system

Abstract

We provide the system. [Solution] A data input means for inputting time information of faculty and staff and spatial information of educational facilities, A calculation means that generates an optimal timetable and public facility usage plan based on the time information and spatial information input by the aforementioned data input means, A visualization means for displaying the information generated by the calculation means, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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 school management, multiple tasks such as class schedule management, budget allocation, and facility management have conventionally been often managed individually, and there has been a problem that a great deal of labor and time are required to efficiently perform each task. In particular, these tasks are often carried out manually, and human errors are likely to occur, which may cause a decline in the efficiency and quality of the entire school management. Therefore, there is a need to provide an effective means for centrally managing these complex tasks and achieving efficiency and optimization.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means. First, it provides an input means for inputting teacher time information and classroom spatial information to build a foundation for generating an efficient timetable. Next, it provides a calculation means for generating an optimal schedule based on this input data, and a display means for displaying the generated schedule so that users can visually confirm it. Furthermore, it provides a resource calculation means for inputting information on the allocation of available resources, analyzing that information, and calculating optimization, and an information presentation means for presenting the results, thereby enabling efficient use of resources, including budget management. In addition, it provides a placement determination means for acquiring facility usage status information and maintenance information and determining the optimal placement, and a means for notifying the determined placement, thereby realizing optimization of facility management. In this way, it provides a system that efficiently manages multiple tasks necessary for school operation.

[0006] An "input means" is a device or interface for a user to input necessary information into a system.

[0007] A "computational means" refers to a processor or algorithm that generates optimal results or suggestions based on the input information.

[0008] "Display means" refers to a device or interface that visually displays the results generated by the calculation means so that the user can confirm them.

[0009] A "resource input means" is a device or interface for inputting the status of available resources into a system.

[0010] A "resource calculation means" is a processor or algorithm that analyzes data obtained through a resource input means and optimizes resource allocation.

[0011] An "information presentation means" is a device or interface for presenting calculated results or optimization proposals to the user.

[0012] "Information input means" refers to a device or interface for inputting facility usage status and maintenance information into a system.

[0013] The "placement determination means" is a processor or algorithm that determines the optimal placement of equipment based on the input facility information.

[0014] "Notification means" refers to a device or interface for notifying the user of the content determined by the placement determination means. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

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

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

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

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

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

[0023] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0036] This invention provides a system for achieving efficient operation in educational facilities, integrating time management for faculty and staff, optimal resource allocation, and monitoring of facility usage. Specific embodiments are described below in natural language.

[0037] This system consists of multiple computer devices used in educational institutions, primarily including a server and user terminals. The server runs programs with multiple functions. Users (e.g., school administrators) use terminals to input necessary information into the system, and this information is sent to the server.

[0038] First, users input faculty and staff time information and classroom spatial information via a terminal. The entered data is sent to a server, which then calculates the optimal timetable based on this information. The calculated timetable is displayed on the terminal's screen, allowing users to review it and make corrections as needed.

[0039] Furthermore, users input budget information and submit resource usage data to the server. The server analyzes the budget data, learns past spending patterns, and calculates the optimal resource allocation. Through this process, it proposes efficient management of available resources.

[0040] Furthermore, when users input information about school facilities and maintenance, the server analyzes this information and calculates the optimal placement based on the usage of the facilities. The server checks which parts of the facilities are being used appropriately and uses natural language processing to notify users of the need for maintenance.

[0041] For example, when class assignments need to be re-evaluated due to an increase in curriculum content at the start of a new school year, this system can be used to calculate the optimal assignment within existing resources, taking into account the schedules of all classrooms and teachers. In this way, the system provides teachers and staff with data to function efficiently, and users can easily review and modify the system to ensure smooth school operations.

[0042] This system enables users to perform complex administrative tasks related to the daily operation of educational institutions in an integrated and efficient manner, significantly reducing human error.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] Users use a terminal to input schedule information for faculty and staff at educational institutions, as well as classroom availability. This input includes the times when faculty and staff are available to teach and the availability of each classroom. Once input is complete, the terminal sends this information to the server.

[0046] Step 2:

[0047] The server analyzes the received schedule information and classroom usage data, comparing each faculty member's availability with the availability of classrooms. At this stage, it checks for data consistency to ensure there are no duplicates or inconsistencies.

[0048] Step 3:

[0049] The server runs an optimization algorithm based on consistent data to generate a timetable that shows which faculty member will teach which class and in which classroom. The optimization process also takes into account faculty preferences and the importance of each class.

[0050] Step 4:

[0051] The timetable generated by the server is sent to the terminal for the user to review. The user checks the displayed timetable and makes corrections as needed. These corrections determine the final confirmed timetable.

[0052] Step 5:

[0053] Users input budget information into their terminals and notify the server of data regarding resource allocation. The input data includes each department's budget and necessary expenses.

[0054] Step 6:

[0055] The server analyzes the entered budget data and compares it with past spending history to identify waste and areas for improvement. The server then uses a budget optimization algorithm to generate the most effective resource allocation plan.

[0056] Step 7:

[0057] The server calculates the optimal budget allocation plan and presents it to the user via the terminal. The user can then review the budget plan, make adjustments as needed, and finalize the budget.

[0058] Step 8:

[0059] Users input information about the usage and maintenance status of school facilities into a terminal and send it to the server. This includes information such as the operational status and maintenance history of the facilities.

[0060] Step 9:

[0061] The server performs calculations based on equipment information to propose the optimal placement and necessary maintenance. The server considers equipment usage frequency and maintenance schedules to generate specific recommendations.

[0062] Step 10:

[0063] The server-generated proposals are displayed on the terminal and viewed by the user. The user reviews the proposals and finalizes the equipment layout and maintenance plan.

[0064] In this way, the entire system operates efficiently, allowing the complex tasks of school management to be managed smoothly.

[0065] (Example 1)

[0066] 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."

[0067] While educational institutions require integrated management of faculty and staff time, resource allocation, and facility utilization, traditional methods have struggled to optimize these elements efficiently and accurately. In particular, human error and the dispersion of information have hindered effective resource utilization and schedule optimization.

[0068] 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.

[0069] In this invention, the server includes an input means for inputting information about the time of faculty and staff and information about the educational space, a calculation means for generating an optimal time allocation, and a presentation means for displaying the generated time allocation. This enables the optimization of faculty and staff schedules, efficient allocation of resources, and effective management of facilities.

[0070] "Information regarding the time spent by faculty and staff" refers to data concerning the working hours and schedules of teachers and staff within educational institutions.

[0071] "Information regarding educational spaces" refers to data on the use and layout of spaces in educational facilities such as classrooms and equipment.

[0072] "Input means" refers to a device or function that acts as an interface or device for taking information into a system.

[0073] A "computational means" is a function or device that performs calculations or analyses based on the received data.

[0074] "Presentation means" refers to a device or function for visually or audibly communicating the calculated or analyzed results to the user.

[0075] "Optimal time allocation" refers to the time allocation that most efficiently arranges the schedules of faculty and staff under given conditions.

[0076] "Resource information" refers to data regarding the quantity and status of physical and human resources available within an educational institution.

[0077] "Analysis tools" refer to functions or devices used to organize input data and determine the most effective way to utilize it through various processes.

[0078] "Display means" refers to a visible method or device for informing the user of the results of a calculation or analysis.

[0079] "Information regarding usage and maintenance" refers to data on the current utilization status of spaces and equipment within the facility and the need for their maintenance.

[0080] A "decision-making tool" is a function or device for selecting the most suitable option from various choices and making a decision in a feasible manner.

[0081] "Means of communication" refers to means or devices for conveying the decided results to users or related organizations.

[0082] This invention is a system aimed at improving the operational efficiency of educational institutions. The system consists of a server and terminals used by multiple users. The server comprehensively analyzes various data owned by the educational institution and proposes optimal time allocation, resource allocation, and facility placement.

[0083] The server first receives information about faculty and staff time and educational space entered by users via terminals. This information is then analyzed using an optimization algorithm based on the Python programming language. During the calculation process, the Pandas data analysis library and Tableau visualization tool are used to optimize time allocation and resource utilization.

[0084] Users input resource information, including budget and equipment details, via a terminal. The server uses this information to analyze past expenditure data with Pandas and calculate the most efficient resource allocation. For facility usage and maintenance information, the server uses the natural language processing library NLTK to evaluate optimal placement and maintenance needs.

[0085] As a concrete example, this system can be used to optimize classroom usage throughout the school at the start of a new academic year. Users simply input the available time for each classroom and the free time of teachers and staff, and the server calculates possible timetables and proposes the most efficient schedule. Multiple timetable options are displayed on the terminal, allowing users to easily review and adjust them.

[0086] An example of a prompt message to the generating AI model would be, "Based on the current classroom usage and teachers' schedules, please calculate the optimal timetable for the new academic year. In particular, please concentrate math classes on weekday afternoons." By inputting such a message, the system can create an optimized schedule.

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] Users use a terminal to input information about faculty and staff time and educational space. The server then receives this input data. Based on this input data, the server uses Python to organize the data and generate the basic dataset necessary for calculating timetables. This process is initiated by the user's specific action of inputting the schedules of specific classrooms and teachers.

[0090] Step 2:

[0091] The server runs an optimization algorithm using the received data. The algorithm processes the input data using the Pandas data analysis library and simulates possible timetable arrangement patterns. This computational process determines the most efficient time allocation. The output generates a provisional timetable and the optimal classroom arrangement. The server returns this to the terminal, preparing it for presentation to the user.

[0092] Step 3:

[0093] The user reviews the proposed timetable presented on the terminal and makes modifications as needed. For example, they might move a specific class to the afternoon. Based on this modification input, the server performs optimization calculations again and generates a new, revised timetable. This feedback loop allows the user to obtain an efficient and customized schedule. This operation is achieved through the user's concrete actions of updating information by manipulating the terminal's interface.

[0094] Step 4:

[0095] The server processes resource utilization data based on user input. Using this pre-processed data, the server learns past budget and resource usage patterns and calculates the optimal budget allocation. The output is a detailed analysis report on how resources can be allocated. This result is displayed to the user via their terminal, allowing them to utilize it for operational purposes.

[0096] Step 5:

[0097] Users input facility usage and maintenance information into a terminal. Based on this information, the server uses natural language processing technology to optimize facility placement and assess maintenance needs. The final output is a report recommending the optimal equipment placement and maintenance plan. Users can review this information and incorporate it into the physical management of their educational facilities.

[0098] (Application Example 1)

[0099] 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."

[0100] In educational and public facilities, the complex schedules of teachers, staff, and users make efficient time management and facility operation difficult. Furthermore, the allocation of physical resources and budget management are often inadequate, leading to waste. Additionally, insufficient management of facility usage and maintenance reduces the efficiency of equipment utilization. Addressing these challenges and optimizing overall facility operations is essential.

[0101] 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.

[0102] In this invention, the server includes data input means for inputting time information of faculty and staff and spatial information of educational facilities; calculation means for generating an optimal timetable and public facility utilization plan based on the time information and spatial information input by the data input means; and visualization means for displaying the information generated by the calculation means. This enables the creation of efficient personnel schedules and optimal use of facilities.

[0103] "Data input means" refers to a device or interface for inputting temporal and spatial information of faculty and staff in educational facilities.

[0104] "Computation means" refers to a processor or algorithm for creating an optimal timetable and facility usage plan based on input time and spatial information.

[0105] "Visualization means" refers to a display device or software that displays the timetable or usage plan generated by the calculation means in an easy-to-understand manner for the user.

[0106] An "input method" is an interface for entering necessary data about facilities and budgets into the system.

[0107] "Analysis means" refers to a function that analyzes information obtained from input means and calculates efficient budget management and physical resource allocation.

[0108] "Information provision means" refers to a medium or device for providing the distribution information calculated by the analysis means to the user.

[0109] "Data acquisition means" refers to sensors and data collection systems used to gather information on facility usage and maintenance.

[0110] A "decision-making tool" is an algorithm used to determine the optimal placement of equipment and whether maintenance is necessary, based on the collected data.

[0111] "Communication means" refers to communication devices or networks used to inform users or administrators of information determined by the decision-making means.

[0112] This invention is a system designed to improve the operational efficiency of educational and public facilities. The system primarily consists of a server and multiple terminals. Users can input time information, budget information, and facility usage status for faculty and staff through these terminals.

[0113] The server runs Python programs and provides a web browser interface as a means of data input. Information sent from terminals is aggregated on the server and analyzed by machine learning algorithms utilizing Scikit-learn. Based on the analyzed data, the server calculates the optimal schedule, resource allocation, and equipment placement.

[0114] The calculated results are visualized by the server via a web application using the Django framework. This visualization allows users to view the results on their device screen and make corrections or updates as needed.

[0115] Furthermore, the NLTK library is used for natural language processing, and if equipment maintenance is required, a notification will be sent in natural language. This notification will be delivered to the user via email or applications on the terminal.

[0116] As a concrete example, when a school in a smart city reviews its class schedule for the new academic year, the server optimizes the class timetable based on existing data. This allows for the maximum utilization of available classrooms and faculty time.

[0117] An example of a prompt message might be: "Generate proposals to optimize the operational efficiency of school facilities throughout the smart city. Consider resource sharing between different schools and the allocation of class time."

[0118] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0119] Step 1:

[0120] Users input data such as faculty and staff time information and educational facility spatial information using a terminal. The terminal then sends this data to a server via a dedicated web application. The input data is structured in CSV or JSON format and stored on the server.

[0121] Step 2:

[0122] The server preprocesses the received data. This primarily involves data manipulation, such as imputing missing values ​​and normalizing the data, to prepare it for use with machine learning algorithms. The processed data is then passed on to the next analysis process.

[0123] Step 3:

[0124] The server executes machine learning algorithms using Scikit-learn based on the formatted data. In this step, statistical analysis is performed based on historical schedule data and usage patterns to generate an optimal timetable and resource utilization plan. The calculated results are stored on the server as timetable data.

[0125] Step 4:

[0126] The server displays the generated timetable using a visualization system based on the Django framework. Users can view the visualized timetable via their terminal and make modifications as needed. This visualization uses an interactive GUI, making it easy to use.

[0127] Step 5:

[0128] If a user enters additional information regarding equipment usage or maintenance, the server uses NLTK-based natural language processing to generate necessary maintenance notifications. This information is sent through the notification system and presented to the user via email or app notifications.

[0129] Step 6:

[0130] Finally, users can download or export all results from their device in a printable format. This output is provided in PDF or Excel spreadsheet format, facilitating further analysis and sharing.

[0131] 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.

[0132] This invention is a system used to improve efficiency in the management of educational facilities. It combines a function to create an optimal timetable based on faculty and staff time information and classroom usage status with an emotion engine that recognizes user emotions. The system aims to provide a better environment through interaction with faculty, staff, and students.

[0133] This system primarily consists of a server and terminals, with users inputting information through the terminals. For example, users input faculty and staff class schedules and classroom reservation status, and this information is sent to the server. The server analyzes this information and generates an optimal timetable that takes into account faculty and staff schedules and classroom availability. The generated timetable is displayed on the terminal, which users can review and modify as needed.

[0134] Furthermore, the present invention incorporates an emotion engine that can recognize the user's emotional state in real time. This emotion engine analyzes voice and facial expression data acquired through interaction with the user to determine the current emotional state. As a result, the server can provide appropriate information and interface settings according to the user's emotions.

[0135] For example, if the emotion engine determines that a user is experiencing fatigue or stress during the timetable creation process, the server will provide a more comfortable operating environment by changing the interface's color scheme to a calmer tone or displaying encouraging messages. This improves user efficiency and makes it possible to support school operations more smoothly.

[0136] This system utilizes the same emotion engine in budget management and equipment management, supporting users in working most efficiently and comfortably. As a result, the overall operation of the educational facility is improved, and an environment is provided where users can perform their duties comfortably through the system.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] Users input faculty and staff time information and classroom space information from their terminals. This information includes each faculty member's available teaching time, classroom reservation status, and educational curriculum. Once input is complete, the terminal sends this data to the server.

[0140] Step 2:

[0141] The server analyzes the received data and verifies the consistency of the temporal and spatial information. During this process, it checks for duplicate schedules and reservation statuses. If necessary, it may also send a correction request to the user.

[0142] Step 3:

[0143] The server runs an optimization algorithm using consistent data. The algorithm considers the preferences of faculty and staff and classroom usage to generate an efficient timetable. This result is then sent to the terminal.

[0144] Step 4:

[0145] The terminal displays the timetable sent from the server. The user can review the displayed timetable and make corrections as needed. If corrections are made, the updated data is sent back to the server via the terminal.

[0146] Step 5:

[0147] In parallel, the emotion engine acquires emotion data in real time during user interaction. This includes collecting changes in the user's facial expressions and voice through the camera and microphone. The device then sends the emotion analysis results to the server.

[0148] Step 6:

[0149] The server analyzes the received emotional data to understand the user's emotional state. If it determines that the user is experiencing stress, the server instructs the device to, for example, change the screen's color tone or send a relaxation message.

[0150] Step 7:

[0151] The terminal displays responses to the user to provide a comfortable experience, based on instructions from the server. This allows the system to adjust so that the user can work smoothly.

[0152] Through this series of processes, the system efficiently supports the operation of educational facilities and helps users work in a better environment.

[0153] (Example 2)

[0154] 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".

[0155] Educational facilities need to efficiently manage the time of faculty and staff and schedule classroom usage, but a lack of consideration for emotional factors makes it difficult to simultaneously enhance convenience and comfort. Furthermore, when optimizing facility use and resource allocation, the inability to provide adaptive information that takes into account the emotional state of users is a problem.

[0156] 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.

[0157] In this invention, the server includes an information input means for inputting employee time information and learning space usage information; an emotion analysis means for analyzing the user's emotional state and adjusting information presentation and interface based on the results; and a configuration determination means for determining the optimal configuration based on facility usage information and maintenance information. This enables an efficient and user-friendly operating environment for educational facilities.

[0158] "Information input means" refers to a device or method for collecting information on the time spent by employees and information on the use of learning spaces, and providing this information to a system.

[0159] "Data processing means" refers to a device or method for analyzing input information and generating an optimal schedule or resource allocation.

[0160] "Display means" refers to a device or method for visually showing the generated schedule or information to the user.

[0161] "Emotion analysis means" refers to a device or method that analyzes data such as a user's voice and facial expressions to determine their emotional state in real time.

[0162] An "adaptive presentation means" is a device or method for optimizing presented information and interfaces based on the user's emotional state to improve the user experience.

[0163] "Layout determination means" refers to a device or method that determines the optimal configuration and layout based on facility usage information and maintenance information.

[0164] "Notification means" refers to a device or method for informing the user of determined information or configuration.

[0165] This invention is a system that improves the efficiency of management operations and user comfort in educational facilities. This system mainly consists of a server and terminals.

[0166] Users input employee time information and learning space usage information using a terminal. The terminal formats this data and sends it to the server. The server generates an optimal schedule based on the received data. Specifically, the server uses an AI model to analyze the data and perform data processing to optimize schedules and resource allocation. This model learns from past data and derives the result that is best suited to the current conditions.

[0167] The generated schedules and information are presented to the user via the device's display. The displayed information is visually easy to understand, allowing the user to easily review and modify it as needed.

[0168] Furthermore, the server uses emotion analysis to detect the user's emotional state. If the user is experiencing fatigue or stress, the adaptive presentation system adjusts the interface, such as changing the screen's color tone or displaying encouraging messages. This emotion analysis utilizes speech recognition and facial recognition technologies to provide accurate feedback while respecting user privacy.

[0169] For example, if a user requests to add a math class for the following week, the server analyzes the information and suggests the optimal time, taking into account classroom availability and the schedules of the instructors. Furthermore, if the user feels "a little tired," the server automatically changes the interface's color scheme to a more calming one.

[0170] An example of a prompt message would be, "Please create a new class schedule, taking into account the current booking status." In this way, the system can streamline the operation of educational facilities while providing a comfortable environment for users.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] This phase involves the user using a terminal to input employee time information and learning space usage information. The terminal's input interface has a predefined form format, into which the user enters the necessary information. The entered data is converted into a structured format and prepared for transmission to the server. The output is in a data format that can be sent to the server.

[0174] Step 2:

[0175] This is the phase where the terminal sends input data to the server. The terminal uses the HTTPS protocol to send data to the server while ensuring data security. During this process, data transmission confirmation is performed, and once confirmation is received, the process proceeds to the next step. The output is the data received by the server.

[0176] Step 3:

[0177] This phase involves the server analyzing the received data and generating an optimal schedule. The server utilizes a generation AI model to analyze the input data and combine it with faculty schedules and available classroom information to calculate the best schedule. This calculation takes into account both past data and current conditions. The output is the generated optimal schedule.

[0178] Step 4:

[0179] This is the phase where the generated schedule is visually displayed to the user on their device. The information is presented on the device's display in an intuitively easy-to-understand format. The user can review it and, if necessary, make corrections from the device. The output is visual information for the user to review.

[0180] Step 5:

[0181] This is the phase in which the device collects user emotional data. Using voice input devices and cameras, the device records the user's voice tone and facial expressions in real time. This provides data to understand the user's emotional state. The output is the collected emotional data.

[0182] Step 6:

[0183] This phase involves the server analyzing emotional data using emotion analysis tools and adjusting the interface based on the results. The server uses machine learning algorithms to classify the user's emotional state. This allows the display and information presentation tools to be modified to best suit the user. The output is the adjusted interface.

[0184] These processes work together to form a system that enables efficient scheduling within educational facilities and provides users with a comfortable user experience.

[0185] (Application Example 2)

[0186] 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".

[0187] When timetables and resource allocation in educational institutions are not efficiently optimized, it can lead to increased burdens on faculty and students, and a deterioration of the educational environment. Furthermore, the lack of consideration for users' emotional states can amplify stress. Therefore, a system is needed that streamlines educational facility management while also considering the emotional well-being of users.

[0188] 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.

[0189] In this invention, the server includes an input means for inputting time information and classroom usage information of faculty and staff at educational institutions, a calculation means for generating an optimal timetable based on the information input by the input means, and an emotion recognition means for recognizing the user's emotional state. This enables the provision of an optimal educational environment in educational settings and the adjustment of the interface according to the user's emotions.

[0190] An "educational institution" is an organization or facility that provides education, and includes schools and universities.

[0191] "Teachers and staff" refers to educators and administrative staff working in educational institutions, and includes people involved in education and management.

[0192] "Time information" refers to data related to the schedules of classes and work for faculty, staff, and students.

[0193] "Classroom usage information" refers to data regarding the usage and availability of classrooms within educational facilities.

[0194] "Input means" refers to a device or software interface for inputting information into a system.

[0195] "Computational means" refers to software or hardware used for analysis and processing based on input data.

[0196] "Emotion recognition means" refers to technology that determines a user's emotional state from data such as voice and facial expressions.

[0197] "Display adjustment means" refers to a function that adjusts the appearance of the interface and the information presented according to the user's emotional state.

[0198] "Resource information input means" refers to a method or device for inputting data related to resource allocation and facility maintenance.

[0199] A "notification method" is a means of transmitting determined information from the system to the user.

[0200] The system that realizes this invention is an efficient system that integrates timetable management and emotion recognition in educational institutions. The program for this system runs mainly on servers and terminals and is constructed using technologies such as Python and React Native.

[0201] The server provides computing power to efficiently process time information and classroom usage information for faculty and staff at educational institutions. Time and usage information is input from client terminals, and the server analyzes this data to generate an optimal timetable. A Python program is used for data analysis and automatic timetable generation, and the generated timetable is displayed on the terminal.

[0202] Furthermore, the server uses emotion recognition to determine the user's emotions in real time from the voice and facial expression data they input. This emotion data is used to provide information tailored to the user's emotions. For example, using React Native, if it is determined that the user is feeling stressed, the interface's color scheme can be changed to softer colors, or an encouraging message can be displayed.

[0203] As a concrete example, suppose a student is using a timetable app during exam week, and the emotion recognition system detects that the student is stressed. In this case, the system displays a message such as, "Relax and prepare well. You can do it!" and changes the UI to a reassuring color scheme.

[0204] Examples of prompts include instructions such as, "Analyze students' emotions and display encouraging messages if they are stressed," and "Send the necessary data to the server to optimize the timetable." This improves the user experience and makes educational activities more effective and efficient.

[0205] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0206] Step 1:

[0207] The terminal receives time information for faculty and staff, as well as classroom usage information, from users. The entered information is converted into a format that can be stored in a database and sent to the server. This allows for efficient management of necessary data.

[0208] Step 2:

[0209] The server analyzes the received time and usage information in a database. This analysis process uses a Python script to perform calculations to generate the optimal timetable. An optimization algorithm is used to generate timetable suggestions. This output becomes a list of candidate timetables.

[0210] Step 3:

[0211] The server sends the generated timetable to the terminal and displays it on the terminal. The user can review this list of options and make corrections as needed. The terminal resends the user's corrections to the server, and the timetable is finalized.

[0212] Step 4:

[0213] The device acquires facial expression data through the user's voice and camera and sends it to a server. This data is processed by emotion recognition means to estimate the user's emotional state. In this step, the degree of relaxation and stress is identified in particular.

[0214] Step 5:

[0215] The server adjusts the interface to suit the user's emotional state based on the emotion recognition results. Specifically, it uses React Native to dynamically change the interface's color scheme and messages. This allows for a more comfortable user experience.

[0216] Step 6:

[0217] When a user uses the device again, it maintains its latest state and synchronizes with the server. This synchronization process is performed to reflect updates to the user's schedule and interface settings. This step ensures the integrity of the entire system.

[0218] 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.

[0219] 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.

[0220] 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.

[0221] [Second Embodiment]

[0222] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0223] 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.

[0224] 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).

[0225] 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.

[0226] 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.

[0227] 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).

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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".

[0234] This invention provides a system for achieving efficient operation in educational facilities, integrating time management for faculty and staff, optimal resource allocation, and monitoring of facility usage. Specific embodiments are described below in natural language.

[0235] This system consists of multiple computer devices used in educational institutions, primarily including a server and user terminals. The server runs programs with multiple functions. Users (e.g., school administrators) use terminals to input necessary information into the system, and this information is sent to the server.

[0236] First, users input faculty and staff time information and classroom spatial information via a terminal. The entered data is sent to a server, which then calculates the optimal timetable based on this information. The calculated timetable is displayed on the terminal's screen, allowing users to review it and make corrections as needed.

[0237] Furthermore, users input budget information and submit resource usage data to the server. The server analyzes the budget data, learns past spending patterns, and calculates the optimal resource allocation. Through this process, it proposes efficient management of available resources.

[0238] Furthermore, when users input information about school facilities and maintenance, the server analyzes this information and calculates the optimal placement based on the usage of the facilities. The server checks which parts of the facilities are being used appropriately and uses natural language processing to notify users of the need for maintenance.

[0239] For example, when class assignments need to be re-evaluated due to an increase in curriculum content at the start of a new school year, this system can be used to calculate the optimal assignment within existing resources, taking into account the schedules of all classrooms and teachers. In this way, the system provides teachers and staff with data to function efficiently, and users can easily review and modify the system to ensure smooth school operations.

[0240] This system enables users to perform complex administrative tasks related to the daily operation of educational institutions in an integrated and efficient manner, significantly reducing human error.

[0241] The following describes the processing flow.

[0242] Step 1:

[0243] Users use a terminal to input schedule information for faculty and staff at educational institutions, as well as classroom availability. This input includes the times when faculty and staff are available to teach and the availability of each classroom. Once input is complete, the terminal sends this information to the server.

[0244] Step 2:

[0245] The server analyzes the received schedule information and classroom usage data, comparing each faculty member's availability with the availability of classrooms. At this stage, it checks for data consistency to ensure there are no duplicates or inconsistencies.

[0246] Step 3:

[0247] The server runs an optimization algorithm based on consistent data to generate a timetable that shows which faculty member will teach which class and in which classroom. The optimization process also takes into account faculty preferences and the importance of each class.

[0248] Step 4:

[0249] The timetable generated by the server is sent to the terminal for the user to review. The user checks the displayed timetable and makes corrections as needed. These corrections determine the final confirmed timetable.

[0250] Step 5:

[0251] Users input budget information into their terminals and notify the server of data regarding resource allocation. The input data includes each department's budget and necessary expenses.

[0252] Step 6:

[0253] The server analyzes the entered budget data and compares it with past spending history to identify waste and areas for improvement. The server then uses a budget optimization algorithm to generate the most effective resource allocation plan.

[0254] Step 7:

[0255] The server calculates the optimal budget allocation plan and presents it to the user via the terminal. The user can then review the budget plan, make adjustments as needed, and finalize the budget.

[0256] Step 8:

[0257] Users input information about the usage and maintenance status of school facilities into a terminal and send it to the server. This includes information such as the operational status and maintenance history of the facilities.

[0258] Step 9:

[0259] The server performs calculations based on equipment information to propose the optimal placement and necessary maintenance. The server considers equipment usage frequency and maintenance schedules to generate specific recommendations.

[0260] Step 10:

[0261] The server-generated proposals are displayed on the terminal and viewed by the user. The user reviews the proposals and finalizes the equipment layout and maintenance plan.

[0262] In this way, the entire system operates efficiently, allowing the complex tasks of school management to be managed smoothly.

[0263] (Example 1)

[0264] 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."

[0265] While educational institutions require integrated management of faculty and staff time, resource allocation, and facility utilization, traditional methods have struggled to optimize these elements efficiently and accurately. In particular, human error and the dispersion of information have hindered effective resource utilization and schedule optimization.

[0266] 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.

[0267] In this invention, the server includes an input means for inputting information about the time of faculty and staff and information about the educational space, a calculation means for generating an optimal time allocation, and a presentation means for displaying the generated time allocation. This enables the optimization of faculty and staff schedules, efficient allocation of resources, and effective management of facilities.

[0268] "Information regarding the time spent by faculty and staff" refers to data concerning the working hours and schedules of teachers and staff within educational institutions.

[0269] "Information regarding educational spaces" refers to data on the use and layout of spaces in educational facilities such as classrooms and equipment.

[0270] "Input means" refers to a device or function that acts as an interface or device for taking information into a system.

[0271] A "computational means" is a function or device that performs calculations or analyses based on the received data.

[0272] "Presentation means" refers to a device or function for visually or audibly communicating the calculated or analyzed results to the user.

[0273] "Optimal time allocation" refers to the time allocation that most efficiently arranges the schedules of faculty and staff under given conditions.

[0274] "Resource information" refers to data regarding the quantity and status of physical and human resources available within an educational institution.

[0275] "Analysis tools" refer to functions or devices used to organize input data and determine the most effective way to utilize it through various processes.

[0276] "Display means" refers to a visible method or device for informing the user of the results of a calculation or analysis.

[0277] "Information regarding usage and maintenance" refers to data on the current utilization status of spaces and equipment within the facility and the need for their maintenance.

[0278] A "decision-making tool" is a function or device for selecting the most suitable option from various choices and making a decision in a feasible manner.

[0279] "Means of communication" refers to means or devices for conveying the decided results to users or related organizations.

[0280] This invention is a system aimed at improving the operational efficiency of educational institutions. The system consists of a server and terminals used by multiple users. The server comprehensively analyzes various data owned by the educational institution and proposes optimal time allocation, resource allocation, and facility placement.

[0281] The server first receives information about faculty and staff time and educational space entered by users via terminals. This information is then analyzed using an optimization algorithm based on the Python programming language. During the calculation process, the Pandas data analysis library and Tableau visualization tool are used to optimize time allocation and resource utilization.

[0282] Users input resource information, including budget and equipment details, via a terminal. The server uses this information to analyze past expenditure data with Pandas and calculate the most efficient resource allocation. For facility usage and maintenance information, the server uses the natural language processing library NLTK to evaluate optimal placement and maintenance needs.

[0283] As a specific example, when the new academic year begins, the entire school's classroom utilization can be optimized using this system. The user only needs to input the available time for each classroom and the free time of the faculty members, and the server calculates the possible class schedules and proposes the most efficient schedule. At this time, multiple schedule candidates are displayed on the terminal, and the user can easily check and adjust them.

[0284] As an example of the prompt text for the generative AI model, by inputting a sentence such as "Based on the current classroom utilization situation and the faculty schedule, calculate the optimal class schedule for the new academic year. In particular, concentrate the math classes in the afternoon on weekdays.", the system can create an optimized schedule.

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

[0286] Step 1:

[0287] The user uses the terminal to input information about the faculty time and educational space. As a result, the server receives the input data. Based on this input data, the server uses Python to organize the data and generate a basic dataset required for calculating the class schedule. This process is started by the user's specific action of inputting specific classrooms and faculty schedules.

[0288] Step 2:

[0289] The server executes an optimization algorithm using the received data. The algorithm uses the data analysis library Pandas to process the input data and simulate possible class schedule arrangement patterns. Through this calculation process, the most efficient time distribution is determined. As output, a provisional class schedule plan and an optimal arrangement of classrooms are generated. The server returns this to the terminal to prepare for presenting it to the user.

[0290] Step 3:

[0291] The user reviews the proposed timetable presented on the terminal and makes modifications as needed. For example, they might move a specific class to the afternoon. Based on this modification input, the server performs optimization calculations again and generates a new, revised timetable. This feedback loop allows the user to obtain an efficient and customized schedule. This operation is achieved through the user's concrete actions of updating information by manipulating the terminal's interface.

[0292] Step 4:

[0293] The server processes resource utilization data based on user input. Using this pre-processed data, the server learns past budget and resource usage patterns and calculates the optimal budget allocation. The output is a detailed analysis report on how resources can be allocated. This result is displayed to the user via their terminal, allowing them to utilize it for operational purposes.

[0294] Step 5:

[0295] Users input facility usage and maintenance information into a terminal. Based on this information, the server uses natural language processing technology to optimize facility placement and assess maintenance needs. The final output is a report recommending the optimal equipment placement and maintenance plan. Users can review this information and incorporate it into the physical management of their educational facilities.

[0296] (Application Example 1)

[0297] 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."

[0298] In educational and public facilities, the complex schedules of teachers, staff, and users make efficient time management and facility operation difficult. Furthermore, the allocation of physical resources and budget management are often inadequate, leading to waste. Additionally, insufficient management of facility usage and maintenance reduces the efficiency of equipment utilization. Addressing these challenges and optimizing overall facility operations is essential.

[0299] 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.

[0300] In this invention, the server includes data input means for inputting time information of faculty and staff and spatial information of educational facilities; calculation means for generating an optimal timetable and public facility utilization plan based on the time information and spatial information input by the data input means; and visualization means for displaying the information generated by the calculation means. This enables the creation of efficient personnel schedules and optimal use of facilities.

[0301] "Data input means" refers to a device or interface for inputting temporal and spatial information of faculty and staff in educational facilities.

[0302] "Computation means" refers to a processor or algorithm for creating an optimal timetable and facility usage plan based on input time and spatial information.

[0303] "Visualization means" refers to a display device or software that displays the timetable or usage plan generated by the calculation means in an easy-to-understand manner for the user.

[0304] An "input method" is an interface for entering necessary data about facilities and budgets into the system.

[0305] "Analysis means" refers to a function that analyzes information obtained from input means and calculates efficient budget management and physical resource allocation.

[0306] The "information providing means" is a medium or device for providing the distribution information calculated by the analysis means to the user.

[0307] The "data acquisition means" is a sensor or data collection system for collecting the usage status and maintenance information of facilities.

[0308] The "decision-making means" is an algorithm for determining the optimal placement of facilities and the necessity of maintenance based on the collected data.

[0309] The "communication means" is a communication device or network for notifying the information judged by the decision-making means to the user or administrator.

[0310] This invention is a system for improving the efficiency of operation in educational facilities and public facilities. This system is mainly composed of a server and a plurality of terminals. Through the terminal, the user can input the time information, budget information of teaching staff, and the usage status of facilities.

[0311] The server runs a Python program and provides an interface using a web browser as the data input means. The information transmitted from the terminal is aggregated by the server and analyzed by a machine learning algorithm utilizing Scikit-learn. Based on the analyzed data, the server calculates the optimal schedule, resource allocation, and facility placement.

[0312] The calculated results are visualized by the server through a web application using the Django framework. Through this visualization means, the user can check the results on the screen of the terminal and make corrections and updates as needed.

[0313] In addition, the NLTK library is used for natural language processing. When facility maintenance is required, a notification in natural language is sent. This notification is delivered to the user via the mail or application of the terminal as the communication means.

[0314] As a concrete example, when a school in a smart city reviews its class schedule for the new academic year, the server optimizes the class timetable based on existing data. This allows for the maximum utilization of available classrooms and faculty time.

[0315] An example of a prompt message might be: "Generate proposals to optimize the operational efficiency of school facilities throughout the smart city. Consider resource sharing between different schools and the allocation of class time."

[0316] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0317] Step 1:

[0318] Users input data such as faculty and staff time information and educational facility spatial information using a terminal. The terminal then sends this data to a server via a dedicated web application. The input data is structured in CSV or JSON format and stored on the server.

[0319] Step 2:

[0320] The server preprocesses the received data. This primarily involves data manipulation, such as imputing missing values ​​and normalizing the data, to prepare it for use with machine learning algorithms. The processed data is then passed on to the next analysis process.

[0321] Step 3:

[0322] The server executes machine learning algorithms using Scikit-learn based on the formatted data. In this step, statistical analysis is performed based on historical schedule data and usage patterns to generate an optimal timetable and resource utilization plan. The calculated results are stored on the server as timetable data.

[0323] Step 4:

[0324] The server displays the generated timetable using a visualization system based on the Django framework. Users can view the visualized timetable via their terminal and make modifications as needed. This visualization uses an interactive GUI, making it easy to use.

[0325] Step 5:

[0326] If a user enters additional information regarding equipment usage or maintenance, the server uses NLTK-based natural language processing to generate necessary maintenance notifications. This information is sent through the notification system and presented to the user via email or app notifications.

[0327] Step 6:

[0328] Finally, users can download or export all results from their device in a printable format. This output is provided in PDF or Excel spreadsheet format, facilitating further analysis and sharing.

[0329] 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.

[0330] This invention is a system used to improve efficiency in the management of educational facilities. It combines a function to create an optimal timetable based on faculty and staff time information and classroom usage status with an emotion engine that recognizes user emotions. The system aims to provide a better environment through interaction with faculty, staff, and students.

[0331] This system primarily consists of a server and terminals, with users inputting information through the terminals. For example, users input faculty and staff class schedules and classroom reservation status, and this information is sent to the server. The server analyzes this information and generates an optimal timetable that takes into account faculty and staff schedules and classroom availability. The generated timetable is displayed on the terminal, which users can review and modify as needed.

[0332] Furthermore, the present invention incorporates an emotion engine that can recognize the user's emotional state in real time. This emotion engine analyzes voice and facial expression data acquired through interaction with the user to determine the current emotional state. As a result, the server can provide appropriate information and interface settings according to the user's emotions.

[0333] For example, if the emotion engine determines that a user is experiencing fatigue or stress during the timetable creation process, the server will provide a more comfortable operating environment by changing the interface's color scheme to a calmer tone or displaying encouraging messages. This improves user efficiency and makes it possible to support school operations more smoothly.

[0334] This system utilizes the same emotion engine in budget management and equipment management, supporting users in working most efficiently and comfortably. As a result, the overall operation of the educational facility is improved, and an environment is provided where users can perform their duties comfortably through the system.

[0335] The following describes the processing flow.

[0336] Step 1:

[0337] Users input faculty and staff time information and classroom space information from their terminals. This information includes each faculty member's available teaching time, classroom reservation status, and educational curriculum. Once input is complete, the terminal sends this data to the server.

[0338] Step 2:

[0339] The server analyzes the received data and verifies the consistency of the temporal and spatial information. During this process, it checks for duplicate schedules and reservation statuses. If necessary, it may also send a correction request to the user.

[0340] Step 3:

[0341] The server runs an optimization algorithm using consistent data. The algorithm considers the preferences of faculty and staff and classroom usage to generate an efficient timetable. This result is then sent to the terminal.

[0342] Step 4:

[0343] The terminal displays the timetable sent from the server. The user can review the displayed timetable and make corrections as needed. If corrections are made, the updated data is sent back to the server via the terminal.

[0344] Step 5:

[0345] In parallel, the emotion engine acquires emotion data in real time during user interaction. This includes collecting changes in the user's facial expressions and voice through the camera and microphone. The device then sends the emotion analysis results to the server.

[0346] Step 6:

[0347] The server analyzes the received emotional data to understand the user's emotional state. If it determines that the user is experiencing stress, the server instructs the device to, for example, change the screen's color tone or send a relaxation message.

[0348] Step 7:

[0349] The terminal displays responses to the user to provide a comfortable experience, based on instructions from the server. This allows the system to adjust so that the user can work smoothly.

[0350] Through this series of processes, the system efficiently supports the operation of educational facilities and helps users work in a better environment.

[0351] (Example 2)

[0352] 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".

[0353] Educational facilities need to efficiently manage the time of faculty and staff and schedule classroom usage, but a lack of consideration for emotional factors makes it difficult to simultaneously enhance convenience and comfort. Furthermore, when optimizing facility use and resource allocation, the inability to provide adaptive information that takes into account the emotional state of users is a problem.

[0354] 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.

[0355] In this invention, the server includes an information input means for inputting employee time information and learning space usage information; an emotion analysis means for analyzing the user's emotional state and adjusting information presentation and interface based on the results; and a configuration determination means for determining the optimal configuration based on facility usage information and maintenance information. This enables an efficient and user-friendly operating environment for educational facilities.

[0356] "Information input means" refers to a device or method for collecting information on the time spent by employees and information on the use of learning spaces, and providing this information to a system.

[0357] "Data processing means" refers to a device or method for analyzing input information and generating an optimal schedule or resource allocation.

[0358] "Display means" refers to a device or method for visually showing the generated schedule or information to the user.

[0359] "Emotion analysis means" refers to a device or method that analyzes data such as a user's voice and facial expressions to determine their emotional state in real time.

[0360] An "adaptive presentation means" is a device or method for optimizing presented information and interfaces based on the user's emotional state to improve the user experience.

[0361] "Layout determination means" refers to a device or method that determines the optimal configuration and layout based on facility usage information and maintenance information.

[0362] "Notification means" refers to a device or method for informing the user of determined information or configuration.

[0363] This invention is a system that improves the efficiency of management operations and user comfort in educational facilities. This system mainly consists of a server and terminals.

[0364] Users input employee time information and learning space usage information using a terminal. The terminal formats this data and sends it to the server. The server generates an optimal schedule based on the received data. Specifically, the server uses an AI model to analyze the data and perform data processing to optimize schedules and resource allocation. This model learns from past data and derives the result that is best suited to the current conditions.

[0365] The generated schedules and information are presented to the user via the device's display. The displayed information is visually easy to understand, allowing the user to easily review and modify it as needed.

[0366] Furthermore, the server uses emotion analysis to detect the user's emotional state. If the user is experiencing fatigue or stress, the adaptive presentation system adjusts the interface, such as changing the screen's color tone or displaying encouraging messages. This emotion analysis utilizes speech recognition and facial recognition technologies to provide accurate feedback while respecting user privacy.

[0367] For example, if a user requests to add a math class for the following week, the server analyzes the information and suggests the optimal time, taking into account classroom availability and the schedules of the instructors. Furthermore, if the user feels "a little tired," the server automatically changes the interface's color scheme to a more calming one.

[0368] An example of a prompt message would be, "Please create a new class schedule, taking into account the current booking status." In this way, the system can streamline the operation of educational facilities while providing a comfortable environment for users.

[0369] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0370] Step 1:

[0371] This phase involves the user using a terminal to input employee time information and learning space usage information. The terminal's input interface has a predefined form format, into which the user enters the necessary information. The entered data is converted into a structured format and prepared for transmission to the server. The output is in a data format that can be sent to the server.

[0372] Step 2:

[0373] This is the phase where the terminal sends input data to the server. The terminal uses the HTTPS protocol to send data to the server while ensuring data security. During this process, data transmission confirmation is performed, and once confirmation is received, the process proceeds to the next step. The output is the data received by the server.

[0374] Step 3:

[0375] This phase involves the server analyzing the received data and generating an optimal schedule. The server utilizes a generation AI model to analyze the input data and combine it with faculty schedules and available classroom information to calculate the best schedule. This calculation takes into account both past data and current conditions. The output is the generated optimal schedule.

[0376] Step 4:

[0377] This is the phase where the generated schedule is visually displayed to the user on their device. The information is presented on the device's display in an intuitively easy-to-understand format. The user can review it and, if necessary, make corrections from the device. The output is visual information for the user to review.

[0378] Step 5:

[0379] This is the phase in which the device collects user emotional data. Using voice input devices and cameras, the device records the user's voice tone and facial expressions in real time. This provides data to understand the user's emotional state. The output is the collected emotional data.

[0380] Step 6:

[0381] This phase involves the server analyzing emotional data using emotion analysis tools and adjusting the interface based on the results. The server uses machine learning algorithms to classify the user's emotional state. This allows the display and information presentation tools to be modified to best suit the user. The output is the adjusted interface.

[0382] These processes work together to form a system that enables efficient scheduling within educational facilities and provides users with a comfortable user experience.

[0383] (Application Example 2)

[0384] 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 as the "terminal".

[0385] When timetables and resource allocation in educational institutions are not efficiently optimized, it can lead to increased burdens on faculty and students, and a deterioration of the educational environment. Furthermore, the lack of consideration for users' emotional states can amplify stress. Therefore, a system is needed that streamlines educational facility management while also considering the emotional well-being of users.

[0386] 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.

[0387] In this invention, the server includes an input means for inputting time information and classroom usage information of faculty and staff at educational institutions, a calculation means for generating an optimal timetable based on the information input by the input means, and an emotion recognition means for recognizing the user's emotional state. This enables the provision of an optimal educational environment in educational settings and the adjustment of the interface according to the user's emotions.

[0388] An "educational institution" is an organization or facility that provides education, and includes schools and universities.

[0389] "Teachers and staff" refers to educators and administrative staff working in educational institutions, and includes people involved in education and management.

[0390] "Time information" refers to data related to the schedules of classes and work for faculty, staff, and students.

[0391] "Classroom usage information" refers to data regarding the usage and availability of classrooms within educational facilities.

[0392] "Input means" refers to a device or software interface for inputting information into a system.

[0393] "Computational means" refers to software or hardware used for analysis and processing based on input data.

[0394] "Emotion recognition means" refers to technology that determines a user's emotional state from data such as voice and facial expressions.

[0395] "Display adjustment means" refers to a function that adjusts the appearance of the interface and the information presented according to the user's emotional state.

[0396] "Resource information input means" refers to a method or device for inputting data related to resource allocation and facility maintenance.

[0397] A "notification method" is a means of transmitting determined information from the system to the user.

[0398] The system that realizes this invention is an efficient system that integrates timetable management and emotion recognition in educational institutions. The program for this system runs mainly on servers and terminals and is constructed using technologies such as Python and React Native.

[0399] The server provides computing power to efficiently process time information and classroom usage information for faculty and staff at educational institutions. Time and usage information is input from client terminals, and the server analyzes this data to generate an optimal timetable. A Python program is used for data analysis and automatic timetable generation, and the generated timetable is displayed on the terminal.

[0400] Furthermore, the server uses emotion recognition to determine the user's emotions in real time from the voice and facial expression data they input. This emotion data is used to provide information tailored to the user's emotions. For example, using React Native, if it is determined that the user is feeling stressed, the interface's color scheme can be changed to softer colors, or an encouraging message can be displayed.

[0401] As a concrete example, suppose a student is using a timetable app during exam week, and the emotion recognition system detects that the student is stressed. In this case, the system displays a message such as, "Relax and prepare well. You can do it!" and changes the UI to a reassuring color scheme.

[0402] Examples of prompts include instructions such as, "Analyze students' emotions and display encouraging messages if they are stressed," and "Send the necessary data to the server to optimize the timetable." This improves the user experience and makes educational activities more effective and efficient.

[0403] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0404] Step 1:

[0405] The terminal receives time information for faculty and staff, as well as classroom usage information, from users. The entered information is converted into a format that can be stored in a database and sent to the server. This allows for efficient management of necessary data.

[0406] Step 2:

[0407] The server analyzes the received time and usage information in a database. This analysis process uses a Python script to perform calculations to generate the optimal timetable. An optimization algorithm is used to generate timetable suggestions. This output becomes a list of candidate timetables.

[0408] Step 3:

[0409] The server sends the generated timetable to the terminal and displays it on the terminal. The user can review this list of options and make corrections as needed. The terminal resends the user's corrections to the server, and the timetable is finalized.

[0410] Step 4:

[0411] The device acquires facial expression data through the user's voice and camera and sends it to a server. This data is processed by emotion recognition means to estimate the user's emotional state. In this step, the degree of relaxation and stress is identified in particular.

[0412] Step 5:

[0413] The server adjusts the interface to suit the user's emotional state based on the emotion recognition results. Specifically, it uses React Native to dynamically change the interface's color scheme and messages. This allows for a more comfortable user experience.

[0414] Step 6:

[0415] When a user uses the device again, it maintains its latest state and synchronizes with the server. This synchronization process is performed to reflect updates to the user's schedule and interface settings. This step ensures the integrity of the entire system.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] [Third Embodiment]

[0420] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0421] 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.

[0422] 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).

[0423] 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.

[0424] 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.

[0425] 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).

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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.

[0431] 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".

[0432] This invention provides a system for achieving efficient operation in educational facilities, integrating time management for faculty and staff, optimal resource allocation, and monitoring of facility usage. Specific embodiments are described below in natural language.

[0433] This system consists of multiple computer devices used in educational institutions, primarily including a server and user terminals. The server runs programs with multiple functions. Users (e.g., school administrators) use terminals to input necessary information into the system, and this information is sent to the server.

[0434] First, users input faculty and staff time information and classroom spatial information via a terminal. The entered data is sent to a server, which then calculates the optimal timetable based on this information. The calculated timetable is displayed on the terminal's screen, allowing users to review it and make corrections as needed.

[0435] Furthermore, users input budget information and submit resource usage data to the server. The server analyzes the budget data, learns past spending patterns, and calculates the optimal resource allocation. Through this process, it proposes efficient management of available resources.

[0436] Furthermore, when users input information about school facilities and maintenance, the server analyzes this information and calculates the optimal placement based on the usage of the facilities. The server checks which parts of the facilities are being used appropriately and uses natural language processing to notify users of the need for maintenance.

[0437] For example, when class assignments need to be re-evaluated due to an increase in curriculum content at the start of a new school year, this system can be used to calculate the optimal assignment within existing resources, taking into account the schedules of all classrooms and teachers. In this way, the system provides teachers and staff with data to function efficiently, and users can easily review and modify the system to ensure smooth school operations.

[0438] This system enables users to perform complex administrative tasks related to the daily operation of educational institutions in an integrated and efficient manner, significantly reducing human error.

[0439] The following describes the processing flow.

[0440] Step 1:

[0441] Users use a terminal to input schedule information for faculty and staff at educational institutions, as well as classroom availability. This input includes the times when faculty and staff are available to teach and the availability of each classroom. Once input is complete, the terminal sends this information to the server.

[0442] Step 2:

[0443] The server analyzes the received schedule information and classroom usage data, comparing each faculty member's availability with the availability of classrooms. At this stage, it checks for data consistency to ensure there are no duplicates or inconsistencies.

[0444] Step 3:

[0445] The server runs an optimization algorithm based on consistent data to generate a timetable that shows which faculty member will teach which class and in which classroom. The optimization process also takes into account faculty preferences and the importance of each class.

[0446] Step 4:

[0447] The timetable generated by the server is sent to the terminal for the user to review. The user checks the displayed timetable and makes corrections as needed. These corrections determine the final confirmed timetable.

[0448] Step 5:

[0449] Users input budget information into their terminals and notify the server of data regarding resource allocation. The input data includes each department's budget and necessary expenses.

[0450] Step 6:

[0451] The server analyzes the entered budget data and compares it with past spending history to identify waste and areas for improvement. The server then uses a budget optimization algorithm to generate the most effective resource allocation plan.

[0452] Step 7:

[0453] The server calculates the optimal budget allocation plan and presents it to the user via the terminal. The user can then review the budget plan, make adjustments as needed, and finalize the budget.

[0454] Step 8:

[0455] Users input information about the usage and maintenance status of school facilities into a terminal and send it to the server. This includes information such as the operational status and maintenance history of the facilities.

[0456] Step 9:

[0457] The server performs calculations based on equipment information to propose the optimal placement and necessary maintenance. The server considers equipment usage frequency and maintenance schedules to generate specific recommendations.

[0458] Step 10:

[0459] The server-generated proposals are displayed on the terminal and viewed by the user. The user reviews the proposals and finalizes the equipment layout and maintenance plan.

[0460] In this way, the entire system operates efficiently, allowing the complex tasks of school management to be managed smoothly.

[0461] (Example 1)

[0462] 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."

[0463] While educational institutions require integrated management of faculty and staff time, resource allocation, and facility utilization, traditional methods have struggled to optimize these elements efficiently and accurately. In particular, human error and the dispersion of information have hindered effective resource utilization and schedule optimization.

[0464] 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.

[0465] In this invention, the server includes an input means for inputting information about the time of faculty and staff and information about the educational space, a calculation means for generating an optimal time allocation, and a presentation means for displaying the generated time allocation. This enables the optimization of faculty and staff schedules, efficient allocation of resources, and effective management of facilities.

[0466] "Information regarding the time spent by faculty and staff" refers to data concerning the working hours and schedules of teachers and staff within educational institutions.

[0467] "Information regarding educational spaces" refers to data on the use and layout of spaces in educational facilities such as classrooms and equipment.

[0468] "Input means" refers to a device or function that acts as an interface or device for taking information into a system.

[0469] A "computational means" is a function or device that performs calculations or analyses based on the received data.

[0470] "Presentation means" refers to a device or function for visually or audibly communicating the calculated or analyzed results to the user.

[0471] "Optimal time allocation" refers to the time allocation that most efficiently arranges the schedules of faculty and staff under given conditions.

[0472] "Resource information" refers to data regarding the quantity and status of physical and human resources available within an educational institution.

[0473] "Analysis tools" refer to functions or devices used to organize input data and determine the most effective way to utilize it through various processes.

[0474] "Display means" refers to a visible method or device for informing the user of the results of a calculation or analysis.

[0475] "Information regarding usage and maintenance" refers to data on the current utilization status of spaces and equipment within the facility and the need for their maintenance.

[0476] A "decision-making tool" is a function or device for selecting the most suitable option from various choices and making a decision in a feasible manner.

[0477] "Means of communication" refers to means or devices for conveying the decided results to users or related organizations.

[0478] This invention is a system aimed at improving the operational efficiency of educational institutions. The system consists of a server and terminals used by multiple users. The server comprehensively analyzes various data owned by the educational institution and proposes optimal time allocation, resource allocation, and facility placement.

[0479] The server first receives information about faculty and staff time and educational space entered by users via terminals. This information is then analyzed using an optimization algorithm based on the Python programming language. During the calculation process, the Pandas data analysis library and Tableau visualization tool are used to optimize time allocation and resource utilization.

[0480] Users input resource information, including budget and equipment details, via a terminal. The server uses this information to analyze past expenditure data with Pandas and calculate the most efficient resource allocation. For facility usage and maintenance information, the server uses the natural language processing library NLTK to evaluate optimal placement and maintenance needs.

[0481] As a concrete example, this system can be used to optimize classroom usage throughout the school at the start of a new academic year. Users simply input the available time for each classroom and the free time of teachers and staff, and the server calculates possible timetables and proposes the most efficient schedule. Multiple timetable options are displayed on the terminal, allowing users to easily review and adjust them.

[0482] An example of a prompt message to the generating AI model would be, "Based on the current classroom usage and teachers' schedules, please calculate the optimal timetable for the new academic year. In particular, please concentrate math classes on weekday afternoons." By inputting such a message, the system can create an optimized schedule.

[0483] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0484] Step 1:

[0485] Users use a terminal to input information about faculty and staff time and educational space. The server then receives this input data. Based on this input data, the server uses Python to organize the data and generate the basic dataset necessary for calculating timetables. This process is initiated by the user's specific action of inputting the schedules of specific classrooms and teachers.

[0486] Step 2:

[0487] The server runs an optimization algorithm using the received data. The algorithm processes the input data using the Pandas data analysis library and simulates possible timetable arrangement patterns. This computational process determines the most efficient time allocation. The output generates a provisional timetable and the optimal classroom arrangement. The server returns this to the terminal, preparing it for presentation to the user.

[0488] Step 3:

[0489] The user reviews the proposed timetable presented on the terminal and makes modifications as needed. For example, they might move a specific class to the afternoon. Based on this modification input, the server performs optimization calculations again and generates a new, revised timetable. This feedback loop allows the user to obtain an efficient and customized schedule. This operation is achieved through the user's concrete actions of updating information by manipulating the terminal's interface.

[0490] Step 4:

[0491] The server processes resource utilization data based on user input. Using this pre-processed data, the server learns past budget and resource usage patterns and calculates the optimal budget allocation. The output is a detailed analysis report on how resources can be allocated. This result is displayed to the user via their terminal, allowing them to utilize it for operational purposes.

[0492] Step 5:

[0493] Users input facility usage and maintenance information into a terminal. Based on this information, the server uses natural language processing technology to optimize facility placement and assess maintenance needs. The final output is a report recommending the optimal equipment placement and maintenance plan. Users can review this information and incorporate it into the physical management of their educational facilities.

[0494] (Application Example 1)

[0495] 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."

[0496] In educational and public facilities, the complex schedules of teachers, staff, and users make efficient time management and facility operation difficult. Furthermore, the allocation of physical resources and budget management are often inadequate, leading to waste. Additionally, insufficient management of facility usage and maintenance reduces the efficiency of equipment utilization. Addressing these challenges and optimizing overall facility operations is essential.

[0497] 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.

[0498] In this invention, the server includes data input means for inputting time information of faculty and staff and spatial information of educational facilities; calculation means for generating an optimal timetable and public facility utilization plan based on the time information and spatial information input by the data input means; and visualization means for displaying the information generated by the calculation means. This enables the creation of efficient personnel schedules and optimal use of facilities.

[0499] "Data input means" refers to a device or interface for inputting temporal and spatial information of faculty and staff in educational facilities.

[0500] "Computation means" refers to a processor or algorithm for creating an optimal timetable and facility usage plan based on input time and spatial information.

[0501] "Visualization means" refers to a display device or software that displays the timetable or usage plan generated by the calculation means in an easy-to-understand manner for the user.

[0502] An "input method" is an interface for entering necessary data about facilities and budgets into the system.

[0503] "Analysis means" refers to a function that analyzes information obtained from input means and calculates efficient budget management and physical resource allocation.

[0504] "Information provision means" refers to a medium or device for providing the distribution information calculated by the analysis means to the user.

[0505] "Data acquisition means" refers to sensors and data collection systems used to gather information on facility usage and maintenance.

[0506] A "decision-making tool" is an algorithm used to determine the optimal placement of equipment and whether maintenance is necessary, based on the collected data.

[0507] "Communication means" refers to communication devices or networks used to inform users or administrators of information determined by the decision-making means.

[0508] This invention is a system designed to improve the operational efficiency of educational and public facilities. The system primarily consists of a server and multiple terminals. Users can input time information, budget information, and facility usage status for faculty and staff through these terminals.

[0509] The server runs Python programs and provides a web browser interface as a means of data input. Information sent from terminals is aggregated on the server and analyzed by machine learning algorithms utilizing Scikit-learn. Based on the analyzed data, the server calculates the optimal schedule, resource allocation, and equipment placement.

[0510] The calculated results are visualized by the server via a web application using the Django framework. This visualization allows users to view the results on their device screen and make corrections or updates as needed.

[0511] Furthermore, the NLTK library is used for natural language processing, and if equipment maintenance is required, a notification will be sent in natural language. This notification will be delivered to the user via email or applications on the terminal.

[0512] As a concrete example, when a school in a smart city reviews its class schedule for the new academic year, the server optimizes the class timetable based on existing data. This allows for the maximum utilization of available classrooms and faculty time.

[0513] An example of a prompt message might be: "Generate proposals to optimize the operational efficiency of school facilities throughout the smart city. Consider resource sharing between different schools and the allocation of class time."

[0514] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0515] Step 1:

[0516] Users input data such as faculty and staff time information and educational facility spatial information using a terminal. The terminal then sends this data to a server via a dedicated web application. The input data is structured in CSV or JSON format and stored on the server.

[0517] Step 2:

[0518] The server preprocesses the received data. This primarily involves data manipulation, such as imputing missing values ​​and normalizing the data, to prepare it for use with machine learning algorithms. The processed data is then passed on to the next analysis process.

[0519] Step 3:

[0520] The server executes machine learning algorithms using Scikit-learn based on the formatted data. In this step, statistical analysis is performed based on historical schedule data and usage patterns to generate an optimal timetable and resource utilization plan. The calculated results are stored on the server as timetable data.

[0521] Step 4:

[0522] The server displays the generated timetable using a visualization system based on the Django framework. Users can view the visualized timetable via their terminal and make modifications as needed. This visualization uses an interactive GUI, making it easy to use.

[0523] Step 5:

[0524] If a user enters additional information regarding equipment usage or maintenance, the server uses NLTK-based natural language processing to generate necessary maintenance notifications. This information is sent through the notification system and presented to the user via email or app notifications.

[0525] Step 6:

[0526] Finally, users can download or export all results from their device in a printable format. This output is provided in PDF or Excel spreadsheet format, facilitating further analysis and sharing.

[0527] 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.

[0528] This invention is a system used to improve efficiency in the management of educational facilities. It combines a function to create an optimal timetable based on faculty and staff time information and classroom usage status with an emotion engine that recognizes user emotions. The system aims to provide a better environment through interaction with faculty, staff, and students.

[0529] This system primarily consists of a server and terminals, with users inputting information through the terminals. For example, users input faculty and staff class schedules and classroom reservation status, and this information is sent to the server. The server analyzes this information and generates an optimal timetable that takes into account faculty and staff schedules and classroom availability. The generated timetable is displayed on the terminal, which users can review and modify as needed.

[0530] Furthermore, the present invention incorporates an emotion engine that can recognize the user's emotional state in real time. This emotion engine analyzes voice and facial expression data acquired through interaction with the user to determine the current emotional state. As a result, the server can provide appropriate information and interface settings according to the user's emotions.

[0531] For example, if the emotion engine determines that a user is experiencing fatigue or stress during the timetable creation process, the server will provide a more comfortable operating environment by changing the interface's color scheme to a calmer tone or displaying encouraging messages. This improves user efficiency and makes it possible to support school operations more smoothly.

[0532] This system utilizes the same emotion engine in budget management and equipment management, supporting users in working most efficiently and comfortably. As a result, the overall operation of the educational facility is improved, and an environment is provided where users can perform their duties comfortably through the system.

[0533] The following describes the processing flow.

[0534] Step 1:

[0535] Users input faculty and staff time information and classroom space information from their terminals. This information includes each faculty member's available teaching time, classroom reservation status, and educational curriculum. Once input is complete, the terminal sends this data to the server.

[0536] Step 2:

[0537] The server analyzes the received data and verifies the consistency of the temporal and spatial information. During this process, it checks for duplicate schedules and reservation statuses. If necessary, it may also send a correction request to the user.

[0538] Step 3:

[0539] The server runs an optimization algorithm using consistent data. The algorithm considers the preferences of faculty and staff and classroom usage to generate an efficient timetable. This result is then sent to the terminal.

[0540] Step 4:

[0541] The terminal displays the timetable sent from the server. The user can review the displayed timetable and make corrections as needed. If corrections are made, the updated data is sent back to the server via the terminal.

[0542] Step 5:

[0543] In parallel, the emotion engine acquires emotion data in real time during user interaction. This includes collecting changes in the user's facial expressions and voice through the camera and microphone. The device then sends the emotion analysis results to the server.

[0544] Step 6:

[0545] The server analyzes the received emotional data to understand the user's emotional state. If it determines that the user is experiencing stress, the server instructs the device to, for example, change the screen's color tone or send a relaxation message.

[0546] Step 7:

[0547] The terminal displays responses to the user to provide a comfortable experience, based on instructions from the server. This allows the system to adjust so that the user can work smoothly.

[0548] Through this series of processes, the system efficiently supports the operation of educational facilities and helps users work in a better environment.

[0549] (Example 2)

[0550] 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."

[0551] Educational facilities need to efficiently manage the time of faculty and staff and schedule classroom usage, but a lack of consideration for emotional factors makes it difficult to simultaneously enhance convenience and comfort. Furthermore, when optimizing facility use and resource allocation, the inability to provide adaptive information that takes into account the emotional state of users is a problem.

[0552] 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.

[0553] In this invention, the server includes an information input means for inputting employee time information and learning space usage information; an emotion analysis means for analyzing the user's emotional state and adjusting information presentation and interface based on the results; and a configuration determination means for determining the optimal configuration based on facility usage information and maintenance information. This enables an efficient and user-friendly operating environment for educational facilities.

[0554] "Information input means" refers to a device or method for collecting information on the time spent by employees and information on the use of learning spaces, and providing this information to a system.

[0555] "Data processing means" refers to a device or method for analyzing input information and generating an optimal schedule or resource allocation.

[0556] "Display means" refers to a device or method for visually showing the generated schedule or information to the user.

[0557] "Emotion analysis means" refers to a device or method that analyzes data such as a user's voice and facial expressions to determine their emotional state in real time.

[0558] An "adaptive presentation means" is a device or method for optimizing presented information and interfaces based on the user's emotional state to improve the user experience.

[0559] "Layout determination means" refers to a device or method that determines the optimal configuration and layout based on facility usage information and maintenance information.

[0560] "Notification means" refers to a device or method for informing the user of determined information or configuration.

[0561] This invention is a system that improves the efficiency of management operations and user comfort in educational facilities. This system mainly consists of a server and terminals.

[0562] Users input employee time information and learning space usage information using a terminal. The terminal formats this data and sends it to the server. The server generates an optimal schedule based on the received data. Specifically, the server uses an AI model to analyze the data and perform data processing to optimize schedules and resource allocation. This model learns from past data and derives the result that is best suited to the current conditions.

[0563] The generated schedules and information are presented to the user via the device's display. The displayed information is visually easy to understand, allowing the user to easily review and modify it as needed.

[0564] Furthermore, the server uses emotion analysis to detect the user's emotional state. If the user is experiencing fatigue or stress, the adaptive presentation system adjusts the interface, such as changing the screen's color tone or displaying encouraging messages. This emotion analysis utilizes speech recognition and facial recognition technologies to provide accurate feedback while respecting user privacy.

[0565] For example, if a user requests to add a math class for the following week, the server analyzes the information and suggests the optimal time, taking into account classroom availability and the schedules of the instructors. Furthermore, if the user feels "a little tired," the server automatically changes the interface's color scheme to a more calming one.

[0566] An example of a prompt message would be, "Please create a new class schedule, taking into account the current booking status." In this way, the system can streamline the operation of educational facilities while providing a comfortable environment for users.

[0567] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0568] Step 1:

[0569] This phase involves the user using a terminal to input employee time information and learning space usage information. The terminal's input interface has a predefined form format, into which the user enters the necessary information. The entered data is converted into a structured format and prepared for transmission to the server. The output is in a data format that can be sent to the server.

[0570] Step 2:

[0571] This is the phase where the terminal sends input data to the server. The terminal uses the HTTPS protocol to send data to the server while ensuring data security. During this process, data transmission confirmation is performed, and once confirmation is received, the process proceeds to the next step. The output is the data received by the server.

[0572] Step 3:

[0573] This phase involves the server analyzing the received data and generating an optimal schedule. The server utilizes a generation AI model to analyze the input data and combine it with faculty schedules and available classroom information to calculate the best schedule. This calculation takes into account both past data and current conditions. The output is the generated optimal schedule.

[0574] Step 4:

[0575] This is the phase where the generated schedule is visually displayed to the user on their device. The information is presented on the device's display in an intuitively easy-to-understand format. The user can review it and, if necessary, make corrections from the device. The output is visual information for the user to review.

[0576] Step 5:

[0577] This is the phase in which the device collects user emotional data. Using voice input devices and cameras, the device records the user's voice tone and facial expressions in real time. This provides data to understand the user's emotional state. The output is the collected emotional data.

[0578] Step 6:

[0579] This phase involves the server analyzing emotional data using emotion analysis tools and adjusting the interface based on the results. The server uses machine learning algorithms to classify the user's emotional state. This allows the display and information presentation tools to be modified to best suit the user. The output is the adjusted interface.

[0580] These processes work together to form a system that enables efficient scheduling within educational facilities and provides users with a comfortable user experience.

[0581] (Application Example 2)

[0582] 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."

[0583] When timetables and resource allocation in educational institutions are not efficiently optimized, it can lead to increased burdens on faculty and students, and a deterioration of the educational environment. Furthermore, the lack of consideration for users' emotional states can amplify stress. Therefore, a system is needed that streamlines educational facility management while also considering the emotional well-being of users.

[0584] 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.

[0585] In this invention, the server includes an input means for inputting time information and classroom usage information of faculty and staff at educational institutions, a calculation means for generating an optimal timetable based on the information input by the input means, and an emotion recognition means for recognizing the user's emotional state. This enables the provision of an optimal educational environment in educational settings and the adjustment of the interface according to the user's emotions.

[0586] An "educational institution" is an organization or facility that provides education, and includes schools and universities.

[0587] "Teachers and staff" refers to educators and administrative staff working in educational institutions, and includes people involved in education and management.

[0588] "Time information" refers to data related to the schedules of classes and work for faculty, staff, and students.

[0589] "Classroom usage information" refers to data regarding the usage and availability of classrooms within educational facilities.

[0590] "Input means" refers to a device or software interface for inputting information into a system.

[0591] "Computational means" refers to software or hardware used for analysis and processing based on input data.

[0592] "Emotion recognition means" refers to technology that determines a user's emotional state from data such as voice and facial expressions.

[0593] "Display adjustment means" refers to a function that adjusts the appearance of the interface and the information presented according to the user's emotional state.

[0594] "Resource information input means" refers to a method or device for inputting data related to resource allocation and facility maintenance.

[0595] A "notification method" is a means of transmitting determined information from the system to the user.

[0596] The system that realizes this invention is an efficient system that integrates timetable management and emotion recognition in educational institutions. The program for this system runs mainly on servers and terminals and is constructed using technologies such as Python and React Native.

[0597] The server provides computing power to efficiently process time information and classroom usage information for faculty and staff at educational institutions. Time and usage information is input from client terminals, and the server analyzes this data to generate an optimal timetable. A Python program is used for data analysis and automatic timetable generation, and the generated timetable is displayed on the terminal.

[0598] Furthermore, the server uses emotion recognition to determine the user's emotions in real time from the voice and facial expression data they input. This emotion data is used to provide information tailored to the user's emotions. For example, using React Native, if it is determined that the user is feeling stressed, the interface's color scheme can be changed to softer colors, or an encouraging message can be displayed.

[0599] As a concrete example, suppose a student is using a timetable app during exam week, and the emotion recognition system detects that the student is stressed. In this case, the system displays a message such as, "Relax and prepare well. You can do it!" and changes the UI to a reassuring color scheme.

[0600] Examples of prompts include instructions such as, "Analyze students' emotions and display encouraging messages if they are stressed," and "Send the necessary data to the server to optimize the timetable." This improves the user experience and makes educational activities more effective and efficient.

[0601] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0602] Step 1:

[0603] The terminal receives time information for faculty and staff, as well as classroom usage information, from users. The entered information is converted into a format that can be stored in a database and sent to the server. This allows for efficient management of necessary data.

[0604] Step 2:

[0605] The server analyzes the received time and usage information in a database. This analysis process uses a Python script to perform calculations to generate the optimal timetable. An optimization algorithm is used to generate timetable suggestions. This output becomes a list of candidate timetables.

[0606] Step 3:

[0607] The server sends the generated timetable to the terminal and displays it on the terminal. The user can review this list of options and make corrections as needed. The terminal resends the user's corrections to the server, and the timetable is finalized.

[0608] Step 4:

[0609] The device acquires facial expression data through the user's voice and camera and sends it to a server. This data is processed by emotion recognition means to estimate the user's emotional state. In this step, the degree of relaxation and stress is identified in particular.

[0610] Step 5:

[0611] The server adjusts the interface to suit the user's emotional state based on the emotion recognition results. Specifically, it uses React Native to dynamically change the interface's color scheme and messages. This allows for a more comfortable user experience.

[0612] Step 6:

[0613] When a user uses the device again, it maintains its latest state and synchronizes with the server. This synchronization process is performed to reflect updates to the user's schedule and interface settings. This step ensures the integrity of the entire system.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] [Fourth Embodiment]

[0618] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0619] 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.

[0620] 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).

[0621] 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.

[0622] 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.

[0623] 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).

[0624] 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.

[0625] 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.

[0626] 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.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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".

[0631] This invention provides a system for achieving efficient operation in educational facilities, integrating time management for faculty and staff, optimal resource allocation, and monitoring of facility usage. Specific embodiments are described below in natural language.

[0632] This system consists of multiple computer devices used in educational institutions, primarily including a server and user terminals. The server runs programs with multiple functions. Users (e.g., school administrators) use terminals to input necessary information into the system, and this information is sent to the server.

[0633] First, users input faculty and staff time information and classroom spatial information via a terminal. The entered data is sent to a server, which then calculates the optimal timetable based on this information. The calculated timetable is displayed on the terminal's screen, allowing users to review it and make corrections as needed.

[0634] Furthermore, users input budget information and submit resource usage data to the server. The server analyzes the budget data, learns past spending patterns, and calculates the optimal resource allocation. Through this process, it proposes efficient management of available resources.

[0635] Furthermore, when users input information about school facilities and maintenance, the server analyzes this information and calculates the optimal placement based on the usage of the facilities. The server checks which parts of the facilities are being used appropriately and uses natural language processing to notify users of the need for maintenance.

[0636] For example, when class assignments need to be re-evaluated due to an increase in curriculum content at the start of a new school year, this system can be used to calculate the optimal assignment within existing resources, taking into account the schedules of all classrooms and teachers. In this way, the system provides teachers and staff with data to function efficiently, and users can easily review and modify the system to ensure smooth school operations.

[0637] This system enables users to perform complex administrative tasks related to the daily operation of educational institutions in an integrated and efficient manner, significantly reducing human error.

[0638] The following describes the processing flow.

[0639] Step 1:

[0640] Users use a terminal to input schedule information for faculty and staff at educational institutions, as well as classroom availability. This input includes the times when faculty and staff are available to teach and the availability of each classroom. Once input is complete, the terminal sends this information to the server.

[0641] Step 2:

[0642] The server analyzes the received schedule information and classroom usage data, comparing each faculty member's availability with the availability of classrooms. At this stage, it checks for data consistency to ensure there are no duplicates or inconsistencies.

[0643] Step 3:

[0644] The server runs an optimization algorithm based on consistent data to generate a timetable that shows which faculty member will teach which class and in which classroom. The optimization process also takes into account faculty preferences and the importance of each class.

[0645] Step 4:

[0646] The timetable generated by the server is sent to the terminal for the user to review. The user checks the displayed timetable and makes corrections as needed. These corrections determine the final confirmed timetable.

[0647] Step 5:

[0648] Users input budget information into their terminals and notify the server of data regarding resource allocation. The input data includes each department's budget and necessary expenses.

[0649] Step 6:

[0650] The server analyzes the entered budget data and compares it with past spending history to identify waste and areas for improvement. The server then uses a budget optimization algorithm to generate the most effective resource allocation plan.

[0651] Step 7:

[0652] The server calculates the optimal budget allocation plan and presents it to the user via the terminal. The user can then review the budget plan, make adjustments as needed, and finalize the budget.

[0653] Step 8:

[0654] Users input information about the usage and maintenance status of school facilities into a terminal and send it to the server. This includes information such as the operational status and maintenance history of the facilities.

[0655] Step 9:

[0656] The server performs calculations based on equipment information to propose the optimal placement and necessary maintenance. The server considers equipment usage frequency and maintenance schedules to generate specific recommendations.

[0657] Step 10:

[0658] The server-generated proposals are displayed on the terminal and viewed by the user. The user reviews the proposals and finalizes the equipment layout and maintenance plan.

[0659] In this way, the entire system operates efficiently, allowing the complex tasks of school management to be managed smoothly.

[0660] (Example 1)

[0661] 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".

[0662] While educational institutions require integrated management of faculty and staff time, resource allocation, and facility utilization, traditional methods have struggled to optimize these elements efficiently and accurately. In particular, human error and the dispersion of information have hindered effective resource utilization and schedule optimization.

[0663] 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.

[0664] In this invention, the server includes an input means for inputting information about the time of faculty and staff and information about the educational space, a calculation means for generating an optimal time allocation, and a presentation means for displaying the generated time allocation. This enables the optimization of faculty and staff schedules, efficient allocation of resources, and effective management of facilities.

[0665] "Information regarding the time spent by faculty and staff" refers to data concerning the working hours and schedules of teachers and staff within educational institutions.

[0666] "Information regarding educational spaces" refers to data on the use and layout of spaces in educational facilities such as classrooms and equipment.

[0667] "Input means" refers to a device or function that acts as an interface or device for taking information into a system.

[0668] A "computational means" is a function or device that performs calculations or analyses based on the received data.

[0669] "Presentation means" refers to a device or function for visually or audibly communicating the calculated or analyzed results to the user.

[0670] "Optimal time allocation" refers to the time allocation that most efficiently arranges the schedules of faculty and staff under given conditions.

[0671] "Resource information" refers to data regarding the quantity and status of physical and human resources available within an educational institution.

[0672] "Analysis tools" refer to functions or devices used to organize input data and determine the most effective way to utilize it through various processes.

[0673] "Display means" refers to a visible method or device for informing the user of the results of a calculation or analysis.

[0674] "Information regarding usage and maintenance" refers to data on the current utilization status of spaces and equipment within the facility and the need for their maintenance.

[0675] A "decision-making tool" is a function or device for selecting the most suitable option from various choices and making a decision in a feasible manner.

[0676] "Means of communication" refers to means or devices for conveying the decided results to users or related organizations.

[0677] This invention is a system aimed at improving the operational efficiency of educational institutions. The system consists of a server and terminals used by multiple users. The server comprehensively analyzes various data owned by the educational institution and proposes optimal time allocation, resource allocation, and facility placement.

[0678] The server first receives information about faculty and staff time and educational space entered by users via terminals. This information is then analyzed using an optimization algorithm based on the Python programming language. During the calculation process, the Pandas data analysis library and Tableau visualization tool are used to optimize time allocation and resource utilization.

[0679] Users input resource information, including budget and equipment details, via a terminal. The server uses this information to analyze past expenditure data with Pandas and calculate the most efficient resource allocation. For facility usage and maintenance information, the server uses the natural language processing library NLTK to evaluate optimal placement and maintenance needs.

[0680] As a concrete example, this system can be used to optimize classroom usage throughout the school at the start of a new academic year. Users simply input the available time for each classroom and the free time of teachers and staff, and the server calculates possible timetables and proposes the most efficient schedule. Multiple timetable options are displayed on the terminal, allowing users to easily review and adjust them.

[0681] An example of a prompt message to the generating AI model would be, "Based on the current classroom usage and teachers' schedules, please calculate the optimal timetable for the new academic year. In particular, please concentrate math classes on weekday afternoons." By inputting such a message, the system can create an optimized schedule.

[0682] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0683] Step 1:

[0684] Users use a terminal to input information about faculty and staff time and educational space. The server then receives this input data. Based on this input data, the server uses Python to organize the data and generate the basic dataset necessary for calculating timetables. This process is initiated by the user's specific action of inputting the schedules of specific classrooms and teachers.

[0685] Step 2:

[0686] The server runs an optimization algorithm using the received data. The algorithm processes the input data using the Pandas data analysis library and simulates possible timetable arrangement patterns. This computational process determines the most efficient time allocation. The output generates a provisional timetable and the optimal classroom arrangement. The server returns this to the terminal, preparing it for presentation to the user.

[0687] Step 3:

[0688] The user reviews the proposed timetable presented on the terminal and makes modifications as needed. For example, they might move a specific class to the afternoon. Based on this modification input, the server performs optimization calculations again and generates a new, revised timetable. This feedback loop allows the user to obtain an efficient and customized schedule. This operation is achieved through the user's concrete actions of updating information by manipulating the terminal's interface.

[0689] Step 4:

[0690] The server processes resource utilization data based on user input. Using this pre-processed data, the server learns past budget and resource usage patterns and calculates the optimal budget allocation. The output is a detailed analysis report on how resources can be allocated. This result is displayed to the user via their terminal, allowing them to utilize it for operational purposes.

[0691] Step 5:

[0692] Users input facility usage and maintenance information into a terminal. Based on this information, the server uses natural language processing technology to optimize facility placement and assess maintenance needs. The final output is a report recommending the optimal equipment placement and maintenance plan. Users can review this information and incorporate it into the physical management of their educational facilities.

[0693] (Application Example 1)

[0694] 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".

[0695] In educational and public facilities, the complex schedules of teachers, staff, and users make efficient time management and facility operation difficult. Furthermore, the allocation of physical resources and budget management are often inadequate, leading to waste. Additionally, insufficient management of facility usage and maintenance reduces the efficiency of equipment utilization. Addressing these challenges and optimizing overall facility operations is essential.

[0696] 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.

[0697] In this invention, the server includes data input means for inputting time information of faculty and staff and spatial information of educational facilities; calculation means for generating an optimal timetable and public facility utilization plan based on the time information and spatial information input by the data input means; and visualization means for displaying the information generated by the calculation means. This enables the creation of efficient personnel schedules and optimal use of facilities.

[0698] "Data input means" refers to a device or interface for inputting temporal and spatial information of faculty and staff in educational facilities.

[0699] "Computation means" refers to a processor or algorithm for creating an optimal timetable and facility usage plan based on input time and spatial information.

[0700] "Visualization means" refers to a display device or software that displays the timetable or usage plan generated by the calculation means in an easy-to-understand manner for the user.

[0701] An "input method" is an interface for entering necessary data about facilities and budgets into the system.

[0702] "Analysis means" refers to a function that analyzes information obtained from input means and calculates efficient budget management and physical resource allocation.

[0703] "Information provision means" refers to a medium or device for providing the distribution information calculated by the analysis means to the user.

[0704] "Data acquisition means" refers to sensors and data collection systems used to gather information on facility usage and maintenance.

[0705] A "decision-making tool" is an algorithm used to determine the optimal placement of equipment and whether maintenance is necessary, based on the collected data.

[0706] "Communication means" refers to communication devices or networks used to inform users or administrators of information determined by the decision-making means.

[0707] This invention is a system designed to improve the operational efficiency of educational and public facilities. The system primarily consists of a server and multiple terminals. Users can input time information, budget information, and facility usage status for faculty and staff through these terminals.

[0708] The server runs Python programs and provides a web browser interface as a means of data input. Information sent from terminals is aggregated on the server and analyzed by machine learning algorithms utilizing Scikit-learn. Based on the analyzed data, the server calculates the optimal schedule, resource allocation, and equipment placement.

[0709] The calculated results are visualized by the server via a web application using the Django framework. This visualization allows users to view the results on their device screen and make corrections or updates as needed.

[0710] Furthermore, the NLTK library is used for natural language processing, and if equipment maintenance is required, a notification will be sent in natural language. This notification will be delivered to the user via email or applications on the terminal.

[0711] As a concrete example, when a school in a smart city reviews its class schedule for the new academic year, the server optimizes the class timetable based on existing data. This allows for the maximum utilization of available classrooms and faculty time.

[0712] An example of a prompt message might be: "Generate proposals to optimize the operational efficiency of school facilities throughout the smart city. Consider resource sharing between different schools and the allocation of class time."

[0713] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0714] Step 1:

[0715] Users input data such as faculty and staff time information and educational facility spatial information using a terminal. The terminal then sends this data to a server via a dedicated web application. The input data is structured in CSV or JSON format and stored on the server.

[0716] Step 2:

[0717] The server preprocesses the received data. This primarily involves data manipulation, such as imputing missing values ​​and normalizing the data, to prepare it for use with machine learning algorithms. The processed data is then passed on to the next analysis process.

[0718] Step 3:

[0719] The server executes machine learning algorithms using Scikit-learn based on the formatted data. In this step, statistical analysis is performed based on historical schedule data and usage patterns to generate an optimal timetable and resource utilization plan. The calculated results are stored on the server as timetable data.

[0720] Step 4:

[0721] The server displays the generated timetable using a visualization system based on the Django framework. Users can view the visualized timetable via their terminal and make modifications as needed. This visualization uses an interactive GUI, making it easy to use.

[0722] Step 5:

[0723] If a user enters additional information regarding equipment usage or maintenance, the server uses NLTK-based natural language processing to generate necessary maintenance notifications. This information is sent through the notification system and presented to the user via email or app notifications.

[0724] Step 6:

[0725] Finally, users can download or export all results from their device in a printable format. This output is provided in PDF or Excel spreadsheet format, facilitating further analysis and sharing.

[0726] 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.

[0727] This invention is a system used to improve efficiency in the management of educational facilities. It combines a function to create an optimal timetable based on faculty and staff time information and classroom usage status with an emotion engine that recognizes user emotions. The system aims to provide a better environment through interaction with faculty, staff, and students.

[0728] This system primarily consists of a server and terminals, with users inputting information through the terminals. For example, users input faculty and staff class schedules and classroom reservation status, and this information is sent to the server. The server analyzes this information and generates an optimal timetable that takes into account faculty and staff schedules and classroom availability. The generated timetable is displayed on the terminal, which users can review and modify as needed.

[0729] Furthermore, the present invention incorporates an emotion engine that can recognize the user's emotional state in real time. This emotion engine analyzes voice and facial expression data acquired through interaction with the user to determine the current emotional state. As a result, the server can provide appropriate information and interface settings according to the user's emotions.

[0730] For example, if the emotion engine determines that a user is experiencing fatigue or stress during the timetable creation process, the server will provide a more comfortable operating environment by changing the interface's color scheme to a calmer tone or displaying encouraging messages. This improves user efficiency and makes it possible to support school operations more smoothly.

[0731] This system utilizes the same emotion engine in budget management and equipment management, supporting users in working most efficiently and comfortably. As a result, the overall operation of the educational facility is improved, and an environment is provided where users can perform their duties comfortably through the system.

[0732] The following describes the processing flow.

[0733] Step 1:

[0734] Users input faculty and staff time information and classroom space information from their terminals. This information includes each faculty member's available teaching time, classroom reservation status, and educational curriculum. Once input is complete, the terminal sends this data to the server.

[0735] Step 2:

[0736] The server analyzes the received data and verifies the consistency of the temporal and spatial information. During this process, it checks for duplicate schedules and reservation statuses. If necessary, it may also send a correction request to the user.

[0737] Step 3:

[0738] The server runs an optimization algorithm using consistent data. The algorithm considers the preferences of faculty and staff and classroom usage to generate an efficient timetable. This result is then sent to the terminal.

[0739] Step 4:

[0740] The terminal displays the timetable sent from the server. The user can review the displayed timetable and make corrections as needed. If corrections are made, the updated data is sent back to the server via the terminal.

[0741] Step 5:

[0742] In parallel, the emotion engine acquires emotion data in real time during user interaction. This includes collecting changes in the user's facial expressions and voice through the camera and microphone. The device then sends the emotion analysis results to the server.

[0743] Step 6:

[0744] The server analyzes the received emotional data to understand the user's emotional state. If it determines that the user is experiencing stress, the server instructs the device to, for example, change the screen's color tone or send a relaxation message.

[0745] Step 7:

[0746] The terminal displays responses to the user to provide a comfortable experience, based on instructions from the server. This allows the system to adjust so that the user can work smoothly.

[0747] Through this series of processes, the system efficiently supports the operation of educational facilities and helps users work in a better environment.

[0748] (Example 2)

[0749] 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".

[0750] Educational facilities need to efficiently manage the time of faculty and staff and schedule classroom usage, but a lack of consideration for emotional factors makes it difficult to simultaneously enhance convenience and comfort. Furthermore, when optimizing facility use and resource allocation, the inability to provide adaptive information that takes into account the emotional state of users is a problem.

[0751] 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.

[0752] In this invention, the server includes an information input means for inputting employee time information and learning space usage information; an emotion analysis means for analyzing the user's emotional state and adjusting information presentation and interface based on the results; and a configuration determination means for determining the optimal configuration based on facility usage information and maintenance information. This enables an efficient and user-friendly operating environment for educational facilities.

[0753] "Information input means" refers to a device or method for collecting information on the time spent by employees and information on the use of learning spaces, and providing this information to a system.

[0754] "Data processing means" refers to a device or method for analyzing input information and generating an optimal schedule or resource allocation.

[0755] "Display means" refers to a device or method for visually showing the generated schedule or information to the user.

[0756] "Emotion analysis means" refers to a device or method that analyzes data such as a user's voice and facial expressions to determine their emotional state in real time.

[0757] An "adaptive presentation means" is a device or method for optimizing presented information and interfaces based on the user's emotional state to improve the user experience.

[0758] "Layout determination means" refers to a device or method that determines the optimal configuration and layout based on facility usage information and maintenance information.

[0759] "Notification means" refers to a device or method for informing the user of determined information or configuration.

[0760] This invention is a system that improves the efficiency of management operations and user comfort in educational facilities. This system mainly consists of a server and terminals.

[0761] Users input employee time information and learning space usage information using a terminal. The terminal formats this data and sends it to the server. The server generates an optimal schedule based on the received data. Specifically, the server uses an AI model to analyze the data and perform data processing to optimize schedules and resource allocation. This model learns from past data and derives the result that is best suited to the current conditions.

[0762] The generated schedules and information are presented to the user via the device's display. The displayed information is visually easy to understand, allowing the user to easily review and modify it as needed.

[0763] Furthermore, the server uses emotion analysis to detect the user's emotional state. If the user is experiencing fatigue or stress, the adaptive presentation system adjusts the interface, such as changing the screen's color tone or displaying encouraging messages. This emotion analysis utilizes speech recognition and facial recognition technologies to provide accurate feedback while respecting user privacy.

[0764] For example, if a user requests to add a math class for the following week, the server analyzes the information and suggests the optimal time, taking into account classroom availability and the schedules of the instructors. Furthermore, if the user feels "a little tired," the server automatically changes the interface's color scheme to a more calming one.

[0765] An example of a prompt message would be, "Please create a new class schedule, taking into account the current booking status." In this way, the system can streamline the operation of educational facilities while providing a comfortable environment for users.

[0766] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0767] Step 1:

[0768] This phase involves the user using a terminal to input employee time information and learning space usage information. The terminal's input interface has a predefined form format, into which the user enters the necessary information. The entered data is converted into a structured format and prepared for transmission to the server. The output is in a data format that can be sent to the server.

[0769] Step 2:

[0770] This is the phase where the terminal sends input data to the server. The terminal uses the HTTPS protocol to send data to the server while ensuring data security. During this process, data transmission confirmation is performed, and once confirmation is received, the process proceeds to the next step. The output is the data received by the server.

[0771] Step 3:

[0772] This phase involves the server analyzing the received data and generating an optimal schedule. The server utilizes a generation AI model to analyze the input data and combine it with faculty schedules and available classroom information to calculate the best schedule. This calculation takes into account both past data and current conditions. The output is the generated optimal schedule.

[0773] Step 4:

[0774] This is the phase where the generated schedule is visually displayed to the user on their device. The information is presented on the device's display in an intuitively easy-to-understand format. The user can review it and, if necessary, make corrections from the device. The output is visual information for the user to review.

[0775] Step 5:

[0776] This is the phase in which the device collects user emotional data. Using voice input devices and cameras, the device records the user's voice tone and facial expressions in real time. This provides data to understand the user's emotional state. The output is the collected emotional data.

[0777] Step 6:

[0778] This phase involves the server analyzing emotional data using emotion analysis tools and adjusting the interface based on the results. The server uses machine learning algorithms to classify the user's emotional state. This allows the display and information presentation tools to be modified to best suit the user. The output is the adjusted interface.

[0779] These processes work together to form a system that enables efficient scheduling within educational facilities and provides users with a comfortable user experience.

[0780] (Application Example 2)

[0781] 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".

[0782] When timetables and resource allocation in educational institutions are not efficiently optimized, it can lead to increased burdens on faculty and students, and a deterioration of the educational environment. Furthermore, the lack of consideration for users' emotional states can amplify stress. Therefore, a system is needed that streamlines educational facility management while also considering the emotional well-being of users.

[0783] 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.

[0784] In this invention, the server includes an input means for inputting time information and classroom usage information of faculty and staff at educational institutions, a calculation means for generating an optimal timetable based on the information input by the input means, and an emotion recognition means for recognizing the user's emotional state. This enables the provision of an optimal educational environment in educational settings and the adjustment of the interface according to the user's emotions.

[0785] An "educational institution" is an organization or facility that provides education, and includes schools and universities.

[0786] "Teachers and staff" refers to educators and administrative staff working in educational institutions, and includes people involved in education and management.

[0787] "Time information" refers to data related to the schedules of classes and work for faculty, staff, and students.

[0788] "Classroom usage information" refers to data regarding the usage and availability of classrooms within educational facilities.

[0789] "Input means" refers to a device or software interface for inputting information into a system.

[0790] "Computational means" refers to software or hardware used for analysis and processing based on input data.

[0791] "Emotion recognition means" refers to technology that determines a user's emotional state from data such as voice and facial expressions.

[0792] "Display adjustment means" refers to a function that adjusts the appearance of the interface and the information presented according to the user's emotional state.

[0793] "Resource information input means" refers to a method or device for inputting data related to resource allocation and facility maintenance.

[0794] A "notification method" is a means of transmitting determined information from the system to the user.

[0795] The system that realizes this invention is an efficient system that integrates timetable management and emotion recognition in educational institutions. The program for this system runs mainly on servers and terminals and is constructed using technologies such as Python and React Native.

[0796] The server provides computing power to efficiently process time information and classroom usage information for faculty and staff at educational institutions. Time and usage information is input from client terminals, and the server analyzes this data to generate an optimal timetable. A Python program is used for data analysis and automatic timetable generation, and the generated timetable is displayed on the terminal.

[0797] Furthermore, the server uses emotion recognition to determine the user's emotions in real time from the voice and facial expression data they input. This emotion data is used to provide information tailored to the user's emotions. For example, using React Native, if it is determined that the user is feeling stressed, the interface's color scheme can be changed to softer colors, or an encouraging message can be displayed.

[0798] As a concrete example, suppose a student is using a timetable app during exam week, and the emotion recognition system detects that the student is stressed. In this case, the system displays a message such as, "Relax and prepare well. You can do it!" and changes the UI to a reassuring color scheme.

[0799] Examples of prompts include instructions such as, "Analyze students' emotions and display encouraging messages if they are stressed," and "Send the necessary data to the server to optimize the timetable." This improves the user experience and makes educational activities more effective and efficient.

[0800] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0801] Step 1:

[0802] The terminal receives time information for faculty and staff, as well as classroom usage information, from users. The entered information is converted into a format that can be stored in a database and sent to the server. This allows for efficient management of necessary data.

[0803] Step 2:

[0804] The server analyzes the received time and usage information in a database. This analysis process uses a Python script to perform calculations to generate the optimal timetable. An optimization algorithm is used to generate timetable suggestions. This output becomes a list of candidate timetables.

[0805] Step 3:

[0806] The server sends the generated timetable to the terminal and displays it on the terminal. The user can review this list of options and make corrections as needed. The terminal resends the user's corrections to the server, and the timetable is finalized.

[0807] Step 4:

[0808] The device acquires facial expression data through the user's voice and camera and sends it to a server. This data is processed by emotion recognition means to estimate the user's emotional state. In this step, the degree of relaxation and stress is identified in particular.

[0809] Step 5:

[0810] The server adjusts the interface to suit the user's emotional state based on the emotion recognition results. Specifically, it uses React Native to dynamically change the interface's color scheme and messages. This allows for a more comfortable user experience.

[0811] Step 6:

[0812] When a user uses the device again, it maintains its latest state and synchronizes with the server. This synchronization process is performed to reflect updates to the user's schedule and interface settings. This step ensures the integrity of the entire system.

[0813] 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.

[0814] 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.

[0815] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0816] 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.

[0817] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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."

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] The following is further disclosed regarding the embodiments described above.

[0835] (Claim 1)

[0836] An input method for entering the teacher's time information and classroom spatial information,

[0837] A calculation means for generating an optimal schedule based on the time information and spatial information input by the aforementioned input means,

[0838] A display means for displaying the schedule generated by the calculation means,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] A resource input means for inputting information on the allocation of available resources,

[0842] A resource calculation means that analyzes the allocation information received from the resource input means and calculates an efficient and optimal allocation,

[0843] Information presentation means that presents the optimal allocation obtained by the resource calculation means,

[0844] The system according to claim 1, including the following:

[0845] (Claim 3)

[0846] Information input means for inputting facility usage status information and maintenance information,

[0847] A placement determination means that determines the optimal placement based on the usage status information and maintenance information obtained from the aforementioned information input means,

[0848] A notification means for notifying the determined arrangement,

[0849] The system according to claim 1, including the following:

[0850] "Example 1"

[0851] (Claim 1)

[0852] An input method for entering information about the time spent by faculty and staff and information about the educational space,

[0853] A calculation means that generates an optimal time allocation based on the time information and spatial information input by the aforementioned input means,

[0854] A presentation means for displaying the time allocation generated by the calculation means,

[0855] An input means for entering information about available resources,

[0856] An analysis means that analyzes information about resources received from the input means and calculates efficient and optimal utilization,

[0857] A display means that presents the optimal use obtained by the aforementioned analysis means,

[0858] An input means for entering information regarding the usage status and maintenance of the facility,

[0859] A determination means that determines the optimal placement based on the usage status and maintenance information obtained from the input means,

[0860] A means of communication to notify the decided arrangement,

[0861] A system that includes this.

[0862] (Claim 2)

[0863] The system according to claim 1, further comprising means for correcting the generated time allocation and resource utilization based on information entered by the user.

[0864] (Claim 3)

[0865] The system according to claim 1, comprising a feedback mechanism for improving operational efficiency through continuous information updates.

[0866] "Application Example 1"

[0867] (Claim 1)

[0868] A data input means for inputting time information of faculty and staff and spatial information of educational facilities,

[0869] A calculation means that generates an optimal timetable and public facility usage plan based on the time information and spatial information input by the aforementioned data input means,

[0870] A visualization means for displaying the information generated by the calculation means,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] An input means for entering available physical resources and budget information,

[0874] An analysis means that analyzes the information received from the input means and calculates an efficient allocation of budget and physical resources based on past usage data,

[0875] Information providing means for providing allocation information obtained by the analysis means,

[0876] The system according to claim 1, including the following:

[0877] (Claim 3)

[0878] A data acquisition method for inputting facility usage status and maintenance information,

[0879] Based on the usage status and maintenance information obtained by the aforementioned data acquisition means, a decision means calculates the optimal placement of equipment and whether maintenance is necessary.

[0880] A means of communication for notifying the determined deployment and maintenance information,

[0881] The system according to claim 1, including the following:

[0882] "Example 2 of combining an emotion engine"

[0883] (Claim 1)

[0884] An information input means for inputting employee time information and learning space usage information,

[0885] A data processing means that generates an optimal schedule based on the time information and usage information entered by the aforementioned information input means,

[0886] A display means for visually displaying the schedule generated by the data processing means,

[0887] A sentiment analysis method that analyzes the user's emotional state and adjusts information presentation and interface based on the results,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] A data input means for inputting information on the allocation of available resources,

[0891] A data processing means that analyzes the distribution information received from the data input means and calculates an efficient and optimal distribution,

[0892] Information presentation means that presents the optimal allocation obtained by the data processing means,

[0893] An adaptive presentation method that presents information adaptively while taking into account the user's emotional state,

[0894] The system according to claim 1, including the following:

[0895] (Claim 3)

[0896] A data input means for inputting facility usage status information and maintenance information,

[0897] A configuration determination means that determines the optimal configuration based on the usage information and maintenance information obtained from the aforementioned data input means,

[0898] A notification means for notifying the determined configuration,

[0899] An environment optimization method that analyzes user emotion data and optimizes the operating environment,

[0900] The system according to claim 1, including the following:

[0901] "Application example 2 when combining with an emotional engine"

[0902] (Claim 1)

[0903] An input method for entering time information and classroom usage information for faculty and staff of educational institutions,

[0904] A calculation means for generating an optimal timetable based on the time information and usage information input by the aforementioned input means,

[0905] A display means that displays the timetable generated by the calculation means and allows the user to confirm and modify it,

[0906] An emotion recognition means for recognizing the user's emotional state,

[0907] Information presentation means that presents information corresponding to the user's emotions recognized by the emotion recognition means,

[0908] A system that includes this.

[0909] (Claim 2)

[0910] An analytical means for analyzing emotional data and adapting the user interface accordingly,

[0911] Includes display adjustment means that dynamically adjust screen color tones and messages according to the user's emotional state,

[0912] The system according to claim 1.

[0913] (Claim 3)

[0914] A resource information input means for inputting resource allocation information and facility maintenance information necessary for the operation of an educational institution,

[0915] A calculation means that determines the optimal allocation of resources and equipment placement, taking into account the emotional state, based on the information input from the resource information input means,

[0916] Includes a notification mechanism to inform the user of the optimal allocation and placement,

[0917] The system according to claim 1. [Explanation of symbols]

[0918] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data input means for inputting time information of faculty and staff and spatial information of educational facilities, A calculation means that generates an optimal timetable and public facility usage plan based on the time information and spatial information input by the aforementioned data input means, A visualization means for displaying the information generated by the calculation means, A system that includes this.

2. An input means for entering available physical resources and budget information, An analysis means that analyzes the information received from the input means and calculates an efficient allocation of budget and physical resources based on past usage data, Information providing means for providing allocation information obtained by the analysis means, The system according to claim 1, including the following:

3. A data acquisition method for inputting facility usage status and maintenance information, Based on the usage status and maintenance information obtained by the aforementioned data acquisition means, a decision means calculates the optimal placement of equipment and whether maintenance is necessary. A means of communication for notifying the determined deployment and maintenance information, The system according to claim 1, including the following:

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