system

Abstract

Provide a system. 【Solution means】 The information acquisition unit is means for receiving information regarding an arbitrary event from the user terminal; The analysis unit is means for searching for and analyzing past similar event information based on the information regarding the event; The TODO list generation unit is means for generating an action list of the event based on the analysis result of the analysis unit; The service proposal unit is means for searching for and proposing surrounding services at the event implementation location; The design generation unit is means for creating a composition template of the event notification material; The budget management unit is means for presenting a recommended fund allocation based on the designated funds; The result storage unit is means for storing the user's decision content in the storage area; The proposal generation module is means for selecting and providing the optimal supply service for the user's event; A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the planning, coordination, and preparation of events, the burden on the organizers is large, which is particularly a factor hindering smooth progress. As a result, many events are cancelled or become low-quality events. Therefore, it is required to automate and streamline the event planning process to realize events with high satisfaction for participants.

Means for Solving the Problems

[0005] This invention provides a system in which an information acquisition unit receives event-related information from a user terminal, and an analysis unit searches and analyzes past similar event data based on that information. Furthermore, a to-do list generation unit generates an optimal to-do list based on the analysis results, and a service proposal unit investigates services around the event location and proposes them to the user. A design generation unit creates design templates for promotional materials, and a budget management unit presents the optimal allocation of funds within the budget. In addition, a results storage unit saves the user's final decision in a database, including functions for progress management and reference for planning future events. Through this series of means, it is possible to improve the efficiency and quality of event preparation and reduce the burden on event organizers.

[0006] The "Information Acquisition Unit" is a part of the system that has the function of receiving necessary information about an event from the user terminal.

[0007] The "Analysis Unit" is a part of the system that searches for and analyzes data of similar past events based on the acquired event information.

[0008] The "TODO List Generation Unit" is a part of the system that uses the analysis results from the Analysis Unit to create a list of specific preparation tasks for an event.

[0009] The "Service Proposal Department" is a part of a system that searches for available services in the event location and surrounding areas, and makes appropriate suggestions to users.

[0010] The "Design Generation Unit" is a part of the system that has the function of creating design templates for event announcements and providing them to users.

[0011] The "Budget Management Department" is part of a system that has the function of proposing the allocation of funds for each item necessary for an event within the specified budget.

[0012] The "results storage unit" is a part of the system that processes and saves the user's final choices and decisions to a database within the system. [Brief explanation of the drawing]

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

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

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

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] The event support system in this invention efficiently plans, coordinates, and prepares events by having multiple functional units.

[0035] First, the user enters basic event information via their device. This information includes the event name, date and time, location, number of participants, and budget. Once this data is entered from the device, the information retrieval unit collects the data and sends it to the server.

[0036] The server processes the data received from the information acquisition unit in the analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This makes it possible to create an optimal to-do list based on lessons learned from past cases.

[0037] Next, the server uses the to-do list generation unit to generate a list of specific preparation tasks for the user. This list covers all the steps necessary for the event to succeed and provides the user with clear guidance.

[0038] Furthermore, the service proposal department searches for available services in and around the event venue (e.g., catering, venue setup, decoration companies, etc.). The server then proposes appropriate services based on the characteristics of the user's event.

[0039] In parallel, the server uses the design generation unit to build design templates for event announcements. Users can customize these templates and select the design that best suits their event.

[0040] In the budget management section, the server calculates and presents recommended funding allocations based on the entered budget. This function allows users to plan events to stay within budget.

[0041] Once all proposals and selections are complete, the user performs a final confirmation via their terminal. The user's decisions are stored in a database by the server's results storage unit. This data is used not only for managing ongoing events but also for planning future events.

[0042] As a concrete example, consider a scenario where a user plans a relative's wedding at a hotel in a certain area. The user enters the date, time, location, number of guests, budget, etc., and the server references past wedding examples to suggest the most suitable preparation tasks and available services. It also provides invitation design suggestions and calculates the optimal allocation of funds within the budget. Once the user makes a final decision, the information is saved for future reference.

[0043] As described above, the present invention utilizes AI to automate various processes necessary for event planning, thereby supporting efficient and effective event management.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users enter event information using a terminal. Input fields include event name, date and time, location, number of participants, and budget. This data is then transmitted from the terminal to the information retrieval unit.

[0047] Step 2:

[0048] The server receives input data from the user through the information acquisition unit. The received data is processed by the analysis unit, which identifies the event category based on the input content.

[0049] Step 3:

[0050] The server's analysis unit searches the database for data on similar past events and begins the analysis. This analysis identifies a suitable to-do list template for the event.

[0051] Step 4:

[0052] The server's to-do list generation unit creates a list of preparation tasks for the user based on the analysis results. This list provides detailed guidelines for event preparation.

[0053] Step 5:

[0054] The server's service proposal department searches the database for available services around the event venue. Based on the characteristics of the event, it proposes suitable service providers to the user.

[0055] Step 6:

[0056] The server's design generation unit generates a design template for event announcements. Users can view this template via their terminal and customize it as needed.

[0057] Step 7:

[0058] The server's budget management system calculates and presents recommended funding allocations based on the budget information entered by the user. This allows the user to plan the optimal events within their budget.

[0059] Step 8:

[0060] The user reviews the to-do list, service proposals, design proposals, and budget plan provided by the server via their device. They make any necessary revisions and send their final decisions to the server.

[0061] Step 9:

[0062] The server's results storage unit saves the user's final decision to the database. The saved data serves as reference data for progress management and future event planning.

[0063] (Example 1)

[0064] 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."

[0065] Current event planning support systems often perform information gathering, analysis, task generation, service proposals, and budget management tasks individually, making efficient and integrated event management difficult. Furthermore, there is a lack of effective ways to leverage best practices from similar past events. Therefore, there is a need for a method to comprehensively optimize event planning and preparation.

[0066] 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.

[0067] In this invention, the server includes means for an information gathering unit to receive event information from a user terminal, means for an analysis function unit to perform analysis based on past similar event information, and means for a task list generation unit to generate a task list for the event based on the analysis results. This makes it possible to integrate everything from efficient information gathering to task generation, service proposals, and budget control throughout the entire process of an event.

[0068] The "Information Gathering Department" is the department responsible for receiving event-related data from user terminals.

[0069] The "Analysis Function Department" is a department that has the function of searching for and analyzing past similar event information based on the received event data.

[0070] The "Task List Generation Unit" is a department that generates task lists for events based on the analysis results obtained from the Analysis Function Unit.

[0071] The "Service Recommendation Department" is a department that searches for surrounding facilities of event venues and makes recommendations based on that information.

[0072] The "Design Generation Department" is the department responsible for creating design templates for event notices and other promotional materials.

[0073] The "Budget Adjustment Department" is a department whose function is to propose recommended funding allocations based on the designated expenditure plan.

[0074] The "Results Storage Department" is the department responsible for storing user decisions on storage media.

[0075] The event support system of this invention efficiently and comprehensively plans, coordinates, and prepares events. The system consists of a terminal used by the user and a server having multiple functional units.

[0076] First, the user enters basic information such as the event name, date and time, location, number of participants, and budget into the terminal. The terminal converts this information into a data format and sends it to the server. The server's information collection unit receives this data.

[0077] The received data is processed by the server's analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This process utilizes database management systems such as MySQL (registered trademark) and natural language processing technology.

[0078] Based on the analysis results, the task list generation unit generates a list of specific preparation tasks. The task list is automatically generated using algorithms written in Python, Java (registered trademark), etc.

[0079] The server's service recommendation section suggests surrounding services tailored to the characteristics of the event. It uses Google® API and third-party APIs to collect information on services within the region and provide users with the most suitable options.

[0080] The design generation unit utilizes design software such as Adobe XD and Canva to generate design templates for event-related notices. Users can customize these templates.

[0081] The budget adjustment department provides recommended funding allocations based on the budget specified by the user. It uses Excel or Google Sheets to calculate and provide the optimal allocation plan to the user.

[0082] After all proposals and selections are complete, the user makes a final confirmation via their terminal, and the decisions are saved in the results storage unit and used for future event planning.

[0083] As a concrete example, consider a scenario where a user plans a birthday party for a close friend at a local hall. The user enters the date, time, location, number of guests, and budget. The server then references past birthday party examples and suggests the most suitable task list and services. It also provides invitation design suggestions and optimizes budget allocation. After the user makes a final decision, the information is saved for future reference.

[0084] An example of a prompt using a generative AI model is, "Please suggest the optimal task list based on successful past events of a similar type."

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] Users input basic information such as the event name, date and time, location, number of participants, and budget via their terminal. This input information is converted into a data structure such as JSON and sent to the server. The terminal validates the input data through the user interface to check for any missing or incorrect information.

[0088] Step 2:

[0089] The server's information gathering unit receives data from terminals and stores it in its internal database. During this process, the server checks data integrity and converts the format as needed. The event information received as input is then used in subsequent analysis steps.

[0090] Step 3:

[0091] The server's analysis unit uses stored data to search the database for information on similar past events. The analysis unit executes SQL queries to extract relevant past event data. The output is an analysis result based on the characteristics of the event.

[0092] Step 4:

[0093] The server uses a task list generation unit to generate an event preparation task list based on the analysis results. It utilizes a generation AI model and prompts to enumerate appropriate tasks. The output is a specific task list, including tasks such as creating invitations, arranging the venue, and preparing decorations.

[0094] Step 5:

[0095] The server's service recommendation section searches for services around the event location via an API and provides service options relevant to the user's event. The input is the user's event characteristics, and the output is a list of services such as catering and venue setup.

[0096] Step 6:

[0097] The design generation unit uses a generation AI model to create design templates for event announcements. Using prompts, it generates design proposals that match the event theme and provides them to the user. The output is a customizable design template.

[0098] Step 7:

[0099] The budget adjustment department proposes item-specific funding allocations based on the budget entered by the user. It receives budget information as input and performs calculations using Excel or Google Sheets. The output is the recommended budget allocation for each task.

[0100] Step 8:

[0101] Users review all suggestions via their terminal, edit them as needed, and then make their final decision. The final selection is sent to the server and stored in a database by the results storage unit. This information is also used as reference data for future event planning.

[0102] (Application Example 1)

[0103] 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."

[0104] In traditional event planning, it is difficult to efficiently integrate and manage the various tasks and services related to an event, and there are particular challenges in optimizing the selection of food delivery services and budget management. As a result, the overall preparation of an event can become complicated, sometimes resulting in unnecessary time and costs.

[0105] 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.

[0106] In this invention, the server includes an information acquisition unit that receives information about an arbitrary event from a user terminal, an analysis unit that searches for and analyzes past similar event information based on the information about the event, and a to-do list generation unit that generates an action list for the event based on the analysis results of the analysis unit. This makes it possible to optimize tasks related to the event and propose an efficient food delivery service.

[0107] The "Information Acquisition Unit" is responsible for receiving event-related information from the user's terminal and transmitting it to the server.

[0108] The "Analysis Unit" provides the functionality to search for data based on information about received events and analyze past similar events.

[0109] The "TODO list generation unit" is a device that creates an action list for an event based on the analysis results from the analysis unit.

[0110] The "Service Proposal Department" is a system that searches for available services around the event venue and provides users with the most suitable suggestions.

[0111] The "Design Generation Unit" is a device that has the function of creating and providing event announcement materials with a structure template.

[0112] The "Budget Management Department" is a system that calculates and presents the optimal allocation of funds to the user based on the designated funds.

[0113] The "results storage unit" is a device that stores the user's decisions in a memory area for future reference and event management.

[0114] A "proposal generation module" is a device that has the function of selecting the most suitable supply service based on the user's input information and providing it to the user.

[0115] The system that realizes this invention consists of a server with multiple functional units and a user terminal. First, the user uses the terminal to input information about the event. This information includes the event title, date and time, location, number of participants, and budget. The information acquisition unit receives this data and transmits it to the server. Based on the received information, the server's analysis unit searches for information on similar past events and performs analysis.

[0116] Based on the analysis results, the TODO list generation unit generates an action list for the event and displays it on the terminal. The service proposal unit searches for available services around the event location and makes the best proposal to the user. The design generation unit creates a template for the announcement materials, allowing users to customize it. The budget management unit calculates the optimal fund allocation based on the entered funds and displays it to the user.

[0117] This entire process utilizes cloud services such as Google Cloud Platform and AWS®, and leverages cloud-based memory storage for the database. Python and R are used for data analysis, and machine learning algorithms such as scikit-learn and TENSORFLOW® are implemented. Finally, the results storage unit stores the user's decisions in memory for future reference and event management.

[0118] As a concrete example, consider a scenario where a user plans a party for 20 people with a budget of 50,000 yen. In this case, once the user inputs the information, the server can suggest the optimal food delivery options based on past party data and indicate how to allocate funds within the budget. An example of an input prompt to the generating AI model would be, "Please tell me the best food delivery options for a party of 20 people that cost under 50,000 yen."

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

[0120] Step 1:

[0121] The user inputs event information from the terminal. This information includes the event title, date and time, location, number of participants, and budget. The terminal sends this data to the information acquisition unit, which then prepares the basic data for the next processing step.

[0122] Step 2:

[0123] The server's information acquisition unit receives event information sent from the terminal. This received data is then passed to the analysis unit. The analysis unit is connected to a database and uses this information as input to search for similar past event information. It retrieves relevant data from the database and performs the analysis.

[0124] Step 3:

[0125] The analysis unit searches past event data based on the received data and performs analysis using machine learning algorithms. In this process, TensorFlow is used to model past data patterns and identify events with high similarity. As output, the analysis results of similar events are generated and provided to the TODO list generation unit.

[0126] Step 4:

[0127] The TODO list generation unit receives analysis results from the analysis unit and generates an action list for the event based on them. This process uses a Python script to automatically create the list and adjust it to include the most effective steps for the user. The generated list is output to the terminal and presented to the user.

[0128] Step 5:

[0129] The server's service suggestion section searches for and suggests available supply services near the event location. It obtains geographical information using the Google Maps API and other tools, and evaluates third-party service providers. The input is the user's event information, and the output provides the user with a list of the most suitable services.

[0130] Step 6:

[0131] The Design Generation Department creates structure templates for event announcement materials. This department utilizes the Adobe Creative Cloud API to build flexible templates that users can customize. The resulting templates are visually appealing to users.

[0132] Step 7:

[0133] The budget management department calculates recommended funding allocations based on the user's entered budget limit. It combines machine learning algorithms and linear optimization to optimize the user's spending for the most effective use of funds. The calculation results are presented to the user to assist in event planning.

[0134] Step 8:

[0135] Finally, the results storage unit saves the user's decisions to a memory area. The saved data is managed in cloud-based data storage and used as a reference for future event planning and progress management. The input is the user's final confirmation information, and the output data is stored in a database.

[0136] 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.

[0137] This invention combines a system that supports event planning, preparation, and operation with an emotion engine that recognizes user emotions. This system integrates multiple functional units, enabling flexible and efficient event preparation according to user needs.

[0138] The user first enters event information using a terminal. This information includes the event name, date and time, location, number of participants, and budget. This information is sent from the terminal to the information retrieval unit and stored in the database on the server.

[0139] The analysis unit on the server searches for similar past events based on the input information and creates an optimal to-do list template. During this process, an efficient event progression is planned based on the analysis results of past data.

[0140] Furthermore, the service proposal department searches for available services around the event venue and proposes them to the user. This allows for the rapid selection of necessary vendors and services. In addition, the design generation department provides design templates for promotional materials, which can be customized to the user's needs.

[0141] The budget management department calculates the optimal allocation of funds within the budget and presents recommended plans to prevent unplanned expenses. Users review these proposals via their devices and make final decisions.

[0142] The emotion engine recognizes emotions from the user's device through voice and text. Based on this recognition, it makes additional suggestions regarding the atmosphere and theme of the event. For example, if the user prefers a relaxed atmosphere, services with such themes will be prioritized. Furthermore, by promoting the customization of designs and services based on the user's emotions, optimization tailored to individual needs is possible.

[0143] Throughout the entire process, users can use their devices to create, refine, and manage comprehensive event plans while receiving feedback from the emotion engine. This reduces the burden on users and ensures highly satisfying events.

[0144] For example, when a user is preparing for a wedding on their device, the emotion engine might analyze the user's mood and recommend a relaxed, casual wedding. The server then reflects this result, suggesting services and designs that fit the casual theme, and the budget management department presents the optimal allocation of funds within that framework. In this way, the user can smoothly prepare an event that matches their mood.

[0145] The following describes the processing flow.

[0146] Step 1:

[0147] Users enter basic event information into a form from their device. This information includes the event name, date and time, location, number of participants, budget, and a brief description or preference.

[0148] Step 2:

[0149] The terminal transmits the input information to the information acquisition unit. The information acquisition unit prepares to transmit this information to the server.

[0150] Step 3:

[0151] The server's analysis unit searches the database for similar past event data based on event information received from the information acquisition unit. Simultaneously, it analyzes this similar data to create a to-do list template for optimal event management.

[0152] Step 4:

[0153] The server uses a service suggestion unit to detect and suggest vendors and services available in the vicinity of the event venue. This includes catering, decorations, sound services, and more.

[0154] Step 5:

[0155] The design generation unit runs on a server and generates design proposals for event-optimized announcements. Templates are provided so that users can select options for personalization.

[0156] Step 6:

[0157] The server's budget management unit calculates and presents recommended cost allocations for each element of an event based on the budget data entered by the user. This helps users avoid unplanned expenses.

[0158] Step 7:

[0159] The emotion engine analyzes the user's emotions using voice and text data from the device and reports the results to the server. Based on these results, the server provides suggestions for customizing the event's theme and atmosphere.

[0160] Step 8:

[0161] The user reviews the to-do list, service proposals, design proposals, budget allocations, and additional sentiment-based suggestions provided by the server on their device. They then apply any necessary step-up revisions and make final decisions.

[0162] Step 9:

[0163] The server's results storage unit saves the user's final decision information to a database. This saved data is used for managing events in progress and as a reference for planning future events.

[0164] (Example 2)

[0165] 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".

[0166] In modern society, efficiently planning and running events is a time-consuming and laborious task. In particular, preparing for the event, selecting appropriate services, managing the budget, and customizing to meet the needs of new participants are all challenging. Furthermore, considering participants' emotions and creating an appropriate atmosphere and design for the event is not easy. There is a need to integrate and solve these complex elements within a single system.

[0167] 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.

[0168] In this invention, the server includes an information acquisition unit that receives information about activities from a user terminal, an analysis unit that searches for and analyzes similar past activity data based on the information about the activities, and an emotion recognition unit that recognizes the user's emotional state based on voice or text data. This enables users to plan and manage personalized events based on emotional data, resulting in efficient and highly satisfying event implementation.

[0169] The "Information Acquisition Department" is the department responsible for receiving event-related information from user terminals.

[0170] The "Analysis Department" is a department that has the function of searching and analyzing past similar activity data based on the information received about the activity.

[0171] The "TODO List Generation Department" is a department that generates a to-do list summarizing the tasks necessary for the progress of an event, based on the analysis results from the Analysis Department.

[0172] The "Service Proposal Department" is a department responsible for searching for services available in the vicinity of the event venue and making appropriate suggestions to users.

[0173] The "Design Generation Department" is a department that creates design templates for event announcements and allows users to customize them.

[0174] The "Budget Management Department" is a department responsible for proposing the optimal allocation of funds necessary for an event based on the designated budget.

[0175] The "emotion recognition unit" is a department that has the function of recognizing the user's emotional state based on voice or text data.

[0176] The "Result Storage Department" is the department responsible for saving the final content decided by the user to a storage device.

[0177] This invention utilizes an integrated system via user terminals, a server, and a network to streamline event planning and management. Users input detailed event information via their user terminals, and this information is quickly transmitted to the server. Multiple functional units within the server perform advanced data processing based on the received information, providing users with various suggestions and adjustments.

[0178] The server retrieves data entered by users through the information acquisition unit and stores it in the database as structured data. The analysis unit searches for similar past event data based on the stored information and performs analysis using machine learning algorithms. The technologies used for this include data analysis libraries in Python and R.

[0179] Based on the analysis results, the to-do list generation unit generates a to-do list to plan the efficient progress of the event. This allows the user to properly understand the event's steps.

[0180] Next, the server's service suggestion unit uses external API services to search for available vendors and services around the event venue and suggests the best options to the user. This could include, for example, suitable catering or decoration vendors. Common APIs used for this purpose include those from general map service providers.

[0181] The design generation unit creates design templates for announcements based on user requests. Using Adobe Creative Cloud APIs, it can provide customizable initial designs. Users can preview and optimize the designs through a designated interface on their device.

[0182] The emotion recognition unit acquires voice and text data to analyze the user's emotions and recognizes their emotional state using natural language processing (NLP) technology. Based on this information, suggestions are made that are tailored to the atmosphere and theme of the event the user desires. For example, if the user wants a relaxed event, the appropriate background music and lighting settings will be prioritized.

[0183] As a concrete example, when a user is preparing for a wedding, the system refers to past data and suggests a relaxed, casual wedding plan. The user enters a prompt such as, "I want to plan a relaxed wedding," and the AI ​​provides specific suggestions tailored to that need. In this way, users can efficiently plan and manage an event that aligns with their emotions through a series of processes.

[0184] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0185] Step 1:

[0186] The user uses their device to enter detailed information about the event. Specifically, they enter data such as the event name, date and time, location, number of participants, and budget into an input form. Once this input is complete, the device packets this data and prepares it for transmission to the server.

[0187] Step 2:

[0188] The terminal sends the entered event information to the server. The information retrieval unit receives this data and stores it in the server's database. In this process, the received data is saved in a structured format using SQL queries. Based on the entered information, related fields are updated and new records are added.

[0189] Step 3:

[0190] The analysis unit on the server uses event information obtained from the database to search for similar past event data. Here, machine learning algorithms are used to identify relevant events and generate analysis results. This analysis uses metrics such as event success rate and participant satisfaction. The output provides a list of related past events and their analysis results.

[0191] Step 4:

[0192] The server's to-do list generation unit generates a list of specific tasks (to-do list) necessary for the event's progress, based on the analysis results from the analysis unit. This list may include items such as schedule confirmation, vendor arrangements, and decoration preparations. This generated to-do list is output in an easy-to-manage format (e.g., checklist format) and provided to the user.

[0193] Step 5:

[0194] The server's service suggestion unit uses an external API to search for appropriate services near the event venue. Geographic information of the venue is used as input, and a list of nearby services (e.g., catering, decorations) is obtained via the API. This result is then presented to the user.

[0195] Step 6:

[0196] The server's design generation unit generates event announcement design templates according to user requests. This process uses a design tool API to customize pre-configured templates. The output is a design file that the user can modify.

[0197] Step 7:

[0198] The server's emotion recognition unit analyzes the user's emotional state. User-provided voice and text data are used as input, and emotion analysis is performed using natural language processing techniques. As output, data related to the user's emotions is generated and reflected in relevant suggestions.

[0199] Step 8:

[0200] The user reviews, adjusts, and finalizes the event plan based on emotion recognition and various suggestions. This decision is then saved again to the database by the results storage unit. The saved information is used for future progress management and as a reference for planning new events.

[0201] (Application Example 2)

[0202] 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".

[0203] In planning and preparing events, users often need to select ideal themes and services while reviewing past data and budgets, but this process is complex and burdensome for users. Furthermore, customization based on users' own feelings and preferences is difficult, making it challenging to improve satisfaction.

[0204] 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.

[0205] In this invention, the server includes an information acquisition unit that receives information about events from a user terminal, an analysis unit that searches for and analyzes similar past event data based on the information about the event, and an emotion analysis unit that analyzes the user's voice and documents to recognize emotions. This makes it possible to provide an optimal event plan tailored to the user's emotions and preferences.

[0206] The "Information Acquisition Unit" is a module that receives input data related to events from the user's operating terminal.

[0207] The "Analysis Unit" is a component that searches for similar past event data based on event-related information obtained from users, and analyzes that information.

[0208] The "TODO List Generation Unit" is a unit that has the function of generating a task list for efficient event preparation based on the results of the analysis unit.

[0209] The "Service Proposal Department" is a section responsible for searching for services in the vicinity of the event venue and proposing appropriate services to users based on the results.

[0210] The "Design Generation Department" is a department that creates design templates for announcements necessary for events and has the function of allowing users to customize them according to their preferences.

[0211] The "Budget Management Department" is a department that supports economic planning by calculating and proposing recommended allocations of funds based on the designated budget.

[0212] The "Emotion Analysis Department" is a department that analyzes users' voice and document data to recognize and understand the emotions behind them.

[0213] The "Proposal Optimization Department" is a part of the team that utilizes the recognition results from the Sentiment Analysis Department to customize event themes and services according to the emotions of the users.

[0214] The "results storage unit" is a component that saves the user's final decisions to a data storage medium, allowing for future reference and use in planning future events.

[0215] This invention is a system that efficiently supports event planning and execution. Based on event information entered by the user, this system analyzes similar past data and provides customized suggestions based on emotions. The user enters event information via a terminal, and this information is sent to the server. On the server, the information acquisition unit receives the data, and the analysis unit searches and analyzes past event data based on that information. Next, the to-do list generation unit creates an efficient task list based on the analysis results. Furthermore, the emotion analysis unit analyzes the voice and text data entered by the user to recognize the user's emotions. Based on these results, the suggestion optimization unit customizes and proposes appropriate event themes and services.

[0216] Users can review the proposed options and make a final decision. The budget management department optimizes the allocation of funds to each service according to the specified budget. The finalized information is saved to a data storage medium by the results storage department and can be used as a reference for planning future events.

[0217] This system utilizes speech recognition technology and data analysis algorithms. Speech recognition uses APIs such as Google Speech Recognition API, and machine learning models are employed for the analysis algorithms.

[0218] As a concrete example, consider a user planning a birthday party at home. The user voice-inputs the event details into the device, and based on sentiment analysis, a relaxed, casual theme is suggested. Following this suggestion, the design and services are customized, and the optimal budget allocation is shown to stay within budget. This allows the user to smoothly prepare an event perfectly tailored to their needs.

[0219] An example of a prompt message is, "Please plan a relaxed family birthday party. The budget is 100,000 yen."

[0220] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0221] Step 1:

[0222] Users input event information using a terminal. This includes the event name, date and time, location, number of participants, and budget. This input data is sent from the terminal to the server and received by the information retrieval unit.

[0223] Step 2:

[0224] The server's analysis unit searches the database for similar past events based on the received data. By analyzing the retrieved data, the foundation for a to-do list suitable for the current event is built. This process uses data mining algorithms to extract past cases similar to the input parameters.

[0225] Step 3:

[0226] The TODO list generation unit generates an efficient TODO list based on the analysis results. It uses the output of the analysis unit as input to compile the most suitable work items. This list is output to the user, showing the steps to proceed to the next stage.

[0227] Step 4:

[0228] The server's sentiment analysis unit recognizes emotions from the user's voice and text. This process involves acquiring voice data, converting it to text using the Google Speech Recognition API, and then performing sentiment analysis on the text. Machine learning algorithms are used here to output the user's expected emotional state.

[0229] Step 5:

[0230] The suggestion optimization unit optimizes and proposes event themes and services based on recognized emotions. It uses the emotion recognition results from the previous step as input, comparing them with event data to generate optimal suggestions. Users receive the customized theme and service suggestions on their devices.

[0231] Step 6:

[0232] The budget management department calculates the optimal allocation of funds to each service based on the specified budget. The user's specified budget and proposed service details are used as input, and the calculated budget allocation is output to the user. This process is performed using a linear programming algorithm.

[0233] Step 7:

[0234] The user makes a final decision and confirms it through their terminal. The user's decision is saved to a data storage medium in the server's results storage unit. This saved data can be used as reference for planning future events and managing progress.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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".

[0251] The event support system in this invention efficiently plans, coordinates, and prepares events by having multiple functional units.

[0252] First, the user enters basic event information via their device. This information includes the event name, date and time, location, number of participants, and budget. Once this data is entered from the device, the information retrieval unit collects the data and sends it to the server.

[0253] The server processes the data received from the information acquisition unit in the analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This makes it possible to create an optimal to-do list based on lessons learned from past cases.

[0254] Next, the server uses the to-do list generation unit to generate a list of specific preparation tasks for the user. This list covers all the steps necessary for the event to succeed and provides the user with clear guidance.

[0255] Furthermore, the service proposal department searches for available services in and around the event venue (e.g., catering, venue setup, decoration companies, etc.). The server then proposes appropriate services based on the characteristics of the user's event.

[0256] In parallel, the server uses the design generation unit to build design templates for event announcements. Users can customize these templates and select the design that best suits their event.

[0257] In the budget management section, the server calculates and presents recommended funding allocations based on the entered budget. This function allows users to plan events to stay within budget.

[0258] Once all proposals and selections are complete, the user performs a final confirmation via their terminal. The user's decisions are stored in a database by the server's results storage unit. This data is used not only for managing ongoing events but also for planning future events.

[0259] As a concrete example, consider a scenario where a user plans a relative's wedding at a hotel in a certain area. The user enters the date, time, location, number of guests, budget, etc., and the server references past wedding examples to suggest the most suitable preparation tasks and available services. It also provides invitation design suggestions and calculates the optimal allocation of funds within the budget. Once the user makes a final decision, the information is saved for future reference.

[0260] As described above, the present invention utilizes AI to automate various processes necessary for event planning, thereby supporting efficient and effective event management.

[0261] The following describes the processing flow.

[0262] Step 1:

[0263] Users enter event information using a terminal. Input fields include event name, date and time, location, number of participants, and budget. This data is then transmitted from the terminal to the information retrieval unit.

[0264] Step 2:

[0265] The server receives input data from the user through the information acquisition unit. The received data is processed by the analysis unit, which identifies the event category based on the input content.

[0266] Step 3:

[0267] The server's analysis unit searches the database for data on similar past events and begins the analysis. This analysis identifies a suitable to-do list template for the event.

[0268] Step 4:

[0269] The server's to-do list generation unit creates a list of preparation tasks for the user based on the analysis results. This list provides detailed guidelines for event preparation.

[0270] Step 5:

[0271] The server's service proposal department searches the database for available services around the event venue. Based on the characteristics of the event, it proposes suitable service providers to the user.

[0272] Step 6:

[0273] The server's design generation unit generates a design template for event announcements. Users can view this template via their terminal and customize it as needed.

[0274] Step 7:

[0275] The server's budget management system calculates and presents recommended funding allocations based on the budget information entered by the user. This allows the user to plan the optimal events within their budget.

[0276] Step 8:

[0277] The user reviews the to-do list, service proposals, design proposals, and budget plan provided by the server via their device. They make any necessary revisions and send their final decisions to the server.

[0278] Step 9:

[0279] The server's results storage unit saves the user's final decision to the database. The saved data serves as reference data for progress management and future event planning.

[0280] (Example 1)

[0281] 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".

[0282] Current event planning support systems often perform information gathering, analysis, task generation, service proposals, and budget management tasks individually, making efficient and integrated event management difficult. Furthermore, there is a lack of effective ways to leverage best practices from similar past events. Therefore, there is a need for a method to comprehensively optimize event planning and preparation.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0284] In this invention, the server includes means for the information collection unit to receive event information from the user terminal, means for the analysis function unit to perform analysis based on past similar event information, and means for the task list generation unit to generate a task list for the event based on the analysis result. Thereby, in the entire process of the event, it is possible to integrally perform all operations from the efficient collection of information to the generation of tasks, service proposal, and budget control.

[0285] The "information collection unit" is a department having a function of receiving data related to events from the user terminal.

[0286] The "analysis function unit" is a department having a function of searching for past similar event information based on the received event data and performing analysis.

[0287] The "task list generation unit" is a department having a function of generating a task list for the event based on the analysis result obtained from the analysis function unit.

[0288] The "service recommendation department" is a department having a function of searching for surrounding functions of the event venue and making recommendations based on them.

[0289] The "design generation unit" is a department having a function of creating a design prototype for event notification materials.

[0290] The "budget adjustment unit" is a department having a function of proposing recommended fund allocation based on the specified expenditure plan.

[0291] The "result storage unit" is a department having a function of storing the user's decision content in a storage medium.

[0292] The event support system of this invention efficiently and integrally plans, coordinates, and prepares for events. The system is composed of a terminal used by the user and a server having a plurality of functional units.

[0293] First, the user enters basic information such as the event name, date and time, location, number of participants, and budget into the terminal. The terminal converts this information into a data format and sends it to the server. The server's information collection unit receives this data.

[0294] The received data is processed by the server's analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This process utilizes database management systems such as MySQL and natural language processing technology.

[0295] Based on the analysis results, the task list generation unit generates a list of specific preparation tasks. The task list is automatically generated using algorithms written in languages ​​such as Python or Java.

[0296] The server's service recommendation section suggests surrounding services tailored to the characteristics of the event. It uses Google APIs and third-party APIs to gather information about services within the region and provide users with the most suitable options.

[0297] The design generation unit utilizes design software such as Adobe XD and Canva to generate design templates for event-related notices. Users can customize these templates.

[0298] The budget adjustment department provides recommended funding allocations based on the budget specified by the user. It uses Excel or Google Sheets to calculate and provide the optimal allocation plan to the user.

[0299] After all proposals and selections are complete, the user makes a final confirmation via their terminal, and the decisions are saved in the results storage unit and used for future event planning.

[0300] As a specific example, consider the case where a user plans a birthday party for a close friend at a local hall. When the user enters the date and time, location, number of invitees, and budget, the server refers to past birthday party cases and proposes an optimal task list and services. It also provides a design proposal for the invitation card and optimizes the fund allocation within the budget. After the user makes a final decision, the information is saved for future reference.

[0301] Examples of prompt sentences using a generative AI model include "Please propose an optimal task list based on the successful cases of past similar events."

[0302] The flow of the specific process in Example 1 will be described using FIG. 11.

[0303] Step 1:

[0304] The user inputs basic information such as the name, date and time, location, number of participants, and budget of the event through the terminal. This input information is converted into a data structure such as JSON format and sent to the server. The terminal verifies the input data through the user interface and checks for any missing or incorrect information.

[0305] Step 2:

[0306] The information collection part of the server receives the data received from the terminal and stores it in the internal database. At this time, the server checks the data consistency and performs format conversion if necessary. The event information received as input is used in the subsequent analysis step.

[0307] Step 3:

[0308] The analysis function part of the server uses the stored data to search for past similar event information from the database. The analysis part executes an SQL query and extracts relevant past event data. The output obtained is the analysis result based on the characteristics of the event.

[0309] Step 4:

[0310] The server uses a task list generation unit to generate an event preparation task list based on the analysis results. It utilizes a generation AI model and prompts to enumerate appropriate tasks. The output is a specific task list, including tasks such as creating invitations, arranging the venue, and preparing decorations.

[0311] Step 5:

[0312] The server's service recommendation section searches for services around the event location via an API and provides service options relevant to the user's event. The input is the user's event characteristics, and the output is a list of services such as catering and venue setup.

[0313] Step 6:

[0314] The design generation unit uses a generation AI model to create design templates for event announcements. Using prompts, it generates design proposals that match the event theme and provides them to the user. The output is a customizable design template.

[0315] Step 7:

[0316] The budget adjustment department proposes item-specific funding allocations based on the budget entered by the user. It receives budget information as input and performs calculations using Excel or Google Sheets. The output is the recommended budget allocation for each task.

[0317] Step 8:

[0318] Users review all suggestions via their terminal, edit them as needed, and then make their final decision. The final selection is sent to the server and stored in a database by the results storage unit. This information is also used as reference data for future event planning.

[0319] (Application Example 1)

[0320] 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."

[0321] In traditional event planning, it is difficult to efficiently integrate and manage the various tasks and services related to an event, and there are particular challenges in optimizing the selection of food delivery services and budget management. As a result, the overall preparation of an event can become complicated, sometimes resulting in unnecessary time and costs.

[0322] 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.

[0323] In this invention, the server includes an information acquisition unit that receives information about an arbitrary event from a user terminal, an analysis unit that searches for and analyzes past similar event information based on the information about the event, and a to-do list generation unit that generates an action list for the event based on the analysis results of the analysis unit. This makes it possible to optimize tasks related to the event and propose an efficient food delivery service.

[0324] The "Information Acquisition Unit" is responsible for receiving event-related information from the user's terminal and transmitting it to the server.

[0325] The "Analysis Unit" provides the functionality to search for data based on information about received events and analyze past similar events.

[0326] The "TODO list generation unit" is a device that creates an action list for an event based on the analysis results from the analysis unit.

[0327] The "Service Proposal Department" is a system that searches for available services around the event venue and provides users with the most suitable suggestions.

[0328] The "Design Generation Unit" is a device that has the function of creating and providing event announcement materials with a structure template.

[0329] The "Budget Management Department" is a system that calculates and presents the optimal allocation of funds to the user based on the designated funds.

[0330] The "results storage unit" is a device that stores the user's decisions in a memory area for future reference and event management.

[0331] A "proposal generation module" is a device that has the function of selecting the most suitable supply service based on the user's input information and providing it to the user.

[0332] The system that realizes this invention consists of a server with multiple functional units and a user terminal. First, the user uses the terminal to input information about the event. This information includes the event title, date and time, location, number of participants, and budget. The information acquisition unit receives this data and transmits it to the server. Based on the received information, the server's analysis unit searches for information on similar past events and performs analysis.

[0333] Based on the analysis results, the TODO list generation unit generates an action list for the event and displays it on the terminal. The service proposal unit searches for available services around the event location and makes the best proposal to the user. The design generation unit creates a template for the announcement materials, allowing users to customize it. The budget management unit calculates the optimal fund allocation based on the entered funds and displays it to the user.

[0334] This entire process utilizes cloud services such as Google Cloud Platform and AWS, and leverages cloud-based memory storage for the database. Python and R are used for data analysis, and machine learning algorithms like scikit-learn and TensorFlow are implemented. Finally, the results storage unit stores the user's decisions in memory for future reference and event management.

[0335] As a concrete example, consider a scenario where a user plans a party for 20 people with a budget of 50,000 yen. In this case, once the user inputs the information, the server can suggest the optimal food delivery options based on past party data and indicate how to allocate funds within the budget. An example of an input prompt to the generating AI model would be, "Please tell me the best food delivery options for a party of 20 people that cost under 50,000 yen."

[0336] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0337] Step 1:

[0338] The user inputs event information from the terminal. This information includes the event title, date and time, location, number of participants, and budget. The terminal sends this data to the information acquisition unit, which then prepares the basic data for the next processing step.

[0339] Step 2:

[0340] The server's information acquisition unit receives event information sent from the terminal. This received data is then passed to the analysis unit. The analysis unit is connected to a database and uses this information as input to search for similar past event information. It retrieves relevant data from the database and performs the analysis.

[0341] Step 3:

[0342] The analysis unit searches past event data based on the received data and performs analysis using machine learning algorithms. In this process, TensorFlow is used to model past data patterns and identify events with high similarity. As output, the analysis results of similar events are generated and provided to the TODO list generation unit.

[0343] Step 4:

[0344] The TODO list generation unit receives analysis results from the analysis unit and generates an action list for the event based on them. This process uses a Python script to automatically create the list and adjust it to include the most effective steps for the user. The generated list is output to the terminal and presented to the user.

[0345] Step 5:

[0346] The server's service suggestion section searches for and suggests available supply services near the event location. It obtains geographical information using the Google Maps API and other tools, and evaluates third-party service providers. The input is the user's event information, and the output provides the user with a list of the most suitable services.

[0347] Step 6:

[0348] The Design Generation Department creates structure templates for event announcement materials. This department utilizes the Adobe Creative Cloud API to build flexible templates that users can customize. The resulting templates are visually appealing to users.

[0349] Step 7:

[0350] The budget management department calculates recommended funding allocations based on the user's entered budget limit. It combines machine learning algorithms and linear optimization to optimize the user's spending for the most effective use of funds. The calculation results are presented to the user to assist in event planning.

[0351] Step 8:

[0352] Finally, the results storage unit saves the user's decisions to a memory area. The saved data is managed in cloud-based data storage and used as a reference for future event planning and progress management. The input is the user's final confirmation information, and the output data is stored in a database.

[0353] 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.

[0354] This invention combines a system that supports event planning, preparation, and operation with an emotion engine that recognizes user emotions. This system integrates multiple functional units, enabling flexible and efficient event preparation according to user needs.

[0355] The user first enters event information using a terminal. This information includes the event name, date and time, location, number of participants, and budget. This information is sent from the terminal to the information retrieval unit and stored in the database on the server.

[0356] The analysis unit on the server searches for similar past events based on the input information and creates an optimal to-do list template. During this process, an efficient event progression is planned based on the analysis results of past data.

[0357] Furthermore, the service proposal department searches for available services around the event venue and proposes them to the user. This allows for the rapid selection of necessary vendors and services. In addition, the design generation department provides design templates for promotional materials, which can be customized to the user's needs.

[0358] The budget management department calculates the optimal allocation of funds within the budget and presents recommended plans to prevent unplanned expenses. Users review these proposals via their devices and make final decisions.

[0359] The emotion engine recognizes emotions from the user's device through voice and text. Based on this recognition, it makes additional suggestions regarding the atmosphere and theme of the event. For example, if the user prefers a relaxed atmosphere, services with such themes will be prioritized. Furthermore, by promoting the customization of designs and services based on the user's emotions, optimization tailored to individual needs is possible.

[0360] Throughout the entire process, users can use their devices to create, refine, and manage comprehensive event plans while receiving feedback from the emotion engine. This reduces the burden on users and ensures highly satisfying events.

[0361] For example, when a user is preparing for a wedding on their device, the emotion engine might analyze the user's mood and recommend a relaxed, casual wedding. The server then reflects this result, suggesting services and designs that fit the casual theme, and the budget management department presents the optimal allocation of funds within that framework. In this way, the user can smoothly prepare an event that matches their mood.

[0362] The following describes the processing flow.

[0363] Step 1:

[0364] Users enter basic event information into a form from their device. This information includes the event name, date and time, location, number of participants, budget, and a brief description or preference.

[0365] Step 2:

[0366] The terminal transmits the input information to the information acquisition unit. The information acquisition unit prepares to transmit this information to the server.

[0367] Step 3:

[0368] The server's analysis unit searches the database for similar past event data based on event information received from the information acquisition unit. Simultaneously, it analyzes this similar data to create a to-do list template for optimal event management.

[0369] Step 4:

[0370] The server uses a service suggestion unit to detect and suggest vendors and services available in the vicinity of the event venue. This includes catering, decorations, sound services, and more.

[0371] Step 5:

[0372] The design generation unit runs on a server and generates design proposals for event-optimized announcements. Templates are provided so that users can select options for personalization.

[0373] Step 6:

[0374] The server's budget management unit calculates and presents recommended cost allocations for each element of an event based on the budget data entered by the user. This helps users avoid unplanned expenses.

[0375] Step 7:

[0376] The emotion engine analyzes the user's emotions using voice and text data from the device and reports the results to the server. Based on these results, the server provides suggestions for customizing the event's theme and atmosphere.

[0377] Step 8:

[0378] The user reviews the to-do list, service proposals, design proposals, budget allocations, and additional sentiment-based suggestions provided by the server on their device. They then apply any necessary step-up revisions and make final decisions.

[0379] Step 9:

[0380] The server's results storage unit saves the user's final decision information to a database. This saved data is used for managing events in progress and as a reference for planning future events.

[0381] (Example 2)

[0382] 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".

[0383] In modern society, efficiently planning and running events is a time-consuming and laborious task. In particular, preparing for the event, selecting appropriate services, managing the budget, and customizing to meet the needs of new participants are all challenging. Furthermore, considering participants' emotions and creating an appropriate atmosphere and design for the event is not easy. There is a need to integrate and solve these complex elements within a single system.

[0384] 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.

[0385] In this invention, the server includes an information acquisition unit that receives information about activities from a user terminal, an analysis unit that searches for and analyzes similar past activity data based on the information about the activities, and an emotion recognition unit that recognizes the user's emotional state based on voice or text data. This enables users to plan and manage personalized events based on emotional data, resulting in efficient and highly satisfying event implementation.

[0386] The "Information Acquisition Department" is the department responsible for receiving event-related information from user terminals.

[0387] The "Analysis Department" is a department that has the function of searching and analyzing past similar activity data based on the information received about the activity.

[0388] The "TODO List Generation Department" is a department that generates a to-do list summarizing the tasks necessary for the progress of an event, based on the analysis results from the Analysis Department.

[0389] The "Service Proposal Department" is a department responsible for searching for services available in the vicinity of the event venue and making appropriate suggestions to users.

[0390] The "Design Generation Department" is a department that creates design templates for event announcements and allows users to customize them.

[0391] The "Budget Management Department" is a department responsible for proposing the optimal allocation of funds necessary for an event based on the designated budget.

[0392] The "emotion recognition unit" is a department that has the function of recognizing the user's emotional state based on voice or text data.

[0393] The "Result Storage Department" is the department responsible for saving the final content decided by the user to a storage device.

[0394] This invention utilizes an integrated system via user terminals, a server, and a network to streamline event planning and management. Users input detailed event information via their user terminals, and this information is quickly transmitted to the server. Multiple functional units within the server perform advanced data processing based on the received information, providing users with various suggestions and adjustments.

[0395] The server retrieves data entered by users through the information acquisition unit and stores it in the database as structured data. The analysis unit searches for similar past event data based on the stored information and performs analysis using machine learning algorithms. The technologies used for this include data analysis libraries in Python and R.

[0396] Based on the analysis results, the to-do list generation unit generates a to-do list to plan the efficient progress of the event. This allows the user to properly understand the event's steps.

[0397] Next, the server's service suggestion unit uses external API services to search for available vendors and services around the event venue and suggests the best options to the user. This could include, for example, suitable catering or decoration vendors. Common APIs used for this purpose include those from general map service providers.

[0398] The design generation unit creates design templates for announcements based on user requests. Using Adobe Creative Cloud APIs, it can provide customizable initial designs. Users can preview and optimize the designs through a designated interface on their device.

[0399] The emotion recognition unit acquires voice and text data to analyze the user's emotions and recognizes their emotional state using natural language processing (NLP) technology. Based on this information, suggestions are made that are tailored to the atmosphere and theme of the event the user desires. For example, if the user wants a relaxed event, the appropriate background music and lighting settings will be prioritized.

[0400] As a concrete example, when a user is preparing for a wedding, the system refers to past data and suggests a relaxed, casual wedding plan. The user enters a prompt such as, "I want to plan a relaxed wedding," and the AI ​​provides specific suggestions tailored to that need. In this way, users can efficiently plan and manage an event that aligns with their emotions through a series of processes.

[0401] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0402] Step 1:

[0403] The user uses their device to enter detailed information about the event. Specifically, they enter data such as the event name, date and time, location, number of participants, and budget into an input form. Once this input is complete, the device packets this data and prepares it for transmission to the server.

[0404] Step 2:

[0405] The terminal sends the entered event information to the server. The information retrieval unit receives this data and stores it in the server's database. In this process, the received data is saved in a structured format using SQL queries. Based on the entered information, related fields are updated and new records are added.

[0406] Step 3:

[0407] The analysis unit on the server uses event information obtained from the database to search for similar past event data. Here, machine learning algorithms are used to identify relevant events and generate analysis results. This analysis uses metrics such as event success rate and participant satisfaction. The output provides a list of related past events and their analysis results.

[0408] Step 4:

[0409] The server's to-do list generation unit generates a list of specific tasks (to-do list) necessary for the event's progress, based on the analysis results from the analysis unit. This list may include items such as schedule confirmation, vendor arrangements, and decoration preparations. This generated to-do list is output in an easy-to-manage format (e.g., checklist format) and provided to the user.

[0410] Step 5:

[0411] The server's service suggestion unit uses an external API to search for appropriate services near the event venue. Geographic information of the venue is used as input, and a list of nearby services (e.g., catering, decorations) is obtained via the API. This result is then presented to the user.

[0412] Step 6:

[0413] The server's design generation unit generates event announcement design templates according to user requests. This process uses a design tool API to customize pre-configured templates. The output is a design file that the user can modify.

[0414] Step 7:

[0415] The server's emotion recognition unit analyzes the user's emotional state. User-provided voice and text data are used as input, and emotion analysis is performed using natural language processing techniques. As output, data related to the user's emotions is generated and reflected in relevant suggestions.

[0416] Step 8:

[0417] The user reviews, adjusts, and finalizes the event plan based on emotion recognition and various suggestions. This decision is then saved again to the database by the results storage unit. The saved information is used for future progress management and as a reference for planning new events.

[0418] (Application Example 2)

[0419] 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."

[0420] In planning and preparing events, users often need to select ideal themes and services while reviewing past data and budgets, but this process is complex and burdensome for users. Furthermore, customization based on users' own feelings and preferences is difficult, making it challenging to improve satisfaction.

[0421] 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.

[0422] In this invention, the server includes an information acquisition unit that receives information about events from a user terminal, an analysis unit that searches for and analyzes similar past event data based on the information about the event, and an emotion analysis unit that analyzes the user's voice and documents to recognize emotions. This makes it possible to provide an optimal event plan tailored to the user's emotions and preferences.

[0423] The "Information Acquisition Unit" is a module that receives input data related to events from the user's operating terminal.

[0424] The "Analysis Unit" is a component that searches for similar past event data based on event-related information obtained from users, and analyzes that information.

[0425] The "TODO List Generation Unit" is a unit that has the function of generating a task list for efficient event preparation based on the results of the analysis unit.

[0426] The "Service Proposal Department" is a section responsible for searching for services in the vicinity of the event venue and proposing appropriate services to users based on the results.

[0427] The "Design Generation Department" is a department that creates design templates for announcements necessary for events and has the function of allowing users to customize them according to their preferences.

[0428] The "Budget Management Department" is a department that supports economic planning by calculating and proposing recommended allocations of funds based on the designated budget.

[0429] The "Emotion Analysis Department" is a department that analyzes users' voice and document data to recognize and understand the emotions behind them.

[0430] The "Proposal Optimization Department" is a part of the team that utilizes the recognition results from the Sentiment Analysis Department to customize event themes and services according to the emotions of the users.

[0431] The "results storage unit" is a component that saves the user's final decisions to a data storage medium, allowing for future reference and use in planning future events.

[0432] This invention is a system that efficiently supports event planning and execution. Based on event information entered by the user, this system analyzes similar past data and provides customized suggestions based on emotions. The user enters event information via a terminal, and this information is sent to the server. On the server, the information acquisition unit receives the data, and the analysis unit searches and analyzes past event data based on that information. Next, the to-do list generation unit creates an efficient task list based on the analysis results. Furthermore, the emotion analysis unit analyzes the voice and text data entered by the user to recognize the user's emotions. Based on these results, the suggestion optimization unit customizes and proposes appropriate event themes and services.

[0433] Users can review the proposed options and make a final decision. The budget management department optimizes the allocation of funds to each service according to the specified budget. The finalized information is saved to a data storage medium by the results storage department and can be used as a reference for planning future events.

[0434] This system utilizes speech recognition technology and data analysis algorithms. Speech recognition uses APIs such as Google Speech Recognition API, and machine learning models are employed for the analysis algorithms.

[0435] As a concrete example, consider a user planning a birthday party at home. The user voice-inputs the event details into the device, and based on sentiment analysis, a relaxed, casual theme is suggested. Following this suggestion, the design and services are customized, and the optimal budget allocation is shown to stay within budget. This allows the user to smoothly prepare an event perfectly tailored to their needs.

[0436] An example of a prompt message is, "Please plan a relaxed family birthday party. The budget is 100,000 yen."

[0437] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0438] Step 1:

[0439] Users input event information using a terminal. This includes the event name, date and time, location, number of participants, and budget. This input data is sent from the terminal to the server and received by the information retrieval unit.

[0440] Step 2:

[0441] The server's analysis unit searches the database for similar past events based on the received data. By analyzing the retrieved data, the foundation for a to-do list suitable for the current event is built. This process uses data mining algorithms to extract past cases similar to the input parameters.

[0442] Step 3:

[0443] The TODO list generation unit generates an efficient TODO list based on the analysis results. It uses the output of the analysis unit as input to compile the most suitable work items. This list is output to the user, showing the steps to proceed to the next stage.

[0444] Step 4:

[0445] The server's sentiment analysis unit recognizes emotions from the user's voice and text. This process involves acquiring voice data, converting it to text using the Google Speech Recognition API, and then performing sentiment analysis on the text. Machine learning algorithms are used here to output the user's expected emotional state.

[0446] Step 5:

[0447] The suggestion optimization unit optimizes and proposes event themes and services based on recognized emotions. It uses the emotion recognition results from the previous step as input, comparing them with event data to generate optimal suggestions. Users receive the customized theme and service suggestions on their devices.

[0448] Step 6:

[0449] The budget management department calculates the optimal allocation of funds to each service based on the specified budget. The user's specified budget and proposed service details are used as input, and the calculated budget allocation is output to the user. This process is performed using a linear programming algorithm.

[0450] Step 7:

[0451] The user makes a final decision and confirms it through their terminal. The user's decision is saved to a data storage medium in the server's results storage unit. This saved data can be used as reference for planning future events and managing progress.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] [Third Embodiment]

[0456] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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).

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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".

[0468] The event support system in this invention efficiently plans, coordinates, and prepares events by having multiple functional units.

[0469] First, the user enters basic event information via their device. This information includes the event name, date and time, location, number of participants, and budget. Once this data is entered from the device, the information retrieval unit collects the data and sends it to the server.

[0470] The server processes the data received from the information acquisition unit in the analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This makes it possible to create an optimal to-do list based on lessons learned from past cases.

[0471] Next, the server uses the to-do list generation unit to generate a list of specific preparation tasks for the user. This list covers all the steps necessary for the event to succeed and provides the user with clear guidance.

[0472] Furthermore, the service proposal department searches for available services in and around the event venue (e.g., catering, venue setup, decoration companies, etc.). The server then proposes appropriate services based on the characteristics of the user's event.

[0473] In parallel, the server uses the design generation unit to build design templates for event announcements. Users can customize these templates and select the design that best suits their event.

[0474] In the budget management section, the server calculates and presents recommended funding allocations based on the entered budget. This function allows users to plan events to stay within budget.

[0475] Once all proposals and selections are complete, the user performs a final confirmation via their terminal. The user's decisions are stored in a database by the server's results storage unit. This data is used not only for managing ongoing events but also for planning future events.

[0476] As a concrete example, consider a scenario where a user plans a relative's wedding at a hotel in a certain area. The user enters the date, time, location, number of guests, budget, etc., and the server references past wedding examples to suggest the most suitable preparation tasks and available services. It also provides invitation design suggestions and calculates the optimal allocation of funds within the budget. Once the user makes a final decision, the information is saved for future reference.

[0477] As described above, the present invention utilizes AI to automate various processes necessary for event planning, thereby supporting efficient and effective event management.

[0478] The following describes the processing flow.

[0479] Step 1:

[0480] Users enter event information using a terminal. Input fields include event name, date and time, location, number of participants, and budget. This data is then transmitted from the terminal to the information retrieval unit.

[0481] Step 2:

[0482] The server receives input data from the user through the information acquisition unit. The received data is processed by the analysis unit, which identifies the event category based on the input content.

[0483] Step 3:

[0484] The server's analysis unit searches the database for data on similar past events and begins the analysis. This analysis identifies a suitable to-do list template for the event.

[0485] Step 4:

[0486] The server's to-do list generation unit creates a list of preparation tasks for the user based on the analysis results. This list provides detailed guidelines for event preparation.

[0487] Step 5:

[0488] The server's service proposal department searches the database for available services around the event venue. Based on the characteristics of the event, it proposes suitable service providers to the user.

[0489] Step 6:

[0490] The server's design generation unit generates a design template for event announcements. Users can view this template via their terminal and customize it as needed.

[0491] Step 7:

[0492] The server's budget management system calculates and presents recommended funding allocations based on the budget information entered by the user. This allows the user to plan the optimal events within their budget.

[0493] Step 8:

[0494] The user reviews the to-do list, service proposals, design proposals, and budget plan provided by the server via their device. They make any necessary revisions and send their final decisions to the server.

[0495] Step 9:

[0496] The server's results storage unit saves the user's final decision to the database. The saved data serves as reference data for progress management and future event planning.

[0497] (Example 1)

[0498] 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."

[0499] Current event planning support systems often perform information gathering, analysis, task generation, service proposals, and budget management tasks individually, making efficient and integrated event management difficult. Furthermore, there is a lack of effective ways to leverage best practices from similar past events. Therefore, there is a need for a method to comprehensively optimize event planning and preparation.

[0500] 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.

[0501] In this invention, the server includes means for an information gathering unit to receive event information from a user terminal, means for an analysis function unit to perform analysis based on past similar event information, and means for a task list generation unit to generate a task list for the event based on the analysis results. This makes it possible to integrate everything from efficient information gathering to task generation, service proposals, and budget control throughout the entire process of an event.

[0502] The "Information Gathering Department" is the department responsible for receiving event-related data from user terminals.

[0503] The "Analysis Function Department" is a department that has the function of searching for and analyzing past similar event information based on the received event data.

[0504] The "Task List Generation Unit" is a department that generates task lists for events based on the analysis results obtained from the Analysis Function Unit.

[0505] The "Service Recommendation Department" is a department that searches for surrounding facilities of event venues and makes recommendations based on that information.

[0506] The "Design Generation Department" is the department responsible for creating design templates for event notices and other promotional materials.

[0507] The "Budget Adjustment Department" is a department whose function is to propose recommended funding allocations based on the designated expenditure plan.

[0508] The "Results Storage Department" is the department responsible for storing user decisions on storage media.

[0509] The event support system of this invention efficiently and comprehensively plans, coordinates, and prepares events. The system consists of a terminal used by the user and a server having multiple functional units.

[0510] First, the user enters basic information such as the event name, date and time, location, number of participants, and budget into the terminal. The terminal converts this information into a data format and sends it to the server. The server's information collection unit receives this data.

[0511] The received data is processed by the server's analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This process utilizes database management systems such as MySQL and natural language processing technology.

[0512] Based on the analysis results, the task list generation unit generates a list of specific preparation tasks. The task list is automatically generated using algorithms written in languages ​​such as Python or Java.

[0513] The server's service recommendation section suggests surrounding services tailored to the characteristics of the event. It uses Google APIs and third-party APIs to gather information about services within the region and provide users with the most suitable options.

[0514] The design generation unit utilizes design software such as Adobe XD and Canva to generate design templates for event-related notices. Users can customize these templates.

[0515] The budget adjustment department provides recommended funding allocations based on the budget specified by the user. It uses Excel or Google Sheets to calculate and provide the optimal allocation plan to the user.

[0516] After all proposals and selections are complete, the user makes a final confirmation via their terminal, and the decisions are saved in the results storage unit and used for future event planning.

[0517] As a concrete example, consider a scenario where a user plans a birthday party for a close friend at a local hall. The user enters the date, time, location, number of guests, and budget. The server then references past birthday party examples and suggests the most suitable task list and services. It also provides invitation design suggestions and optimizes budget allocation. After the user makes a final decision, the information is saved for future reference.

[0518] An example of a prompt using a generative AI model is, "Please suggest the optimal task list based on successful past events of a similar type."

[0519] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0520] Step 1:

[0521] Users input basic information such as the event name, date and time, location, number of participants, and budget via their terminal. This input information is converted into a data structure such as JSON and sent to the server. The terminal validates the input data through the user interface to check for any missing or incorrect information.

[0522] Step 2:

[0523] The server's information gathering unit receives data from terminals and stores it in its internal database. During this process, the server checks data integrity and converts the format as needed. The event information received as input is then used in subsequent analysis steps.

[0524] Step 3:

[0525] The server's analysis unit uses stored data to search the database for information on similar past events. The analysis unit executes SQL queries to extract relevant past event data. The output is an analysis result based on the characteristics of the event.

[0526] Step 4:

[0527] The server uses a task list generation unit to generate an event preparation task list based on the analysis results. It utilizes a generation AI model and prompts to enumerate appropriate tasks. The output is a specific task list, including tasks such as creating invitations, arranging the venue, and preparing decorations.

[0528] Step 5:

[0529] The server's service recommendation section searches for services around the event location via an API and provides service options relevant to the user's event. The input is the user's event characteristics, and the output is a list of services such as catering and venue setup.

[0530] Step 6:

[0531] The design generation unit uses a generation AI model to create design templates for event announcements. Using prompts, it generates design proposals that match the event theme and provides them to the user. The output is a customizable design template.

[0532] Step 7:

[0533] The budget adjustment department proposes item-specific funding allocations based on the budget entered by the user. It receives budget information as input and performs calculations using Excel or Google Sheets. The output is the recommended budget allocation for each task.

[0534] Step 8:

[0535] Users review all suggestions via their terminal, edit them as needed, and then make their final decision. The final selection is sent to the server and stored in a database by the results storage unit. This information is also used as reference data for future event planning.

[0536] (Application Example 1)

[0537] 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."

[0538] In traditional event planning, it is difficult to efficiently integrate and manage the various tasks and services related to an event, and there are particular challenges in optimizing the selection of food delivery services and budget management. As a result, the overall preparation of an event can become complicated, sometimes resulting in unnecessary time and costs.

[0539] 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.

[0540] In this invention, the server includes an information acquisition unit that receives information about an arbitrary event from a user terminal, an analysis unit that searches for and analyzes past similar event information based on the information about the event, and a to-do list generation unit that generates an action list for the event based on the analysis results of the analysis unit. This makes it possible to optimize tasks related to the event and propose an efficient food delivery service.

[0541] The "Information Acquisition Unit" is responsible for receiving event-related information from the user's terminal and transmitting it to the server.

[0542] The "Analysis Unit" provides the functionality to search for data based on information about received events and analyze past similar events.

[0543] The "TODO list generation unit" is a device that creates an action list for an event based on the analysis results from the analysis unit.

[0544] The "Service Proposal Department" is a system that searches for available services around the event venue and provides users with the most suitable suggestions.

[0545] The "Design Generation Unit" is a device that has the function of creating and providing event announcement materials with a structure template.

[0546] The "Budget Management Department" is a system that calculates and presents the optimal allocation of funds to the user based on the designated funds.

[0547] The "results storage unit" is a device that stores the user's decisions in a memory area for future reference and event management.

[0548] A "proposal generation module" is a device that has the function of selecting the most suitable supply service based on the user's input information and providing it to the user.

[0549] The system that realizes this invention consists of a server with multiple functional units and a user terminal. First, the user uses the terminal to input information about the event. This information includes the event title, date and time, location, number of participants, and budget. The information acquisition unit receives this data and transmits it to the server. Based on the received information, the server's analysis unit searches for information on similar past events and performs analysis.

[0550] Based on the analysis results, the TODO list generation unit generates an action list for the event and displays it on the terminal. The service proposal unit searches for available services around the event location and makes the best proposal to the user. The design generation unit creates a template for the announcement materials, allowing users to customize it. The budget management unit calculates the optimal fund allocation based on the entered funds and displays it to the user.

[0551] This entire process utilizes cloud services such as Google Cloud Platform and AWS, and leverages cloud-based memory storage for the database. Python and R are used for data analysis, and machine learning algorithms like scikit-learn and TensorFlow are implemented. Finally, the results storage unit stores the user's decisions in memory for future reference and event management.

[0552] As a concrete example, consider a scenario where a user plans a party for 20 people with a budget of 50,000 yen. In this case, once the user inputs the information, the server can suggest the optimal food delivery options based on past party data and indicate how to allocate funds within the budget. An example of an input prompt to the generating AI model would be, "Please tell me the best food delivery options for a party of 20 people that cost under 50,000 yen."

[0553] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0554] Step 1:

[0555] The user inputs event information from the terminal. This information includes the event title, date and time, location, number of participants, and budget. The terminal sends this data to the information acquisition unit, which then prepares the basic data for the next processing step.

[0556] Step 2:

[0557] The server's information acquisition unit receives event information sent from the terminal. This received data is then passed to the analysis unit. The analysis unit is connected to a database and uses this information as input to search for similar past event information. It retrieves relevant data from the database and performs the analysis.

[0558] Step 3:

[0559] The analysis unit searches past event data based on the received data and performs analysis using machine learning algorithms. In this process, TensorFlow is used to model past data patterns and identify events with high similarity. As output, the analysis results of similar events are generated and provided to the TODO list generation unit.

[0560] Step 4:

[0561] The TODO list generation unit receives analysis results from the analysis unit and generates an action list for the event based on them. This process uses a Python script to automatically create the list and adjust it to include the most effective steps for the user. The generated list is output to the terminal and presented to the user.

[0562] Step 5:

[0563] The server's service suggestion section searches for and suggests available supply services near the event location. It obtains geographical information using the Google Maps API and other tools, and evaluates third-party service providers. The input is the user's event information, and the output provides the user with a list of the most suitable services.

[0564] Step 6:

[0565] The Design Generation Department creates structure templates for event announcement materials. This department utilizes the Adobe Creative Cloud API to build flexible templates that users can customize. The resulting templates are visually appealing to users.

[0566] Step 7:

[0567] The budget management department calculates recommended funding allocations based on the user's entered budget limit. It combines machine learning algorithms and linear optimization to optimize the user's spending for the most effective use of funds. The calculation results are presented to the user to assist in event planning.

[0568] Step 8:

[0569] Finally, the results storage unit saves the user's decisions to a memory area. The saved data is managed in cloud-based data storage and used as a reference for future event planning and progress management. The input is the user's final confirmation information, and the output data is stored in a database.

[0570] 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.

[0571] This invention combines a system that supports event planning, preparation, and operation with an emotion engine that recognizes user emotions. This system integrates multiple functional units, enabling flexible and efficient event preparation according to user needs.

[0572] The user first enters event information using a terminal. This information includes the event name, date and time, location, number of participants, and budget. This information is sent from the terminal to the information retrieval unit and stored in the database on the server.

[0573] The analysis unit on the server searches for similar past events based on the input information and creates an optimal to-do list template. During this process, an efficient event progression is planned based on the analysis results of past data.

[0574] Furthermore, the service proposal department searches for available services around the event venue and proposes them to the user. This allows for the rapid selection of necessary vendors and services. In addition, the design generation department provides design templates for promotional materials, which can be customized to the user's needs.

[0575] The budget management department calculates the optimal allocation of funds within the budget and presents recommended plans to prevent unplanned expenses. Users review these proposals via their devices and make final decisions.

[0576] The emotion engine recognizes emotions from the user's device through voice and text. Based on this recognition, it makes additional suggestions regarding the atmosphere and theme of the event. For example, if the user prefers a relaxed atmosphere, services with such themes will be prioritized. Furthermore, by promoting the customization of designs and services based on the user's emotions, optimization tailored to individual needs is possible.

[0577] Throughout the entire process, users can use their devices to create, refine, and manage comprehensive event plans while receiving feedback from the emotion engine. This reduces the burden on users and ensures highly satisfying events.

[0578] For example, when a user is preparing for a wedding on their device, the emotion engine might analyze the user's mood and recommend a relaxed, casual wedding. The server then reflects this result, suggesting services and designs that fit the casual theme, and the budget management department presents the optimal allocation of funds within that framework. In this way, the user can smoothly prepare an event that matches their mood.

[0579] The following describes the processing flow.

[0580] Step 1:

[0581] Users enter basic event information into a form from their device. This information includes the event name, date and time, location, number of participants, budget, and a brief description or preference.

[0582] Step 2:

[0583] The terminal transmits the input information to the information acquisition unit. The information acquisition unit prepares to transmit this information to the server.

[0584] Step 3:

[0585] The server's analysis unit searches the database for similar past event data based on event information received from the information acquisition unit. Simultaneously, it analyzes this similar data to create a to-do list template for optimal event management.

[0586] Step 4:

[0587] The server uses a service suggestion unit to detect and suggest vendors and services available in the vicinity of the event venue. This includes catering, decorations, sound services, and more.

[0588] Step 5:

[0589] The design generation unit runs on a server and generates design proposals for event-optimized announcements. Templates are provided so that users can select options for personalization.

[0590] Step 6:

[0591] The server's budget management unit calculates and presents recommended cost allocations for each element of an event based on the budget data entered by the user. This helps users avoid unplanned expenses.

[0592] Step 7:

[0593] The emotion engine analyzes the user's emotions using voice and text data from the device and reports the results to the server. Based on these results, the server provides suggestions for customizing the event's theme and atmosphere.

[0594] Step 8:

[0595] The user reviews the to-do list, service proposals, design proposals, budget allocations, and additional sentiment-based suggestions provided by the server on their device. They then apply any necessary step-up revisions and make final decisions.

[0596] Step 9:

[0597] The server's results storage unit saves the user's final decision information to a database. This saved data is used for managing events in progress and as a reference for planning future events.

[0598] (Example 2)

[0599] 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."

[0600] In modern society, efficiently planning and running events is a time-consuming and laborious task. In particular, preparing for the event, selecting appropriate services, managing the budget, and customizing to meet the needs of new participants are all challenging. Furthermore, considering participants' emotions and creating an appropriate atmosphere and design for the event is not easy. There is a need to integrate and solve these complex elements within a single system.

[0601] 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.

[0602] In this invention, the server includes an information acquisition unit that receives information about activities from a user terminal, an analysis unit that searches for and analyzes similar past activity data based on the information about the activities, and an emotion recognition unit that recognizes the user's emotional state based on voice or text data. This enables users to plan and manage personalized events based on emotional data, resulting in efficient and highly satisfying event implementation.

[0603] The "Information Acquisition Department" is the department responsible for receiving event-related information from user terminals.

[0604] The "Analysis Department" is a department that has the function of searching and analyzing past similar activity data based on the information received about the activity.

[0605] The "TODO List Generation Department" is a department that generates a to-do list summarizing the tasks necessary for the progress of an event, based on the analysis results from the Analysis Department.

[0606] The "Service Proposal Department" is a department responsible for searching for services available in the vicinity of the event venue and making appropriate suggestions to users.

[0607] The "Design Generation Department" is a department that creates design templates for event announcements and allows users to customize them.

[0608] The "Budget Management Department" is a department responsible for proposing the optimal allocation of funds necessary for an event based on the designated budget.

[0609] The "emotion recognition unit" is a department that has the function of recognizing the user's emotional state based on voice or text data.

[0610] The "Result Storage Department" is the department responsible for saving the final content decided by the user to a storage device.

[0611] This invention utilizes an integrated system via user terminals, a server, and a network to streamline event planning and management. Users input detailed event information via their user terminals, and this information is quickly transmitted to the server. Multiple functional units within the server perform advanced data processing based on the received information, providing users with various suggestions and adjustments.

[0612] The server retrieves data entered by users through the information acquisition unit and stores it in the database as structured data. The analysis unit searches for similar past event data based on the stored information and performs analysis using machine learning algorithms. The technologies used for this include data analysis libraries in Python and R.

[0613] Based on the analysis results, the to-do list generation unit generates a to-do list to plan the efficient progress of the event. This allows the user to properly understand the event's steps.

[0614] Next, the server's service suggestion unit uses external API services to search for available vendors and services around the event venue and suggests the best options to the user. This could include, for example, suitable catering or decoration vendors. Common APIs used for this purpose include those from general map service providers.

[0615] The design generation unit creates design templates for announcements based on user requests. Using Adobe Creative Cloud APIs, it can provide customizable initial designs. Users can preview and optimize the designs through a designated interface on their device.

[0616] The emotion recognition unit acquires voice and text data to analyze the user's emotions and recognizes their emotional state using natural language processing (NLP) technology. Based on this information, suggestions are made that are tailored to the atmosphere and theme of the event the user desires. For example, if the user wants a relaxed event, the appropriate background music and lighting settings will be prioritized.

[0617] As a concrete example, when a user is preparing for a wedding, the system refers to past data and suggests a relaxed, casual wedding plan. The user enters a prompt such as, "I want to plan a relaxed wedding," and the AI ​​provides specific suggestions tailored to that need. In this way, users can efficiently plan and manage an event that aligns with their emotions through a series of processes.

[0618] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0619] Step 1:

[0620] The user uses their device to enter detailed information about the event. Specifically, they enter data such as the event name, date and time, location, number of participants, and budget into an input form. Once this input is complete, the device packets this data and prepares it for transmission to the server.

[0621] Step 2:

[0622] The terminal sends the entered event information to the server. The information retrieval unit receives this data and stores it in the server's database. In this process, the received data is saved in a structured format using SQL queries. Based on the entered information, related fields are updated and new records are added.

[0623] Step 3:

[0624] The analysis unit on the server uses event information obtained from the database to search for similar past event data. Here, machine learning algorithms are used to identify relevant events and generate analysis results. This analysis uses metrics such as event success rate and participant satisfaction. The output provides a list of related past events and their analysis results.

[0625] Step 4:

[0626] The server's to-do list generation unit generates a list of specific tasks (to-do list) necessary for the event's progress, based on the analysis results from the analysis unit. This list may include items such as schedule confirmation, vendor arrangements, and decoration preparations. This generated to-do list is output in an easy-to-manage format (e.g., checklist format) and provided to the user.

[0627] Step 5:

[0628] The server's service suggestion unit uses an external API to search for appropriate services near the event venue. Geographic information of the venue is used as input, and a list of nearby services (e.g., catering, decorations) is obtained via the API. This result is then presented to the user.

[0629] Step 6:

[0630] The server's design generation unit generates event announcement design templates according to user requests. This process uses a design tool API to customize pre-configured templates. The output is a design file that the user can modify.

[0631] Step 7:

[0632] The server's emotion recognition unit analyzes the user's emotional state. User-provided voice and text data are used as input, and emotion analysis is performed using natural language processing techniques. As output, data related to the user's emotions is generated and reflected in relevant suggestions.

[0633] Step 8:

[0634] The user reviews, adjusts, and finalizes the event plan based on emotion recognition and various suggestions. This decision is then saved again to the database by the results storage unit. The saved information is used for future progress management and as a reference for planning new events.

[0635] (Application Example 2)

[0636] 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."

[0637] In planning and preparing events, users often need to select ideal themes and services while reviewing past data and budgets, but this process is complex and burdensome for users. Furthermore, customization based on users' own feelings and preferences is difficult, making it challenging to improve satisfaction.

[0638] 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.

[0639] In this invention, the server includes an information acquisition unit that receives information about events from a user terminal, an analysis unit that searches for and analyzes similar past event data based on the information about the event, and an emotion analysis unit that analyzes the user's voice and documents to recognize emotions. This makes it possible to provide an optimal event plan tailored to the user's emotions and preferences.

[0640] The "Information Acquisition Unit" is a module that receives input data related to events from the user's operating terminal.

[0641] The "Analysis Unit" is a component that searches for similar past event data based on event-related information obtained from users, and analyzes that information.

[0642] The "TODO List Generation Unit" is a unit that has the function of generating a task list for efficient event preparation based on the results of the analysis unit.

[0643] The "Service Proposal Department" is a section responsible for searching for services in the vicinity of the event venue and proposing appropriate services to users based on the results.

[0644] The "Design Generation Department" is a department that creates design templates for announcements necessary for events and has the function of allowing users to customize them according to their preferences.

[0645] The "Budget Management Department" is a department that supports economic planning by calculating and proposing recommended allocations of funds based on the designated budget.

[0646] The "Emotion Analysis Department" is a department that analyzes users' voice and document data to recognize and understand the emotions behind them.

[0647] The "Proposal Optimization Department" is a part of the team that utilizes the recognition results from the Sentiment Analysis Department to customize event themes and services according to the emotions of the users.

[0648] The "results storage unit" is a component that saves the user's final decisions to a data storage medium, allowing for future reference and use in planning future events.

[0649] This invention is a system that efficiently supports event planning and execution. Based on event information entered by the user, this system analyzes similar past data and provides customized suggestions based on emotions. The user enters event information via a terminal, and this information is sent to the server. On the server, the information acquisition unit receives the data, and the analysis unit searches and analyzes past event data based on that information. Next, the to-do list generation unit creates an efficient task list based on the analysis results. Furthermore, the emotion analysis unit analyzes the voice and text data entered by the user to recognize the user's emotions. Based on these results, the suggestion optimization unit customizes and proposes appropriate event themes and services.

[0650] Users can review the proposed options and make a final decision. The budget management department optimizes the allocation of funds to each service according to the specified budget. The finalized information is saved to a data storage medium by the results storage department and can be used as a reference for planning future events.

[0651] This system utilizes speech recognition technology and data analysis algorithms. Speech recognition uses APIs such as Google Speech Recognition API, and machine learning models are employed for the analysis algorithms.

[0652] As a concrete example, consider a user planning a birthday party at home. The user voice-inputs the event details into the device, and based on sentiment analysis, a relaxed, casual theme is suggested. Following this suggestion, the design and services are customized, and the optimal budget allocation is shown to stay within budget. This allows the user to smoothly prepare an event perfectly tailored to their needs.

[0653] An example of a prompt message is, "Please plan a relaxed family birthday party. The budget is 100,000 yen."

[0654] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0655] Step 1:

[0656] Users input event information using a terminal. This includes the event name, date and time, location, number of participants, and budget. This input data is sent from the terminal to the server and received by the information retrieval unit.

[0657] Step 2:

[0658] The server's analysis unit searches the database for similar past events based on the received data. By analyzing the retrieved data, the foundation for a to-do list suitable for the current event is built. This process uses data mining algorithms to extract past cases similar to the input parameters.

[0659] Step 3:

[0660] The TODO list generation unit generates an efficient TODO list based on the analysis results. It uses the output of the analysis unit as input to compile the most suitable work items. This list is output to the user, showing the steps to proceed to the next stage.

[0661] Step 4:

[0662] The server's sentiment analysis unit recognizes emotions from the user's voice and text. This process involves acquiring voice data, converting it to text using the Google Speech Recognition API, and then performing sentiment analysis on the text. Machine learning algorithms are used here to output the user's expected emotional state.

[0663] Step 5:

[0664] The suggestion optimization unit optimizes and proposes event themes and services based on recognized emotions. It uses the emotion recognition results from the previous step as input, comparing them with event data to generate optimal suggestions. Users receive the customized theme and service suggestions on their devices.

[0665] Step 6:

[0666] The budget management department calculates the optimal allocation of funds to each service based on the specified budget. The user's specified budget and proposed service details are used as input, and the calculated budget allocation is output to the user. This process is performed using a linear programming algorithm.

[0667] Step 7:

[0668] The user makes a final decision and confirms it through their terminal. The user's decision is saved to a data storage medium in the server's results storage unit. This saved data can be used as reference for planning future events and managing progress.

[0669] 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.

[0670] 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.

[0671] 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.

[0672] [Fourth Embodiment]

[0673] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0674] 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.

[0675] 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).

[0676] 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.

[0677] 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.

[0678] 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).

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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".

[0686] The event support system in this invention efficiently plans, coordinates, and prepares events by having multiple functional units.

[0687] First, the user enters basic event information via their device. This information includes the event name, date and time, location, number of participants, and budget. Once this data is entered from the device, the information retrieval unit collects the data and sends it to the server.

[0688] The server processes the data received from the information acquisition unit in the analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This makes it possible to create an optimal to-do list based on lessons learned from past cases.

[0689] Next, the server uses the to-do list generation unit to generate a list of specific preparation tasks for the user. This list covers all the steps necessary for the event to succeed and provides the user with clear guidance.

[0690] Furthermore, the service proposal department searches for available services in and around the event venue (e.g., catering, venue setup, decoration companies, etc.). The server then proposes appropriate services based on the characteristics of the user's event.

[0691] In parallel, the server uses the design generation unit to build design templates for event announcements. Users can customize these templates and select the design that best suits their event.

[0692] In the budget management section, the server calculates and presents recommended funding allocations based on the entered budget. This function allows users to plan events to stay within budget.

[0693] Once all proposals and selections are complete, the user performs a final confirmation via their terminal. The user's decisions are stored in a database by the server's results storage unit. This data is used not only for managing ongoing events but also for planning future events.

[0694] As a concrete example, consider a scenario where a user plans a relative's wedding at a hotel in a certain area. The user enters the date, time, location, number of guests, budget, etc., and the server references past wedding examples to suggest the most suitable preparation tasks and available services. It also provides invitation design suggestions and calculates the optimal allocation of funds within the budget. Once the user makes a final decision, the information is saved for future reference.

[0695] As described above, the present invention utilizes AI to automate various processes necessary for event planning, thereby supporting efficient and effective event management.

[0696] The following describes the processing flow.

[0697] Step 1:

[0698] Users enter event information using a terminal. Input fields include event name, date and time, location, number of participants, and budget. This data is then transmitted from the terminal to the information retrieval unit.

[0699] Step 2:

[0700] The server receives input data from the user through the information acquisition unit. The received data is processed by the analysis unit, which identifies the event category based on the input content.

[0701] Step 3:

[0702] The server's analysis unit searches the database for data on similar past events and begins the analysis. This analysis identifies a suitable to-do list template for the event.

[0703] Step 4:

[0704] The server's to-do list generation unit creates a list of preparation tasks for the user based on the analysis results. This list provides detailed guidelines for event preparation.

[0705] Step 5:

[0706] The server's service proposal department searches the database for available services around the event venue. Based on the characteristics of the event, it proposes suitable service providers to the user.

[0707] Step 6:

[0708] The server's design generation unit generates a design template for event announcements. Users can view this template via their terminal and customize it as needed.

[0709] Step 7:

[0710] The server's budget management system calculates and presents recommended funding allocations based on the budget information entered by the user. This allows the user to plan the optimal events within their budget.

[0711] Step 8:

[0712] The user reviews the to-do list, service proposals, design proposals, and budget plan provided by the server via their device. They make any necessary revisions and send their final decisions to the server.

[0713] Step 9:

[0714] The server's results storage unit saves the user's final decision to the database. The saved data serves as reference data for progress management and future event planning.

[0715] (Example 1)

[0716] 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".

[0717] Current event planning support systems often perform information gathering, analysis, task generation, service proposals, and budget management tasks individually, making efficient and integrated event management difficult. Furthermore, there is a lack of effective ways to leverage best practices from similar past events. Therefore, there is a need for a method to comprehensively optimize event planning and preparation.

[0718] 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.

[0719] In this invention, the server includes means for an information gathering unit to receive event information from a user terminal, means for an analysis function unit to perform analysis based on past similar event information, and means for a task list generation unit to generate a task list for the event based on the analysis results. This makes it possible to integrate everything from efficient information gathering to task generation, service proposals, and budget control throughout the entire process of an event.

[0720] The "Information Gathering Department" is the department responsible for receiving event-related data from user terminals.

[0721] The "Analysis Function Department" is a department that has the function of searching for and analyzing past similar event information based on the received event data.

[0722] The "Task List Generation Unit" is a department that generates task lists for events based on the analysis results obtained from the Analysis Function Unit.

[0723] The "Service Recommendation Department" is a department that searches for surrounding facilities of event venues and makes recommendations based on that information.

[0724] The "Design Generation Department" is the department responsible for creating design templates for event notices and other promotional materials.

[0725] The "Budget Adjustment Department" is a department whose function is to propose recommended funding allocations based on the designated expenditure plan.

[0726] The "Results Storage Department" is the department responsible for storing user decisions on storage media.

[0727] The event support system of this invention efficiently and comprehensively plans, coordinates, and prepares events. The system consists of a terminal used by the user and a server having multiple functional units.

[0728] First, the user enters basic information such as the event name, date and time, location, number of participants, and budget into the terminal. The terminal converts this information into a data format and sends it to the server. The server's information collection unit receives this data.

[0729] The received data is processed by the server's analysis unit. The analysis unit searches the database for similar past event data and performs analysis. This process utilizes database management systems such as MySQL and natural language processing technology.

[0730] Based on the analysis results, the task list generation unit generates a list of specific preparation tasks. The task list is automatically generated using algorithms written in languages ​​such as Python or Java.

[0731] The server's service recommendation section suggests surrounding services tailored to the characteristics of the event. It uses Google APIs and third-party APIs to gather information about services within the region and provide users with the most suitable options.

[0732] The design generation unit utilizes design software such as Adobe XD and Canva to generate design templates for event-related notices. Users can customize these templates.

[0733] The budget adjustment department provides recommended funding allocations based on the budget specified by the user. It uses Excel or Google Sheets to calculate and provide the optimal allocation plan to the user.

[0734] After all proposals and selections are complete, the user makes a final confirmation via their terminal, and the decisions are saved in the results storage unit and used for future event planning.

[0735] As a concrete example, consider a scenario where a user plans a birthday party for a close friend at a local hall. The user enters the date, time, location, number of guests, and budget. The server then references past birthday party examples and suggests the most suitable task list and services. It also provides invitation design suggestions and optimizes budget allocation. After the user makes a final decision, the information is saved for future reference.

[0736] An example of a prompt using a generative AI model is, "Please suggest the optimal task list based on successful past events of a similar type."

[0737] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0738] Step 1:

[0739] Users input basic information such as the event name, date and time, location, number of participants, and budget via their terminal. This input information is converted into a data structure such as JSON and sent to the server. The terminal validates the input data through the user interface to check for any missing or incorrect information.

[0740] Step 2:

[0741] The server's information gathering unit receives data from terminals and stores it in its internal database. During this process, the server checks data integrity and converts the format as needed. The event information received as input is then used in subsequent analysis steps.

[0742] Step 3:

[0743] The server's analysis unit uses stored data to search the database for information on similar past events. The analysis unit executes SQL queries to extract relevant past event data. The output is an analysis result based on the characteristics of the event.

[0744] Step 4:

[0745] The server uses a task list generation unit to generate an event preparation task list based on the analysis results. It utilizes a generation AI model and prompts to enumerate appropriate tasks. The output is a specific task list, including tasks such as creating invitations, arranging the venue, and preparing decorations.

[0746] Step 5:

[0747] The server's service recommendation section searches for services around the event location via an API and provides service options relevant to the user's event. The input is the user's event characteristics, and the output is a list of services such as catering and venue setup.

[0748] Step 6:

[0749] The design generation unit uses a generation AI model to create design templates for event announcements. Using prompts, it generates design proposals that match the event theme and provides them to the user. The output is a customizable design template.

[0750] Step 7:

[0751] The budget adjustment department proposes item-specific funding allocations based on the budget entered by the user. It receives budget information as input and performs calculations using Excel or Google Sheets. The output is the recommended budget allocation for each task.

[0752] Step 8:

[0753] Users review all suggestions via their terminal, edit them as needed, and then make their final decision. The final selection is sent to the server and stored in a database by the results storage unit. This information is also used as reference data for future event planning.

[0754] (Application Example 1)

[0755] 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".

[0756] In traditional event planning, it is difficult to efficiently integrate and manage the various tasks and services related to an event, and there are particular challenges in optimizing the selection of food delivery services and budget management. As a result, the overall preparation of an event can become complicated, sometimes resulting in unnecessary time and costs.

[0757] 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.

[0758] In this invention, the server includes an information acquisition unit that receives information about an arbitrary event from a user terminal, an analysis unit that searches for and analyzes past similar event information based on the information about the event, and a to-do list generation unit that generates an action list for the event based on the analysis results of the analysis unit. This makes it possible to optimize tasks related to the event and propose an efficient food delivery service.

[0759] The "Information Acquisition Unit" is responsible for receiving event-related information from the user's terminal and transmitting it to the server.

[0760] The "Analysis Unit" provides the functionality to search for data based on information about received events and analyze past similar events.

[0761] The "TODO list generation unit" is a device that creates an action list for an event based on the analysis results from the analysis unit.

[0762] The "Service Proposal Department" is a system that searches for available services around the event venue and provides users with the most suitable suggestions.

[0763] The "Design Generation Unit" is a device that has the function of creating and providing event announcement materials with a structure template.

[0764] The "Budget Management Department" is a system that calculates and presents the optimal allocation of funds to the user based on the designated funds.

[0765] The "results storage unit" is a device that stores the user's decisions in a memory area for future reference and event management.

[0766] A "proposal generation module" is a device that has the function of selecting the most suitable supply service based on the user's input information and providing it to the user.

[0767] The system that realizes this invention consists of a server with multiple functional units and a user terminal. First, the user uses the terminal to input information about the event. This information includes the event title, date and time, location, number of participants, and budget. The information acquisition unit receives this data and transmits it to the server. Based on the received information, the server's analysis unit searches for information on similar past events and performs analysis.

[0768] Based on the analysis results, the TODO list generation unit generates an action list for the event and displays it on the terminal. The service proposal unit searches for available services around the event location and makes the best proposal to the user. The design generation unit creates a template for the announcement materials, allowing users to customize it. The budget management unit calculates the optimal fund allocation based on the entered funds and displays it to the user.

[0769] This entire process utilizes cloud services such as Google Cloud Platform and AWS, and leverages cloud-based memory storage for the database. Python and R are used for data analysis, and machine learning algorithms like scikit-learn and TensorFlow are implemented. Finally, the results storage unit stores the user's decisions in memory for future reference and event management.

[0770] As a concrete example, consider a scenario where a user plans a party for 20 people with a budget of 50,000 yen. In this case, once the user inputs the information, the server can suggest the optimal food delivery options based on past party data and indicate how to allocate funds within the budget. An example of an input prompt to the generating AI model would be, "Please tell me the best food delivery options for a party of 20 people that cost under 50,000 yen."

[0771] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0772] Step 1:

[0773] The user inputs event information from the terminal. This information includes the event title, date and time, location, number of participants, and budget. The terminal sends this data to the information acquisition unit, which then prepares the basic data for the next processing step.

[0774] Step 2:

[0775] The server's information acquisition unit receives event information sent from the terminal. This received data is then passed to the analysis unit. The analysis unit is connected to a database and uses this information as input to search for similar past event information. It retrieves relevant data from the database and performs the analysis.

[0776] Step 3:

[0777] The analysis unit searches past event data based on the received data and performs analysis using machine learning algorithms. In this process, TensorFlow is used to model past data patterns and identify events with high similarity. As output, the analysis results of similar events are generated and provided to the TODO list generation unit.

[0778] Step 4:

[0779] The TODO list generation unit receives analysis results from the analysis unit and generates an action list for the event based on them. This process uses a Python script to automatically create the list and adjust it to include the most effective steps for the user. The generated list is output to the terminal and presented to the user.

[0780] Step 5:

[0781] The server's service suggestion section searches for and suggests available supply services near the event location. It obtains geographical information using the Google Maps API and other tools, and evaluates third-party service providers. The input is the user's event information, and the output provides the user with a list of the most suitable services.

[0782] Step 6:

[0783] The Design Generation Department creates structure templates for event announcement materials. This department utilizes the Adobe Creative Cloud API to build flexible templates that users can customize. The resulting templates are visually appealing to users.

[0784] Step 7:

[0785] The budget management department calculates recommended funding allocations based on the user's entered budget limit. It combines machine learning algorithms and linear optimization to optimize the user's spending for the most effective use of funds. The calculation results are presented to the user to assist in event planning.

[0786] Step 8:

[0787] Finally, the results storage unit saves the user's decisions to a memory area. The saved data is managed in cloud-based data storage and used as a reference for future event planning and progress management. The input is the user's final confirmation information, and the output data is stored in a database.

[0788] 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.

[0789] This invention combines a system that supports event planning, preparation, and operation with an emotion engine that recognizes user emotions. This system integrates multiple functional units, enabling flexible and efficient event preparation according to user needs.

[0790] The user first enters event information using a terminal. This information includes the event name, date and time, location, number of participants, and budget. This information is sent from the terminal to the information retrieval unit and stored in the database on the server.

[0791] The analysis unit on the server searches for similar past events based on the input information and creates an optimal to-do list template. During this process, an efficient event progression is planned based on the analysis results of past data.

[0792] Furthermore, the service proposal department searches for available services around the event venue and proposes them to the user. This allows for the rapid selection of necessary vendors and services. In addition, the design generation department provides design templates for promotional materials, which can be customized to the user's needs.

[0793] The budget management department calculates the optimal allocation of funds within the budget and presents recommended plans to prevent unplanned expenses. Users review these proposals via their devices and make final decisions.

[0794] The emotion engine recognizes emotions from the user's device through voice and text. Based on this recognition, it makes additional suggestions regarding the atmosphere and theme of the event. For example, if the user prefers a relaxed atmosphere, services with such themes will be prioritized. Furthermore, by promoting the customization of designs and services based on the user's emotions, optimization tailored to individual needs is possible.

[0795] Throughout the entire process, users can use their devices to create, refine, and manage comprehensive event plans while receiving feedback from the emotion engine. This reduces the burden on users and ensures highly satisfying events.

[0796] For example, when a user is preparing for a wedding on their device, the emotion engine might analyze the user's mood and recommend a relaxed, casual wedding. The server then reflects this result, suggesting services and designs that fit the casual theme, and the budget management department presents the optimal allocation of funds within that framework. In this way, the user can smoothly prepare an event that matches their mood.

[0797] The following describes the processing flow.

[0798] Step 1:

[0799] Users enter basic event information into a form from their device. This information includes the event name, date and time, location, number of participants, budget, and a brief description or preference.

[0800] Step 2:

[0801] The terminal transmits the input information to the information acquisition unit. The information acquisition unit prepares to transmit this information to the server.

[0802] Step 3:

[0803] The server's analysis unit searches the database for similar past event data based on event information received from the information acquisition unit. Simultaneously, it analyzes this similar data to create a to-do list template for optimal event management.

[0804] Step 4:

[0805] The server uses a service suggestion unit to detect and suggest vendors and services available in the vicinity of the event venue. This includes catering, decorations, sound services, and more.

[0806] Step 5:

[0807] The design generation unit runs on a server and generates design proposals for event-optimized announcements. Templates are provided so that users can select options for personalization.

[0808] Step 6:

[0809] The server's budget management unit calculates and presents recommended cost allocations for each element of an event based on the budget data entered by the user. This helps users avoid unplanned expenses.

[0810] Step 7:

[0811] The emotion engine analyzes the user's emotions using voice and text data from the device and reports the results to the server. Based on these results, the server provides suggestions for customizing the event's theme and atmosphere.

[0812] Step 8:

[0813] The user reviews the to-do list, service proposals, design proposals, budget allocations, and additional sentiment-based suggestions provided by the server on their device. They then apply any necessary step-up revisions and make final decisions.

[0814] Step 9:

[0815] The server's results storage unit saves the user's final decision information to a database. This saved data is used for managing events in progress and as a reference for planning future events.

[0816] (Example 2)

[0817] 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".

[0818] In modern society, efficiently planning and running events is a time-consuming and laborious task. In particular, preparing for the event, selecting appropriate services, managing the budget, and customizing to meet the needs of new participants are all challenging. Furthermore, considering participants' emotions and creating an appropriate atmosphere and design for the event is not easy. There is a need to integrate and solve these complex elements within a single system.

[0819] 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.

[0820] In this invention, the server includes an information acquisition unit that receives information about activities from a user terminal, an analysis unit that searches for and analyzes similar past activity data based on the information about the activities, and an emotion recognition unit that recognizes the user's emotional state based on voice or text data. This enables users to plan and manage personalized events based on emotional data, resulting in efficient and highly satisfying event implementation.

[0821] The "Information Acquisition Department" is the department responsible for receiving event-related information from user terminals.

[0822] The "Analysis Department" is a department that has the function of searching and analyzing past similar activity data based on the information received about the activity.

[0823] The "TODO List Generation Department" is a department that generates a to-do list summarizing the tasks necessary for the progress of an event, based on the analysis results from the Analysis Department.

[0824] The "Service Proposal Department" is a department responsible for searching for services available in the vicinity of the event venue and making appropriate suggestions to users.

[0825] The "Design Generation Department" is a department that creates design templates for event announcements and allows users to customize them.

[0826] The "Budget Management Department" is a department responsible for proposing the optimal allocation of funds necessary for an event based on the designated budget.

[0827] The "emotion recognition unit" is a department that has the function of recognizing the user's emotional state based on voice or text data.

[0828] The "Result Storage Department" is the department responsible for saving the final content decided by the user to a storage device.

[0829] This invention utilizes an integrated system via user terminals, a server, and a network to streamline event planning and management. Users input detailed event information via their user terminals, and this information is quickly transmitted to the server. Multiple functional units within the server perform advanced data processing based on the received information, providing users with various suggestions and adjustments.

[0830] The server retrieves data entered by users through the information acquisition unit and stores it in the database as structured data. The analysis unit searches for similar past event data based on the stored information and performs analysis using machine learning algorithms. The technologies used for this include data analysis libraries in Python and R.

[0831] Based on the analysis results, the to-do list generation unit generates a to-do list to plan the efficient progress of the event. This allows the user to properly understand the event's steps.

[0832] Next, the server's service suggestion unit uses external API services to search for available vendors and services around the event venue and suggests the best options to the user. This could include, for example, suitable catering or decoration vendors. Common APIs used for this purpose include those from general map service providers.

[0833] The design generation unit creates design templates for announcements based on user requests. Using Adobe Creative Cloud APIs, it can provide customizable initial designs. Users can preview and optimize the designs through a designated interface on their device.

[0834] The emotion recognition unit acquires voice and text data to analyze the user's emotions and recognizes their emotional state using natural language processing (NLP) technology. Based on this information, suggestions are made that are tailored to the atmosphere and theme of the event the user desires. For example, if the user wants a relaxed event, the appropriate background music and lighting settings will be prioritized.

[0835] As a concrete example, when a user is preparing for a wedding, the system refers to past data and suggests a relaxed, casual wedding plan. The user enters a prompt such as, "I want to plan a relaxed wedding," and the AI ​​provides specific suggestions tailored to that need. In this way, users can efficiently plan and manage an event that aligns with their emotions through a series of processes.

[0836] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0837] Step 1:

[0838] The user uses their device to enter detailed information about the event. Specifically, they enter data such as the event name, date and time, location, number of participants, and budget into an input form. Once this input is complete, the device packets this data and prepares it for transmission to the server.

[0839] Step 2:

[0840] The terminal sends the entered event information to the server. The information retrieval unit receives this data and stores it in the server's database. In this process, the received data is saved in a structured format using SQL queries. Based on the entered information, related fields are updated and new records are added.

[0841] Step 3:

[0842] The analysis unit on the server uses event information obtained from the database to search for similar past event data. Here, machine learning algorithms are used to identify relevant events and generate analysis results. This analysis uses metrics such as event success rate and participant satisfaction. The output provides a list of related past events and their analysis results.

[0843] Step 4:

[0844] The server's to-do list generation unit generates a list of specific tasks (to-do list) necessary for the event's progress, based on the analysis results from the analysis unit. This list may include items such as schedule confirmation, vendor arrangements, and decoration preparations. This generated to-do list is output in an easy-to-manage format (e.g., checklist format) and provided to the user.

[0845] Step 5:

[0846] The server's service suggestion unit uses an external API to search for appropriate services near the event venue. Geographic information of the venue is used as input, and a list of nearby services (e.g., catering, decorations) is obtained via the API. This result is then presented to the user.

[0847] Step 6:

[0848] The server's design generation unit generates event announcement design templates according to user requests. This process uses a design tool API to customize pre-configured templates. The output is a design file that the user can modify.

[0849] Step 7:

[0850] The server's emotion recognition unit analyzes the user's emotional state. User-provided voice and text data are used as input, and emotion analysis is performed using natural language processing techniques. As output, data related to the user's emotions is generated and reflected in relevant suggestions.

[0851] Step 8:

[0852] The user reviews, adjusts, and finalizes the event plan based on emotion recognition and various suggestions. This decision is then saved again to the database by the results storage unit. The saved information is used for future progress management and as a reference for planning new events.

[0853] (Application Example 2)

[0854] 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".

[0855] In planning and preparing events, users often need to select ideal themes and services while reviewing past data and budgets, but this process is complex and burdensome for users. Furthermore, customization based on users' own feelings and preferences is difficult, making it challenging to improve satisfaction.

[0856] 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.

[0857] In this invention, the server includes an information acquisition unit that receives information about events from a user terminal, an analysis unit that searches for and analyzes similar past event data based on the information about the event, and an emotion analysis unit that analyzes the user's voice and documents to recognize emotions. This makes it possible to provide an optimal event plan tailored to the user's emotions and preferences.

[0858] The "Information Acquisition Unit" is a module that receives input data related to events from the user's operating terminal.

[0859] The "Analysis Unit" is a component that searches for similar past event data based on event-related information obtained from users, and analyzes that information.

[0860] The "TODO List Generation Unit" is a unit that has the function of generating a task list for efficient event preparation based on the results of the analysis unit.

[0861] The "Service Proposal Department" is a section responsible for searching for services in the vicinity of the event venue and proposing appropriate services to users based on the results.

[0862] The "Design Generation Department" is a department that creates design templates for announcements necessary for events and has the function of allowing users to customize them according to their preferences.

[0863] The "Budget Management Department" is a department that supports economic planning by calculating and proposing recommended allocations of funds based on the designated budget.

[0864] The "Emotion Analysis Department" is a department that analyzes users' voice and document data to recognize and understand the emotions behind them.

[0865] The "Proposal Optimization Department" is a part of the team that utilizes the recognition results from the Sentiment Analysis Department to customize event themes and services according to the emotions of the users.

[0866] The "results storage unit" is a component that saves the user's final decisions to a data storage medium, allowing for future reference and use in planning future events.

[0867] This invention is a system that efficiently supports event planning and execution. Based on event information entered by the user, this system analyzes similar past data and provides customized suggestions based on emotions. The user enters event information via a terminal, and this information is sent to the server. On the server, the information acquisition unit receives the data, and the analysis unit searches and analyzes past event data based on that information. Next, the to-do list generation unit creates an efficient task list based on the analysis results. Furthermore, the emotion analysis unit analyzes the voice and text data entered by the user to recognize the user's emotions. Based on these results, the suggestion optimization unit customizes and proposes appropriate event themes and services.

[0868] Users can review the proposed options and make a final decision. The budget management department optimizes the allocation of funds to each service according to the specified budget. The finalized information is saved to a data storage medium by the results storage department and can be used as a reference for planning future events.

[0869] This system utilizes speech recognition technology and data analysis algorithms. Speech recognition uses APIs such as Google Speech Recognition API, and machine learning models are employed for the analysis algorithms.

[0870] As a concrete example, consider a user planning a birthday party at home. The user voice-inputs the event details into the device, and based on sentiment analysis, a relaxed, casual theme is suggested. Following this suggestion, the design and services are customized, and the optimal budget allocation is shown to stay within budget. This allows the user to smoothly prepare an event perfectly tailored to their needs.

[0871] An example of a prompt message is, "Please plan a relaxed family birthday party. The budget is 100,000 yen."

[0872] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0873] Step 1:

[0874] Users input event information using a terminal. This includes the event name, date and time, location, number of participants, and budget. This input data is sent from the terminal to the server and received by the information retrieval unit.

[0875] Step 2:

[0876] The server's analysis unit searches the database for similar past events based on the received data. By analyzing the retrieved data, the foundation for a to-do list suitable for the current event is built. This process uses data mining algorithms to extract past cases similar to the input parameters.

[0877] Step 3:

[0878] The TODO list generation unit generates an efficient TODO list based on the analysis results. It uses the output of the analysis unit as input to compile the most suitable work items. This list is output to the user, showing the steps to proceed to the next stage.

[0879] Step 4:

[0880] The server's sentiment analysis unit recognizes emotions from the user's voice and text. This process involves acquiring voice data, converting it to text using the Google Speech Recognition API, and then performing sentiment analysis on the text. Machine learning algorithms are used here to output the user's expected emotional state.

[0881] Step 5:

[0882] The suggestion optimization unit optimizes and proposes event themes and services based on recognized emotions. It uses the emotion recognition results from the previous step as input, comparing them with event data to generate optimal suggestions. Users receive the customized theme and service suggestions on their devices.

[0883] Step 6:

[0884] The budget management department calculates the optimal allocation of funds to each service based on the specified budget. The user's specified budget and proposed service details are used as input, and the calculated budget allocation is output to the user. This process is performed using a linear programming algorithm.

[0885] Step 7:

[0886] The user makes a final decision and confirms it through their terminal. The user's decision is saved to a data storage medium in the server's results storage unit. This saved data can be used as reference for planning future events and managing progress.

[0887] 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.

[0888] 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.

[0889] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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."

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] 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.

[0908] The following is further disclosed regarding the embodiments described above.

[0909] (Claim 1)

[0910] The information acquisition unit has means for receiving event-related information from the user terminal,

[0911] The analysis unit has means for searching and analyzing past similar event data based on information about the aforementioned event,

[0912] The TODO list generation unit includes means for generating an event TODO list based on the analysis results of the analysis unit,

[0913] The service proposal department will search for and propose services in the vicinity of the event venue.

[0914] The design generation unit provides a means for creating design templates for event announcements,

[0915] The Budget Management Department has a means of proposing recommended funding allocations based on the designated budget,

[0916] The results storage unit includes means for saving the user's decisions to a database,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, wherein information about an event includes the event name, date and time, location, number of participants, and budget.

[0920] (Claim 3)

[0921] The system according to claim 1, wherein the final decisions stored in the database are used for progress management or as reference for planning the next event.

[0922] "Example 1"

[0923] (Claim 1)

[0924] The information gathering unit has a means of receiving event-related data from user terminals,

[0925] The analysis function unit includes means for searching for and analyzing past similar event information based on data related to the event,

[0926] The task list generation unit includes means for generating a task list for an event based on the analysis results of the analysis function unit,

[0927] The service recommendation department will search for and propose functions in the vicinity of the event venue.

[0928] The design generation unit provides a means for creating design templates for event notices,

[0929] The Budget Coordination Department has a means of proposing recommended funding allocations based on a designated expenditure plan,

[0930] The results storage unit includes means for storing the user's decisions on a storage medium,

[0931] A system that includes this.

[0932] (Claim 2)

[0933] The system according to claim 1, wherein the data relating to an event includes the event name, date and time, area, number of participants, and expenditure plan.

[0934] (Claim 3)

[0935] The system according to claim 1, wherein the final decisions stored on a storage medium are used for progress management or as reference for planning future events.

[0936] "Application Example 1"

[0937] (Claim 1)

[0938] The information acquisition unit has means for receiving information about arbitrary events from the user terminal,

[0939] The analysis unit has means for searching for and analyzing past similar event information based on the information about the event,

[0940] The TODO list generation unit includes means for generating an action list for events based on the analysis results of the analysis unit,

[0941] The service proposal department has a means of searching for and proposing services in the vicinity of the event venue.

[0942] The design generation unit provides a means for creating a structure template for event announcement materials,

[0943] The Budget Management Department has a means of presenting recommended funding allocations based on designated funds,

[0944] The results storage unit includes means for storing the user's decisions in a memory area,

[0945] The proposal generation module selects and provides the most suitable supply service for the user's event,

[0946] A system that includes this.

[0947] (Claim 2)

[0948] The system according to claim 1, wherein information about an event includes the event title, date and time, location, number of participants, and funding.

[0949] (Claim 3)

[0950] The system according to claim 1, wherein the final decision stored in the memory area is used for progress management or as a reference for planning the next activity.

[0951] "Example 2 of combining an emotion engine"

[0952] (Claim 1)

[0953] The information acquisition unit has means for receiving activity-related information from the user terminal,

[0954] The analysis unit has means for searching and analyzing past similar activity data based on the information regarding the aforementioned activity,

[0955] The TODO list generation unit includes means for generating a TODO list of activities based on the analysis results of the analysis unit,

[0956] The service proposal department has a means of searching for and proposing services in the vicinity of the activity location.

[0957] The design generation unit provides a means for creating design templates for activity announcements,

[0958] The Budget Management Department has a means of proposing recommended funding allocations based on the designated budget,

[0959] The emotion recognition unit includes means for recognizing the user's emotional state based on voice or text data,

[0960] The results storage unit includes means for storing the user's decisions in a storage device,

[0961] A system that includes this.

[0962] (Claim 2)

[0963] The system according to claim 1, wherein information about an activity includes the activity name, date, location, number of participants, and budget.

[0964] (Claim 3)

[0965] The system according to claim 1, wherein the final decision stored in the storage device is used as a reference for progress management or for planning the next activity.

[0966] "Application example 2 when combining with an emotional engine"

[0967] (Claim 1)

[0968] The information acquisition unit has means for receiving event-related information from the user terminal,

[0969] The analysis unit has means for searching and analyzing past similar event data based on information about the aforementioned event,

[0970] The TODO list generation unit includes means for generating an event TODO list based on the analysis results of the analysis unit,

[0971] The service proposal department will search for and propose services in the vicinity of the event venue.

[0972] The design generation unit provides a means for creating design templates for event announcements,

[0973] The Budget Management Department has a means of proposing recommended funding allocations based on the designated budget,

[0974] The emotion analysis department has developed a means to recognize emotions by analyzing the user's voice and documents,

[0975] The proposal optimization unit provides means for customizing event themes and services based on the recognition results of the sentiment analysis unit,

[0976] The results storage unit includes means for saving the user's decisions to a data storage medium,

[0977] A system that includes this.

[0978] (Claim 2)

[0979] The system according to claim 1, wherein information about an event includes the event name, date, location, number of participants, and budget.

[0980] (Claim 3)

[0981] The system according to claim 1, wherein the final decisions stored on a data storage medium are used for progress management or as reference for planning the next event. [Explanation of symbols]

[0982] 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. The information acquisition unit has means for receiving information about arbitrary events from the user terminal, The analysis unit has means for searching for and analyzing past similar event information based on the information about the event, The TODO list generation unit includes means for generating an action list for events based on the analysis results of the analysis unit, The service proposal department has a means of searching for and proposing services in the vicinity of the event venue. The design generation unit provides a means for creating a structure template for event announcement materials, The Budget Management Department has a means of presenting recommended funding allocations based on designated funds, The results storage unit includes means for storing the user's decisions in a memory area, The proposal generation module selects and provides the most suitable supply service for the user's event, A system that includes this.

2. The system according to claim 1, wherein information about an event includes the event title, date and time, location, number of participants, and funding.

3. The system according to claim 1, wherein the final decision stored in the memory area is used for progress management or as reference for planning the next activity.

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