)

[0813] 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".

[0814] Conventional store information management systems were limited to providing congestion information and special offers, and were unable to personalize services that took into account the emotional state of the user. As a result, it was difficult to improve user satisfaction and propose the most suitable facilities and services. This invention aims to solve these problems and enable the provision of advanced services based on the emotions of the user.

[0815] 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.

[0816] In this invention, the server includes means for determining the user's emotional state using an emotion analysis engine, means for capturing the user's facial expressions using image recognition technology and linking this to emotion analysis, and means for recommending appropriate facilities based on the user's location information and emotional state. This makes it possible to recommend the optimal store, rest area, and service in real time according to the user's emotional state, thereby improving the quality of the user's experience.

[0817] A "device for acquiring congestion information in stores in digital format" is a device that electronically detects the congestion level within a facility and acquires that information as digital data.

[0818] A "centralized processing unit" is a central computer that receives information collected from multiple terminals in a unified manner, and stores and processes that information.

[0819] "User's device" refers to a mobile information device such as a smartphone or tablet that the user carries with them.

[0820] An "emotion analysis engine" is a software component that analyzes a user's psychological state based on data acquired from them.

[0821] A "device that captures a user's facial expressions using image recognition technology and uses that information for emotion analysis" is a device equipped with technology that uses cameras and sensors to identify a user's facial expressions and uses that information for emotion analysis.

[0822] A "device that recommends appropriate facilities based on the user's location information and emotional state" is a system that combines the user's current location with an analysis of their emotions to suggest the most suitable place or facility for the user.

[0823] A "digital coupon" is an electronic voucher containing discounts or special offers that is distributed electronically.

[0824] A "report generation device" is a device that analyzes facility and user usage information and uses that information to create detailed reports.

[0825] This invention is a system that personalizes facilities and services based on the user's emotional state. The server uses an emotion analysis engine to analyze the user's emotions from their facial expressions, keyboard typing speed, voice, etc. In this process, OpenCV is introduced as an image recognition technology to identify facial expressions and provide data for emotion analysis. In addition, location information is obtained from the user's terminal and used to select recommended facilities. Based on these analysis results, the server recommends appropriate cafes or rest areas where the user can relax.

[0826] Furthermore, the server uses an API to retrieve the latest congestion and special offer information from facilities and generates digital coupons based on that information. These digital coupons are sent to the user's device, and when the user presents them, the authentication process at the facility is completed. The results of the facility's service provision are re-evaluated, and user feedback is used to improve future services. A possible prompt for users might be: "Please recommend a relaxing store for a tired user."

[0827] As a concrete example, consider a scenario where a customer visiting a shopping mall is fatigued from prolonged shopping. The server can detect this state using facial recognition and location information, recommend a nearby comfortable cafe, and provide a digital coupon for a free drink. In this way, the present invention can provide information services based on emotional states and improve customer satisfaction.

[0828] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0829] Step 1:

[0830] The device captures the user's facial expressions with a camera and performs face detection using OpenCV. The input is image data from the camera, and the output is feature data related to facial expressions. This feature data serves as basic information to be sent to the emotion analysis engine.

[0831] Step 2:

[0832] The server receives facial feature data transmitted from the terminal and analyzes the user's emotions using an emotion analysis engine. The input is facial feature data, and the output is the user's emotional state (e.g., fatigue, satisfaction, stress). Based on this emotional state, the server prepares recommended services.

[0833] Step 3:

[0834] The server obtains location information from the terminal and determines the user's current location. The input is location data, and the output is information about the facility where the user is located and its surroundings. Based on this location information, the server selects the most suitable store.

[0835] Step 4:

[0836] The server recommends the most suitable facility for the user, taking into account both their emotional state and location. The input is the user's emotional state and location, and the output is a list of recommended facilities. For example, it might select and suggest a relaxing cafe or a comfortable rest area.

[0837] Step 5:

[0838] The server retrieves information about benefits related to selected facilities and services via an API and generates digital coupons based on that information. The input is information about recommended facilities and benefits, and the output is an electronically issued digital coupon. This coupon may include benefits such as free drinks or relaxation items.

[0839] Step 6:

[0840] The terminal displays digital coupons received from the server to the user. The input is digital coupon information, and the output is a display of coupon data in a format usable by the user. Users can use the displayed coupons to receive discounts and benefits at stores and services.

[0841] Step 7:

[0842] After a user visits a store, the terminal sends feedback to the server to evaluate the effectiveness of the suggested services and benefits. The input is user feedback data, and the output is analysis data for the server. Based on this feedback, the server makes improvements to future services.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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."

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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 to be incorporated by reference.

[0864] The following is further disclosed regarding the embodiments described above.

[0865] (Claim 1)

[0866] A means of obtaining store congestion information in digital format,

[0867] A means of transferring the acquired congestion information to a central server,

[0868] A means for storing and processing acquired congestion information on a central server,

[0869] A means of displaying readily available congestion information on the user's terminal,

[0870] A means of providing information about special offers related to the store selected by the user,

[0871] A means of generating an electronic coupon using special offer information and displaying it on the user's terminal,

[0872] A means of authenticating electronic coupons in stores,

[0873] Means of providing authenticated reward information,

[0874] A means of analyzing store and user usage data and generating reports,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, comprising means for recommending the most suitable store based on the user's current location information.

[0878] (Claim 3)

[0879] The system according to claim 1, comprising means for providing analyzed usage data for local governments.

[0880] "Example 1"

[0881] (Claim 1)

[0882] A method for acquiring digital data on the dwell time of customers in a store,

[0883] A means for transferring the acquired dwelling status to a central information processing unit,

[0884] In the central information processing system, means for accumulating and processing the acquired dwell status,

[0885] The user's device provides a means for visually confirming the status of occupancy, which can be quickly utilized.

[0886] A means of providing profit information related to the store selected by the user,

[0887] A means for generating electronic discount coupons using profit information and visually outputting them to a user device,

[0888] A means of verifying electronic discount coupons at the store,

[0889] Means for providing confirmed profit information,

[0890] A means for analyzing store and user usage data and generating reports,

[0891] Means of conveying information clearly using audio guidance and visual effects,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, comprising means for suggesting the most suitable store based on the user's current location data.

[0895] (Claim 3)

[0896] The system according to claim 1, comprising means for providing analyzed usage data for use by local government agencies.

[0897] "Application Example 1"

[0898] (Claim 1)

[0899] A means of obtaining store congestion information in digital format,

[0900] A means for transferring acquired congestion information to an information processing device,

[0901] An information processing device includes means for storing and processing acquired congestion information,

[0902] A means by which an information processing device presents congestion information using audio guidance and visual effects,

[0903] A means of displaying readily available congestion information on the user's terminal,

[0904] A means of providing information about special offers related to the facility selected by the user,

[0905] A means of generating an electronic coupon using special offer information and displaying it on the user's terminal,

[0906] A means of authenticating electronic coupons at the facility,

[0907] Means of providing authenticated reward information,

[0908] A means for analyzing facility and user usage data and generating reports,

[0909] A means of superimposing congestion information onto real-world visual information using augmented reality technology,

[0910] A system that includes this.

[0911] (Claim 2)

[0912] The system according to claim 1, comprising means for recommending the most suitable store based on the user's current location information.

[0913] (Claim 3)

[0914] The system according to claim 1, comprising means for providing analyzed usage data for local government agencies.

[0915] "Example 2 of combining an emotion engine"

[0916] (Claim 1)

[0917] A means of obtaining store congestion information in digital format,

[0918] A means of transferring the acquired congestion information to a central server,

[0919] A means for storing and processing acquired congestion information on a central server,

[0920] A means of displaying readily available congestion information on the user's terminal,

[0921] A means of providing information about special offers related to the store selected by the user,

[0922] A means of generating an electronic coupon using special offer information and displaying it on the user's terminal,

[0923] A means of authenticating electronic coupons in stores,

[0924] Means of providing authenticated reward information,

[0925] A means of analyzing store and user usage data and generating reports,

[0926] A means of analyzing the user's emotional state,

[0927] A means of providing personalized store recommendations based on analyzed emotional states,

[0928] A means of collecting user feedback and storing it in a database for future service improvements,

[0929] A system that includes this.

[0930] (Claim 2)

[0931] The system according to claim 1, comprising means for making optimal store recommendations based on the user's current location information and means for making more effective recommendations by combining this with analyzed emotional states.

[0932] (Claim 3)

[0933] The system according to claim 1, comprising means for providing usage data analyzed for use by local governments, and means for utilizing user feedback to revitalize the local economy.

[0934] "Application example 2 when combining with an emotional engine"

[0935] (Claim 1)

[0936] A device for acquiring store congestion information in digital format,

[0937] A device that transfers acquired congestion information to a central processing unit,

[0938] In a centralized processing system, there is a device for storing and processing acquired congestion information,

[0939] A device that displays immediately available congestion information on the user's terminal,

[0940] A device that provides information about special offers related to the facility selected by the user,

[0941] A device that generates digital coupons using special offer information and displays them on the user's device,

[0942] A device for authenticating digital coupons at the facility,

[0943] A device that provides authenticated reward information,

[0944] A device that analyzes facility and user usage information and generates reports,

[0945] A device that uses an emotion analysis engine to determine the user's emotional state and recommends the most suitable store or service based on that emotional state,

[0946] A device that uses image recognition technology to capture the user's facial expressions and use that information for emotion analysis,

[0947] A device that recommends appropriate facilities based on the user's location information and emotional state,

[0948] A system that includes this.

[0949] (Claim 2)

[0950] The system according to claim 1, which analyzes the emotional state of users in real time and recommends the most suitable resting place within the facility based on that emotional state.

[0951] (Claim 3)

[0952] The system according to claim 1, which provides usage information based on analyzed user sentiment for local governments. [Explanation of Symbols]

[0953] 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 store congestion information in digital format, A means of transferring the acquired congestion information to a central server, A means for storing and processing acquired congestion information on a central server, A means of displaying readily available congestion information on the user's terminal, A means of providing information about special offers related to the store selected by the user, A means of generating an electronic coupon using special offer information and displaying it on the user's terminal, A means of authenticating electronic coupons in stores, Means of providing authenticated reward information, A means of analyzing store and user usage data and generating reports, A system that includes this.

2. The system according to claim 1, comprising means for recommending the most suitable store based on the user's current location information.

3. The system according to claim 1, comprising means for providing analyzed usage data for local governments.

Images