system

Abstract

We provide the system. [Solution] Means of collecting information regarding the operation of local events, A means of generating participant recruitment information based on collected information, A means of distributing the generated recruitment information to local participants, A means of receiving registration information from participants, A means of notifying participants of the schedule and precautions for holding local events, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Traditional local events are becoming difficult to recruit participants due to the aging of carriers and population decline. Against this background, there is a problem that it is difficult to sustainably operate local events, which may have a negative impact on local activation. Therefore, it is desired to provide a system that improves the efficiency of local event operation and promotes the recruitment of participants.

Means for Solving the Problems

[0005] This invention provides a system that collects information related to the operation of local events, generates participant recruitment information based on this information, and distributes it to local participants. This system accepts registration information from participants and also has the function of notifying them of the schedule and precautions necessary for holding local events. In addition, by acquiring the location information of participants and providing necessary information in real time, it enables the smooth operation of local events. Specifically, it optimizes the route plan for local events using the generated information and achieves efficient participant mobilization.

[0006] A "local event" is a traditional or cultural event that is held regularly in a specific region.

[0007] "Operational information" refers to data related to the schedule, number of participants, route, and setup arrangements necessary for the implementation of local events.

[0008] "Participant recruitment information" refers to information that outlines the content and conditions for encouraging participation in local events.

[0009] "Means of distribution" refers to the technology or medium used to deliver information to participants, and this includes the internet and social media.

[0010] "Registration information" refers to data including personal information and intentions provided by participants when they register to indicate their willingness to participate in local events.

[0011] "Means of notification" refers to technologies and methods for informing participants of pre-programmed event information.

[0012] "Location information" refers to data that indicates the geographical location of a participant or event.

[0013] A "route plan" is a plan for determining the travel routes and paths taken by participants in a local event. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a tagged processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a tagged RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a tagged storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] The present invention will now be described in terms of embodiments. The server collects and analyzes past data on local events from a database. This data includes the number of participants in the event, their age groups, past schedules, and geographical information of the event location. Based on the results of the analysis, the server uses AI to generate the optimal route for the local event and information on recruiting participants. Next, the terminal receives this information provided by the server and distributes recruitment advertisements to prospective participants via social media or a dedicated app.

[0036] Users can receive recruitment information through their devices and register to participate by clicking a link. Once a user completes registration, the server receives the information and notifies them in advance of necessary schedules and important notes. Furthermore, the device obtains the user's location information in real time and provides traffic information and route guidance for the day, enabling participants to smoothly enjoy local events.

[0037] As a concrete example, consider a summer festival held in a certain region. The server analyzes summer festival data from the past three years and uses AI to optimize this year's festival route. The terminal also uses a local community app to distribute information about recruiting volunteers to carry the portable shrine. Users register to participate based on this information and receive the festival schedule and important notices through the terminal. This ensures that the traditional local event is run efficiently and smoothly, providing a fulfilling experience for both participants and the community.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The server collects historical data on local events from a database. This includes the number and age range of participants, weather conditions, past routes, event schedules, and relevant economic data.

[0041] Step 2:

[0042] The server inputs the collected data into an AI model and uses statistical analysis and machine learning techniques to analyze participant mobilization trends, optimal routes, and patterns for effective event management.

[0043] Step 3:

[0044] Based on the analysis results, the server uses AI to generate the optimal routes and participant recruitment strategies for this year's local events. This information aims to maximize the success rate of the events.

[0045] Step 4:

[0046] The terminal receives routes and recruitment information provided by the server and distributes recruitment advertisements and related information to local residents via local social networking services and dedicated apps.

[0047] Step 5:

[0048] Users receive advertisements delivered through their devices, and if they are interested, they click on the link in the advertisement to access the registration page.

[0049] Step 6:

[0050] Users enter their information on the registration page and officially register their participation in local events.

[0051] Step 7:

[0052] The server receives registration information from users and, along with registration confirmation, sends users the necessary schedule and important notes for participation via email or app notification.

[0053] Step 8:

[0054] On the day of the festival, the device will acquire the user's location information in real time, update traffic conditions and the progress of the event as needed, and provide navigation and change information to the user as required.

[0055] (Example 1)

[0056] 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."

[0057] In modern community activities, there is a need to ensure that diverse participants can participate efficiently. However, traditional methods have faced challenges such as insufficient information and inadequate optimization in event preparation and participant guidance on the day of the event. Therefore, there is a need for means to achieve smooth operation of community activities and improve participant satisfaction.

[0058] 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.

[0059] In this invention, the server includes means for collecting data related to local activities, means for analyzing the collected data, and means for generating optimal route plans and participant recruitment information using a generation model based on the analysis results. This enables efficient optimization of the planning and operation of local activities, and facilitates the smooth provision of information and guidance to participants.

[0060] "Community activities" refer to events and activities carried out jointly by local residents in a specific geographical area.

[0061] "Data collection" refers to the act of gathering necessary data from target information sources, and includes information on participants in local activities and geographical information.

[0062] "Data analysis" refers to the process of organizing collected data and using statistical and machine learning techniques to gain useful insights.

[0063] A "generative model" refers to an algorithm or artificial intelligence framework that uses collected data to derive new information or optimal solutions.

[0064] "Route planning" refers to the process of creating routes that allow participants to move efficiently within a community activity.

[0065] "Participant recruitment information" refers to information provided to encourage participation in community activities and to attract new participants.

[0066] The embodiments for carrying out the present invention will be described in detail.

[0067] The server first collects data related to community activities. This data includes information on past participants in community activities, age groups, past schedules, and geographical information, and is stored using a database management system. The server uses a relational database such as MySQL® and retrieves the data by querying it with a Python script.

[0068] Next, the server analyzes the collected data. The analysis is performed using Python and machine learning libraries (e.g., Tensorflow® and PyTorch). This allows for the detection of data patterns and the deriving of optimal responses regarding participants' interests and movements. Specifically, an AI model based on past data optimizes the routes for this year's event.

[0069] The terminals play a role in distributing recruitment information to local participants using information provided by the server. The terminals send notifications using SNS platforms or dedicated applications. For example, mobile devices running iOS or Android® fall into this category.

[0070] Users can register to participate based on information received through their devices. Once a user clicks a link and completes registration, the server will notify the user of relevant schedules and important notices on the server side. Notifications will be sent via email or push notifications.

[0071] Furthermore, the device acquires the user's real-time location information and uses the Google® Maps API to provide specific traffic information and route guidance, thereby supporting users in smoothly participating in local activities.

[0072] As a concrete example, let's consider a summer festival in a specific region. The server collects and analyzes festival data from the past three years. The generating AI model performs route optimization using the prompt message "Analyze the summer festival data from the past three years and propose the optimal route." Using terminals, volunteer recruitment information is distributed through a local community app, and participants can receive necessary information in real time through their terminals. This structure allows community activities to be managed more efficiently, and participants can comfortably enjoy the events.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The server collects data related to local activities. It retrieves information from the database using SQL queries, extracting data including participant information, age groups, schedules, and geographical information. The input requires database connection information and query conditions for the desired data; the output is structured data based on the query. This process provides foundational data for analysis.

[0076] Step 2:

[0077] The server analyzes the collected data. Using Python and machine learning frameworks, it performs data analysis with an AI model. The input is structured data extracted from a database. The server formats the data, inputs it into the AI ​​model, and uses prompts to instruct it to "generate the optimal route based on past data." The output is optimized routes and participant recruitment information.

[0078] Step 3:

[0079] The server sends the generated information to the terminal, which then uses that information to distribute recruitment advertisements for participants. The terminal then spreads the information using social networking platforms and dedicated applications. Data from the server is required as input, and the output is in the form of application notifications and social networking posts. This ensures that the information reaches a wide range of participants.

[0080] Step 4:

[0081] Users register to participate based on information received from their devices. Users click a link, fill out a form, and their devices send this information to the server. The input includes the user's personal information and participation preference, while the output is a registration confirmation notification sent to the user. This step confirms and records the user's intention to participate.

[0082] Step 5:

[0083] The server uses registration information to notify users in advance of the event schedule and important notes. The device then transmits this information to the user via push notifications or email. Inputs include user information and event details from registration, while output is the notification content delivered to the user. In this way, participants can obtain necessary information early.

[0084] Step 6:

[0085] The device acquires the user's real-time location data and provides traffic information and route guidance using the Google Maps API. It periodically receives the user's location information as input and displays the optimal mode of transport and route guidance as output. This makes it possible to support smooth travel throughout the day.

[0086] (Application Example 1)

[0087] 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."

[0088] In managing community activities and events, providing information to participants and stakeholders is cumbersome, making efficient participant recruitment and scheduling difficult. Furthermore, the use of past data to develop optimal plans is insufficient. Additionally, features such as real-time participant location tracking and appropriate route guidance are limited. A system is needed to solve these problems and facilitate the smooth operation of community activities.

[0089] 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.

[0090] In this invention, the server includes means for collecting information related to the management of local activities, means for generating participant guidance information based on the collected information, and means for analyzing past activity data to create an optimal plan. This enables efficient participant recruitment, optimization of schedules and routes, and real-time location information management and information provision.

[0091] "Community activities" refer to collaborative initiatives and events held in a specific area, involving residents and participants.

[0092] "Management" is the act of controlling and systematically utilizing resources and information in order to achieve specific goals.

[0093] "Information" is a collection of knowledge and facts that are gathered as data, and whose value is created through analysis and use.

[0094] A "participant" is an individual or group that has expressed their intention to participate in a particular activity or event.

[0095] "Information" refers to instructions provided to participants and related parties regarding the activity, such as the date, time, location, and procedures.

[0096] "Past activity data" refers to records and history of activities that have been carried out in the past, and this information can be used to help formulate future plans through analysis.

[0097] An "optimal plan" is a set of action or procedures formulated to achieve a goal most effectively within given conditions and constraints.

[0098] A "server" is a device or software that processes information and provides services to other computers or terminals via a network.

[0099] "Location information" refers to data that indicates the physical location of a specific object, and is expressed in forms such as latitude, longitude, or address.

[0100] To implement this invention, the process begins with a server collecting and analyzing historical data related to local activities from a database. This data includes the number and age range of participants, past schedules, and geographical information of the event location. Based on this data, the server uses a generative AI model to generate an optimal plan for local activities and information for recruiting participants.

[0101] Information generated by the server is distributed to local stakeholders via terminals. Stakeholders can use the terminal's application to receive the distributed guidance information and obtain their real-time location. Activity schedules and important notices are also notified via the terminal, allowing stakeholders to check necessary information at any time. Furthermore, the terminal provides optimal route guidance based on past data and current location information.

[0102] As a concrete example, in a local event, the server uses AI to analyze past event data and create an optimal participant recruitment plan for the current year. It also provides real-time route guidance and schedule information to relevant parties via terminals, ensuring efficient event management. An example of a prompt to input into the generating AI model might be, "Please suggest the optimal route for local activities during the year-end and New Year period."

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] The server collects historical data on community activities from a database. The input is the records of community activities in the database, and the output is the collected dataset. This dataset includes information such as the number of participants, age groups, past schedules, and geographical information of the location. The server uses database queries to filter and collect the necessary data.

[0106] Step 2:

[0107] The server performs analysis using a generative AI model based on the collected data. The input is the dataset of local activities collected in the previous step, and the output is the optimal local activity plan and participant recruitment information. The server processes the data using computing resources and generates the plan proposed by the AI ​​model, taking past trends and patterns into consideration.

[0108] Step 3:

[0109] The server sends the generated participant recruitment information to the terminal and distributes it to local stakeholders. The input is the generated information, and the output is the dissemination of information to all stakeholders. The server uses network communication to send information to the terminal, and the terminal notifies or displays the received information.

[0110] Step 4:

[0111] The device acquires and collects the user's location information in real time. The input is location data obtained via the device's GPS function, and the output is real-time location information. The device periodically reads data from the GPS sensor and sends it to the server or uses it for internal processing.

[0112] Step 5:

[0113] The server creates and provides optimal route guidance to the user based on location information. Input is real-time location information and the generated plan, while output is the optimal route information presented to the user. The server uses a Geographic Information System (GIS) to calculate the route and transmit the route guidance to the terminal.

[0114] Step 6:

[0115] Users receive guidance information through their devices and participate in local activities. Input is the schedule and route information displayed on the device, and output is the user participating in the activity at the appropriate time. Users operate the device's interface and act based on the information provided.

[0116] 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.

[0117] An excellent embodiment for carrying out the present invention is shown below. In addition to the functions of efficiently collecting operational information for local events and generating and distributing participant recruitment information, this system is equipped with an emotion engine that recognizes the user's emotions and optimizes local events based on them.

[0118] The server collects data on the operation of local events from a database and uses AI to analyze participant trends and the performance of past events. Based on these results, it generates the optimal event route and participant recruitment information. The terminal then receives this generated information and delivers advertisements to participants via social media and a dedicated app.

[0119] Users can access recruitment information received through their devices and easily register to participate in local events. Once registration is complete, the server distributes schedule information and important notes to the user. Furthermore, the server obtains participants' real-time location information and provides traffic information and updates on the event's progress.

[0120] In addition, this system incorporates an emotion engine, which analyzes the user's behavior patterns and responses. The results of this analysis are used to adjust routes to improve participant satisfaction and to provide personalized information notifications.

[0121] For example, if the emotion engine determines that a user's stress level is high on the day of the festival, the device will immediately provide the user with information on routes to avoid crowds and areas where they can relax. In this way, the experience of participating in local events can be improved, leading to further regional revitalization and increased participant satisfaction.

[0122] The following describes the processing flow.

[0123] Step 1:

[0124] The server collects historical data related to local events from a database. This includes a variety of information such as the number of participants, age distribution, geographical information of the event location, and user feedback during the event.

[0125] Step 2:

[0126] The server uses AI models to analyze the collected data and generate optimal routes and participant recruitment methods. This analysis includes extracting past success stories and analyzing participant behavioral trends.

[0127] Step 3:

[0128] The device receives optimization information generated from the server and distributes recruitment advertisements to prospective participants via local social media and dedicated apps.

[0129] Step 4:

[0130] Users view recruitment advertisements on their devices and, if interested, access the registration page via the provided link.

[0131] Step 5:

[0132] Users officially register their participation by entering the required personal information on the registration page. This indicates their intention to participate in the event.

[0133] Step 6:

[0134] The server receives registration information from the user, automatically generates an optimal schedule and notes, and sends a confirmation notification to the user.

[0135] Step 7:

[0136] The device uses an emotion engine to analyze user behavior data and input data, and evaluates the user's emotional state.

[0137] Step 8:

[0138] Based on the evaluated emotional state, the server adjusts the route or provides special notifications to improve the participant's experience.

[0139] Step 9:

[0140] On the day of the festival, the device will acquire the user's location information in real time and provide navigation information and emotionally tailored advice as needed. Based on this information, users can enjoy local events efficiently and comfortably.

[0141] (Example 2)

[0142] 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".

[0143] In managing local events, efficiently recruiting participants and providing information is challenging, resulting in a lack of customized experiences tailored to the individual needs of participants. Furthermore, the limited means of tracking participants' movements in real time and providing relevant information make improving participant satisfaction a challenge.

[0144] 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.

[0145] In this invention, the server includes means for collecting data related to the operation of local events, means for creating participant recruitment information based on the collected data, and means equipped with an emotion recognition engine that analyzes user behavior and provides personalized information. This enables the provision of customized information adapted to the needs of participants and improves satisfaction by utilizing real-time participant location information.

[0146] A "local event" refers to a public or private event, such as a festival, workshop, or other event held in a specific region.

[0147] "Operational data" refers to information related to the planning, preparation, and execution of an event, including the number of participants, time, location, content, and necessary resources.

[0148] "Participant recruitment information" refers to information provided to encourage participation in an event, and includes details about the event's content, how to participate, how to register, and more.

[0149] An "emotion recognition engine" is software or a system that analyzes user behavior data and reactions to infer the user's emotional state and provide information based on that inference.

[0150] "Location data" refers to geographical data obtained from GPS information and location services that indicate the current location of participants.

[0151] "Itinerary optimization" refers to the process of optimizing routes and schedules to make the user's travel and event participation process efficient and comfortable.

[0152] The server is responsible for the core functions of this invention, aggregating operational data for local events. A commonly used database software is used as the database management system to manage historical event data, participant information, and related operational information. The collected data is formatted for analysis and analyzed using AI. For the analysis, machine learning platforms such as TensorFlow and PyTorch are used to predict participant trends and event performance.

[0153] The server generates optimal participant recruitment information based on the analysis results and creates prompt messages using a generative AI model. This can utilize language generation models and natural language processing technologies to provide effective catchphrases and text that will attract participants' interest.

[0154] The terminal receives participant recruitment information sent from the server and delivers advertisements to users via social media and dedicated apps. Specifically, the terminal's role is to efficiently attract participants by using APIs from Facebook and Twitter to implement targeted advertising.

[0155] Users can register to participate in local events based on recruitment information received through their devices. The registration process is conducted using an application with an intuitive user interface, designed to allow users to quickly and accurately enter the necessary information.

[0156] Furthermore, devices equipped with an emotion recognition engine analyze user usage patterns and feedback, and execute algorithms to provide personalized information. This enables optimal event routes and information notifications based on the user's emotional state. For example, if the emotion engine determines that the user's stress level is high on the day of a festival, the device can immediately guide the user to routes that avoid crowds or to areas where they can relax.

[0157] An example of a prompt message might be, "Generate route guidance to provide when the user's stress level is high." This allows users to enjoy local events comfortably, resulting in improved event satisfaction and participation experience.

[0158] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0159] Step 1:

[0160] The server first retrieves operational data related to local events from a database. Inputs include past event data, participant numbers, and weather information. This data undergoes a cleansing process to remove irregular data and outliers, resulting in an analyzable dataset. The output is this formatted dataset.

[0161] Step 2:

[0162] The server inputs the formatted dataset into an AI algorithm and performs data analysis. Specifically, it uses TensorFlow or PyTorch to perform time-series analysis of event trends and participant behavior. In this process, it extracts features and performs pattern recognition to output trends based on participants' interests and preferences. The analysis results become a predictive model used in the next step.

[0163] Step 3:

[0164] The server uses an AI model based on the analysis results to generate optimal participant recruitment information and prompt messages. The input consists of the analysis results and the AI ​​model, and the generated prompt messages include elements that will attract participants' interest. For example, a message like "We'll introduce you to local events you can enjoy participating in!" might be output.

[0165] Step 4:

[0166] The terminal receives prompt messages and participant recruitment information sent from the server and delivers advertisements via social media and a dedicated app. Specifically, it delivers targeted content based on participants' interests via social media APIs. The input is generated information from the server, and the output is the delivered advertisement.

[0167] Step 5:

[0168] Users check recruitment information received via their devices and register to participate in local events. Input is done through a registration form displayed on the device, and the operation is performed within the app. Output is registration information sent to the server, which is used to confirm participation in events.

[0169] Step 6:

[0170] The server notifies users who have completed registration of the event schedule and important information. The input is registration information, and the output is a notification message to the user. This message is provided via email or push notification.

[0171] Step 7:

[0172] The server uses GPS information from smart devices to track the user's location in real time. The input is device location data, and the output is dynamic traffic information and event progress updates. This allows for real-time support to be provided to the user.

[0173] Step 8:

[0174] The device uses an emotion recognition engine to analyze user behavior patterns and responses. Inputs include app usage history and user responses, and based on the analysis, it outputs personalized information and route suggestions. This output is designed to help participants enjoy the event more comfortably.

[0175] (Application Example 2)

[0176] 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".

[0177] In today's diverse community events and retail environments, there is a growing need for information tailored to the individual interests and satisfaction levels of participants and consumers. However, traditional systems have struggled to instantly provide personalized suggestions based on individual participants' emotions and location information, making it difficult to improve the consumer experience. Therefore, new methods are needed to enhance participant satisfaction in community events and store visits.

[0178] 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.

[0179] In this invention, the server includes means for collecting information related to the operation of local events, means for generating participant recruitment information based on the collected information, a mechanism for distributing the generated recruitment information to local consumers, a device for receiving registration information from participants, a device for notifying users of the schedule and precautions for holding local events, and a mechanism for analyzing consumer sentiment and generating personalized suggestions based on the analysis results. This enables participants to receive information tailored to their individual needs, making local events and retail experiences more attractive and satisfying.

[0180] "Information regarding the operation of local events" refers to detailed data and plans for events, festivals, meetings, etc., held in the local area. This information includes the number of participants, the results of past events, schedules, locations, and related operational details.

[0181] "Participant recruitment information" refers to the content of announcements and advertisements designed to attract people to participate in local events and activities. This information includes the date, time, location, participation requirements, and registration method of the event.

[0182] A "consumer distribution mechanism" refers to a system or method for distributing specific information to targeted consumers or participants. This is done through communication methods such as email, SMS, and smartphone apps.

[0183] A "device for receiving registration information" refers to a system or device for participants to input and submit the necessary information to participate in local events and activities. This device is implemented through online forms, dedicated application applications, and the like.

[0184] "Devices for notifying users of schedules and important information" refers to devices or systems used to inform participants of event-related schedules and important points. This includes calendar apps and notification systems.

[0185] A "mechanism for analyzing consumer emotions" refers to a system or algorithm for evaluating consumers' emotional states and analyzing data based on those evaluations. This includes artificial intelligence that evaluates emotions using behavioral data and biometric information.

[0186] A "mechanism for generating personalized suggestions" refers to a system that creates customized advice and suggestions based on the individual user's preferences and emotional state. This includes recommendation engines and profiling technologies.

[0187] To realize this application, it is crucial that a server equipped with advanced data collection and analysis capabilities throughout the entire system is coordinated with the terminals used by users. The server collects information related to the operation of local events using sensors and statistical data, and stores this information in a database. Furthermore, artificial intelligence is used to analyze this data and generate participant recruitment information and personalized route guidance based on the movements of individual participants.

[0188] The devices function as an interface with the user, receiving and displaying generated information in real time. Specifically, applications installed on smartphones and smart glasses send the user's emotional information to an emotion engine, and the system provides optimal information based on the analysis results. These devices also acquire the user's location information and act as a means of communication to suggest routes that avoid congestion and recommended rest spots.

[0189] For example, when a user visits a physical store, the system analyzes emotional data and, if it determines that the user is seeking relaxation, guides them to a location where relaxing products are displayed or to a quiet corner. Furthermore, by inputting a specific prompt example such as, "Please suggest application scenarios for proposing the optimal purchasing experience in a physical store using consumer emotional data," the generative AI model will provide appropriate suggestions.

[0190] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0191] Step 1:

[0192] The server collects data related to local events from various sensors and databases. This input data includes historical information about past events, participant numbers, and event dates. By collecting this data, the server prepares the foundational information necessary for the next analysis step.

[0193] Step 2:

[0194] The server inputs the collected data into an artificial intelligence engine to analyze participant behavior. As a result of this data analysis, it generates optimized event plans and recruitment information. At this time, the AI ​​model uses a generative AI model to analyze data trends and identify emerging patterns.

[0195] Step 3:

[0196] The terminal receives optimized event and recruitment information sent from the server. This information is displayed through the user interface, allowing the user to review the necessary details and consider participating in the event.

[0197] Step 4:

[0198] Users register to participate through their device. During this process, users enter necessary personal information and their preferred participation date and time. The device then sends this information to the server, completing the event registration.

[0199] Step 5:

[0200] The server uses the registration information received from the user to notify them of the scheduled event schedule and important notes. This output information is delivered directly to the user's device and serves as helpful guidance when participating in the event.

[0201] Step 6:

[0202] The device acquires the user's location information and emotional data in real time. When this data is input, the emotional engine within the device analyzes the data and generates optimal information based on the user's current state.

[0203] Step 7:

[0204] Based on the results of emotion analysis, the device presents personalized suggestions to the user. For example, if the user is feeling stressed, it will notify them of routes to avoid crowds or places where they can relax. In this way, the user can have the most useful and comfortable experience at that moment.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] [Second Embodiment]

[0209] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0210] 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.

[0211] 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).

[0212] 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.

[0213] 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.

[0214] 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).

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] 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".

[0221] The present invention will now be described in terms of embodiments. The server collects and analyzes past data on local events from a database. This data includes the number of participants in the event, their age groups, past schedules, and geographical information of the event location. Based on the results of the analysis, the server uses AI to generate the optimal route for the local event and information on recruiting participants. Next, the terminal receives this information provided by the server and distributes recruitment advertisements to prospective participants via social media or a dedicated app.

[0222] Users can receive recruitment information through their devices and register to participate by clicking a link. Once a user completes registration, the server receives the information and notifies them in advance of necessary schedules and important notes. Furthermore, the device obtains the user's location information in real time and provides traffic information and route guidance for the day, enabling participants to smoothly enjoy local events.

[0223] As a concrete example, consider a summer festival held in a certain region. The server analyzes summer festival data from the past three years and uses AI to optimize this year's festival route. The terminal also uses a local community app to distribute information about recruiting volunteers to carry the portable shrine. Users register to participate based on this information and receive the festival schedule and important notices through the terminal. This ensures that the traditional local event is run efficiently and smoothly, providing a fulfilling experience for both participants and the community.

[0224] The following describes the processing flow.

[0225] Step 1:

[0226] The server collects historical data on local events from a database. This includes the number and age range of participants, weather conditions, past routes, event schedules, and relevant economic data.

[0227] Step 2:

[0228] The server inputs the collected data into an AI model and uses statistical analysis and machine learning techniques to analyze participant mobilization trends, optimal routes, and patterns for effective event management.

[0229] Step 3:

[0230] Based on the analysis results, the server uses AI to generate the optimal routes and participant recruitment strategies for this year's local events. This information aims to maximize the success rate of the events.

[0231] Step 4:

[0232] The terminal receives routes and recruitment information provided by the server and distributes recruitment advertisements and related information to local residents via local social networking services and dedicated apps.

[0233] Step 5:

[0234] Users receive advertisements delivered through their devices, and if they are interested, they click on the link in the advertisement to access the registration page.

[0235] Step 6:

[0236] Users enter their information on the registration page and officially register their participation in local events.

[0237] Step 7:

[0238] The server receives registration information from users and, along with registration confirmation, sends users emails or app notifications containing the necessary schedule and important information for participation.

[0239] Step 8:

[0240] On the day of the festival, the device will acquire the user's location information in real time, update traffic conditions and the progress of the event as needed, and provide navigation and change information to the user as required.

[0241] (Example 1)

[0242] 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."

[0243] In modern community activities, there is a need to ensure that diverse participants can participate efficiently. However, traditional methods have faced challenges such as insufficient information and inadequate optimization in event preparation and participant guidance on the day of the event. Therefore, there is a need for means to achieve smooth operation of community activities and improve participant satisfaction.

[0244] 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.

[0245] In this invention, the server includes means for collecting data related to local activities, means for analyzing the collected data, and means for generating optimal route plans and participant recruitment information using a generation model based on the analysis results. This enables efficient optimization of the planning and operation of local activities, and facilitates the smooth provision of information and guidance to participants.

[0246] "Community activities" refer to events and activities carried out jointly by local residents in a specific geographical area.

[0247] "Data collection" refers to the act of gathering necessary data from target information sources, and includes information on participants in local activities and geographical information.

[0248] "Data analysis" refers to the process of organizing collected data and using statistical and machine learning techniques to gain useful insights.

[0249] A "generative model" refers to an algorithm or artificial intelligence framework that uses collected data to derive new information or optimal solutions.

[0250] "Route planning" refers to the process of creating routes that allow participants to move efficiently within a community activity.

[0251] "Participant recruitment information" refers to information provided to encourage participation in community activities and to attract new participants.

[0252] The embodiments for carrying out the present invention will be described in detail.

[0253] The server first collects data related to community activities. This data includes information on past participants, age groups, past schedules, and geographical information, and is stored using a database management system. The server uses a relational database such as MySQL and retrieves the data by querying it with a Python script.

[0254] Next, the server analyzes the collected data. This analysis is performed using Python and machine learning libraries (e.g., TensorFlow and PyTorch). This allows for the detection of data patterns and the deriving of optimal responses regarding participants' interests and movements. Specifically, an AI model based on past data optimizes the routes for this year's event.

[0255] The terminals play a role in distributing recruitment information to local participants using information provided by the server. The terminals send notifications using social networking platforms or dedicated applications. For example, mobile devices running iOS or Android fall into this category.

[0256] Users can register to participate based on information received through their devices. Once a user clicks a link and completes registration, the server will notify the user of relevant schedules and important notices on the server side. Notifications will be sent via email or push notifications.

[0257] Furthermore, the device acquires the user's real-time location information and uses the Google Maps API to provide specific traffic information and route guidance, thereby supporting users in smoothly participating in local activities.

[0258] As a concrete example, let's consider a summer festival in a specific region. The server collects and analyzes festival data from the past three years. The generating AI model performs route optimization using the prompt message "Analyze the summer festival data from the past three years and propose the optimal route." Using terminals, volunteer recruitment information is distributed through a local community app, and participants can receive necessary information in real time through their terminals. This structure allows community activities to be managed more efficiently, and participants can comfortably enjoy the events.

[0259] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0260] Step 1:

[0261] The server collects data related to local activities. It retrieves information from the database using SQL queries, extracting data including participant information, age groups, schedules, and geographical information. The input requires database connection information and query conditions for the desired data; the output is structured data based on the query. This process provides foundational data for analysis.

[0262] Step 2:

[0263] The server analyzes the collected data. Using Python and machine learning frameworks, it performs data analysis with an AI model. The input is structured data extracted from a database. The server formats the data, inputs it into the AI ​​model, and uses prompts to instruct it to "generate the optimal route based on past data." The output is optimized routes and participant recruitment information.

[0264] Step 3:

[0265] The server sends the generated information to the terminal, which then uses that information to distribute recruitment advertisements for participants. The terminal then spreads the information using social networking platforms and dedicated applications. Data from the server is required as input, and the output is in the form of application notifications and social networking posts. This ensures that the information reaches a wide range of participants.

[0266] Step 4:

[0267] Users register to participate based on information received from their devices. Users click a link, fill out a form, and their devices send this information to the server. The input includes the user's personal information and participation preference, while the output is a registration confirmation notification sent to the user. This step confirms and records the user's intention to participate.

[0268] Step 5:

[0269] The server uses registration information to notify users in advance of the event schedule and important notes. The device then transmits this information to the user via push notifications or email. Inputs include user information and event details from registration, while output is the notification content delivered to the user. In this way, participants can obtain necessary information early.

[0270] Step 6:

[0271] The device acquires the user's real-time location data and provides traffic information and route guidance using the Google Maps API. It periodically receives the user's location information as input and displays the optimal mode of transport and route guidance as output. This makes it possible to support smooth travel throughout the day.

[0272] (Application Example 1)

[0273] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0274] In managing community activities and events, providing information to participants and stakeholders is cumbersome, making efficient participant recruitment and scheduling difficult. Furthermore, the use of past data to develop optimal plans is insufficient. Additionally, features such as real-time participant location tracking and appropriate route guidance are limited. A system is needed to solve these problems and facilitate the smooth operation of community activities.

[0275] 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.

[0276] In this invention, the server includes means for collecting information related to the management of local activities, means for generating participant guidance information based on the collected information, and means for analyzing past activity data to create an optimal plan. This enables efficient participant recruitment, optimization of schedules and routes, and real-time location information management and information provision.

[0277] "Community activities" refer to collaborative initiatives and events held in a specific area, involving residents and participants.

[0278] "Management" is the act of controlling and systematically utilizing resources and information in order to achieve specific goals.

[0279] "Information" is a collection of knowledge and facts that are gathered as data, and whose value is created through analysis and use.

[0280] A "participant" is an individual or group that has expressed their intention to participate in a particular activity or event.

[0281] "Information" refers to instructions provided to participants and related parties regarding the activity, such as the date, time, location, and procedures.

[0282] "Past activity data" refers to records and history of activities that have been carried out in the past, and this information can be used to help formulate future plans through analysis.

[0283] The "optimal plan" is an action guideline or procedure formulated to most effectively achieve the goal under the given conditions and constraints.

[0284] A "server" refers to a device or software that processes information and provides services to other computers or terminals via a network.

[0285] "Location information" is data indicating the location where a specific object physically exists, and is represented in forms such as latitude and longitude or address.

[0286] To implement this invention, it first begins with the server collecting past data related to regional activities from the database and performing analysis. This data includes the number of participants, age groups, past schedules, geographical information of the venue, etc. Based on these data, the server uses the generated AI model to generate information on the optimal plan for regional activities and participant recruitment.

[0287] The information generated by the server is distributed to relevant parties in the region through the terminal. The relevant parties can receive the distributed guidance information using the terminal application and obtain their own location information in real time. Also, since the schedule and precautions of the activity are notified via the terminal, the relevant parties can check the necessary information at any time. Furthermore, the terminal provides an optimal route guidance based on past data and current location information.

[0288] As a specific example, in an event in a certain region, the server analyzes past event data with AI to create an optimal participant recruitment plan for this year. Also, it notifies the relevant parties of the route guidance and schedule in real time through the terminal, realizing efficient operation of the activity. Examples of prompt sentences input into the generated AI model can be something like "Please propose an optimal route for regional activities during the New Year holidays."

[0289] [[ID=

[0290] Step 1:

[0291] The server collects historical data on community activities from a database. The input is the records of community activities in the database, and the output is the collected dataset. This dataset includes information such as the number of participants, age groups, past schedules, and geographical information of the location. The server uses database queries to filter and collect the necessary data.

[0292] Step 2:

[0293] The server performs analysis using a generative AI model based on the collected data. The input is the dataset of local activities collected in the previous step, and the output is the optimal local activity plan and participant recruitment information. The server processes the data using computing resources and generates the plan proposed by the AI ​​model, taking past trends and patterns into consideration.

[0294] Step 3:

[0295] The server sends the generated participant recruitment information to the terminal and distributes it to local stakeholders. The input is the generated information, and the output is the dissemination of information to all stakeholders. The server uses network communication to send information to the terminal, and the terminal notifies or displays the received information.

[0296] Step 4:

[0297] The device acquires and collects the user's location information in real time. The input is location data obtained via the device's GPS function, and the output is real-time location information. The device periodically reads data from the GPS sensor and sends it to the server or uses it for internal processing.

[0298] Step 5:

[0299] The server creates and provides optimal route guidance to the user based on location information. Input is real-time location information and the generated plan, while output is the optimal route information presented to the user. The server uses a Geographic Information System (GIS) to calculate the route and transmit the route guidance to the terminal.

[0300] Step 6:

[0301] Users receive guidance information through their devices and participate in local activities. Input is the schedule and route information displayed on the device, and output is the user participating in the activity at the appropriate time. Users operate the device's interface and act based on the information provided.

[0302] 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.

[0303] An excellent embodiment for carrying out the present invention is shown below. In addition to the functions of efficiently collecting operational information for local events and generating and distributing participant recruitment information, this system is equipped with an emotion engine that recognizes the user's emotions and optimizes local events based on them.

[0304] The server collects data on the operation of local events from a database and uses AI to analyze participant trends and the performance of past events. Based on these results, it generates the optimal event route and participant recruitment information. The terminal then receives this generated information and delivers advertisements to participants via social media and a dedicated app.

[0305] Users can access recruitment information received through their devices and easily register to participate in local events. Once registration is complete, the server distributes schedule information and important notes to the user. Furthermore, the server obtains participants' real-time location information and provides traffic information and updates on the event's progress.

[0306] In addition, this system incorporates an emotion engine, and the terminal analyzes the user's behavior patterns and responses using the emotion engine. The results of this analysis are used for route adjustment to improve the satisfaction of participants and for personalized information notification.

[0307] As a specific example, when the emotion engine determines that the user's stress level is high on the day of the festival, the terminal immediately provides the user with information on routes to avoid crowds and areas where they can relax. In this way, the experience of participating in local events can be improved, further promoting local activation and enhancing the satisfaction of participants.

[0308] The following describes the process flow.

[0309] Step 1:

[0310] The server collects past data related to local events from the database. This includes a variety of information such as the number of participants, age distribution, geographical information of the event location, and user feedback during the event.

[0311] Step 2:

[0312] The server uses the collected data to perform analysis using an AI model and generates an optimal route and means of recruiting participants. This analysis includes extracting past successful cases and analyzing the behavior trends of participants.

[0313] Step 3:

[0314] The terminal receives the optimization information generated by the server and distributes recruitment advertisements to potential participants through the local SNS or dedicated app.

[0315] Step 4:

[0316] The user uses the terminal to view the recruitment advertisement and accesses the participation registration page from the provided link if they are interested.

[0317] Step 5:

[0318] Users officially register their participation by entering the required personal information on the registration page. This indicates their intention to participate in the event.

[0319] Step 6:

[0320] The server receives registration information from the user, automatically generates an optimal schedule and notes, and sends a confirmation notification to the user.

[0321] Step 7:

[0322] The device uses an emotion engine to analyze user behavior data and input data, and evaluates the user's emotional state.

[0323] Step 8:

[0324] Based on the evaluated emotional state, the server adjusts the route or provides special notifications to improve the participant's experience.

[0325] Step 9:

[0326] On the day of the festival, the device will acquire the user's location information in real time and provide navigation information and emotionally tailored advice as needed. Based on this information, users can enjoy local events efficiently and comfortably.

[0327] (Example 2)

[0328] 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".

[0329] In managing local events, efficiently recruiting participants and providing information is challenging, resulting in a lack of customized experiences tailored to the individual needs of participants. Furthermore, the limited means of tracking participants' movements in real time and providing relevant information make improving participant satisfaction a challenge.

[0330] 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.

[0331] In this invention, the server includes means for collecting data related to the operation of local events, means for creating participant recruitment information based on the collected data, and means equipped with an emotion recognition engine that analyzes user behavior and provides personalized information. This enables the provision of customized information adapted to the needs of participants and improves satisfaction by utilizing real-time participant location information.

[0332] A "local event" refers to a public or private event, such as a festival, workshop, or other event held in a specific region.

[0333] "Operational data" refers to information related to the planning, preparation, and execution of an event, including the number of participants, time, location, content, and necessary resources.

[0334] "Participant recruitment information" refers to information provided to encourage participation in an event, and includes details about the event's content, how to participate, how to register, and more.

[0335] An "emotion recognition engine" is software or a system that analyzes user behavior data and reactions to infer the user's emotional state and provide information based on that inference.

[0336] "Location data" refers to geographical data obtained from GPS information and location services that indicate the current location of participants.

[0337] "Itinerary optimization" refers to the process of optimizing routes and schedules to make the user's travel and event participation process efficient and comfortable.

[0338] The server is responsible for the core functions of this invention, aggregating operational data for local events. A commonly used database software is used as the database management system to manage historical event data, participant information, and related operational information. The collected data is formatted for analysis and analyzed using AI. For the analysis, machine learning platforms such as TensorFlow and PyTorch are used to predict participant trends and event performance.

[0339] The server generates optimal participant recruitment information based on the analysis results and creates prompt messages using a generative AI model. This can utilize language generation models and natural language processing technologies to provide effective catchphrases and text that will attract participants' interest.

[0340] The terminal receives participant recruitment information sent from the server and delivers advertisements to users via social media and dedicated apps. Specifically, the terminal's role is to efficiently attract participants by using APIs from Facebook and Twitter to implement targeted advertising.

[0341] Users can register to participate in local events based on recruitment information received through their devices. The registration process is conducted using an application with an intuitive user interface, designed to allow users to quickly and accurately enter the necessary information.

[0342] Furthermore, devices equipped with an emotion recognition engine analyze user usage patterns and feedback, and execute algorithms to provide personalized information. This enables optimal event routes and information notifications based on the user's emotional state. For example, if the emotion engine determines that the user's stress level is high on the day of a festival, the device can immediately guide the user to routes that avoid crowds or to areas where they can relax.

[0343] An example of a prompt message might be, "Generate route guidance to provide when the user's stress level is high." This allows users to enjoy local events comfortably, resulting in improved event satisfaction and participation experience.

[0344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0345] Step 1:

[0346] The server first retrieves operational data related to local events from a database. Inputs include past event data, participant numbers, and weather information. This data undergoes a cleansing process to remove irregular data and outliers, resulting in an analyzable dataset. The output is this formatted dataset.

[0347] Step 2:

[0348] The server inputs the formatted dataset into an AI algorithm and performs data analysis. Specifically, it uses TensorFlow or PyTorch to perform time-series analysis of event trends and participant behavior. In this process, it extracts features and performs pattern recognition to output trends based on participants' interests and preferences. The analysis results become a predictive model used in the next step.

[0349] Step 3:

[0350] The server uses an AI model based on the analysis results to generate optimal participant recruitment information and prompt messages. The input consists of the analysis results and the AI ​​model, and the generated prompt messages include elements that will attract participants' interest. For example, a message like "We'll introduce you to local events you can enjoy participating in!" might be output.

[0351] Step 4:

[0352] The terminal receives prompt messages and participant recruitment information sent from the server and delivers advertisements via social media and a dedicated app. Specifically, it delivers targeted content based on participants' interests via social media APIs. The input is generated information from the server, and the output is the delivered advertisement.

[0353] Step 5:

[0354] Users check recruitment information received via their devices and register to participate in local events. Input is done through a registration form displayed on the device, and the operation is performed within the app. Output is registration information sent to the server, which is used to confirm participation in events.

[0355] Step 6:

[0356] The server notifies users who have completed registration of the event schedule and important information. The input is registration information, and the output is a notification message to the user. This message is provided via email or push notification.

[0357] Step 7:

[0358] The server uses GPS information from smart devices to track the user's location in real time. The input is device location data, and the output is dynamic traffic information and event progress updates. This allows for real-time support to be provided to the user.

[0359] Step 8:

[0360] The device uses an emotion recognition engine to analyze user behavior patterns and responses. Inputs include app usage history and user responses, and based on the analysis, it outputs personalized information and route suggestions. This output is designed to help participants enjoy the event more comfortably.

[0361] (Application Example 2)

[0362] 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."

[0363] In today's diverse community events and retail environments, there is a growing need for information tailored to the individual interests and satisfaction levels of participants and consumers. However, traditional systems have struggled to instantly provide personalized suggestions based on individual participants' emotions and location information, making it difficult to improve the consumer experience. Therefore, new methods are needed to enhance participant satisfaction in community events and store visits.

[0364] 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.

[0365] In this invention, the server includes means for collecting information related to the operation of local events, means for generating participant recruitment information based on the collected information, a mechanism for distributing the generated recruitment information to local consumers, a device for receiving registration information from participants, a device for notifying users of the schedule and precautions for holding local events, and a mechanism for analyzing consumer sentiment and generating personalized suggestions based on the analysis results. This enables participants to receive information tailored to their individual needs, making local events and retail experiences more attractive and satisfying.

[0366] "Information regarding the operation of local events" refers to detailed data and plans for events, festivals, meetings, etc., held in the local area. This information includes the number of participants, the results of past events, schedules, locations, and related operational details.

[0367] "Participant recruitment information" refers to the content of announcements and advertisements designed to attract people to participate in local events and activities. This information includes the date, time, location, participation requirements, and registration method of the event.

[0368] A "consumer distribution mechanism" refers to a system or method for distributing specific information to targeted consumers or participants. This is done through communication methods such as email, SMS, and smartphone apps.

[0369] A "device for receiving registration information" refers to a system or device for participants to input and submit the necessary information to participate in local events and activities. This device is implemented through online forms, dedicated application applications, and the like.

[0370] "Devices for notifying users of schedules and important information" refers to devices or systems used to inform participants of event-related schedules and important points. This includes calendar apps and notification systems.

[0371] A "mechanism for analyzing consumer emotions" refers to a system or algorithm for evaluating consumers' emotional states and analyzing data based on those evaluations. This includes artificial intelligence that evaluates emotions using behavioral data and biometric information.

[0372] A "mechanism for generating personalized suggestions" refers to a system that creates customized advice and suggestions based on the individual user's preferences and emotional state. This includes recommendation engines and profiling technologies.

[0373] To realize this application, it is crucial that a server equipped with advanced data collection and analysis capabilities throughout the entire system is coordinated with the terminals used by users. The server collects information related to the operation of local events using sensors and statistical data, and stores this information in a database. Furthermore, artificial intelligence is used to analyze this data and generate participant recruitment information and personalized route guidance based on the movements of individual participants.

[0374] The devices function as an interface with the user, receiving and displaying generated information in real time. Specifically, applications installed on smartphones and smart glasses send the user's emotional information to an emotion engine, and the system provides optimal information based on the analysis results. These devices also acquire the user's location information and act as a means of communication to suggest routes that avoid congestion and recommended rest spots.

[0375] For example, when a user visits a physical store, the system analyzes emotional data and, if it determines that the user is seeking relaxation, guides them to a location where relaxing products are displayed or to a quiet corner. Furthermore, by inputting a specific prompt example such as, "Please suggest application scenarios for proposing the optimal purchasing experience in a physical store using consumer emotional data," the generative AI model will provide appropriate suggestions.

[0376] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0377] Step 1:

[0378] The server collects data related to local events from various sensors and databases. This input data includes historical information about past events, participant numbers, and event dates. By collecting this data, the server prepares the foundational information necessary for the next analysis step.

[0379] Step 2:

[0380] The server inputs the collected data into an artificial intelligence engine to analyze participant behavior. As a result of this data analysis, it generates optimized event plans and recruitment information. At this time, the AI ​​model uses a generative AI model to analyze data trends and identify emerging patterns.

[0381] Step 3:

[0382] The terminal receives optimized event and recruitment information sent from the server. This information is displayed through the user interface, allowing the user to review the necessary details and consider participating in the event.

[0383] Step 4:

[0384] Users register to participate through their device. During this process, users enter necessary personal information and their preferred participation date and time. The device then sends this information to the server, completing the event registration.

[0385] Step 5:

[0386] The server uses the registration information received from the user to notify them of the scheduled event schedule and important notes. This output information is delivered directly to the user's device and serves as helpful guidance when participating in the event.

[0387] Step 6:

[0388] The device acquires the user's location information and emotional data in real time. When this data is input, the emotional engine within the device analyzes the data and generates optimal information based on the user's current state.

[0389] Step 7:

[0390] Based on the results of emotion analysis, the device presents personalized suggestions to the user. For example, if the user is feeling stressed, it will notify them of routes to avoid crowds or places where they can relax. In this way, the user can have the most useful and comfortable experience at that moment.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] [Third Embodiment]

[0395] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0396] 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.

[0397] 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).

[0398] 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.

[0399] 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.

[0400] 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).

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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".

[0407] The present invention will now be described in terms of embodiments. The server collects and analyzes past data on local events from a database. This data includes the number of participants in the event, their age groups, past schedules, and geographical information of the event location. Based on the results of the analysis, the server uses AI to generate the optimal route for the local event and information on recruiting participants. Next, the terminal receives this information provided by the server and distributes recruitment advertisements to prospective participants via social media or a dedicated app.

[0408] Users can receive recruitment information through their devices and register to participate by clicking a link. Once a user completes registration, the server receives the information and notifies them in advance of necessary schedules and important notes. Furthermore, the device obtains the user's location information in real time and provides traffic information and route guidance for the day, enabling participants to smoothly enjoy local events.

[0409] As a concrete example, consider a summer festival held in a certain region. The server analyzes summer festival data from the past three years and uses AI to optimize this year's festival route. The terminal also uses a local community app to distribute information about recruiting volunteers to carry the portable shrine. Users register to participate based on this information and receive the festival schedule and important notices through the terminal. This ensures that the traditional local event is run efficiently and smoothly, providing a fulfilling experience for both participants and the community.

[0410] The following describes the processing flow.

[0411] Step 1:

[0412] The server collects historical data on local events from a database. This includes the number and age range of participants, weather conditions, past routes, event schedules, and relevant economic data.

[0413] Step 2:

[0414] The server inputs the collected data into an AI model and uses statistical analysis and machine learning techniques to analyze participant mobilization trends, optimal routes, and patterns for effective event management.

[0415] Step 3:

[0416] Based on the analysis results, the server uses AI to generate the optimal routes and participant recruitment strategies for this year's local events. This information aims to maximize the success rate of the events.

[0417] Step 4:

[0418] The terminal receives routes and recruitment information provided by the server and distributes recruitment advertisements and related information to local residents via local social networking services and dedicated apps.

[0419] Step 5:

[0420] Users receive advertisements delivered through their devices, and if they are interested, they click on the link in the advertisement to access the registration page.

[0421] Step 6:

[0422] Users enter their information on the registration page and officially register their participation in local events.

[0423] Step 7:

[0424] The server receives registration information from users and, along with registration confirmation, sends users emails or app notifications containing the necessary schedule and important information for participation.

[0425] Step 8:

[0426] On the day of the festival, the device will acquire the user's location information in real time, update traffic conditions and the progress of the event as needed, and provide navigation and change information to the user as required.

[0427] (Example 1)

[0428] 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."

[0429] In modern community activities, there is a need to ensure that diverse participants can participate efficiently. However, traditional methods have faced challenges such as insufficient information and inadequate optimization in event preparation and participant guidance on the day of the event. Therefore, there is a need for means to achieve smooth operation of community activities and improve participant satisfaction.

[0430] 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.

[0431] In this invention, the server includes means for collecting data related to local activities, means for analyzing the collected data, and means for generating optimal route plans and participant recruitment information using a generation model based on the analysis results. This enables efficient optimization of the planning and operation of local activities, and facilitates the smooth provision of information and guidance to participants.

[0432] "Community activities" refer to events and activities carried out jointly by local residents in a specific geographical area.

[0433] "Data collection" refers to the act of gathering necessary data from target information sources, and includes information on participants in local activities and geographical information.

[0434] "Data analysis" refers to the process of organizing collected data and using statistical and machine learning techniques to gain useful insights.

[0435] A "generative model" refers to an algorithm or artificial intelligence framework that uses collected data to derive new information or optimal solutions.

[0436] "Route planning" refers to the process of creating routes that allow participants to move efficiently within a community activity.

[0437] "Participant recruitment information" refers to information provided to encourage participation in community activities and to attract new participants.

[0438] The embodiments for carrying out the present invention will be described in detail.

[0439] The server first collects data related to community activities. This data includes information on past participants, age groups, past schedules, and geographical information, and is stored using a database management system. The server uses a relational database such as MySQL and retrieves the data by querying it with a Python script.

[0440] Next, the server analyzes the collected data. This analysis is performed using Python and machine learning libraries (e.g., TensorFlow and PyTorch). This allows for the detection of data patterns and the deriving of optimal responses regarding participants' interests and movements. Specifically, an AI model based on past data optimizes the routes for this year's event.

[0441] The terminals play a role in distributing recruitment information to local participants using information provided by the server. The terminals send notifications using social networking platforms or dedicated applications. For example, mobile devices running iOS or Android fall into this category.

[0442] Users can register to participate based on information received through their devices. Once a user clicks a link and completes registration, the server will notify the user of relevant schedules and important notices on the server side. Notifications will be sent via email or push notifications.

[0443] Furthermore, the device acquires the user's real-time location information and uses the Google Maps API to provide specific traffic information and route guidance, thereby supporting users in smoothly participating in local activities.

[0444] As a concrete example, let's consider a summer festival in a specific region. The server collects and analyzes festival data from the past three years. The generating AI model performs route optimization using the prompt message "Analyze the summer festival data from the past three years and propose the optimal route." Using terminals, volunteer recruitment information is distributed through a local community app, and participants can receive necessary information in real time through their terminals. This structure allows community activities to be managed more efficiently, and participants can comfortably enjoy the events.

[0445] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0446] Step 1:

[0447] The server collects data related to local activities. It retrieves information from the database using SQL queries, extracting data including participant information, age groups, schedules, and geographical information. The input requires database connection information and query conditions for the desired data; the output is structured data based on the query. This process provides foundational data for analysis.

[0448] Step 2:

[0449] The server analyzes the collected data. Using Python and machine learning frameworks, it performs data analysis with an AI model. The input is structured data extracted from a database. The server formats the data, inputs it into the AI ​​model, and uses prompts to instruct it to "generate the optimal route based on past data." The output is optimized routes and participant recruitment information.

[0450] Step 3:

[0451] The server sends the generated information to the terminal, which then uses that information to distribute recruitment advertisements for participants. The terminal then spreads the information using social networking platforms and dedicated applications. Data from the server is required as input, and the output is in the form of application notifications and social networking posts. This ensures that the information reaches a wide range of participants.

[0452] Step 4:

[0453] Users register to participate based on information received from their devices. Users click a link, fill out a form, and their devices send this information to the server. The input includes the user's personal information and participation preference, while the output is a registration confirmation notification sent to the user. This step confirms and records the user's intention to participate.

[0454] Step 5:

[0455] The server uses registration information to notify users in advance of the event schedule and important notes. The device then transmits this information to the user via push notifications or email. Inputs include user information and event details from registration, while output is the notification content delivered to the user. In this way, participants can obtain necessary information early.

[0456] Step 6:

[0457] The device acquires the user's real-time location data and provides traffic information and route guidance using the Google Maps API. It periodically receives the user's location information as input and displays the optimal mode of transport and route guidance as output. This makes it possible to support smooth travel throughout the day.

[0458] (Application Example 1)

[0459] 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."

[0460] In managing community activities and events, providing information to participants and stakeholders is cumbersome, making efficient participant recruitment and scheduling difficult. Furthermore, the use of past data to develop optimal plans is insufficient. Additionally, features such as real-time participant location tracking and appropriate route guidance are limited. A system is needed to solve these problems and facilitate the smooth operation of community activities.

[0461] 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.

[0462] In this invention, the server includes means for collecting information related to the management of local activities, means for generating participant guidance information based on the collected information, and means for analyzing past activity data to create an optimal plan. This enables efficient participant recruitment, optimization of schedules and routes, and real-time location information management and information provision.

[0463] "Community activities" refer to collaborative initiatives and events held in a specific area, involving residents and participants.

[0464] "Management" is the act of controlling and systematically utilizing resources and information in order to achieve specific goals.

[0465] "Information" is a collection of knowledge and facts that are gathered as data, and whose value is created through analysis and use.

[0466] A "participant" is an individual or group that has expressed their intention to participate in a particular activity or event.

[0467] "Information" refers to instructions provided to participants and related parties regarding the activity, such as the date, time, location, and procedures.

[0468] "Past activity data" refers to records and history of activities that have been carried out in the past, and this information can be used to help formulate future plans through analysis.

[0469] An "optimal plan" is a set of action or procedures formulated to achieve a goal most effectively within given conditions and constraints.

[0470] A "server" is a device or software that processes information and provides services to other computers or terminals via a network.

[0471] "Location information" refers to data that indicates the physical location of a specific object, and is expressed in forms such as latitude, longitude, or address.

[0472] To implement this invention, the process begins with a server collecting and analyzing historical data related to local activities from a database. This data includes the number and age range of participants, past schedules, and geographical information of the event location. Based on this data, the server uses a generative AI model to generate an optimal plan for local activities and information for recruiting participants.

[0473] Information generated by the server is distributed to local stakeholders via terminals. Stakeholders can use the terminal's application to receive the distributed guidance information and obtain their real-time location. Activity schedules and important notices are also notified via the terminal, allowing stakeholders to check necessary information at any time. Furthermore, the terminal provides optimal route guidance based on past data and current location information.

[0474] As a concrete example, in a local event, the server uses AI to analyze past event data and create an optimal participant recruitment plan for the current year. It also provides real-time route guidance and schedule information to relevant parties via terminals, ensuring efficient event management. An example of a prompt to input into the generating AI model might be, "Please suggest the optimal route for local activities during the year-end and New Year period."

[0475] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0476] Step 1:

[0477] The server collects historical data on community activities from a database. The input is the records of community activities in the database, and the output is the collected dataset. This dataset includes information such as the number of participants, age groups, past schedules, and geographical information of the location. The server uses database queries to filter and collect the necessary data.

[0478] Step 2:

[0479] The server performs analysis using a generative AI model based on the collected data. The input is the dataset of local activities collected in the previous step, and the output is the optimal local activity plan and participant recruitment information. The server processes the data using computing resources and generates the plan proposed by the AI ​​model, taking past trends and patterns into consideration.

[0480] Step 3:

[0481] The server sends the generated participant recruitment information to the terminal and distributes it to local stakeholders. The input is the generated information, and the output is the dissemination of information to all stakeholders. The server uses network communication to send information to the terminal, and the terminal notifies or displays the received information.

[0482] Step 4:

[0483] The device acquires and collects the user's location information in real time. The input is location data obtained via the device's GPS function, and the output is real-time location information. The device periodically reads data from the GPS sensor and sends it to the server or uses it for internal processing.

[0484] Step 5:

[0485] The server creates and provides optimal route guidance to the user based on location information. Input is real-time location information and the generated plan, while output is the optimal route information presented to the user. The server uses a Geographic Information System (GIS) to calculate the route and transmit the route guidance to the terminal.

[0486] Step 6:

[0487] Users receive guidance information through their devices and participate in local activities. Input is the schedule and route information displayed on the device, and output is the user participating in the activity at the appropriate time. Users operate the device's interface and act based on the information provided.

[0488] 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.

[0489] An excellent embodiment for carrying out the present invention is shown below. In addition to the functions of efficiently collecting operational information for local events and generating and distributing participant recruitment information, this system is equipped with an emotion engine that recognizes the user's emotions and optimizes local events based on them.

[0490] The server collects data on the operation of local events from a database and uses AI to analyze participant trends and the performance of past events. Based on these results, it generates the optimal event route and participant recruitment information. The terminal then receives this generated information and delivers advertisements to participants via social media and a dedicated app.

[0491] Users can access recruitment information received through their devices and easily register to participate in local events. Once registration is complete, the server distributes schedule information and important notices to the user. Furthermore, the server obtains participants' real-time location information and provides traffic information and updates on the event's progress.

[0492] In addition, this system incorporates an emotion engine, which analyzes the user's behavior patterns and responses. The results of this analysis are used to adjust routes to improve participant satisfaction and to provide personalized information notifications.

[0493] For example, if the emotion engine determines that a user's stress level is high on the day of the festival, the device will immediately provide the user with information on routes to avoid crowds and areas where they can relax. In this way, the experience of participating in local events can be improved, leading to further regional revitalization and increased participant satisfaction.

[0494] The following describes the processing flow.

[0495] Step 1:

[0496] The server collects historical data related to local events from a database. This includes a variety of information such as the number of participants, age distribution, geographical information of the event location, and user feedback during the event.

[0497] Step 2:

[0498] The server uses AI models to analyze the collected data and generate optimal routes and participant recruitment methods. This analysis includes extracting past success stories and analyzing participant behavioral trends.

[0499] Step 3:

[0500] The device receives optimization information generated from the server and distributes recruitment advertisements to prospective participants via local social media and dedicated apps.

[0501] Step 4:

[0502] Users view recruitment advertisements on their devices and, if interested, access the registration page via the provided link.

[0503] Step 5:

[0504] Users officially register their participation by entering the required personal information on the registration page. This indicates their intention to participate in the event.

[0505] Step 6:

[0506] The server receives registration information from the user, automatically generates an optimal schedule and notes, and sends a confirmation notification to the user.

[0507] Step 7:

[0508] The device uses an emotion engine to analyze user behavior data and input data, and evaluates the user's emotional state.

[0509] Step 8:

[0510] Based on the evaluated emotional state, the server adjusts the route or provides special notifications to improve the participant's experience.

[0511] Step 9:

[0512] On the day of the festival, the device will acquire the user's location information in real time and provide navigation information and emotionally tailored advice as needed. Based on this information, users can enjoy local events efficiently and comfortably.

[0513] (Example 2)

[0514] 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."

[0515] In managing local events, efficiently recruiting participants and providing information is challenging, resulting in a lack of customized experiences tailored to the individual needs of participants. Furthermore, the limited means of tracking participants' movements in real time and providing relevant information make improving participant satisfaction a challenge.

[0516] 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.

[0517] In this invention, the server includes means for collecting data related to the operation of local events, means for creating participant recruitment information based on the collected data, and means equipped with an emotion recognition engine that analyzes user behavior and provides personalized information. This enables the provision of customized information adapted to the needs of participants and improves satisfaction by utilizing real-time participant location information.

[0518] A "local event" refers to a public or private event, such as a festival, workshop, or lecture, held in a specific region.

[0519] "Operational data" refers to information related to the planning, preparation, and execution of an event, including the number of participants, time, location, content, and necessary resources.

[0520] "Participant recruitment information" refers to information provided to encourage participation in an event, and includes details about the event's content, how to participate, how to register, and more.

[0521] An "emotion recognition engine" is software or a system that analyzes user behavior data and reactions to infer the user's emotional state and provide information based on that inference.

[0522] "Location data" refers to geographical data obtained from GPS information and location services that indicate the current location of participants.

[0523] "Itinerary optimization" refers to the process of optimizing routes and schedules to make the user's travel and event participation process efficient and comfortable.

[0524] The server is responsible for the core functions of this invention, aggregating operational data for local events. A commonly used database software is used as the database management system to manage historical event data, participant information, and related operational information. The collected data is formatted for analysis and analyzed using AI. For the analysis, machine learning platforms such as TensorFlow and PyTorch are used to predict participant trends and event performance.

[0525] The server generates optimal participant recruitment information based on the analysis results and creates prompt messages using a generative AI model. This can utilize language generation models and natural language processing technologies to provide effective catchphrases and text that will attract participants' interest.

[0526] The terminal receives participant recruitment information sent from the server and delivers advertisements to users via social media and dedicated apps. Specifically, the terminal's role is to efficiently attract participants by using APIs from Facebook and Twitter to implement targeted advertising.

[0527] Users can register to participate in local events based on recruitment information received through their devices. The registration process is conducted using an application with an intuitive user interface, designed to allow users to quickly and accurately enter the necessary information.

[0528] Furthermore, devices equipped with an emotion recognition engine analyze user usage patterns and feedback, and execute algorithms to provide personalized information. This enables optimal event routes and information notifications based on the user's emotional state. For example, if the emotion engine determines that the user's stress level is high on the day of a festival, the device can immediately guide the user to routes that avoid crowds or to areas where they can relax.

[0529] An example of a prompt message might be, "Generate route guidance to provide when the user's stress level is high." This allows users to enjoy local events comfortably, resulting in improved event satisfaction and participation experience.

[0530] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0531] Step 1:

[0532] The server first retrieves operational data related to local events from a database. Inputs include past event data, participant numbers, and weather information. This data undergoes a cleansing process to remove irregular data and outliers, resulting in an analyzable dataset. The output is this formatted dataset.

[0533] Step 2:

[0534] The server inputs the formatted dataset into an AI algorithm and performs data analysis. Specifically, it uses TensorFlow or PyTorch to perform time-series analysis of event trends and participant behavior. In this process, it extracts features and performs pattern recognition to output trends based on participants' interests and preferences. The analysis results become a predictive model used in the next step.

[0535] Step 3:

[0536] The server uses an AI model based on the analysis results to generate optimal participant recruitment information and prompt messages. The input consists of the analysis results and the AI ​​model, and the generated prompt messages include elements that will attract participants' interest. For example, a message like "We'll introduce you to local events you can enjoy participating in!" might be output.

[0537] Step 4:

[0538] The terminal receives prompt messages and participant recruitment information sent from the server and delivers advertisements via social media and a dedicated app. Specifically, it delivers targeted content based on participants' interests via social media APIs. The input is generated information from the server, and the output is the delivered advertisement.

[0539] Step 5:

[0540] Users check recruitment information received via their devices and register to participate in local events. Input is done through a registration form displayed on the device, and the operation is performed within the app. Output is registration information sent to the server, which is used to confirm participation in events.

[0541] Step 6:

[0542] The server notifies users who have completed registration of the event schedule and important information. The input is registration information, and the output is a notification message to the user. This message is provided via email or push notification.

[0543] Step 7:

[0544] The server uses GPS information from smart devices to track the user's location in real time. The input is device location data, and the output is dynamic traffic information and event progress updates. This allows for real-time support to be provided to the user.

[0545] Step 8:

[0546] The device uses an emotion recognition engine to analyze user behavior patterns and responses. Inputs include app usage history and user responses, and based on the analysis, it outputs personalized information and route suggestions. This output is designed to help participants enjoy the event more comfortably.

[0547] (Application Example 2)

[0548] 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."

[0549] In today's diverse community events and retail environments, there is a growing need for information tailored to the individual interests and satisfaction levels of participants and consumers. However, traditional systems have struggled to instantly provide personalized suggestions based on individual participants' emotions and location information, making it difficult to improve the consumer experience. Therefore, new methods are needed to enhance participant satisfaction in community events and store visits.

[0550] 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.

[0551] In this invention, the server includes means for collecting information related to the operation of local events, means for generating participant recruitment information based on the collected information, a mechanism for distributing the generated recruitment information to local consumers, a device for receiving registration information from participants, a device for notifying users of the schedule and precautions for holding local events, and a mechanism for analyzing consumer sentiment and generating personalized suggestions based on the analysis results. This enables participants to receive information tailored to their individual needs, making local events and retail experiences more attractive and satisfying.

[0552] "Information regarding the operation of local events" refers to detailed data and plans for events, festivals, meetings, etc., held in the local area. This information includes the number of participants, the results of past events, schedules, locations, and related operational details.

[0553] "Participant recruitment information" refers to the content of announcements and advertisements designed to attract people to participate in local events and activities. This information includes the date, time, location, participation requirements, and registration method of the event.

[0554] A "consumer distribution mechanism" refers to a system or method for distributing specific information to targeted consumers or participants. This is done through communication methods such as email, SMS, and smartphone apps.

[0555] A "device for receiving registration information" refers to a system or device for participants to input and submit the necessary information to participate in local events and activities. This device is implemented through online forms, dedicated application applications, and the like.

[0556] "Devices for notifying users of schedules and important information" refers to devices or systems used to inform participants of event-related schedules and important points. This includes calendar apps and notification systems.

[0557] A "mechanism for analyzing consumer emotions" refers to a system or algorithm for evaluating consumers' emotional states and analyzing data based on those evaluations. This includes artificial intelligence that evaluates emotions using behavioral data and biometric information.

[0558] A "mechanism for generating personalized suggestions" refers to a system that creates customized advice and suggestions based on the individual user's preferences and emotional state. This includes recommendation engines and profiling technologies.

[0559] To realize this application, it is crucial that a server equipped with advanced data collection and analysis capabilities throughout the entire system is coordinated with the terminals used by users. The server collects information related to the operation of local events using sensors and statistical data, and stores this information in a database. Furthermore, artificial intelligence is used to analyze this data and generate participant recruitment information and personalized route guidance based on the movements of individual participants.

[0560] The devices function as an interface with the user, receiving and displaying generated information in real time. Specifically, applications installed on smartphones and smart glasses send the user's emotional information to an emotion engine, and the system provides optimal information based on the analysis results. These devices also acquire the user's location information and act as a means of communication to suggest routes that avoid congestion and recommended rest spots.

[0561] For example, when a user visits a physical store, the system analyzes emotional data and, if it determines that the user is seeking relaxation, guides them to a location where relaxing products are displayed or to a quiet corner. Furthermore, by inputting a specific prompt example such as, "Please suggest application scenarios for proposing the optimal purchasing experience in a physical store using consumer emotional data," the generative AI model will provide appropriate suggestions.

[0562] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0563] Step 1:

[0564] The server collects data related to local events from various sensors and databases. This input data includes historical information about past events, participant numbers, and event dates. By collecting this data, the server prepares the foundational information necessary for the next analysis step.

[0565] Step 2:

[0566] The server inputs the collected data into an artificial intelligence engine to analyze participant behavior. As a result of this data analysis, it generates optimized event plans and recruitment information. At this time, the AI ​​model uses a generative AI model to analyze data trends and identify emerging patterns.

[0567] Step 3:

[0568] The terminal receives optimized event and recruitment information sent from the server. This information is displayed through the user interface, allowing the user to review the necessary details and consider participating in the event.

[0569] Step 4:

[0570] Users register to participate through their device. During this process, users enter necessary personal information and their preferred participation date and time. The device then sends this information to the server, completing the event registration.

[0571] Step 5:

[0572] The server uses the registration information received from the user to notify them of the schedule and important notes for upcoming events. This output information is delivered directly to the user's device and serves as helpful guidance when participating in the event.

[0573] Step 6:

[0574] The device acquires the user's location information and emotional data in real time. When this data is input, the emotional engine within the device analyzes the data and generates optimal information based on the user's current state.

[0575] Step 7:

[0576] Based on the results of emotion analysis, the device presents personalized suggestions to the user. For example, if the user is feeling stressed, it will notify them of routes to avoid crowds or places where they can relax. In this way, the user can have the most useful and comfortable experience at that moment.

[0577] 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.

[0578] 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.

[0579] 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.

[0580] [Fourth Embodiment]

[0581] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0582] 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.

[0583] 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).

[0584] 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.

[0585] 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.

[0586] 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).

[0587] 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.

[0588] 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.

[0589] 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.

[0590] 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.

[0591] 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.

[0592] 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.

[0593] 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".

[0594] The present invention will now be described in terms of embodiments. The server collects and analyzes past data on local events from a database. This data includes the number of participants in the event, their age groups, past schedules, and geographical information of the event location. Based on the results of the analysis, the server uses AI to generate the optimal route for the local event and information on recruiting participants. Next, the terminal receives this information provided by the server and distributes recruitment advertisements to prospective participants via social media or a dedicated app.

[0595] Users can receive recruitment information through their devices and register to participate by clicking a link. Once a user completes registration, the server receives the information and notifies them in advance of necessary schedules and important notes. Furthermore, the device obtains the user's location information in real time and provides traffic information and route guidance for the day, enabling participants to smoothly enjoy local events.

[0596] As a concrete example, consider a summer festival held in a certain region. The server analyzes summer festival data from the past three years and uses AI to optimize this year's festival route. The terminal also uses a local community app to distribute information about recruiting volunteers to carry the portable shrine. Users register to participate based on this information and receive the festival schedule and important notices through the terminal. This ensures that the traditional local event is run efficiently and smoothly, providing a fulfilling experience for both participants and the community.

[0597] The following describes the processing flow.

[0598] Step 1:

[0599] The server collects historical data on local events from a database. This includes the number and age range of participants, weather conditions, past routes, event schedules, and relevant economic data.

[0600] Step 2:

[0601] The server inputs the collected data into an AI model and uses statistical analysis and machine learning techniques to analyze participant mobilization trends, optimal routes, and patterns for effective event management.

[0602] Step 3:

[0603] Based on the analysis results, the server uses AI to generate the optimal routes and participant recruitment strategies for this year's local events. This information aims to maximize the success rate of the events.

[0604] Step 4:

[0605] The terminal receives routes and recruitment information provided by the server and distributes recruitment advertisements and related information to local residents via local social networking services and dedicated apps.

[0606] Step 5:

[0607] Users receive advertisements delivered through their devices, and if they are interested, they click on the link in the advertisement to access the registration page.

[0608] Step 6:

[0609] Users enter their information on the registration page and officially register their participation in local events.

[0610] Step 7:

[0611] The server receives registration information from users and, along with registration confirmation, sends users emails or app notifications containing the necessary schedule and important information for participation.

[0612] Step 8:

[0613] On the day of the festival, the device will acquire the user's location information in real time, update traffic conditions and the progress of the event as needed, and provide navigation and change information to the user as required.

[0614] (Example 1)

[0615] 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".

[0616] In modern community activities, there is a need to ensure that diverse participants can participate efficiently. However, traditional methods have faced challenges such as insufficient information and inadequate optimization in event preparation and participant guidance on the day of the event. Therefore, there is a need for means to achieve smooth operation of community activities and improve participant satisfaction.

[0617] 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.

[0618] In this invention, the server includes means for collecting data related to local activities, means for analyzing the collected data, and means for generating optimal route plans and participant recruitment information using a generation model based on the analysis results. This enables efficient optimization of the planning and operation of local activities, and facilitates the smooth provision of information and guidance to participants.

[0619] "Community activities" refer to events and activities carried out jointly by local residents in a specific geographical area.

[0620] "Data collection" refers to the act of gathering necessary data from target information sources, and includes information on participants in local activities and geographical information.

[0621] "Data analysis" refers to the process of organizing collected data and using statistical and machine learning techniques to gain useful insights.

[0622] A "generative model" refers to an algorithm or artificial intelligence framework that uses collected data to derive new information or optimal solutions.

[0623] "Route planning" refers to the process of creating routes that allow participants to move efficiently within a community activity.

[0624] "Participant recruitment information" refers to information provided to encourage participation in community activities and to attract new participants.

[0625] The embodiments for carrying out the present invention will be described in detail.

[0626] The server first collects data related to community activities. This data includes information on past participants, age groups, past schedules, and geographical information, and is stored using a database management system. The server uses a relational database such as MySQL and retrieves the data by querying it with a Python script.

[0627] Next, the server analyzes the collected data. This analysis is performed using Python and machine learning libraries (e.g., TensorFlow and PyTorch). This allows for the detection of data patterns and the deriving of optimal responses regarding participants' interests and movements. Specifically, an AI model based on past data optimizes the routes for this year's event.

[0628] The terminals play a role in distributing recruitment information to local participants using information provided by the server. The terminals send notifications using social networking platforms or dedicated applications. For example, mobile devices running iOS or Android fall into this category.

[0629] Users can register to participate based on information received through their devices. Once a user clicks a link and completes registration, the server will notify the user of relevant schedules and important notices on the server side. Notifications will be sent via email or push notifications.

[0630] Furthermore, the device acquires the user's real-time location information and uses the Google Maps API to provide specific traffic information and route guidance, thereby supporting users in smoothly participating in local activities.

[0631] As a concrete example, let's consider a summer festival in a specific region. The server collects and analyzes festival data from the past three years. The generating AI model performs route optimization using the prompt message "Analyze the summer festival data from the past three years and propose the optimal route." Using terminals, volunteer recruitment information is distributed through a local community app, and participants can receive necessary information in real time through their terminals. This structure allows community activities to be managed more efficiently, and participants can comfortably enjoy the events.

[0632] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0633] Step 1:

[0634] The server collects data related to local activities. It retrieves information from the database using SQL queries, extracting data including participant information, age groups, schedules, and geographical information. The input requires database connection information and query conditions for the desired data; the output is structured data based on the query. This process provides foundational data for analysis.

[0635] Step 2:

[0636] The server analyzes the collected data. Using Python and machine learning frameworks, it performs data analysis with an AI model. The input is structured data extracted from a database. The server formats the data, inputs it into the AI ​​model, and uses prompts to instruct it to "generate the optimal route based on past data." The output is optimized routes and participant recruitment information.

[0637] Step 3:

[0638] The server sends the generated information to the terminal, which then uses that information to distribute recruitment advertisements for participants. The terminal then spreads the information using social networking platforms and dedicated applications. Data from the server is required as input, and the output is in the form of application notifications and social networking posts. This ensures that the information reaches a wide range of participants.

[0639] Step 4:

[0640] Users register to participate based on information received from their devices. Users click a link, fill out a form, and their devices send this information to the server. The input includes the user's personal information and participation preference, while the output is a registration confirmation notification sent to the user. This step confirms and records the user's intention to participate.

[0641] Step 5:

[0642] The server uses registration information to notify users in advance of the event schedule and important notes. The device then transmits this information to the user via push notifications or email. Inputs include user information and event details from registration, while output is the notification content delivered to the user. In this way, participants can obtain necessary information early.

[0643] Step 6:

[0644] The device acquires the user's real-time location data and provides traffic information and route guidance using the Google Maps API. It periodically receives the user's location information as input and displays the optimal mode of transport and route guidance as output. This makes it possible to support smooth travel throughout the day.

[0645] (Application Example 1)

[0646] 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".

[0647] In managing community activities and events, providing information to participants and stakeholders is cumbersome, making efficient participant recruitment and scheduling difficult. Furthermore, the use of past data to develop optimal plans is insufficient. Additionally, features such as real-time participant location tracking and appropriate route guidance are limited. A system is needed to solve these problems and facilitate the smooth operation of community activities.

[0648] 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.

[0649] In this invention, the server includes means for collecting information related to the management of local activities, means for generating participant guidance information based on the collected information, and means for analyzing past activity data to create an optimal plan. This enables efficient participant recruitment, optimization of schedules and routes, and real-time location information management and information provision.

[0650] "Community activities" refer to collaborative initiatives and events held in a specific area, involving residents and participants.

[0651] "Management" is the act of controlling and systematically utilizing resources and information in order to achieve specific goals.

[0652] "Information" is a collection of knowledge and facts that are gathered as data, and whose value is created through analysis and use.

[0653] A "participant" is an individual or group that has expressed their intention to participate in a particular activity or event.

[0654] "Information" refers to instructions provided to participants and related parties regarding the activity, such as the date, time, location, and procedures.

[0655] "Past activity data" refers to records and history of activities that have been carried out in the past, and this information can be used to help formulate future plans through analysis.

[0656] An "optimal plan" is a set of action or procedures formulated to achieve a goal most effectively within given conditions and constraints.

[0657] A "server" is a device or software that processes information and provides services to other computers or terminals via a network.

[0658] "Location information" refers to data that indicates the physical location of a specific object, and is expressed in forms such as latitude, longitude, or address.

[0659] To implement this invention, the process begins with a server collecting and analyzing historical data related to local activities from a database. This data includes the number and age range of participants, past schedules, and geographical information of the event location. Based on this data, the server uses a generative AI model to generate an optimal plan for local activities and information for recruiting participants.

[0660] Information generated by the server is distributed to local stakeholders via terminals. Stakeholders can use the terminal's application to receive the distributed guidance information and obtain their real-time location. Activity schedules and important notices are also notified via the terminal, allowing stakeholders to check necessary information at any time. Furthermore, the terminal provides optimal route guidance based on past data and current location information.

[0661] As a concrete example, in a local event, the server uses AI to analyze past event data and create an optimal participant recruitment plan for the current year. It also provides real-time route guidance and schedule information to relevant parties via terminals, ensuring efficient event management. An example of a prompt to input into the generating AI model might be, "Please suggest the optimal route for local activities during the year-end and New Year period."

[0662] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0663] Step 1:

[0664] The server collects historical data on community activities from a database. The input is the records of community activities in the database, and the output is the collected dataset. This dataset includes information such as the number of participants, age groups, past schedules, and geographical information of the location. The server uses database queries to filter and collect the necessary data.

[0665] Step 2:

[0666] The server performs analysis using a generative AI model based on the collected data. The input is the dataset of local activities collected in the previous step, and the output is the optimal local activity plan and participant recruitment information. The server processes the data using computing resources and generates the plan proposed by the AI ​​model, taking past trends and patterns into consideration.

[0667] Step 3:

[0668] The server sends the generated participant recruitment information to the terminal and distributes it to local stakeholders. The input is the generated information, and the output is the dissemination of information to all stakeholders. The server uses network communication to send information to the terminal, and the terminal notifies or displays the received information.

[0669] Step 4:

[0670] The device acquires and collects the user's location information in real time. The input is location data obtained via the device's GPS function, and the output is real-time location information. The device periodically reads data from the GPS sensor and sends it to the server or uses it for internal processing.

[0671] Step 5:

[0672] The server creates and provides optimal route guidance to the user based on location information. Input is real-time location information and the generated plan, while output is the optimal route information presented to the user. The server uses a Geographic Information System (GIS) to calculate the route and transmit the route guidance to the terminal.

[0673] Step 6:

[0674] Users receive guidance information through their devices and participate in local activities. Input is the schedule and route information displayed on the device, and output is the user participating in the activity at the appropriate time. Users operate the device's interface and act based on the information provided.

[0675] 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.

[0676] An excellent embodiment for carrying out the present invention is shown below. In addition to the functions of efficiently collecting operational information for local events and generating and distributing participant recruitment information, this system is equipped with an emotion engine that recognizes the user's emotions and optimizes local events based on them.

[0677] The server collects data on the operation of local events from a database and uses AI to analyze participant trends and the performance of past events. Based on these results, it generates the optimal event route and participant recruitment information. The terminal then receives this generated information and delivers advertisements to participants via social media and a dedicated app.

[0678] Users can access recruitment information received through their devices and easily register to participate in local events. Once registration is complete, the server distributes schedule information and important notices to the user. Furthermore, the server obtains participants' real-time location information and provides traffic information and updates on the event's progress.

[0679] In addition, this system incorporates an emotion engine, which analyzes the user's behavior patterns and responses. The results of this analysis are used to adjust routes to improve participant satisfaction and to provide personalized information notifications.

[0680] For example, if the emotion engine determines that a user's stress level is high on the day of the festival, the device will immediately provide the user with information on routes to avoid crowds and areas where they can relax. In this way, the experience of participating in local events can be improved, leading to further regional revitalization and increased participant satisfaction.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] The server collects historical data related to local events from a database. This includes a variety of information such as the number of participants, age distribution, geographical information of the event location, and user feedback during the event.

[0684] Step 2:

[0685] The server uses AI models to analyze the collected data and generate optimal routes and participant recruitment methods. This analysis includes extracting past success stories and analyzing participant behavioral trends.

[0686] Step 3:

[0687] The device receives optimization information generated from the server and distributes recruitment advertisements to prospective participants via local social media and dedicated apps.

[0688] Step 4:

[0689] Users view recruitment advertisements on their devices and, if interested, access the registration page via the provided link.

[0690] Step 5:

[0691] Users officially register their participation by entering the required personal information on the registration page. This indicates their intention to participate in the event.

[0692] Step 6:

[0693] The server receives registration information from the user, automatically generates an optimal schedule and notes, and sends a confirmation notification to the user.

[0694] Step 7:

[0695] The device uses an emotion engine to analyze user behavior data and input data, and evaluates the user's emotional state.

[0696] Step 8:

[0697] Based on the evaluated emotional state, the server adjusts the route or provides special notifications to improve the participant's experience.

[0698] Step 9:

[0699] On the day of the festival, the device will acquire the user's location information in real time and provide navigation information and emotionally tailored advice as needed. Based on this information, users can enjoy local events efficiently and comfortably.

[0700] (Example 2)

[0701] 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".

[0702] In managing local events, efficiently recruiting participants and providing information is challenging, resulting in a lack of customized experiences tailored to the individual needs of participants. Furthermore, the limited means of tracking participants' movements in real time and providing relevant information make improving participant satisfaction a challenge.

[0703] 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.

[0704] In this invention, the server includes means for collecting data related to the operation of local events, means for creating participant recruitment information based on the collected data, and means equipped with an emotion recognition engine that analyzes user behavior and provides personalized information. This enables the provision of customized information adapted to the needs of participants and improves satisfaction by utilizing real-time participant location information.

[0705] A "local event" refers to a public or private event, such as a festival, workshop, or lecture, held in a specific region.

[0706] "Operational data" refers to information related to the planning, preparation, and execution of an event, including the number of participants, time, location, content, and necessary resources.

[0707] "Participant recruitment information" refers to information provided to encourage participation in an event, and includes details about the event's content, how to participate, how to register, and more.

[0708] An "emotion recognition engine" is software or a system that analyzes user behavior data and reactions to infer the user's emotional state and provide information based on that inference.

[0709] "Location data" refers to geographical data obtained from GPS information and location services that indicate the current location of participants.

[0710] "Itinerary optimization" refers to the process of optimizing routes and schedules to make the user's travel and event participation process efficient and comfortable.

[0711] The server is responsible for the core functions of this invention, aggregating operational data for local events. A commonly used database software is used as the database management system to manage historical event data, participant information, and related operational information. The collected data is formatted for analysis and analyzed using AI. For the analysis, machine learning platforms such as TensorFlow and PyTorch are used to predict participant trends and event performance.

[0712] The server generates optimal participant recruitment information based on the analysis results and creates prompt messages using a generative AI model. This can utilize language generation models and natural language processing technologies to provide effective catchphrases and text that will attract participants' interest.

[0713] The terminal receives participant recruitment information sent from the server and delivers advertisements to users via social media and dedicated apps. Specifically, the terminal's role is to efficiently attract participants by using APIs from Facebook and Twitter to implement targeted advertising.

[0714] Users can register to participate in local events based on recruitment information received through their devices. The registration process is conducted using an application with an intuitive user interface, designed to allow users to quickly and accurately enter the necessary information.

[0715] Furthermore, devices equipped with an emotion recognition engine analyze user usage patterns and feedback, and execute algorithms to provide personalized information. This enables optimal event routes and information notifications based on the user's emotional state. For example, if the emotion engine determines that the user's stress level is high on the day of a festival, the device can immediately guide the user to routes that avoid crowds or to areas where they can relax.

[0716] An example of a prompt message might be, "Generate route guidance to provide when the user's stress level is high." This allows users to enjoy local events comfortably, resulting in improved event satisfaction and participation experience.

[0717] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0718] Step 1:

[0719] The server first retrieves operational data related to local events from a database. Inputs include past event data, participant numbers, and weather information. This data undergoes a cleansing process to remove irregular data and outliers, resulting in an analyzable dataset. The output is this formatted dataset.

[0720] Step 2:

[0721] The server inputs the formatted dataset into an AI algorithm and performs data analysis. Specifically, it uses TensorFlow or PyTorch to perform time-series analysis of event trends and participant behavior. In this process, it extracts features and performs pattern recognition to output trends based on participants' interests and preferences. The analysis results become a predictive model used in the next step.

[0722] Step 3:

[0723] The server uses an AI model based on the analysis results to generate optimal participant recruitment information and prompt messages. The input consists of the analysis results and the AI ​​model, and the generated prompt messages include elements that will attract participants' interest. For example, a message like "We'll introduce you to local events you can enjoy participating in!" might be output.

[0724] Step 4:

[0725] The terminal receives prompt messages and participant recruitment information sent from the server and delivers advertisements via social media and a dedicated app. Specifically, it delivers targeted content based on participants' interests via social media APIs. The input is generated information from the server, and the output is the delivered advertisement.

[0726] Step 5:

[0727] Users check recruitment information received via their devices and register to participate in local events. Input is done through a registration form displayed on the device, and the operation is performed within the app. Output is registration information sent to the server, which is used to confirm participation in events.

[0728] Step 6:

[0729] The server notifies users who have completed registration of the event schedule and important information. The input is registration information, and the output is a notification message to the user. This message is provided via email or push notification.

[0730] Step 7:

[0731] The server uses GPS information from smart devices to track the user's location in real time. The input is device location data, and the output is dynamic traffic information and event progress updates. This allows for real-time support to be provided to the user.

[0732] Step 8:

[0733] The device uses an emotion recognition engine to analyze user behavior patterns and responses. Inputs include app usage history and user responses, and based on the analysis, it outputs personalized information and route suggestions. This output is designed to help participants enjoy the event more comfortably.

[0734] (Application Example 2)

[0735] 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".

[0736] In today's diverse community events and retail environments, there is a growing need for information tailored to the individual interests and satisfaction levels of participants and consumers. However, traditional systems have struggled to instantly provide personalized suggestions based on individual participants' emotions and location information, making it difficult to improve the consumer experience. Therefore, new methods are needed to enhance participant satisfaction in community events and store visits.

[0737] 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.

[0738] In this invention, the server includes means for collecting information related to the operation of local events, means for generating participant recruitment information based on the collected information, a mechanism for distributing the generated recruitment information to local consumers, a device for receiving registration information from participants, a device for notifying users of the schedule and precautions for holding local events, and a mechanism for analyzing consumer sentiment and generating personalized suggestions based on the analysis results. This enables participants to receive information tailored to their individual needs, making local events and retail experiences more attractive and satisfying.

[0739] "Information regarding the operation of local events" refers to detailed data and plans for events, festivals, meetings, etc., held in the local area. This information includes the number of participants, the results of past events, schedules, locations, and related operational details.

[0740] "Participant recruitment information" refers to the content of announcements and advertisements designed to attract people to participate in local events and activities. This information includes the date, time, location, participation requirements, and registration method of the event.

[0741] A "consumer distribution mechanism" refers to a system or method for distributing specific information to targeted consumers or participants. This is done through communication methods such as email, SMS, and smartphone apps.

[0742] A "device for receiving registration information" refers to a system or device for participants to input and submit the necessary information to participate in local events and activities. This device is implemented through online forms, dedicated application applications, and the like.

[0743] "Devices for notifying users of schedules and important information" refers to devices or systems used to inform participants of event-related schedules and important points. This includes calendar apps and notification systems.

[0744] A "mechanism for analyzing consumer emotions" refers to a system or algorithm for evaluating consumers' emotional states and analyzing data based on those evaluations. This includes artificial intelligence that evaluates emotions using behavioral data and biometric information.

[0745] A "mechanism for generating personalized suggestions" refers to a system that creates customized advice and suggestions based on the individual user's preferences and emotional state. This includes recommendation engines and profiling technologies.

[0746] To realize this application, it is crucial that a server equipped with advanced data collection and analysis capabilities throughout the entire system is coordinated with the terminals used by users. The server collects information related to the operation of local events using sensors and statistical data, and stores this information in a database. Furthermore, artificial intelligence is used to analyze this data and generate participant recruitment information and personalized route guidance based on the movements of individual participants.

[0747] The devices function as an interface with the user, receiving and displaying generated information in real time. Specifically, applications installed on smartphones and smart glasses send the user's emotional information to an emotion engine, and the system provides optimal information based on the analysis results. These devices also acquire the user's location information and act as a means of communication to suggest routes that avoid congestion and recommended rest spots.

[0748] For example, when a user visits a physical store, the system analyzes emotional data and, if it determines that the user is seeking relaxation, guides them to a location where relaxing products are displayed or to a quiet corner. Furthermore, by inputting a specific prompt example such as, "Please suggest application scenarios for proposing the optimal purchasing experience in a physical store using consumer emotional data," the generative AI model will provide appropriate suggestions.

[0749] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0750] Step 1:

[0751] The server collects data related to local events from various sensors and databases. This input data includes historical information about past events, participant numbers, and event dates. By collecting this data, the server prepares the foundational information necessary for the next analysis step.

[0752] Step 2:

[0753] The server inputs the collected data into an artificial intelligence engine to analyze participant behavior. As a result of this data analysis, it generates optimized event plans and recruitment information. At this time, the AI ​​model uses a generative AI model to analyze data trends and identify emerging patterns.

[0754] Step 3:

[0755] The terminal receives optimized event and recruitment information sent from the server. This information is displayed through the user interface, allowing the user to review the necessary details and consider participating in the event.

[0756] Step 4:

[0757] Users register to participate through their device. During this process, users enter necessary personal information and their preferred participation date and time. The device then sends this information to the server, completing the event registration.

[0758] Step 5:

[0759] The server uses the registration information received from the user to notify them of the schedule and important notes for upcoming events. This output information is delivered directly to the user's device and serves as helpful guidance when participating in the event.

[0760] Step 6:

[0761] The device acquires the user's location information and emotional data in real time. When this data is input, the emotional engine within the device analyzes the data and generates optimal information based on the user's current state.

[0762] Step 7:

[0763] Based on the results of emotion analysis, the device presents personalized suggestions to the user. For example, if the user is feeling stressed, it will notify them of routes to avoid crowds or places where they can relax. In this way, the user can have the most useful and comfortable experience at that moment.

[0764] 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.

[0765] 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.

[0766] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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."

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] The following is further disclosed regarding the embodiments described above.

[0786] (Claim 1)

[0787] Means of collecting information regarding the operation of local events,

[0788] A means of generating participant recruitment information based on collected information,

[0789] A means of distributing the generated recruitment information to local participants,

[0790] A means of receiving registration information from participants,

[0791] A means of notifying participants of the schedule and precautions for holding local events,

[0792] A system that includes this.

[0793] (Claim 2)

[0794] The system according to claim 1, comprising means for acquiring the location information of participants in real time and providing necessary information.

[0795] (Claim 3)

[0796] The system according to claim 1, comprising means for optimizing the route planning of local events using generated information.

[0797] "Example 1"

[0798] (Claim 1)

[0799] Means of collecting data related to community activities,

[0800] Methods for analyzing the collected data,

[0801] Based on the analysis results, a means for generating an optimal route plan and participant recruitment information using a generation model,

[0802] A means of distributing the generated recruitment information to users,

[0803] A means of receiving application information from users,

[0804] A means of notifying users of the schedule and precautions regarding the implementation of the activity,

[0805] An information processing system that includes this.

[0806] (Claim 2)

[0807] The information processing system according to claim 1, comprising means for acquiring user location data in real time and providing related information.

[0808] (Claim 3)

[0809] The information processing system according to claim 1, comprising means for optimizing travel routes for local activities using generated information.

[0810] "Application Example 1"

[0811] (Claim 1)

[0812] Means of collecting information on the management of community activities,

[0813] A means of generating participant guidance information based on collected information,

[0814] A means of distributing the generated information to local stakeholders,

[0815] A means of receiving registration information from relevant parties,

[0816] A means of notifying relevant parties of the schedule and points to note regarding the implementation of community activities,

[0817] A means of analyzing past activity data to create an optimal plan,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, comprising means for acquiring the location information of relevant parties in real time and providing related information.

[0821] (Claim 3)

[0822] The system according to claim 1, further comprising means for optimizing the procedural plan of local activities using the generated information.

[0823] "Example 2 of combining an emotion engine"

[0824] (Claim 1)

[0825] A means of collecting data related to the operation of local events,

[0826] A method for creating participant recruitment information based on collected data,

[0827] A means of distributing the created recruitment information to participants in the local community,

[0828] A means of receiving registration data from participants,

[0829] A means of informing participants of the schedule and precautions for holding local events,

[0830] A means equipped with an emotion recognition engine that analyzes user behavior and provides personalized information,

[0831] Means of using information to improve the participant experience based on behavioral patterns,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, comprising means for acquiring participant location data in real time and providing dynamic information.

[0835] (Claim 3)

[0836] The system according to claim 1, comprising means for optimizing the itinerary of a local event using generated information.

[0837] "Application example 2 when combining with an emotional engine"

[0838] (Claim 1)

[0839] A device for collecting information on the operation of local events,

[0840] A device that generates participant recruitment information based on collected information,

[0841] A mechanism for distributing generated recruitment information to local consumers,

[0842] A device for receiving registration information from participants,

[0843] A device for notifying users of the schedule and precautions for local events,

[0844] A mechanism that analyzes consumer emotions and generates personalized suggestions based on the analysis results,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, comprising a device that acquires participant location data in real time and provides necessary suggestions.

[0848] (Claim 3)

[0849] The system according to claim 1, further comprising a device for adjusting the route plan for local events using the generated information. [Explanation of symbols]

[0850] 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. Means of collecting information regarding the operation of local events, A means of generating participant recruitment information based on collected information, A means of distributing the generated recruitment information to local participants, A means of receiving registration information from participants, A means of notifying participants of the schedule and precautions for holding local events, A system that includes this.

2. The system according to claim 1, comprising means for acquiring the location information of participants in real time and providing necessary information.

3. The system according to claim 1, further comprising means for optimizing the route planning of local events using generated information.

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