system

Abstract

We provide the system. [Solution] A means of centrally managing information on multiple preferential services held by a user, For each of the aforementioned preferential services, a means for calculating the priority of use based on geographical location information, event information, and the expiration date of the preferential service, A means of notifying users of recommended preferential services based on the aforementioned usage priority, A means of collecting usage data for preferential services, analyzing it, and generating industry trend data, Means for providing the aforementioned industry trend data to external organizations, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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 modern times, many consumers own multiple point cards and have to manage the apps corresponding to each point card, which causes confusion and complexity in daily life. Also, it is difficult to determine which card should be used at which store, and it is difficult to optimize the use of points. In addition, for companies, there are limited means to comprehensively collect and analyze user consumption behavior data, which hinders the formulation of efficient marketing strategies.

Means for Solving the Problems

[0005] This invention provides a system that centrally manages information on multiple point cards held by a user and calculates usage priority based on location information, event information, and point expiration dates. This allows the system to notify users of recommended point cards, supporting efficient point utilization. Furthermore, by collecting point card usage data, analyzing that data, and generating market trend data, which is then provided to third-party companies, it enables the development of more effective marketing strategies.

[0006] A "user" refers to an individual who owns a point card and uses that card.

[0007] A "point card" is a card-like information system that awards points based on consumer spending and provides the right to receive benefits and discounts.

[0008] "Location information" refers to information that indicates a geographical location and is data used to identify a specific place.

[0009] "Event information" refers to information related to campaigns and special offers held during a specific period.

[0010] "Expiration date" refers to the date and time when points awarded to a loyalty card become invalid.

[0011] "Usage priority" is an indicator that shows which card should be used first when comparing multiple loyalty cards.

[0012] "Usage data" refers to information about how the point card was used, including items such as date and time, amount spent, and store used.

[0013] "Market trend data" refers to information obtained as a result of analyzing consumer behavior and consumption trends, used to predict future market movements.

[0014] A "third party" refers to a company or organization that provides data to another company, distinct from the company that provides the point card. [Brief explanation of the drawing]

[0015] [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]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying out the Invention

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

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

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

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

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

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

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

[0023] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0036] This invention provides a system for efficiently managing multiple point cards held by a user and optimizing the use of those cards. This system is configured to exchange information between a terminal, a server, and the user, and to maximize the convenience of each point card.

[0037] First, the user downloads the application via their device and enters their personal information and loyalty card details to begin using the service. The device then sends this information to a server, which stores it in a central database. This allows the user to manage all of their loyalty cards in one place.

[0038] Next, the server retrieves the user's location information and information on currently running events and promotions. Based on this, the server calculates usage priority. For example, it can prioritize selecting a point card that offers greater benefits when used at a particular store. The terminal then notifies the user of recommended point cards based on instructions from the server. This allows the user to quickly decide which card to use.

[0039] Furthermore, the server analyzes point card usage data to understand usage patterns. Using AI generation, it collects data such as which cards are frequently used on specific days and times. This analysis is provided to companies and used to develop new marketing strategies.

[0040] For example, if a user frequently shops at a particular supermarket on weekdays, the server can recommend a card that offers discounts valid during those times. Furthermore, if there is a points multiplier campaign at a nearby Starbucks, the server can notify the user of this information and help them make the most of the benefits.

[0041] In addition, the server periodically checks the expiration date of point cards and notifies the user via their terminal if the points are about to expire. This system reduces the risk of users unknowingly losing points.

[0042] Thus, the system according to the present invention can effectively manage and optimize the use of point cards, bringing benefits to both users and companies.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user downloads the app and enters personal information and loyalty card information through their device. The device sends this information to the server. The server receives this information and stores it in a database.

[0046] Step 2:

[0047] The device acquires the user's location information and sends it to the server. The server then uses this location information to collect current promotion and event information.

[0048] Step 3:

[0049] The server calculates the usage priority based on the benefits, point balance, location information, and event information of each point card. Usage priority is an indicator that shows which point card should be used first.

[0050] Step 4:

[0051] Based on the calculated usage priority, the server generates specific card usage suggestions for the user. The terminal receives these suggestions and notifies the user with a message such as, "The recommended point card is XX."

[0052] Step 5:

[0053] When a user uses a specific loyalty card, the terminal sends usage information (store name, amount spent, date and time of use, etc.) to the server. The server records this usage data in a database.

[0054] Step 6:

[0055] The system analyzes usage patterns through data collected by the server. Generative AI is used to extract trends such as which cards are used most frequently on specific days of the week or during specific time periods.

[0056] Step 7:

[0057] Based on the analysis results, the server creates and provides market trend data to companies. This data is used by companies as a reference when formulating their promotional strategies.

[0058] Step 8:

[0059] The server periodically checks the expiration date of point cards. When the expiration date is approaching, it notifies the user via the terminal that "Points on your XX card will expire in △ days."

[0060] (Example 1)

[0061] 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."

[0062] In modern society, it is difficult for individuals to efficiently manage a large amount of identification information and authentication methods. Furthermore, there is a lack of mechanisms to support optimal choices based on individual information when utilizing this identification information, so users often miss out on opportunities to enjoy potential benefits and advantages. In addition, users risk missing out on many opportunities because they are not properly notified of the expiration dates of identification information or temporary promotional information.

[0063] 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.

[0064] In this invention, the server includes means for integrally managing data relating to multiple pieces of identification information held by the user, means for calculating a usage priority for each piece of identification information based on location data, event information, and data expiration date, and means for notifying the user of recommended identification information based on the usage priority. As a result, the user can make timely use of the most appropriate identification information for the situation, enabling efficient management and maximizing the enjoyment of benefits.

[0065] "User" refers to an individual or entity that uses the system and is responsible for possessing and managing identification information.

[0066] "Identification information" refers to the collective term for data related to personal benefits and convenience, including loyalty cards and other authentication methods.

[0067] A "server" refers to a central computing resource within a system that handles processing, manages data, and communicates with users.

[0068] "Integrated management" means centralizing and organizing identification information in one place so that it can be managed efficiently.

[0069] "Location data" refers to data that indicates a user's current geographical information and is one of the factors that promotes the optimal use of identification information.

[0070] "Event information" refers to data that shows information about specific events or promotions, either geographically or temporally.

[0071] "Expiration date" refers to information such as a date that indicates the period during which identification information and its benefits can be used.

[0072] "Usage priority" refers to a priority order based on the degree of convenience and benefits expected from the use of identification information.

[0073] "Recommendation" means providing users with identification information that is considered most beneficial under specific conditions.

[0074] "External entities" refer to third parties other than users and servers, and generally include organizations and groups to which market trend data is provided.

[0075] This invention provides a system for effectively managing multiple pieces of identification information held by a user and optimizing their use. The invention utilizes information exchange between a terminal, a server, and the user as its main components.

[0076] First, the user downloads and launches a dedicated application using a mobile device or computer. The application requests the user to enter personal information and any identification data they possess upon their initial connection to the system. This information is temporarily stored on the device before being sent to the server.

[0077] The server analyzes the received data and stores it in a central database. Centralized management of user identification information enables rapid data access as needed. The server also collects user location data and event information, and uses a generative AI model to calculate the priority of using identification information. This allows for the identification information that is most useful to the user geographically or temporally to be identified.

[0078] The device notifies the user of recommended identification information received from the server. For example, if there is identification information that provides immediate benefits to the user when they are in a specific location, this information may be displayed on the device screen. Furthermore, data regarding the use of this identification information is collected and analyzed by the server and provided to external entities as market trend data.

[0079] This system also includes a mechanism where the server periodically checks the expiration date of identification information and notifies the user via their device when the expiration date is approaching. Furthermore, it can provide information about promotions that are about to end based on the user's location data.

[0080] As a concrete example, a user can instantly receive optimal identification information through a prompt such as, "Please tell me the best discount information available near my current location." This allows the user to make the best choice for their situation.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user downloads and launches the application on their device and enters personal and identification information. The device temporarily stores the entered data and prepares to send it to the server. Specifically, the user enters information into a form and presses the submit button, which sends the data to the server. The input consists of personal and identification information, and the output is the transmission of this data to the server.

[0084] Step 2:

[0085] The server verifies personal and identification information received from the terminal and stores it in a central database. This forms the foundation for centralized data management. Specifically, the process involves accumulating data as records in the database. The input is personal and identification information from the terminal, and the output is the storage of this information in the database.

[0086] Step 3:

[0087] The server acquires user location data and event information, and uses a generative AI model to calculate the priority of using the identification information. Specifically, the AI ​​calculates the priority of the identification information according to specific conditions based on location and event information. The input is location data and event information, and the output is data calculated as the usage priority.

[0088] Step 4:

[0089] The server sends recommended identification information to the device based on the calculated usage priority. The device notifies the user of this information, specifically through push notifications or screen displays. The input is usage priority data, and the output is a notification of recommended information to the user.

[0090] Step 5:

[0091] The server collects and analyzes usage data for identification information. It utilizes a generative AI model to generate market trend data and prepares it for provision to external entities. Specifically, it analyzes usage history data using AI and creates reports. The input is usage data, and the output is market trend data.

[0092] Step 6:

[0093] The server periodically checks the expiration date of the identification information and notifies the user via the terminal when the expiration date is approaching. Specifically, it uses a reminder function to send notifications. The input is the expiration date data of the identification information, and the output is a user notification when the expiration date is approaching.

[0094] Step 7:

[0095] The server provides information about promotions that are about to end based on the user's location data. The terminal receives this information and presents it to the user. A specific prompt might be, "Please tell me the best discounts available near my current location," to which the terminal responds immediately. The input is location data, and the output is the provision of promotion information.

[0096] (Application Example 1)

[0097] 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."

[0098] For companies offering multiple preferential treatment services, it is not easy for individual consumers to maximize the use of each service and manage them centrally. Furthermore, it is difficult to effectively notify consumers of expiring benefits, ensure consumer convenience, and grasp market trends. Providing each consumer with the most relevant sales promotion information based on their geographical location is also a challenge.

[0099] 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.

[0100] In this invention, the server includes means for centrally managing information on multiple preferential services held by a user, means for calculating the priority of use for each of the preferential services based on geographical location information, event information, and the expiration date of the preferential service, and means for acquiring the user's geographical location information and providing sales promotion information that is nearing its end based on that geographical location information. As a result, consumers can make the most of each preferential service, and companies can more easily grasp the usage trends of each consumer.

[0101] A "preferential service" is a system that provides added value to users through benefits and discounts offered to them.

[0102] "Geographic location information" refers to data that indicates the user's current location, and is used to provide appropriate services and information based on this information.

[0103] "Event information" refers to information about events and promotions, and is an important element for encouraging user engagement.

[0104] The "expiration date" indicates the period during which a special offer is valid, and once this date passes, it becomes unusable.

[0105] "Industry trend data" refers to information about market and consumer usage trends obtained by analyzing data on the use of preferential services.

[0106] "Sales promotion information" refers to information about special offers and campaigns provided to encourage users to make purchases.

[0107] This system is designed to efficiently manage multiple preferential services held by users and optimize their use. Users install a dedicated application on their smartphones or other devices. This application provides an interface for inputting the user's personal information and preferential service information, and has the function to send this information to a server. The server stores the received information in a central database and updates it in real time.

[0108] Based on this information, the server calculates the priority of using preferential services, using geographical location information, event information, and the expiration date of the preferential treatment. In calculating the priority of use, a generative AI model such as TENSORFLOW® is used to comprehensively evaluate multiple factors. The server analyzes the usage data of preferential services and utilizes machine learning algorithms to understand usage trends. For example, if there is a tendency for preferential treatment to be used frequently in a particular area on weekdays, the server can recommend preferential treatment on specific days of the week.

[0109] The analysis results are provided to external organizations and used to develop new sales strategies. When the expiration date of a discount is approaching, the server sends a notification to the user to encourage its use. It also provides currently valid sales promotion information based on geographical location to increase the user's purchasing intent. For example, it might send a notification saying, "There is currently a campaign at a nearby commercial facility where certain discounts are doubled."

[0110] Thus, the present invention effectively manages the use of preferential services and brings benefits to both users and companies.

[0111] An example of a prompt message would be: "Please tell me how to design an app that, when a user visits a location, selects the most suitable discount from all available discount services and maximizes the benefits based on effective sales promotion information."

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The user launches the application using their device. The device collects information about the promotional service and personal information entered by the user and sends this data to the server. The entered data includes the name of the promotional service, applicable stores, and expiration date. The server receives this data and stores it in a central database.

[0115] Step 2:

[0116] The server acquires geographical location information and event information based on the preferential service information submitted by users. Using this information, it employs a generative AI model such as TensorFlow to calculate the priority of using the preferential services. It combines the preferential service information, location information, and event information as input to perform data calculations and output the priority of use. The calculated priority is stored in a central database.

[0117] Step 3:

[0118] The server periodically analyzes usage data for the preferential treatment service to understand user trends. This process involves analyzing past usage history and trends. Using machine learning algorithms, it processes the usage history of the preferential treatment service as input data and generates predictive usage trends and market trend data. These results are provided as information to external organizations.

[0119] Step 4:

[0120] The server monitors the expiration date of discount services and sends a notification to the device when the deadline approaches. This process retrieves information about the expiration date from the database and generates a notification message when the deadline is nearing. The notification displays information about discounts that are about to expire on the user's smartphone.

[0121] Step 5:

[0122] A server that obtains the user's geographical location information generates promotional information based on the current location and sends it to the terminal. The user's current location and special offer information are used as input, and the relevant promotional information is provided as output. The application displays a notification in the form of, "There are stores nearby where you can receive special offers."

[0123] 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.

[0124] This invention provides a system that efficiently and effectively manages multiple point cards held by a user, and further combines this with an emotion engine to suggest the optimal use of point cards according to the user's emotions. This system is designed to exchange information between terminals, servers, and users, and to provide the best service based on the user's needs and emotional state.

[0125] First, the user downloads the application through their device and enters their personal information and any loyalty card information they have. The device sends this information to a server, which records it in a central database. Subsequently, the device periodically analyzes the user's emotional state using an emotion engine and sends the results to the server.

[0126] Next, the server comprehensively adjusts the user's location information, current events, and promotional information. Taking actual usage scenarios into account, it calculates usage priorities in conjunction with the user's emotional state. This priority is adjusted to prioritize cards that allow points to be used more effectively when the user's emotions are in a state that increases their desire to shop.

[0127] The server suggests the most suitable card usage for the user based on the calculated usage priority. For example, if the analysis indicates that the user is feeling stressed, it will suggest using a card that offers discounts on relaxation products. The terminal receives this suggestion and notifies the user, "Our current recommended points card is XX. Relaxation products are on sale during our special campaign."

[0128] Furthermore, the server collects loyalty card usage data and combines it with the results of the emotion engine's analysis to generate market trend data. This analysis makes it possible to comprehensively understand trends such as which cards are frequently used in which emotional states.

[0129] Companies are provided with this detailed market trend data, which can be used to develop new marketing strategies. For example, based on sentiment analysis, they can plan the most effective promotions when specific emotional states are triggered.

[0130] Thus, the present invention can effectively manage the use of point cards and provide companies with new market forecasting clues while improving the user experience by making suggestions based on the user's emotions.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The user downloads the app through their device and enters their personal information and loyalty card information. The device sends this information to the server, which records it in a database.

[0134] Step 2:

[0135] The device transmits the user's emotional state to the emotion engine via its camera and sensors. The emotion engine analyzes the user's voice tone and facial expressions to recognize their emotions and sends the results to the server.

[0136] Step 3:

[0137] The server uses location information acquisition to determine the user's current location and also retrieves information about ongoing events. Based on this data, it generates promotional information.

[0138] Step 4:

[0139] The server integrates emotion recognition data from the emotion engine with collected location and event information to calculate usage priority. Priority is determined based on the loyalty card that best matches the emotions the user is currently experiencing.

[0140] Step 5:

[0141] Based on the calculation results, the server suggests to the user the use of a specific card. The terminal notifies the user of this suggestion and guides them with a message such as, "Based on your emotional state, the XX card is currently the best choice."

[0142] Step 6:

[0143] When a user uses a suggested card, the terminal records the usage data (date and time of use, location, amount, etc.) and sends it to the server. The server adds this data to its database.

[0144] Step 7:

[0145] The server analyzes usage data and emotion recognition results to identify which emotional states influence consumer behavior. As a result, detailed market trend data is generated for businesses.

[0146] Step 8:

[0147] The server provides companies with generated market trend data to help them develop emotionally driven promotions and marketing strategies. This data is then used to plan new campaigns.

[0148] (Example 2)

[0149] 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".

[0150] Traditionally, there was no system in place to effectively manage and optimally utilize the reward cards held by users. Emotional states could not be considered when determining the usage status or priority of reward cards, and there was a lack of efficient methods for collecting data to understand market trends. As a result, users were unable to use their reward cards effectively, potentially leading to the risk of rewards expiring or missing out on appropriate promotions.

[0151] 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.

[0152] In this invention, the server includes means for centrally managing information on multiple reward cards held by a user, means for calculating the usage priority for each of the reward cards based on location information, event information, and the expiration date of the reward, and means for analyzing the user's emotional state and incorporating the analysis results into the calculation of usage priority. This enables the user to use reward cards that are appropriate to their emotional state and circumstances at any given time, preventing the loss of rewards and the missed opportunity for effective promotions, and also enabling them to grasp market trends.

[0153] A "reward card" is a card used by users to receive benefits when using a service or product, and includes point cards, membership cards, and other similar cards.

[0154] "Centralized management" refers to the unified management of multiple pieces of information or data within a single location or system.

[0155] "Usage priority" is an index that calculates the importance and priority of using a reward card based on specific conditions or circumstances.

[0156] "Emotional state" refers to the user's psychological state and includes various emotional states such as joy, sadness, and anger.

[0157] "Analysis" refers to the process of examining data in detail and deriving meaning and patterns from it.

[0158] "Market trend data" refers to data that shows market trends and patterns, and includes information based on the usage and emotional state of reward cards.

[0159] An "external organization" refers to a group or company that is different from the system's operator and is subject to information sharing.

[0160] This invention is a system that allows users to efficiently manage and utilize reward cards and receive optimal usage suggestions tailored to their emotional state. This system is primarily realized through the exchange of information between a server, a terminal, and the user.

[0161] Users download and begin using an application compatible with their smartphone or tablet. Through this application, users enter personal information and details about any reward cards they possess. The device collects this information and transmits it to a server using a security protocol. The server records the received information in a database in preparation for subsequent processing. Database management systems such as MySQL® or MongoDB may be used for the database.

[0162] On the other hand, the device uses the user's sensor devices, such as the camera and microphone, to periodically analyze the user's emotional state. This analysis may utilize an emotion analysis engine, specifically the emotion analysis APIs of IBM Watson® or Microsoft® Azure®. The emotion data obtained from the device is sent to a server and managed integrally with other information.

[0163] The server calculates a priority for use based on the user's current location information, relevant event information, the expiration date of the reward card, and their emotional state. Based on this calculated priority, the server suggests the use of a specific reward card to the user. This suggestion is notified to the user via their terminal, allowing them to effectively use the reward card accordingly.

[0164] This system collects reward card usage data and combines it with the results of an emotion engine analysis to generate market trend data. Companies can use this trend data to develop new marketing strategies.

[0165] For example, if the emotion engine analyzes that the user is feeling stressed, the device might notify the user with a message like, "We recommend using the XX rewards card, which offers a discount on aromatherapy candles." This approach can improve the user experience.

[0166] An example of a prompt to a generative AI model could be: "Please show a method for providing the best reward card usage suggestion when the emotional state is stressful."

[0167] The system of this invention is designed to allow users to make the most of their reward cards, and it is also valuable to companies because it allows them to predict market trends based on the collected data.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user downloads and launches the application on their device. The user enters personal information and reward card information on the application screen. The entered data is temporarily stored on the device, preparing for information transfer. This data becomes the input to the server. The device sends the user information as input data to the server via a security protocol. The server receives this data and outputs it to its database.

[0171] Step 2:

[0172] The device uses its camera and microphone to collect user emotion data. Information obtained from the user's facial expressions and voice is input into an emotion analysis engine. This engine performs calculations that output the emotional state as numerical data. The obtained emotional state data is prepared on the device for transmission to the server. The server receives this emotion data as input and uses it, along with other known user information, as material for the next calculation.

[0173] Step 3:

[0174] The server retrieves location information, event information, and the expiration date of reward cards from the database. This information is then combined with sentiment data to calculate usage priority. Specifically, a weighted averaging method is used to output a single priority index. This priority index serves as an indicator for determining which reward cards the user should use next.

[0175] Step 4:

[0176] Based on the calculated usage priority, the server generates a suggestion for the user to use the most suitable reward card. The generated suggestion is output to the terminal as a notification message. The terminal receives this and displays it to the user. Specifically, a message such as "We recommend using the XX reward card, which offers great deals on relaxation products" pops up on the terminal screen.

[0177] Step 5:

[0178] The server collects usage data for reward cards and performs calculations to generate market trend data by adding emotional data to it. This data is output as an analysis report and provided to companies. This provides information that allows them to understand trends such as which cards are preferred to be used in which emotional states.

[0179] Through these steps, the entire system will operate in a way that provides users with effective and efficient reward card services.

[0180] (Application Example 2)

[0181] 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".

[0182] There is a need for a system that efficiently manages the multiple means of value exchange held by users and suggests the optimal use of value exchange cards based on the user's emotional state and location data. This will enable users to exchange value in the most advantageous way at any given time, and in addition, it will create an environment that allows companies to efficiently analyze market trends.

[0183] 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.

[0184] In this invention, the server includes means for centrally managing information on multiple value exchange cards held by a user, means for calculating a usage priority for each of the value exchange cards based on location data, activity information, and the expiration date of the value, and means for analyzing the user's emotional state and optimizing the use of the value exchange cards based on that state. As a result, the optimal value exchange is proposed to the user, and effective value utilization based on emotional state and location information becomes possible.

[0185] A "value exchange card" is a card that allows users to obtain value in the form of points or discounts in specific activities.

[0186] "Usage priority" is an indicator that shows which value exchange cards should be used preferentially, based on factors such as location data, activity information, and value expiration dates.

[0187] "Emotional state" refers to the user's psychological and emotional condition, and is information used to optimize the user's behavior and choices based on this state.

[0188] "Information trend data" refers to data that analyzes collected value exchange card usage data to show trends and developments in the market.

[0189] "Location data" refers to data that indicates the geographical location of users and is useful for optimizing the use of activity information and value exchange cards.

[0190] The system required to implement this application consists of a server, a user's device (e.g., a smartphone), and network infrastructure.

[0191] The server first receives information about the value exchange cards held by the user and manages this information centrally. Cloud-based database software (e.g., Firebase) is used for this purpose. Next, the server calculates usage priority based on the user's location data, activity information, and the expiration date of the value exchange cards. At this time, an emotion analysis API (e.g., Microsoft Azure's Face API) is used to analyze the user's emotional state and optimize the use of the value exchange cards.

[0192] The user's emotional state is acquired using the smartphone's sensors, and this is analyzed by an emotion engine. Furthermore, the user's location information is acquired using the device's GPS function. The server comprehensively analyzes this information and provides feedback to the user recommending optimal card usage.

[0193] As a concrete example, if a user visits a shopping mall on a Sunday afternoon, it will be determined that they are in an excited emotional state. At this time, the server will recommend and notify the user of a value exchange card that offers additional points from a fashion brand store.

[0194] Through this system, users can access the most advantageous value exchange at any given time. For companies, the collected data serves as valuable information trend data for building marketing strategies.

[0195] The prompt messages for the generative AI model are as follows:

[0196] "Based on the user's emotional state, suggest the most advantageous loyalty card. The user is in a shopping mall on a Sunday afternoon. His emotional state is excited."

[0197] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0198] Step 1:

[0199] The user launches a smartphone application and enters information about their value exchange card. This information includes the card name, balance, and expiration date. The device sends this information to a cloud database. As output, the card information is stored in a centrally managed database on a server.

[0200] Step 2:

[0201] The device collects the user's location information and emotional data in real time. Location information is obtained from a GPS sensor, and emotional data is acquired through the camera and microphone, and analyzed using an emotional analysis API. The input location information and analyzed emotional data are sent to the server. As output, the user's current location and emotional state are stored on the server.

[0202] Step 3:

[0203] The server calculates usage priority based on the received location information, emotional state, and value exchange card information. In this process, a data processing program considers current promotional information and card expiration information to determine the priority of each card. The inputs are the user's location information, emotional state, and card information, and the output is a list of card usage priority levels.

[0204] Step 4:

[0205] The server notifies the user of the most recommended value exchange card based on the calculated usage priority. A recommendation message is then sent to the user's smartphone using a notification system. The input is a usage priority list, and the output is a card recommendation message to the user.

[0206] Step 5:

[0207] The server periodically collects usage data for value exchange cards and generates market trend data. This data is used to analyze the frequency of card usage and the emotional state of users at the time of use, which is then utilized for future marketing strategies. The input is usage data, and the output is a market trend analysis report.

[0208] 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.

[0209] 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.

[0210] 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.

[0211] [Second Embodiment]

[0212] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0213] 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.

[0214] 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).

[0215] 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.

[0216] 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.

[0217] 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).

[0218] 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.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] 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".

[0224] This invention provides a system for efficiently managing multiple point cards held by a user and optimizing the use of those cards. This system is configured to exchange information between a terminal, a server, and the user, and to maximize the convenience of each point card.

[0225] First, the user downloads the application via their device and enters their personal information and loyalty card details to begin using the service. The device then sends this information to a server, which stores it in a central database. This allows the user to manage all of their loyalty cards in one place.

[0226] Next, the server retrieves the user's location information and information on currently running events and promotions. Based on this, the server calculates usage priority. For example, it can prioritize selecting a point card that offers greater benefits when used at a particular store. The terminal then notifies the user of recommended point cards based on instructions from the server. This allows the user to quickly decide which card to use.

[0227] Furthermore, the server analyzes point card usage data to understand usage patterns. Using AI generation, it collects data such as which cards are frequently used on specific days and times. This analysis is provided to companies and used to develop new marketing strategies.

[0228] For example, if a user frequently shops at a particular supermarket on weekdays, the server can recommend a card that offers discounts valid during those times. Furthermore, if there is a points multiplier campaign at a nearby Starbucks, the server can notify the user of this information and help them make the most of the benefits.

[0229] In addition, the server periodically checks the expiration date of point cards and notifies the user via their terminal if the points are about to expire. This system reduces the risk of users unknowingly losing points.

[0230] Thus, the system according to the present invention can effectively manage and optimize the use of point cards, bringing benefits to both users and companies.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The user downloads the app and enters personal information and loyalty card information through their device. The device sends this information to the server. The server receives this information and stores it in a database.

[0234] Step 2:

[0235] The device acquires the user's location information and sends it to the server. The server then uses this location information to collect current promotion and event information.

[0236] Step 3:

[0237] The server calculates the usage priority based on the benefits, point balance, location information, and event information of each point card. Usage priority is an indicator that shows which point card should be used first.

[0238] Step 4:

[0239] Based on the calculated usage priority, the server generates specific card usage suggestions for the user. The terminal receives these suggestions and notifies the user with a message such as, "The recommended point card is XX."

[0240] Step 5:

[0241] When a user uses a specific loyalty card, the terminal sends usage information (store name, amount spent, date and time of use, etc.) to the server. The server records this usage data in a database.

[0242] Step 6:

[0243] The system analyzes usage patterns through data collected by the server. Generative AI is used to extract trends such as which cards are used most frequently on specific days of the week or during specific time periods.

[0244] Step 7:

[0245] Based on the analysis results, the server creates and provides market trend data to companies. This data is used by companies as a reference when formulating their promotional strategies.

[0246] Step 8:

[0247] The server periodically checks the expiration date of point cards. When the expiration date is approaching, it notifies the user via the terminal that "Points on your XX card will expire in △ days."

[0248] (Example 1)

[0249] 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."

[0250] In modern society, it is difficult for individuals to efficiently manage a large amount of identification information and authentication methods. Furthermore, there is a lack of mechanisms to support optimal choices based on individual information when utilizing this identification information, so users often miss out on opportunities to enjoy potential benefits and advantages. In addition, users risk missing out on many opportunities because they are not properly notified of the expiration dates of identification information or temporary promotional information.

[0251] 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.

[0252] In this invention, the server includes means for integrally managing data relating to multiple pieces of identification information held by a user, means for calculating a usage priority for each piece of identification information based on location data, event information, and data expiration date, and means for notifying the user of recommended identification information based on the usage priority. As a result, the user can make timely use of the most appropriate identification information for the situation, enabling efficient management and maximizing the enjoyment of benefits.

[0253] "User" refers to an individual or entity that uses the system and is responsible for possessing and managing its identification information.

[0254] "Identification information" refers to the collective term for data related to personal benefits and convenience, including loyalty cards and other authentication methods.

[0255] A "server" refers to a central computing resource within a system that handles processing, data management, and communication with users.

[0256] "Integrated management" means centralizing and organizing identification information in one place so that it can be managed efficiently.

[0257] "Location data" refers to data that indicates a user's current geographical information and is one of the factors that promotes the optimal use of identification information.

[0258] "Event information" refers to data that shows information about specific events or promotions, either geographically or temporally.

[0259] "Expiration date" refers to information such as a date that indicates the period during which identification information and its benefits can be used.

[0260] "Usage priority" refers to a priority order based on the degree of convenience and benefits expected from the use of identification information.

[0261] "Recommendation" means providing users with identification information that is considered most beneficial under specific conditions.

[0262] "External entities" refer to third parties other than users and servers, and generally include organizations and groups to which market trend data is provided.

[0263] This invention provides a system for effectively managing multiple pieces of identification information held by a user and optimizing their use. The invention utilizes information exchange between a terminal, a server, and the user as its main components.

[0264] First, the user downloads and launches a dedicated application using a mobile device or computer. The application requests the user to enter personal information and any identification data they possess upon their initial connection to the system. This information is temporarily stored on the device and then transmitted to the server.

[0265] The server analyzes the received data and stores it in a central database. Centralized management of user identification information enables rapid data access as needed. The server also collects user location data and event information, and uses a generative AI model to calculate the priority of using identification information. This allows for the identification information that is most useful to the user geographically or temporally to be identified.

[0266] The device notifies the user of recommended identification information received from the server. For example, if there is identification information that provides immediate benefits to the user when they are in a specific location, this information may be displayed on the device screen. Furthermore, data regarding the use of this identification information is collected and analyzed by the server and provided to external entities as market trend data.

[0267] This system also includes a mechanism where the server periodically checks the expiration date of identification information and notifies the user via their device when the expiration date is approaching. Furthermore, it can provide information about promotions that are about to end based on the user's location data.

[0268] As a concrete example, a user can instantly receive optimal identification information through a prompt message such as, "Please tell me the best discount information available near my current location." This allows the user to make the best choice for their situation.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] The user downloads and launches the application on their device and enters personal and identification information. The device temporarily stores the entered data and prepares to send it to the server. Specifically, the user enters information into a form and presses the submit button, which sends the data to the server. The input consists of personal and identification information, and the output is the transmission of this data to the server.

[0272] Step 2:

[0273] The server verifies personal and identification information received from the terminal and stores it in a central database. This forms the foundation for centralized data management. Specifically, the process involves accumulating data as records in the database. The input is personal and identification information from the terminal, and the output is the storage of this information in the database.

[0274] Step 3:

[0275] The server acquires user location data and event information, and uses a generative AI model to calculate the priority of using the identification information. Specifically, the AI ​​calculates the priority of the identification information according to specific conditions based on location and event information. The input is location data and event information, and the output is data calculated as the usage priority.

[0276] Step 4:

[0277] The server sends recommended identification information to the device based on the calculated usage priority. The device notifies the user of this information, specifically through push notifications or screen displays. The input is usage priority data, and the output is a notification of recommended information to the user.

[0278] Step 5:

[0279] The server collects usage data of identification information and analyzes it. It prepares to generate market trend data using a generative AI model and provide it to external entities. As a specific operation, it analyzes usage history data with AI and creates a report. The input is usage data, and the output is market trend data.

[0280] Step 6:

[0281] The server periodically checks the expiration date of identification information and, if the deadline is approaching, notifies the user through the terminal. As a specific operation, it is a mechanism that uses a reminder function to send notifications. The input is the expiration date data of identification information, and the output is a user notification when the deadline is near.

[0282] Step 7:

[0283] Based on the user's location data, the server provides promotion information that is about to end. The terminal receives this and presents it to the user. As a specific prompt sentence, there is "Please tell me the optimal discount information available around my current location", and it shows an immediate response accordingly. The input is location data, and the output is the provision of promotion information.

[0284] (Application Example 1)

[0285] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0286] In a company that provides multiple preferential services, it is not easy for individual consumers to maximize the utilization of each preferential service and manage them uniformly. Furthermore, it is difficult to effectively notify consumers of approaching expiration dates and grasp market trends while ensuring consumer convenience. Also, providing optimal sales promotion information to each consumer based on geographical location is also an issue.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0288] In this invention, the server includes means for centrally managing information on multiple preferential services held by a user, means for calculating the priority of use for each of the preferential services based on geographical location information, event information, and the expiration date of the preferential service, and means for acquiring the user's geographical location information and providing sales promotion information that is nearing its end based on that geographical location information. As a result, consumers can make the most of each preferential service, and companies can more easily grasp the usage trends of each consumer.

[0289] A "preferential service" is a system that provides added value to users through benefits and discounts offered to them.

[0290] "Geographic location information" refers to data that indicates the user's current location, and is used to provide appropriate services and information based on this information.

[0291] "Event information" refers to information about events and promotions, and is an important element for encouraging user engagement.

[0292] The "expiration date" indicates the period during which a special offer is valid, and once this date passes, it becomes unusable.

[0293] "Industry trend data" refers to information about market and consumer usage trends obtained by analyzing data on the use of preferential services.

[0294] "Sales promotion information" refers to information about special offers and campaigns provided to encourage users to make purchases.

[0295] This system is designed to efficiently manage multiple preferential services held by users and optimize their use. Users install a dedicated application on their smartphones or other devices. This application provides an interface for inputting the user's personal information and preferential service information, and has the function to send this information to a server. The server stores the received information in a central database and updates it in real time.

[0296] Based on this information, the server calculates the priority of using preferential services, using geographical location information, event information, and the expiration date of the preferential treatment. In calculating the priority, generative AI models such as TensorFlow are used to comprehensively evaluate multiple factors. The server analyzes the usage data of preferential services and utilizes machine learning algorithms to understand usage trends. For example, if there is a tendency for preferential treatment to be frequently used in a particular area on weekdays, the server can recommend preferential treatment on specific days of the week.

[0297] The analysis results are provided to external organizations and used to develop new sales strategies. When the expiration date of a discount is approaching, the server sends a notification to the user to encourage its use. It also provides currently valid sales promotion information based on geographical location to increase the user's purchasing intent. For example, it might send a notification saying, "There is currently a campaign at a nearby commercial facility where certain discounts are doubled."

[0298] Thus, the present invention effectively manages the use of preferential services and brings benefits to both users and companies.

[0299] An example of a prompt message would be: "Please tell me how to design an app that, when a user visits a location, selects the most suitable discount from all available discount services and maximizes the benefits based on effective sales promotion information."

[0300] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0301] Step 1:

[0302] The user uses the terminal to launch the application. The terminal collects the information of the preferential service and personal information input by the user, and sends this data to the server. The data to be input includes the name of the preferential service, the applicable store, the expiration date, etc. The server receives this data and stores it in the central database.

[0303] Step 2:

[0304] Based on the preferential service information sent by the user, the server obtains geographical location information and event information. Based on this information, a generative AI model such as TensorFlow is used to calculate the utilization priority of the preferential service. As input, the preferential information, location information, and event information are combined to perform data operations, and the utilization priority is output. The calculated utilization priority is saved in the central database.

[0305] Step 3:

[0306] The server periodically analyzes the usage data of the preferential service to understand the user's usage trends. In this process, past usage history and trend analysis are carried out. Using machine learning algorithms, the usage history of the preference is processed as input data to generate predicted usage trends and market trend data. This result is provided as information to external institutions.

[0307] Step 4:

[0308] The server monitors the expiration date of the preferential service and sends a notification to the terminal when the deadline approaches. In this operation, information regarding the expiration date is obtained from the database as input, and a notification message is generated when the deadline is approaching. As a notification, the preferential information approaching the deadline is presented to the user's smartphone.

[0309] Step 5:

[0310] A server that obtains the user's geographical location information generates promotional information based on the current location and sends it to the terminal. The user's current location and special offer information are used as input, and the relevant promotional information is provided as output. The application displays a notification in the form of, "There are stores nearby where you can receive special offers."

[0311] 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.

[0312] This invention provides a system that efficiently and effectively manages multiple point cards held by a user, and further combines this with an emotion engine to suggest the optimal use of point cards according to the user's emotions. This system is designed to exchange information between terminals, servers, and users, and to provide the best service based on the user's needs and emotional state.

[0313] First, the user downloads the application through their device and enters their personal information and any loyalty card information they have. The device sends this information to a server, which records it in a central database. Subsequently, the device periodically analyzes the user's emotional state using an emotion engine and sends the results to the server.

[0314] Next, the server comprehensively adjusts the user's location information, current events, and promotional information. Taking actual usage scenarios into account, it calculates usage priorities in conjunction with the user's emotional state. This priority is adjusted to prioritize cards that allow points to be used more effectively when the user's emotions are in a state that increases their desire to shop.

[0315] The server suggests the most suitable card usage for the user based on the calculated usage priority. For example, if the analysis indicates that the user is feeling stressed, it will suggest using a card that offers discounts on relaxation products. The terminal receives this suggestion and notifies the user, "Our current recommended points card is XX. Relaxation products are on sale during our special campaign."

[0316] Furthermore, the server collects loyalty card usage data and combines it with the results of the emotion engine's analysis to generate market trend data. This analysis makes it possible to comprehensively understand trends such as which cards are frequently used in which emotional states.

[0317] Companies are provided with this detailed market trend data, which can be used to develop new marketing strategies. For example, based on sentiment analysis, they can plan the most effective promotions when specific emotional states are triggered.

[0318] Thus, the present invention can effectively manage the use of point cards and provide companies with new market forecasting clues while improving the user experience by making suggestions based on the user's emotions.

[0319] The following describes the processing flow.

[0320] Step 1:

[0321] The user downloads the app through their device and enters their personal information and loyalty card information. The device sends this information to the server, which records it in a database.

[0322] Step 2:

[0323] The device transmits the user's emotional state to the emotion engine via its camera and sensors. The emotion engine analyzes the user's voice tone and facial expressions to recognize their emotions and sends the results to the server.

[0324] Step 3:

[0325] The server uses location information acquisition to determine the user's current location and also retrieves information about ongoing events. Based on this data, it generates promotional information.

[0326] Step 4:

[0327] The server integrates emotion recognition data from the emotion engine with collected location and event information to calculate usage priority. Priority is determined based on the loyalty card that best matches the user's current emotions.

[0328] Step 5:

[0329] Based on the calculation results, the server suggests to the user the use of a specific card. The terminal notifies the user of this suggestion and guides them with a message such as, "Based on your emotional state, the XX card is currently the best choice."

[0330] Step 6:

[0331] When a user uses a suggested card, the terminal records the usage data (date and time of use, location, amount, etc.) and sends it to the server. The server adds this data to its database.

[0332] Step 7:

[0333] The server analyzes usage data and emotion recognition results to identify which emotional states influence consumer behavior. As a result, detailed market trend data is generated for businesses.

[0334] Step 8:

[0335] The server provides companies with generated market trend data to help them develop emotionally driven promotions and marketing strategies. This data is then used to create new campaigns.

[0336] (Example 2)

[0337] 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".

[0338] Traditionally, there was no system in place to effectively manage and optimally utilize the reward cards held by users. Emotional states could not be considered when determining the usage status or priority of reward cards, and there was a lack of efficient methods for collecting data to understand market trends. As a result, users were unable to use their reward cards effectively, potentially leading to the risk of rewards expiring or missing out on appropriate promotions.

[0339] 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.

[0340] In this invention, the server includes means for centrally managing information on multiple reward cards held by a user, means for calculating the usage priority for each of the reward cards based on location information, event information, and the expiration date of the reward, and means for analyzing the user's emotional state and incorporating the analysis results into the calculation of usage priority. This enables the user to use reward cards that are appropriate to their emotional state and circumstances at any given time, preventing the loss of rewards and the missed opportunity for effective promotions, and also enabling them to grasp market trends.

[0341] A "reward card" is a card used by users to receive benefits when using a service or product, and includes point cards, membership cards, and other similar cards.

[0342] "Centralized management" refers to the unified management of multiple pieces of information or data within a single location or system.

[0343] "Usage priority" is an index that calculates the importance and priority of using a reward card based on specific conditions or circumstances.

[0344] "Emotional state" refers to the user's psychological state and includes various emotional states such as joy, sadness, and anger.

[0345] "Analysis" refers to the process of examining data in detail and deriving meaning and patterns from it.

[0346] "Market trend data" refers to data that shows market trends and patterns, and includes information based on the usage and emotional state of reward cards.

[0347] An "external organization" refers to a group or company that is different from the system's operator and is subject to information sharing.

[0348] This invention is a system that allows users to efficiently manage and utilize reward cards and receive optimal usage suggestions tailored to their emotional state. This system is primarily realized through the exchange of information between a server, a terminal, and the user.

[0349] Users download and begin using an application compatible with their smartphone or tablet. Through this application, users enter personal information and details about any reward cards they possess. The device collects this information and transmits it to a server using a security protocol. The server records the received information in a database in preparation for subsequent processing. Database management systems such as MySQL or MongoDB may be used for this database.

[0350] On the other hand, the device uses the user's sensor devices, such as the camera and microphone, to periodically analyze the user's emotional state. This analysis may utilize an emotion analysis engine, specifically IBM Watson or Microsoft Azure's emotion analysis API. The emotional data obtained from the device is sent to a server and managed integrally with other information.

[0351] The server calculates a priority for use based on the user's current location information, relevant event information, the expiration date of the reward card, and their emotional state. Based on this calculated priority, the server suggests the use of a specific reward card to the user. This suggestion is notified to the user via their terminal, allowing them to effectively use the reward card accordingly.

[0352] This system collects reward card usage data and combines it with the results of an emotion engine analysis to generate market trend data. Companies can use this trend data to develop new marketing strategies.

[0353] For example, if the emotion engine analyzes that the user is feeling stressed, the device might notify the user with a message like, "We recommend using the XX rewards card, which offers a discount on aromatherapy candles." This approach can improve the user experience.

[0354] An example of a prompt to a generative AI model could be: "Please show a method for providing the best reward card usage suggestion when the emotional state is stressful."

[0355] The system of this invention is designed to allow users to make the most of their reward cards, and it is also valuable to companies because it allows them to predict market trends based on the collected data.

[0356] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0357] Step 1:

[0358] The user downloads and launches the application on their device. The user enters personal information and reward card information on the application screen. The entered data is temporarily stored on the device, preparing for information transfer. This data becomes the input to the server. The device sends the user information as input data to the server via a security protocol. The server receives this data and outputs it to its database.

[0359] Step 2:

[0360] The device uses its camera and microphone to collect user emotion data. Information obtained from the user's facial expressions and voice is input into an emotion analysis engine. This engine performs calculations that output the emotional state as numerical data. The obtained emotional state data is prepared on the device for transmission to the server. The server receives this emotion data as input and uses it, along with other known user information, as material for the next calculation.

[0361] Step 3:

[0362] The server retrieves location information, event information, and the expiration date of reward cards from the database. This information is then combined with sentiment data to calculate usage priority. Specifically, a weighted averaging method is used to output a single priority index. This priority index serves as an indicator for determining which reward cards the user should use next.

[0363] Step 4:

[0364] Based on the calculated usage priority, the server generates a suggestion for the user to use the most suitable reward card. The generated suggestion is output to the terminal as a notification message. The terminal receives this and displays it to the user. Specifically, a message such as "We recommend using the XX reward card, which offers great deals on relaxation products" pops up on the terminal screen.

[0365] Step 5:

[0366] The server collects usage data for reward cards and performs calculations to generate market trend data by adding emotional data to it. This data is output as an analysis report and provided to companies. This provides information that allows them to understand trends such as which cards are preferred to be used in which emotional states.

[0367] Through these steps, the entire system will operate in a way that provides users with effective and efficient reward card services.

[0368] (Application Example 2)

[0369] 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."

[0370] There is a need for a system that efficiently manages the multiple means of value exchange held by users and suggests the optimal use of value exchange cards based on the user's emotional state and location data. This will enable users to exchange value in the most advantageous way at any given time, and in addition, it will create an environment that allows companies to efficiently analyze market trends.

[0371] 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.

[0372] In this invention, the server includes means for centrally managing information on multiple value exchange cards held by a user, means for calculating a usage priority for each of the value exchange cards based on location data, activity information, and the expiration date of the value, and means for analyzing the user's emotional state and optimizing the use of the value exchange cards based on that state. As a result, the optimal value exchange is proposed to the user, and effective value utilization based on emotional state and location information becomes possible.

[0373] A "value exchange card" is a card that allows users to obtain value in the form of points or discounts in specific activities.

[0374] "Usage priority" is an indicator that shows which value exchange cards should be used preferentially, based on factors such as location data, activity information, and value expiration dates.

[0375] "Emotional state" refers to the user's psychological and emotional condition, and is information used to optimize the user's behavior and choices based on this state.

[0376] "Information trend data" refers to data that analyzes collected value exchange card usage data to show trends and developments in the market.

[0377] "Location data" refers to data that indicates the geographical location of users and is useful for optimizing the use of activity information and value exchange cards.

[0378] The system required to implement this application consists of a server, a user's device (e.g., a smartphone), and network infrastructure.

[0379] The server first receives information about the value exchange cards held by the user and manages this information centrally. Cloud-based database software (e.g., Firebase) is used for this purpose. Next, the server calculates usage priority based on the user's location data, activity information, and the expiration date of the value exchange cards. At this time, an emotion analysis API (e.g., Microsoft Azure's Face API) is used to analyze the user's emotional state and optimize the use of the value exchange cards.

[0380] The user's emotional state is acquired using the smartphone's sensors, and this is analyzed by an emotion engine. Furthermore, the user's location information is acquired using the device's GPS function. The server comprehensively analyzes this information and provides feedback to the user recommending optimal card usage.

[0381] As a concrete example, if a user visits a shopping mall on a Sunday afternoon, it will be determined that they are in an excited emotional state. At this time, the server will recommend and notify the user of a value exchange card that offers additional points from a fashion brand store.

[0382] Through this system, users can access the most advantageous value exchange at any given time. For companies, the collected data is useful as information trend data for building marketing strategies.

[0383] The prompt messages for the generative AI model are as follows:

[0384] "Based on the user's emotional state, suggest the most advantageous loyalty card. The user is in a shopping mall on a Sunday afternoon. His emotional state is excited."

[0385] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0386] Step 1:

[0387] The user launches a smartphone application and enters information about their value exchange card. This information includes the card name, balance, and expiration date. The device sends this information to a cloud database. As output, the card information is stored in a centrally managed database on a server.

[0388] Step 2:

[0389] The device collects the user's location information and emotional data in real time. Location information is obtained from a GPS sensor, and emotional data is acquired through the camera and microphone, and analyzed using an emotional analysis API. The input location information and analyzed emotional data are sent to the server. As output, the user's current location and emotional state are stored on the server.

[0390] Step 3:

[0391] The server calculates usage priority based on the received location information, emotional state, and value exchange card information. In this process, a data processing program considers current promotional information and card expiration information to determine the priority of each card. The inputs are the user's location information, emotional state, and card information, and the output is a list of card usage priority levels.

[0392] Step 4:

[0393] The server notifies the user of the most recommended value exchange card based on the calculated usage priority. A recommendation message is then sent to the user's smartphone using a notification system. The input is a usage priority list, and the output is a card recommendation message to the user.

[0394] Step 5:

[0395] The server periodically collects usage data for value exchange cards and generates market trend data. This data is used to analyze the frequency of card usage and the emotional state of users at the time of use, and is utilized for future marketing strategies. The input is usage data, and the output is a market trend analysis report.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] [Third Embodiment]

[0400] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0401] 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.

[0402] 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).

[0403] 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.

[0404] 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.

[0405] 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).

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] 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".

[0412] This invention provides a system for efficiently managing multiple point cards held by a user and optimizing the use of those cards. This system is configured to exchange information between a terminal, a server, and the user, and to maximize the convenience of each point card.

[0413] First, the user downloads the application via their device and enters their personal information and loyalty card details to begin using the service. The device then sends this information to a server, which stores it in a central database. This allows the user to manage all of their loyalty cards in one place.

[0414] Next, the server retrieves the user's location information and information on currently running events and promotions. Based on this, the server calculates usage priority. For example, it can prioritize selecting a point card that offers greater benefits when used at a particular store. The terminal then notifies the user of recommended point cards based on instructions from the server. This allows the user to quickly decide which card to use.

[0415] Furthermore, the server analyzes point card usage data to understand usage patterns. Using AI generation, it collects data such as which cards are frequently used on specific days and times. This analysis is provided to companies and used to develop new marketing strategies.

[0416] For example, if a user frequently shops at a particular supermarket on weekdays, the server can recommend a card that offers discounts valid during those times. Furthermore, if there is a points multiplier campaign at a nearby Starbucks, the server can notify the user of this information and help them make the most of the benefits.

[0417] In addition, the server periodically checks the expiration date of point cards and notifies the user via their terminal if the points are about to expire. This system reduces the risk of users unknowingly losing points.

[0418] Thus, the system according to the present invention can effectively manage and optimize the use of point cards, bringing benefits to both users and companies.

[0419] The following describes the processing flow.

[0420] Step 1:

[0421] The user downloads the app and enters personal information and loyalty card information through their device. The device sends this information to the server. The server receives this information and stores it in a database.

[0422] Step 2:

[0423] The device acquires the user's location information and sends it to the server. The server then uses this location information to collect current promotion and event information.

[0424] Step 3:

[0425] The server calculates the usage priority based on the benefits, point balance, location information, and event information of each point card. Usage priority is an indicator that shows which point card should be used first.

[0426] Step 4:

[0427] Based on the calculated usage priority, the server generates specific card usage suggestions for the user. The terminal receives these suggestions and notifies the user with a message such as, "The recommended point card is XX."

[0428] Step 5:

[0429] When a user uses a specific loyalty card, the terminal sends usage information (store name, amount spent, date and time of use, etc.) to the server. The server records this usage data in a database.

[0430] Step 6:

[0431] The system analyzes usage patterns through data collected by the server. Generative AI is used to extract trends such as which cards are used most frequently on specific days of the week or during specific time periods.

[0432] Step 7:

[0433] Based on the analysis results, the server creates and provides market trend data to companies. This data is used by companies as a reference when formulating their promotional strategies.

[0434] Step 8:

[0435] The server periodically checks the expiration date of point cards. When the expiration date is approaching, it notifies the user via the terminal that "Points on your XX card will expire in △ days."

[0436] (Example 1)

[0437] 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."

[0438] In modern society, it is difficult for individuals to efficiently manage a large amount of identification information and authentication methods. Furthermore, there is a lack of mechanisms to support optimal choices based on individual information when utilizing this identification information, so users often miss out on opportunities to enjoy potential benefits and advantages. In addition, users risk missing out on many opportunities because they are not properly notified of the expiration dates of identification information or temporary promotional information.

[0439] 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.

[0440] In this invention, the server includes means for integrally managing data relating to multiple pieces of identification information held by a user, means for calculating a usage priority for each piece of identification information based on location data, event information, and data expiration date, and means for notifying the user of recommended identification information based on the usage priority. As a result, the user can make timely use of the most appropriate identification information for the situation, enabling efficient management and maximizing the enjoyment of benefits.

[0441] "User" refers to an individual or entity that uses the system and is responsible for possessing and managing its identification information.

[0442] "Identification information" refers to the collective term for data related to personal benefits and convenience, including loyalty cards and other authentication methods.

[0443] A "server" refers to a central computing resource within a system that handles processing, data management, and communication with users.

[0444] "Integrated management" means centralizing and organizing identification information in one place so that it can be managed efficiently.

[0445] "Location data" refers to data that indicates a user's current geographical information and is one of the factors that promotes the optimal use of identification information.

[0446] "Event information" refers to data that shows information about specific events or promotions, either geographically or temporally.

[0447] "Expiration date" refers to information such as a date that indicates the period during which identification information and its benefits can be used.

[0448] "Usage priority" refers to a priority order based on the degree of convenience and benefits expected from the use of identification information.

[0449] "Recommendation" means providing users with identification information that is considered most beneficial under specific conditions.

[0450] "External entities" refer to third parties other than users and servers, and generally include organizations and groups to which market trend data is provided.

[0451] This invention provides a system for effectively managing multiple pieces of identification information held by a user and optimizing their use. The invention utilizes information exchange between a terminal, a server, and the user as its main components.

[0452] First, the user downloads and launches a dedicated application using a mobile device or computer. The application requests the user to enter personal information and any identification data they possess upon their initial connection to the system. This information is temporarily stored on the device and then transmitted to the server.

[0453] The server analyzes the received data and stores it in a central database. Centralized management of user identification information enables rapid data access as needed. The server also collects user location data and event information, and uses a generative AI model to calculate the priority of using identification information. This allows for the identification information that is most useful to the user geographically or temporally to be identified.

[0454] The device notifies the user of recommended identification information received from the server. For example, if there is identification information that provides immediate benefits to the user when they are in a specific location, this information may be displayed on the device screen. Furthermore, data regarding the use of this identification information is collected and analyzed by the server and provided to external entities as market trend data.

[0455] This system also includes a mechanism where the server periodically checks the expiration date of identification information and notifies the user via their device when the expiration date is approaching. Furthermore, it can provide information about promotions that are about to end based on the user's location data.

[0456] As a concrete example, a user can instantly receive optimal identification information through a prompt message such as, "Please tell me the best discount information available near my current location." This allows the user to make the best choice for their situation.

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

[0458] Step 1:

[0459] The user downloads and launches the application on their device and enters personal and identification information. The device temporarily stores the entered data and prepares to send it to the server. Specifically, the user enters information into a form and presses the submit button, which sends the data to the server. The input consists of personal and identification information, and the output is the transmission of this data to the server.

[0460] Step 2:

[0461] The server verifies personal and identification information received from the terminal and stores it in a central database. This forms the foundation for centralized data management. Specifically, the process involves accumulating data as records in the database. The input is personal and identification information from the terminal, and the output is the storage of this information in the database.

[0462] Step 3:

[0463] The server acquires user location data and event information, and uses a generative AI model to calculate the priority of using the identification information. Specifically, the AI ​​calculates the priority of the identification information according to specific conditions based on location and event information. The input is location data and event information, and the output is data calculated as the usage priority.

[0464] Step 4:

[0465] The server sends recommended identification information to the device based on the calculated usage priority. The device notifies the user of this information, specifically through push notifications or screen displays. The input is usage priority data, and the output is a notification of recommended information to the user.

[0466] Step 5:

[0467] The server collects and analyzes usage data for identification information. It utilizes a generative AI model to generate market trend data and prepares it for provision to external entities. Specifically, it analyzes usage history data using AI and creates reports. The input is usage data, and the output is market trend data.

[0468] Step 6:

[0469] The server periodically checks the expiration date of the identification information and notifies the user via the terminal when the expiration date is approaching. Specifically, it uses a reminder function to send notifications. The input is the expiration date data of the identification information, and the output is a user notification when the expiration date is approaching.

[0470] Step 7:

[0471] The server provides information about promotions that are about to end based on the user's location data. The terminal receives this information and presents it to the user. A specific prompt might be, "Please tell me the best discounts available near my current location," to which the terminal responds immediately. The input is location data, and the output is the provision of promotion information.

[0472] (Application Example 1)

[0473] 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."

[0474] For companies offering multiple preferential treatment services, it is not easy for individual consumers to maximize the use of each service and manage them centrally. Furthermore, it is difficult to effectively notify consumers of expiring benefits, ensure consumer convenience, and grasp market trends. Providing each consumer with the most relevant sales promotion information based on their geographical location is also a challenge.

[0475] 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.

[0476] In this invention, the server includes means for centrally managing information on multiple preferential services held by a user, means for calculating the priority of use for each of the preferential services based on geographical location information, event information, and the expiration date of the preferential service, and means for acquiring the user's geographical location information and providing sales promotion information that is nearing its end based on that geographical location information. As a result, consumers can make the most of each preferential service, and companies can more easily grasp the usage trends of each consumer.

[0477] A "preferential service" is a system that provides added value to users through benefits and discounts offered to them.

[0478] "Geographic location information" refers to data that indicates the user's current location, and is used to provide appropriate services and information based on this information.

[0479] "Event information" refers to information about events and promotions, and is an important element for encouraging user engagement.

[0480] The "expiration date" indicates the period during which a special offer is valid, and once this date passes, it becomes unusable.

[0481] "Industry trend data" refers to information about market and consumer usage trends obtained by analyzing data on the use of preferential services.

[0482] "Sales promotion information" refers to information about special offers and campaigns provided to encourage users to make purchases.

[0483] This system is designed to efficiently manage multiple preferential services held by users and optimize their use. Users install a dedicated application on their smartphones or other devices. This application provides an interface for inputting the user's personal information and preferential service information, and has the function to send this information to a server. The server stores the received information in a central database and updates it in real time.

[0484] Based on this information, the server calculates the priority of using preferential services, using geographical location information, event information, and the expiration date of the preferential treatment. In calculating the priority, generative AI models such as TensorFlow are used to comprehensively evaluate multiple factors. The server analyzes the usage data of preferential services and utilizes machine learning algorithms to understand usage trends. For example, if there is a tendency for preferential treatment to be frequently used in a particular area on weekdays, the server can recommend preferential treatment on specific days of the week.

[0485] The analysis results are provided to external organizations and used to develop new sales strategies. When the expiration date of a discount is approaching, the server sends a notification to the user to encourage its use. It also provides currently valid sales promotion information based on geographical location to increase the user's purchasing intent. For example, it might send a notification saying, "There is currently a campaign at a nearby commercial facility where certain discounts are doubled."

[0486] Thus, the present invention effectively manages the use of preferential services and brings benefits to both users and companies.

[0487] An example of a prompt message would be: "Please tell me how to design an app that, when a user visits a location, selects the most suitable discount from all available discount services and maximizes the benefits based on effective sales promotion information."

[0488] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0489] Step 1:

[0490] The user launches the application using their device. The device collects information about the promotional service and personal information entered by the user and sends this data to the server. The entered data includes the name of the promotional service, applicable stores, and expiration date. The server receives this data and stores it in a central database.

[0491] Step 2:

[0492] The server acquires geographical location information and event information based on the preferential service information submitted by users. Using this information, it employs a generative AI model such as TensorFlow to calculate the priority of using the preferential services. It combines the preferential service information, location information, and event information as input to perform data calculations and output the priority of use. The calculated priority is stored in a central database.

[0493] Step 3:

[0494] The server periodically analyzes usage data for the preferential treatment service to understand user trends. This process involves analyzing past usage history and trends. Using machine learning algorithms, it processes the usage history of the preferential treatment service as input data and generates predictive usage trends and market trend data. These results are provided as information to external organizations.

[0495] Step 4:

[0496] The server monitors the expiration date of discount services and sends a notification to the device when the deadline approaches. This process retrieves information about the expiration date from the database and generates a notification message when the deadline is nearing. The notification displays information about discounts that are about to expire on the user's smartphone.

[0497] Step 5:

[0498] A server that obtains the user's geographical location information generates promotional information based on the current location and sends it to the terminal. The user's current location and special offer information are used as input, and the relevant promotional information is provided as output. The application displays a notification in the form of, "There are stores nearby where you can receive special offers."

[0499] 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.

[0500] This invention provides a system that efficiently and effectively manages multiple point cards held by a user, and further combines this with an emotion engine to suggest the optimal use of point cards according to the user's emotions. This system is designed to exchange information between terminals, servers, and users, and to provide the best service based on the user's needs and emotional state.

[0501] First, the user downloads the application through their device and enters their personal information and any loyalty card information they have. The device sends this information to a server, which records it in a central database. Subsequently, the device periodically analyzes the user's emotional state using an emotion engine and sends the results to the server.

[0502] Next, the server comprehensively adjusts the user's location information, current events, and promotional information. Taking actual usage scenarios into account, it calculates usage priorities in conjunction with the user's emotional state. This priority is adjusted to prioritize cards that allow points to be used more effectively when the user's emotions are in a state that increases their desire to shop.

[0503] The server suggests the most suitable card usage for the user based on the calculated usage priority. For example, if the analysis indicates that the user is feeling stressed, it will suggest using a card that offers discounts on relaxation products. The terminal receives this suggestion and notifies the user, "Our current recommended points card is XX. Relaxation products are on sale during our special campaign."

[0504] Furthermore, the server collects loyalty card usage data and combines it with the results of the emotion engine's analysis to generate market trend data. This analysis makes it possible to comprehensively understand trends such as which cards are frequently used in which emotional states.

[0505] Companies are provided with this detailed market trend data, which can be used to develop new marketing strategies. For example, based on sentiment analysis, they can plan the most effective promotions when specific emotional states are triggered.

[0506] Thus, the present invention can effectively manage the use of point cards and provide companies with new market forecasting clues while improving the user experience by making suggestions based on the user's emotions.

[0507] The following describes the processing flow.

[0508] Step 1:

[0509] The user downloads the app through their device and enters their personal information and loyalty card information. The device sends this information to the server, which records it in a database.

[0510] Step 2:

[0511] The device transmits the user's emotional state to the emotion engine via its camera and sensors. The emotion engine analyzes the user's voice tone and facial expressions to recognize their emotions and sends the results to the server.

[0512] Step 3:

[0513] The server uses location information acquisition to determine the user's current location and also retrieves information about ongoing events. Based on this data, it generates promotional information.

[0514] Step 4:

[0515] The server integrates emotion recognition data from the emotion engine with collected location and event information to calculate usage priority. Priority is determined based on the loyalty card that best matches the user's current emotions.

[0516] Step 5:

[0517] Based on the calculation results, the server suggests to the user the use of a specific card. The terminal notifies the user of this suggestion and guides them with a message such as, "Based on your emotional state, the XX card is currently the best choice."

[0518] Step 6:

[0519] When a user uses a suggested card, the terminal records the usage data (date and time of use, location, amount, etc.) and sends it to the server. The server adds this data to its database.

[0520] Step 7:

[0521] The server analyzes usage data and emotion recognition results to identify which emotional states influence consumer behavior. As a result, detailed market trend data is generated for businesses.

[0522] Step 8:

[0523] The server provides companies with generated market trend data to help them develop emotionally driven promotions and marketing strategies. This data is then used to create new campaigns.

[0524] (Example 2)

[0525] 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."

[0526] Traditionally, there was no system in place to effectively manage and optimally utilize the reward cards held by users. Emotional states could not be considered when determining the usage status or priority of reward cards, and there was a lack of efficient methods for collecting data to understand market trends. As a result, users were unable to use their reward cards effectively, potentially leading to the risk of rewards expiring or missing out on appropriate promotions.

[0527] 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.

[0528] In this invention, the server includes means for centrally managing information on multiple reward cards held by a user, means for calculating the usage priority for each of the reward cards based on location information, event information, and the expiration date of the reward, and means for analyzing the user's emotional state and incorporating the analysis results into the calculation of usage priority. This enables the user to use reward cards that are appropriate to their emotional state and circumstances at any given time, preventing the loss of rewards and the missed opportunity for effective promotions, and also enabling them to grasp market trends.

[0529] A "reward card" is a card used by users to receive benefits when using a service or product, and includes point cards, membership cards, and other similar cards.

[0530] "Centralized management" refers to the unified management of multiple pieces of information or data within a single location or system.

[0531] "Usage priority" is an index that calculates the importance and priority of using a reward card based on specific conditions or circumstances.

[0532] "Emotional state" refers to the user's psychological state and includes various emotional states such as joy, sadness, and anger.

[0533] "Analysis" refers to the process of examining data in detail and deriving meaning and patterns from it.

[0534] "Market trend data" refers to data that shows market trends and patterns, and includes information based on the usage and emotional state of reward cards.

[0535] An "external organization" refers to a group or company that is different from the system's operator and is subject to information sharing.

[0536] This invention is a system that allows users to efficiently manage and utilize reward cards and receive optimal usage suggestions tailored to their emotional state. This system is primarily realized through the exchange of information between a server, a terminal, and the user.

[0537] Users download and begin using an application compatible with their smartphone or tablet. Through this application, users enter personal information and details about any reward cards they possess. The device collects this information and transmits it to a server using a security protocol. The server records the received information in a database in preparation for subsequent processing. Database management systems such as MySQL or MongoDB may be used for this database.

[0538] On the other hand, the device uses the user's sensor devices, such as the camera and microphone, to periodically analyze the user's emotional state. This analysis may utilize an emotion analysis engine, specifically IBM Watson or Microsoft Azure's emotion analysis API. The emotional data obtained from the device is sent to a server and managed integrally with other information.

[0539] The server calculates a priority for use based on the user's current location information, relevant event information, the expiration date of the reward card, and their emotional state. Based on this calculated priority, the server suggests the use of a specific reward card to the user. This suggestion is notified to the user via their terminal, allowing them to effectively use the reward card accordingly.

[0540] This system collects reward card usage data and combines it with the results of an emotion engine analysis to generate market trend data. Companies can use this trend data to develop new marketing strategies.

[0541] For example, if the emotion engine analyzes that the user is feeling stressed, the device might notify the user with a message like, "We recommend using the XX rewards card, which offers a discount on aromatherapy candles." This approach can improve the user experience.

[0542] An example of a prompt to a generative AI model could be: "Please show a method for providing the best reward card usage suggestion when the emotional state is stressful."

[0543] The system of this invention is designed to allow users to make the most of their reward cards, and it is also valuable to companies because it allows them to predict market trends based on the collected data.

[0544] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0545] Step 1:

[0546] The user downloads and launches the application on their device. The user enters personal information and reward card information on the application screen. The entered data is temporarily stored on the device, preparing for information transfer. This data becomes the input to the server. The device sends the user information as input data to the server via a security protocol. The server receives this data and outputs it to its database.

[0547] Step 2:

[0548] The device uses its camera and microphone to collect user emotion data. Information obtained from the user's facial expressions and voice is input into an emotion analysis engine. This engine performs calculations that output the emotional state as numerical data. The obtained emotional state data is prepared on the device for transmission to the server. The server receives this emotion data as input and uses it, along with other known user information, as material for the next calculation.

[0549] Step 3:

[0550] The server retrieves location information, event information, and the expiration date of reward cards from the database. This information is then combined with sentiment data to calculate usage priority. Specifically, a weighted averaging method is used to output a single priority index. This priority index serves as an indicator for determining which reward cards the user should use next.

[0551] Step 4:

[0552] Based on the calculated usage priority, the server generates a suggestion for the user to use the most suitable reward card. The generated suggestion is output to the terminal as a notification message. The terminal receives this and displays it to the user. Specifically, a message such as "We recommend using the XX reward card, which offers great deals on relaxation products" pops up on the terminal screen.

[0553] Step 5:

[0554] The server collects usage data for reward cards and performs calculations to generate market trend data by adding emotional data to it. This data is output as an analysis report and provided to companies. This provides information that allows them to understand trends such as which cards are preferred to be used in which emotional states.

[0555] Through these steps, the entire system will operate in a way that provides users with effective and efficient reward card services.

[0556] (Application Example 2)

[0557] 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."

[0558] There is a need for a system that efficiently manages the multiple means of value exchange held by users and suggests the optimal use of value exchange cards based on the user's emotional state and location data. This will enable users to exchange value in the most advantageous way at any given time, and in addition, it will create an environment that allows companies to efficiently analyze market trends.

[0559] 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.

[0560] In this invention, the server includes means for centrally managing information on multiple value exchange cards held by a user, means for calculating a usage priority for each of the value exchange cards based on location data, activity information, and the expiration date of the value, and means for analyzing the user's emotional state and optimizing the use of the value exchange cards based on that state. As a result, the optimal value exchange is proposed to the user, and effective value utilization based on emotional state and location information becomes possible.

[0561] A "value exchange card" is a card that allows users to obtain value in the form of points or discounts in specific activities.

[0562] "Usage priority" is an indicator that shows which value exchange cards should be used preferentially, based on factors such as location data, activity information, and value expiration dates.

[0563] "Emotional state" refers to the user's psychological and emotional condition, and is information used to optimize the user's behavior and choices based on this state.

[0564] "Information trend data" refers to data that analyzes collected value exchange card usage data to show trends and developments in the market.

[0565] "Location data" refers to data that indicates the geographical location of users and is useful for optimizing the use of activity information and value exchange cards.

[0566] The system required to implement this application consists of a server, a user's device (e.g., a smartphone), and network infrastructure.

[0567] The server first receives information about the value exchange cards held by the user and manages this information centrally. Cloud-based database software (e.g., Firebase) is used for this purpose. Next, the server calculates usage priority based on the user's location data, activity information, and the expiration date of the value exchange cards. At this time, an emotion analysis API (e.g., Microsoft Azure's Face API) is used to analyze the user's emotional state and optimize the use of the value exchange cards.

[0568] The user's emotional state is acquired using the smartphone's sensors, and this is analyzed by an emotion engine. Furthermore, the user's location information is acquired using the device's GPS function. The server comprehensively analyzes this information and provides feedback to the user recommending optimal card usage.

[0569] As a concrete example, if a user visits a shopping mall on a Sunday afternoon, it will be determined that they are in an excited emotional state. At this time, the server will recommend and notify the user of a value exchange card that offers additional points from a fashion brand store.

[0570] Through this system, users can access the most advantageous value exchange at any given time. For companies, the collected data is useful as information trend data for building marketing strategies.

[0571] The prompt messages for the generative AI model are as follows:

[0572] "Based on the user's emotional state, suggest the most advantageous loyalty card. The user is in a shopping mall on a Sunday afternoon. His emotional state is excited."

[0573] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0574] Step 1:

[0575] The user launches a smartphone application and enters information about their value exchange card. This information includes the card name, balance, and expiration date. The device sends this information to a cloud database. As output, the card information is stored in a centrally managed database on a server.

[0576] Step 2:

[0577] The device collects the user's location information and emotional data in real time. Location information is obtained from a GPS sensor, and emotional data is acquired through the camera and microphone, and analyzed using an emotional analysis API. The input location information and analyzed emotional data are sent to the server. As output, the user's current location and emotional state are stored on the server.

[0578] Step 3:

[0579] The server calculates usage priority based on the received location information, emotional state, and value exchange card information. In this process, a data processing program considers current promotional information and card expiration information to determine the priority of each card. The inputs are the user's location information, emotional state, and card information, and the output is a list of card usage priority levels.

[0580] Step 4:

[0581] The server notifies the user of the most recommended value exchange card based on the calculated usage priority. A recommendation message is then sent to the user's smartphone using a notification system. The input is a usage priority list, and the output is a card recommendation message to the user.

[0582] Step 5:

[0583] The server periodically collects usage data for value exchange cards and generates market trend data. This data is used to analyze the frequency of card usage and the emotional state of users at the time of use, and is utilized for future marketing strategies. The input is usage data, and the output is a market trend analysis report.

[0584] 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.

[0585] 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.

[0586] 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.

[0587] [Fourth Embodiment]

[0588] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0589] 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.

[0590] 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).

[0591] 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.

[0592] 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.

[0593] 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).

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] 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".

[0601] This invention provides a system for efficiently managing multiple point cards held by a user and optimizing the use of those cards. This system is configured to exchange information between a terminal, a server, and the user, and to maximize the convenience of each point card.

[0602] First, the user downloads the application via their device and enters their personal information and loyalty card details to begin using the service. The device then sends this information to a server, which stores it in a central database. This allows the user to manage all of their loyalty cards in one place.

[0603] Next, the server retrieves the user's location information and information on currently running events and promotions. Based on this, the server calculates usage priority. For example, it can prioritize selecting a point card that offers greater benefits when used at a particular store. The terminal then notifies the user of recommended point cards based on instructions from the server. This allows the user to quickly decide which card to use.

[0604] Furthermore, the server analyzes point card usage data to understand usage patterns. Using AI generation, it collects data such as which cards are frequently used on specific days and times. This analysis is provided to companies and used to develop new marketing strategies.

[0605] For example, if a user frequently shops at a particular supermarket on weekdays, the server can recommend a card that offers discounts valid during those times. Furthermore, if there is a points multiplier campaign at a nearby Starbucks, the server can notify the user of this information and help them make the most of the benefits.

[0606] In addition, the server periodically checks the expiration date of point cards and notifies the user via their terminal if the points are about to expire. This system reduces the risk of users unknowingly losing points.

[0607] Thus, the system according to the present invention can effectively manage and optimize the use of point cards, bringing benefits to both users and companies.

[0608] The following describes the processing flow.

[0609] Step 1:

[0610] The user downloads the app and enters personal information and loyalty card information through their device. The device sends this information to the server. The server receives this information and stores it in a database.

[0611] Step 2:

[0612] The device acquires the user's location information and sends it to the server. The server then uses this location information to collect current promotion and event information.

[0613] Step 3:

[0614] The server calculates the usage priority based on the benefits, point balance, location information, and event information of each point card. Usage priority is an indicator that shows which point card should be used first.

[0615] Step 4:

[0616] Based on the calculated usage priority, the server generates specific card usage suggestions for the user. The terminal receives these suggestions and notifies the user with a message such as, "The recommended point card is XX."

[0617] Step 5:

[0618] When a user uses a specific loyalty card, the terminal sends usage information (store name, amount spent, date and time of use, etc.) to the server. The server records this usage data in a database.

[0619] Step 6:

[0620] The system analyzes usage patterns through data collected by the server. Generative AI is used to extract trends such as which cards are used most frequently on specific days of the week or during specific time periods.

[0621] Step 7:

[0622] Based on the analysis results, the server creates and provides market trend data to companies. This data is used by companies as a reference when formulating their promotional strategies.

[0623] Step 8:

[0624] The server periodically checks the expiration date of point cards. When the expiration date is approaching, it notifies the user via the terminal that "Points on your XX card will expire in △ days."

[0625] (Example 1)

[0626] 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".

[0627] In modern society, it is difficult for individuals to efficiently manage a large amount of identification information and authentication methods. Furthermore, there is a lack of mechanisms to support optimal choices based on individual information when utilizing this identification information, so users often miss out on opportunities to enjoy potential benefits and advantages. In addition, users risk missing out on many opportunities because they are not properly notified of the expiration dates of identification information or temporary promotional information.

[0628] 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.

[0629] In this invention, the server includes means for integrally managing data relating to multiple pieces of identification information held by a user, means for calculating a usage priority for each piece of identification information based on location data, event information, and data expiration date, and means for notifying the user of recommended identification information based on the usage priority. As a result, the user can make timely use of the most appropriate identification information for the situation, enabling efficient management and maximizing the enjoyment of benefits.

[0630] "User" refers to an individual or entity that uses the system and is responsible for possessing and managing its identification information.

[0631] "Identification information" refers to the collective term for data related to personal benefits and convenience, including loyalty cards and other authentication methods.

[0632] A "server" refers to a central computing resource within a system that handles processing, data management, and communication with users.

[0633] "Integrated management" means centralizing and organizing identification information in one place so that it can be managed efficiently.

[0634] "Location data" refers to data that indicates a user's current geographical information and is one of the factors that promotes the optimal use of identification information.

[0635] "Event information" refers to data that shows information about specific events or promotions, either geographically or temporally.

[0636] "Expiration date" refers to information such as a date that indicates the period during which identification information and its benefits can be used.

[0637] "Usage priority" refers to a priority order based on the degree of convenience and benefits expected from the use of identification information.

[0638] "Recommendation" means providing users with identification information that is considered most beneficial under specific conditions.

[0639] "External entities" refer to third parties other than users and servers, and generally include organizations and groups to which market trend data is provided.

[0640] This invention provides a system for effectively managing multiple pieces of identification information held by a user and optimizing their use. The invention utilizes information exchange between a terminal, a server, and the user as its main components.

[0641] First, the user downloads and launches a dedicated application using a mobile device or computer. The application requests the user to enter personal information and any identification data they possess upon their initial connection to the system. This information is temporarily stored on the device and then transmitted to the server.

[0642] The server analyzes the received data and stores it in a central database. Centralized management of user identification information enables rapid data access as needed. The server also collects user location data and event information, and uses a generative AI model to calculate the priority of using identification information. This allows for the identification information that is most useful to the user geographically or temporally to be identified.

[0643] The device notifies the user of recommended identification information received from the server. For example, if there is identification information that provides immediate benefits to the user when they are in a specific location, this information may be displayed on the device screen. Furthermore, data regarding the use of this identification information is collected and analyzed by the server and provided to external entities as market trend data.

[0644] This system also includes a mechanism where the server periodically checks the expiration date of identification information and notifies the user via their device when the expiration date is approaching. Furthermore, it can provide information about promotions that are about to end based on the user's location data.

[0645] As a concrete example, a user can instantly receive optimal identification information through a prompt message such as, "Please tell me the best discount information available near my current location." This allows the user to make the best choice for their situation.

[0646] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0647] Step 1:

[0648] The user downloads and launches the application on their device and enters personal and identification information. The device temporarily stores the entered data and prepares to send it to the server. Specifically, the user enters information into a form and presses the submit button, which sends the data to the server. The input consists of personal and identification information, and the output is the transmission of this data to the server.

[0649] Step 2:

[0650] The server verifies personal and identification information received from the terminal and stores it in a central database. This forms the foundation for centralized data management. Specifically, the process involves accumulating data as records in the database. The input is personal and identification information from the terminal, and the output is the storage of this information in the database.

[0651] Step 3:

[0652] The server acquires user location data and event information, and uses a generative AI model to calculate the priority of using the identification information. Specifically, the AI ​​calculates the priority of the identification information according to specific conditions based on location and event information. The input is location data and event information, and the output is data calculated as the usage priority.

[0653] Step 4:

[0654] The server sends recommended identification information to the device based on the calculated usage priority. The device notifies the user of this information, specifically through push notifications or screen displays. The input is usage priority data, and the output is a notification of recommended information to the user.

[0655] Step 5:

[0656] The server collects and analyzes usage data for identification information. It utilizes a generative AI model to generate market trend data and prepares it for provision to external entities. Specifically, it analyzes usage history data using AI and creates reports. The input is usage data, and the output is market trend data.

[0657] Step 6:

[0658] The server periodically checks the expiration date of the identification information and notifies the user via the terminal when the expiration date is approaching. Specifically, it uses a reminder function to send notifications. The input is the expiration date data of the identification information, and the output is a user notification when the expiration date is approaching.

[0659] Step 7:

[0660] The server provides information about promotions that are about to end based on the user's location data. The terminal receives this information and presents it to the user. A specific prompt might be, "Please tell me the best discounts available near my current location," to which the terminal responds immediately. The input is location data, and the output is the provision of promotion information.

[0661] (Application Example 1)

[0662] 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".

[0663] For companies offering multiple preferential treatment services, it is not easy for individual consumers to maximize the use of each service and manage them centrally. Furthermore, it is difficult to effectively notify consumers of expiring benefits, ensure consumer convenience, and grasp market trends. Providing each consumer with the most relevant sales promotion information based on their geographical location is also a challenge.

[0664] 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.

[0665] In this invention, the server includes means for centrally managing information on multiple preferential services held by a user, means for calculating the priority of use for each of the preferential services based on geographical location information, event information, and the expiration date of the preferential service, and means for acquiring the user's geographical location information and providing sales promotion information that is nearing its end based on that geographical location information. As a result, consumers can make the most of each preferential service, and companies can more easily grasp the usage trends of each consumer.

[0666] A "preferential service" is a system that provides added value to users through benefits and discounts offered to them.

[0667] "Geographic location information" refers to data that indicates the user's current location, and is used to provide appropriate services and information based on this information.

[0668] "Event information" refers to information about events and promotions, and is an important element for encouraging user engagement.

[0669] The "expiration date" indicates the period during which a special offer is valid, and once this date passes, it becomes unusable.

[0670] "Industry trend data" refers to information about market and consumer usage trends obtained by analyzing data on the use of preferential services.

[0671] "Sales promotion information" refers to information about special offers and campaigns provided to encourage users to make purchases.

[0672] This system is designed to efficiently manage multiple preferential services held by users and optimize their use. Users install a dedicated application on their smartphones or other devices. This application provides an interface for inputting the user's personal information and preferential service information, and has the function to send this information to a server. The server stores the received information in a central database and updates it in real time.

[0673] Based on this information, the server calculates the priority of using preferential services, using geographical location information, event information, and the expiration date of the preferential treatment. In calculating the priority, generative AI models such as TensorFlow are used to comprehensively evaluate multiple factors. The server analyzes the usage data of preferential services and utilizes machine learning algorithms to understand usage trends. For example, if there is a tendency for preferential treatment to be frequently used in a particular area on weekdays, the server can recommend preferential treatment on specific days of the week.

[0674] The analysis results are provided to external organizations and used to develop new sales strategies. When the expiration date of a discount is approaching, the server sends a notification to the user to encourage its use. It also provides currently valid sales promotion information based on geographical location to increase the user's purchasing intent. For example, it might send a notification saying, "There is currently a campaign at a nearby commercial facility where certain discounts are doubled."

[0675] Thus, the present invention effectively manages the use of preferential services and brings benefits to both users and companies.

[0676] An example of a prompt message would be: "Please tell me how to design an app that, when a user visits a location, selects the most suitable discount from all available discount services and maximizes the benefits based on effective sales promotion information."

[0677] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0678] Step 1:

[0679] The user launches the application using their device. The device collects information about the promotional service and personal information entered by the user and sends this data to the server. The entered data includes the name of the promotional service, applicable stores, and expiration date. The server receives this data and stores it in a central database.

[0680] Step 2:

[0681] The server acquires geographical location information and event information based on the preferential service information submitted by users. Using this information, it employs a generative AI model such as TensorFlow to calculate the priority of using the preferential services. It combines the preferential service information, location information, and event information as input to perform data calculations and output the priority of use. The calculated priority is stored in a central database.

[0682] Step 3:

[0683] The server periodically analyzes usage data for the preferential treatment service to understand user trends. This process involves analyzing past usage history and trends. Using machine learning algorithms, it processes the usage history of the preferential treatment service as input data and generates predictive usage trends and market trend data. These results are provided as information to external organizations.

[0684] Step 4:

[0685] The server monitors the expiration date of discount services and sends a notification to the device when the deadline approaches. This process retrieves information about the expiration date from the database and generates a notification message when the deadline is nearing. The notification displays information about discounts that are about to expire on the user's smartphone.

[0686] Step 5:

[0687] A server that obtains the user's geographical location information generates promotional information based on the current location and sends it to the terminal. The user's current location and special offer information are used as input, and the relevant promotional information is provided as output. The application displays a notification in the form of, "There are stores nearby where you can receive special offers."

[0688] 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.

[0689] This invention provides a system that efficiently and effectively manages multiple point cards held by a user, and further combines this with an emotion engine to suggest the optimal use of point cards according to the user's emotions. This system is designed to exchange information between terminals, servers, and users, and to provide the best service based on the user's needs and emotional state.

[0690] First, the user downloads the application through their device and enters their personal information and any loyalty card information they have. The device sends this information to a server, which records it in a central database. Subsequently, the device periodically analyzes the user's emotional state using an emotion engine and sends the results to the server.

[0691] Next, the server comprehensively adjusts the user's location information, current events, and promotional information. Taking actual usage scenarios into account, it calculates usage priorities in conjunction with the user's emotional state. This priority is adjusted to prioritize cards that allow points to be used more effectively when the user's emotions are in a state that increases their desire to shop.

[0692] The server suggests the most suitable card usage for the user based on the calculated usage priority. For example, if the analysis indicates that the user is feeling stressed, it will suggest using a card that offers discounts on relaxation products. The terminal receives this suggestion and notifies the user, "Our current recommended points card is XX. Relaxation products are on sale during our special campaign."

[0693] Furthermore, the server collects loyalty card usage data and combines it with the results of the emotion engine's analysis to generate market trend data. This analysis makes it possible to comprehensively understand trends such as which cards are frequently used in which emotional states.

[0694] Companies are provided with this detailed market trend data, which can be used to develop new marketing strategies. For example, based on sentiment analysis, they can plan the most effective promotions when specific emotional states are triggered.

[0695] Thus, the present invention can effectively manage the use of point cards and provide companies with new market forecasting clues while improving the user experience by making suggestions based on the user's emotions.

[0696] The following describes the processing flow.

[0697] Step 1:

[0698] The user downloads the app through their device and enters their personal information and loyalty card information. The device sends this information to the server, which records it in a database.

[0699] Step 2:

[0700] The device transmits the user's emotional state to the emotion engine via its camera and sensors. The emotion engine analyzes the user's voice tone and facial expressions to recognize their emotions and sends the results to the server.

[0701] Step 3:

[0702] The server uses location information acquisition to determine the user's current location and also retrieves information about ongoing events. Based on this data, it generates promotional information.

[0703] Step 4:

[0704] The server integrates emotion recognition data from the emotion engine with collected location and event information to calculate usage priority. Priority is determined based on the loyalty card that best matches the user's current emotions.

[0705] Step 5:

[0706] Based on the calculation results, the server suggests to the user the use of a specific card. The terminal notifies the user of this suggestion and guides them with a message such as, "Based on your emotional state, the XX card is currently the best choice."

[0707] Step 6:

[0708] When a user uses a suggested card, the terminal records the usage data (date and time of use, location, amount, etc.) and sends it to the server. The server adds this data to its database.

[0709] Step 7:

[0710] The server analyzes usage data and emotion recognition results to identify which emotional states influence consumer behavior. As a result, detailed market trend data is generated for businesses.

[0711] Step 8:

[0712] The server provides companies with generated market trend data to help them develop emotionally driven promotions and marketing strategies. This data is then used to create new campaigns.

[0713] (Example 2)

[0714] 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".

[0715] Traditionally, there was no system in place to effectively manage and optimally utilize the reward cards held by users. Emotional states could not be considered when determining the usage status or priority of reward cards, and there was a lack of efficient methods for collecting data to understand market trends. As a result, users were unable to use their reward cards effectively, potentially leading to the risk of rewards expiring or missing out on appropriate promotions.

[0716] 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.

[0717] In this invention, the server includes means for centrally managing information on multiple reward cards held by a user, means for calculating the usage priority for each of the reward cards based on location information, event information, and the expiration date of the reward, and means for analyzing the user's emotional state and incorporating the analysis results into the calculation of usage priority. This enables the user to use reward cards that are appropriate to their emotional state and circumstances at any given time, preventing the loss of rewards and the missed opportunity for effective promotions, and also enabling them to grasp market trends.

[0718] A "reward card" is a card used by users to receive benefits when using a service or product, and includes point cards, membership cards, and other similar cards.

[0719] "Centralized management" refers to the unified management of multiple pieces of information or data within a single location or system.

[0720] "Usage priority" is an index that calculates the importance and priority of using a reward card based on specific conditions or circumstances.

[0721] "Emotional state" refers to the user's psychological state and includes various emotional states such as joy, sadness, and anger.

[0722] "Analysis" refers to the process of examining data in detail and deriving meaning and patterns from it.

[0723] "Market trend data" refers to data that shows market trends and patterns, and includes information based on the usage and emotional state of reward cards.

[0724] An "external organization" refers to a group or company that is different from the system's operator and is subject to information sharing.

[0725] This invention is a system that allows users to efficiently manage and utilize reward cards and receive optimal usage suggestions tailored to their emotional state. This system is primarily realized through the exchange of information between a server, a terminal, and the user.

[0726] Users download and begin using an application compatible with their smartphone or tablet. Through this application, users enter personal information and details about any reward cards they possess. The device collects this information and transmits it to a server using a security protocol. The server records the received information in a database in preparation for subsequent processing. Database management systems such as MySQL or MongoDB may be used for this database.

[0727] On the other hand, the device uses the user's sensor devices, such as the camera and microphone, to periodically analyze the user's emotional state. This analysis may utilize an emotion analysis engine, specifically IBM Watson or Microsoft Azure's emotion analysis API. The emotional data obtained from the device is sent to a server and managed integrally with other information.

[0728] The server calculates a priority for use based on the user's current location information, relevant event information, the expiration date of the reward card, and their emotional state. Based on this calculated priority, the server suggests the use of a specific reward card to the user. This suggestion is notified to the user via their terminal, allowing them to effectively use the reward card accordingly.

[0729] This system collects reward card usage data and combines it with the results of an emotion engine analysis to generate market trend data. Companies can use this trend data to develop new marketing strategies.

[0730] For example, if the emotion engine analyzes that the user is feeling stressed, the device might notify the user with a message like, "We recommend using the XX rewards card, which offers a discount on aromatherapy candles." This approach can improve the user experience.

[0731] An example of a prompt to a generative AI model could be: "Please show a method for providing the best reward card usage suggestion when the emotional state is stressful."

[0732] The system of this invention is designed to allow users to make the most of their reward cards, and it is also valuable to companies because it allows them to predict market trends based on the collected data.

[0733] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0734] Step 1:

[0735] The user downloads and launches the application on their device. The user enters personal information and reward card information on the application screen. The entered data is temporarily stored on the device, preparing for information transfer. This data becomes the input to the server. The device sends the user information as input data to the server via a security protocol. The server receives this data and outputs it to its database.

[0736] Step 2:

[0737] The device uses its camera and microphone to collect user emotion data. Information obtained from the user's facial expressions and voice is input into an emotion analysis engine. This engine performs calculations that output the emotional state as numerical data. The obtained emotional state data is prepared on the device for transmission to the server. The server receives this emotion data as input and uses it, along with other known user information, as material for the next calculation.

[0738] Step 3:

[0739] The server retrieves location information, event information, and the expiration date of reward cards from the database. This information is then combined with sentiment data to calculate usage priority. Specifically, a weighted averaging method is used to output a single priority index. This priority index serves as an indicator for determining which reward cards the user should use next.

[0740] Step 4:

[0741] Based on the calculated usage priority, the server generates a suggestion for the user to use the most suitable reward card. The generated suggestion is output to the terminal as a notification message. The terminal receives this and displays it to the user. Specifically, a message such as "We recommend using the XX reward card, which offers great deals on relaxation products" pops up on the terminal screen.

[0742] Step 5:

[0743] The server collects usage data for reward cards and performs calculations to generate market trend data by adding emotional data to it. This data is output as an analysis report and provided to companies. This provides information that allows them to understand trends such as which cards are preferred to be used in which emotional states.

[0744] Through these steps, the entire system will operate in a way that provides users with effective and efficient reward card services.

[0745] (Application Example 2)

[0746] 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".

[0747] There is a need for a system that efficiently manages the multiple means of value exchange held by users and suggests the optimal use of value exchange cards based on the user's emotional state and location data. This will enable users to exchange value in the most advantageous way at any given time, and in addition, it will create an environment that allows companies to efficiently analyze market trends.

[0748] 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.

[0749] In this invention, the server includes means for centrally managing information on multiple value exchange cards held by a user, means for calculating a usage priority for each of the value exchange cards based on location data, activity information, and the expiration date of the value, and means for analyzing the user's emotional state and optimizing the use of the value exchange cards based on that state. As a result, the optimal value exchange is proposed to the user, and effective value utilization based on emotional state and location information becomes possible.

[0750] A "value exchange card" is a card that allows users to obtain value in the form of points or discounts in specific activities.

[0751] "Usage priority" is an indicator that shows which value exchange cards should be used preferentially, based on factors such as location data, activity information, and value expiration dates.

[0752] "Emotional state" refers to the user's psychological and emotional condition, and is information used to optimize the user's behavior and choices based on this state.

[0753] "Information trend data" refers to data that analyzes collected value exchange card usage data to show trends and developments in the market.

[0754] "Location data" refers to data that indicates the geographical location of users and is useful for optimizing the use of activity information and value exchange cards.

[0755] The system required to implement this application consists of a server, a user's device (e.g., a smartphone), and network infrastructure.

[0756] The server first receives information about the value exchange cards held by the user and manages this information centrally. Cloud-based database software (e.g., Firebase) is used for this purpose. Next, the server calculates usage priority based on the user's location data, activity information, and the expiration date of the value exchange cards. At this time, an emotion analysis API (e.g., Microsoft Azure's Face API) is used to analyze the user's emotional state and optimize the use of the value exchange cards.

[0757] The user's emotional state is acquired using the smartphone's sensors, and this is analyzed by an emotion engine. Furthermore, the user's location information is acquired using the device's GPS function. The server comprehensively analyzes this information and provides feedback to the user recommending optimal card usage.

[0758] As a concrete example, if a user visits a shopping mall on a Sunday afternoon, it will be determined that they are in an excited emotional state. At this time, the server will recommend and notify the user of a value exchange card that offers additional points from a fashion brand store.

[0759] Through this system, users can access the most advantageous value exchange at any given time. For companies, the collected data is useful as information trend data for building marketing strategies.

[0760] The prompt messages for the generative AI model are as follows:

[0761] "Based on the user's emotional state, suggest the most advantageous loyalty card. The user is in a shopping mall on a Sunday afternoon. His emotional state is excited."

[0762] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0763] Step 1:

[0764] The user launches a smartphone application and enters information about their value exchange card. This information includes the card name, balance, and expiration date. The device sends this information to a cloud database. As output, the card information is stored in a centrally managed database on a server.

[0765] Step 2:

[0766] The device collects the user's location information and emotional data in real time. Location information is obtained from a GPS sensor, and emotional data is acquired through the camera and microphone, and analyzed using an emotional analysis API. The input location information and analyzed emotional data are sent to the server. As output, the user's current location and emotional state are stored on the server.

[0767] Step 3:

[0768] The server calculates usage priority based on the received location information, emotional state, and value exchange card information. In this process, a data processing program considers current promotional information and card expiration information to determine the priority of each card. The inputs are the user's location information, emotional state, and card information, and the output is a list of card usage priority levels.

[0769] Step 4:

[0770] The server notifies the user of the most recommended value exchange card based on the calculated usage priority. A recommendation message is then sent to the user's smartphone using a notification system. The input is a usage priority list, and the output is a card recommendation message to the user.

[0771] Step 5:

[0772] The server periodically collects usage data for value exchange cards and generates market trend data. This data is used to analyze the frequency of card usage and the emotional state of users at the time of use, and is utilized for future marketing strategies. The input is usage data, and the output is a market trend analysis report.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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."

[0782] 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.

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] The following is further disclosed regarding the embodiments described above.

[0795] (Claim 1)

[0796] A means of centrally managing information on multiple point cards held by a user,

[0797] For each of the aforementioned point cards, a means for calculating the priority of use based on location information, event information, and the expiration date of the points,

[0798] A means of notifying users of recommended point cards based on the aforementioned usage priority,

[0799] A means of collecting point card usage data, analyzing it, and generating market trend data,

[0800] Means for providing the aforementioned market trend data to a third party,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, further comprising means for periodically checking the expiration date of the point card and notifying the user when the expiration date is approaching.

[0804] (Claim 3)

[0805] The system according to claim 1, further comprising means for acquiring the user's location information and providing promotional information that is nearing its end based on that location information.

[0806] "Example 1"

[0807] (Claim 1)

[0808] A means of comprehensively managing data related to multiple pieces of identification information held by a user,

[0809] For each of the aforementioned identification pieces of information, a means for calculating the priority of use based on location data, event information, and the expiration date of the data,

[0810] A means for notifying users of recommended identification information based on the aforementioned usage priority,

[0811] A means for acquiring data on the use of identification information, analyzing it, and generating market trend data,

[0812] Means for providing the aforementioned market trend data to external entities,

[0813] A system that includes this.

[0814] (Claim 2)

[0815] The system according to claim 1, which periodically checks the expiration date of the aforementioned identification information and notifies the user when the expiration date is approaching.

[0816] (Claim 3)

[0817] The system according to claim 1, which acquires the user's location data and provides promotional information that is nearing its end based on that location data.

[0818] "Application Example 1"

[0819] (Claim 1)

[0820] A means of centrally managing information on multiple preferential services held by a user,

[0821] For each of the aforementioned preferential services, a means for calculating the priority of use based on geographical location information, event information, and the expiration date of the preferential service,

[0822] A means of notifying users of recommended preferential services based on the aforementioned usage priority,

[0823] A means of collecting usage data for preferential services, analyzing it, and generating industry trend data,

[0824] Means for providing the aforementioned industry trend data to external organizations,

[0825] A system that includes this.

[0826] (Claim 2)

[0827] The system according to claim 1, further comprising means for periodically checking the expiration date of the aforementioned preferential service and notifying the user when the expiration date is approaching.

[0828] (Claim 3)

[0829] The system according to claim 1, further comprising means for obtaining the geographical location information of a user and providing sales promotion information that is nearing its end based on that geographical location information.

[0830] "Example 2 of combining an emotion engine"

[0831] (Claim 1)

[0832] A means of centrally managing information about multiple reward cards held by a user,

[0833] For each of the aforementioned reward cards, a means for calculating the priority of use based on location information, event information, and the expiration date of the reward,

[0834] A means of notifying users of recommended reward cards based on the aforementioned priority of use,

[0835] A means of analyzing the emotional state of users and incorporating the results of that analysis into the calculation of usage priority,

[0836] A means of compiling usage data for reward cards and creating market trend data using that data and the results of an analysis of emotional states,

[0837] Means for providing the aforementioned market trend data to an external organization,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, which periodically checks the expiration date of the aforementioned benefit card and notifies the user when the expiration date is approaching.

[0841] (Claim 3)

[0842] The system according to claim 1, which acquires the user's location information and provides advertising information that is nearing its end based on that location information.

[0843] "Application example 2 when combining with an emotional engine"

[0844] (Claim 1)

[0845] A means of centrally managing information about multiple value exchange cards held by a user,

[0846] For each of the aforementioned value exchange cards, a means for calculating the priority of use based on location data, activity information, and the expiration date of the value,

[0847] A means for notifying users of recommended value exchange cards based on the aforementioned usage priority,

[0848] A means of collecting usage data for value exchange cards, analyzing it, and generating information trend data,

[0849] Means for providing the aforementioned information trend data to others,

[0850] A means for analyzing the emotional state of users and optimizing the use of value exchange cards based on those emotions,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, which periodically checks the expiration date of the value exchange card and notifies the user when the expiration date is approaching.

[0854] (Claim 3)

[0855] The system according to claim 1, which acquires the user's location data and provides activity information that is nearing completion based on that location data. [Explanation of Symbols]

[0856] 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 centrally managing information on multiple preferential services held by a user, For each of the aforementioned preferential services, a means for calculating the priority of use based on geographical location information, event information, and the expiration date of the preferential service, A means of notifying users of recommended preferential services based on the aforementioned usage priority, A means of collecting usage data for preferential services, analyzing it, and generating industry trend data, Means for providing the aforementioned industry trend data to external organizations, A system that includes this.

2. The system according to claim 1, further comprising means for periodically checking the expiration date of the aforementioned preferential service and notifying the user when the expiration date is approaching.

3. The system according to claim 1, further comprising means for acquiring the geographical location information of a user and providing sales promotion information that is nearing its end based on that geographical location information.

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