system

Abstract

We provide the system. [Solution] A data processing device acquires data from various electronic scheduling systems and reservation management systems, and a means for anonymizing said data. A means for monitoring the usage status of meeting facilities in real time using the anonymized data and detecting available reservations, A means for optimizing and automatically adjusting the reservation of meeting facilities based on the aforementioned usage status, A means to notify the user when the aforementioned vacant reservation is detected, and to automatically cancel the reservation if no response is received, A system that includes means for performing analysis based on usage data in order to propose an appropriate layout for the aforementioned conference facility.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds 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 conference facilities, there are problems such as reservations not being satisfied, a shortage of appropriately sized conference rooms, and frequent empty reservations. Such problems lead to a situation where employees cannot use the conference rooms when they want to, which is a factor reducing work efficiency. Furthermore, due to the current situation where excessive man-hours are required for data collection and analysis, it has become difficult to improve the operation of conference rooms. A method for comprehensively solving these problems is required.

Means for Solving the Problems

[0005] In this invention, a data processing device acquires data from various electronic scheduling systems and reservation management systems and anonymizes it. Using the acquired anonymized data, the usage status of meeting facilities is monitored in real time, and available reservations are detected. At that time, the reservation of meeting facilities is optimized and automatically adjusted based on the usage status. Furthermore, when an available reservation is detected, the system notifies the user and has a function to automatically cancel the reservation if no response is received. In addition, by performing analysis to propose an appropriate layout for the meeting facilities, efficient operation tailored to each usage situation is realized. In this way, by improving the efficiency of meeting room use, a comfortable environment is provided to users.

[0006] A "data processing device" is a device that acquires data from various electronic scheduling systems and reservation management systems and has the function of performing necessary calculations and linking operations.

[0007] An "electronic scheduling system" is an application or service that operates on a digital device and is used to manage information such as appointments and reservations.

[0008] A "reservation management system" is a system that manages information related to the reservation of meeting rooms and facilities, and is used to efficiently coordinate their use.

[0009] "Anonymization" is the process of removing personally identifiable information from data and storing the data in a way that does not link it to any specific individual.

[0010] "Conference facilities" is a general term for facilities that include rooms and equipment used for holding meetings and discussions.

[0011] "Available reservation" refers to a situation where a reservation has been made, but the user is not actually using the meeting facility, or where only the reservation remains.

[0012] "Optimization" refers to adjusting plans and arrangements to utilize resources most efficiently under given conditions.

[0013] "Automatic adjustment" refers to the process by which a system autonomously reviews its settings and schedules and changes them to an optimal state.

[0014] "Automatic cancellation" is a function where the system automatically cancels a reservation if it is not met under certain conditions.

[0015] "Layout" refers to the arrangement and design of a space, including the arrangement of equipment within a conference facility.

[0016] "Analysis" refers to the processing and techniques used to understand the structure and characteristics of obtained data. [Brief explanation of the drawing]

[0017] [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]Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 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 an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0018] 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.

[0019] First, the language used in the following description will be explained.

[0020] In the following embodiments, a numbered processor (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.

[0021] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] 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.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] The system according to the present invention is based on the principle of acquiring data from multiple electronic scheduling systems and reservation management systems using a data processing device, anonymizing that data, and then analyzing it, in order to achieve efficient management of conference facilities. The server uses this data to monitor the usage status of conference facilities in real time and automatically detect available reservations.

[0039] This system uses a server to analyze user schedule data and identify underutilized time slots and trends in available bookings. This enables the optimization and automatic adjustment of appropriate meeting facility reservations. Based on the analysis results from the server, users can receive information on which meeting facilities are available and what the optimal dates and times are.

[0040] As a concrete example, suppose a user wants to hold a meeting the following Tuesday and sends a reservation request via their device. The server first receives the request and, considering existing reservation data and the availability of meeting facilities on that day from the electronic scheduling system, suggests the most suitable meeting room and time. If a reservation becomes available, the server automatically cancels it and offers the user the opportunity.

[0041] Furthermore, the server generates optimization suggestions for the meeting facility layout based on the analysis. For example, for a meeting room frequently used by two people, it suggests changing it to a phone booth to help utilize the space more efficiently. This suggestion is notified to users and operators via terminals, and a final decision is made based on their feedback.

[0042] This system significantly improves the operational efficiency of meeting facilities, creating an environment where users can use meeting rooms when needed without stress. Because these processes are automated, human resources are drastically reduced, allowing for more efficient use of time.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The server periodically retrieves meeting facility reservation data via APIs from multiple electronic scheduling and reservation management systems. The retrieved data is stored in a database on the server.

[0046] Step 2:

[0047] The server anonymizes the acquired data. Specifically, it replaces personally identifiable information such as user IDs and personal names with random identifiers and stores it in a database in a format that protects privacy.

[0048] Step 3:

[0049] The server monitors the real-time usage status of meeting facilities based on anonymized data. Using input from sensors and IoT devices installed in meeting rooms, it verifies actual usage and identifies available reservations.

[0050] Step 4:

[0051] The server analyzes usage and reservation data to calculate the optimal reservation schedule. It analyzes reservation imbalances and trends in available reservations to generate an efficient usage schedule.

[0052] Step 5:

[0053] The terminal notifies the user of optimized reservation information provided by the server. The user reviews the proposal presented through the terminal and approves or modifies the reservation as needed.

[0054] Step 6:

[0055] When the server detects an available reservation, it sends a confirmation notification to the user. If the user does not respond within a certain period of time, the server automatically initiates a procedure to cancel the reservation.

[0056] Step 7:

[0057] The server analyzes the usage data of meeting facilities and, if meetings with only two people occur frequently, generates suggestions for layout improvements, such as moving to smaller spaces like phone booths.

[0058] Step 8:

[0059] The terminal notifies the facility administrator of the layout proposal from the server and receives feedback. Based on this feedback, the final layout changes are decided.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] Efficiently managing the booking status of meeting facilities and event spaces and minimizing unused time slots is a major challenge for many companies and organizations. Currently, duplicate bookings and unused bookings are frequent, reducing the operational efficiency of facilities. Furthermore, a lack of information necessary for users to select appropriate facilities is hindering a smooth booking process.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for acquiring information from various information management systems and reservation management systems from an information processing device and anonymizing the information; means for optimizing and automatically adjusting facility reservations based on the usage status; and means for analyzing usage patterns using a machine learning algorithm and identifying time periods with low utilization rates. This makes it possible to improve the efficiency of facility utilization and to quickly provide appropriate facility information to users.

[0065] An "information processing device" is a device that acquires and processes information from various information management systems and reservation management systems.

[0066] "Anonymization" is a process that transforms information so that personal information cannot be identified, thereby protecting privacy.

[0067] A "facility" is a space or building used for holding meetings or events.

[0068] An "unused reservation" is a reservation that has been made but has not actually been used.

[0069] "Optimization" is the process of adjusting and improving how resources are used and allocated in order to increase their efficiency.

[0070] A "machine learning algorithm" is a computational method that analyzes data and learns patterns to improve future predictions and decisions.

[0071] "Usage patterns" refer to the tendencies and habits that indicate how facility users utilize the facility.

[0072] A "user terminal" is a computer device used by a user to receive and input information.

[0073] This invention relates to a system that efficiently and automatically optimizes the use of conference facilities. The server operates as an information processing device and is connected to various information management and reservation management systems. This allows the server to acquire necessary information and anonymize it. The server uses machine learning algorithms to analyze the collected data and learn patterns of facility usage. This enables the identification of time slots with low utilization rates and the optimization of facility reservations.

[0074] Furthermore, the server provides users with information on the most suitable facility for booking via their terminals. For example, if a user wants to use a facility next Tuesday, they can simply type "I would like to have a two-hour meeting next Tuesday. Please find and book the most suitable meeting facility" into their terminal, and the server will suggest the most suitable facility and automatically process the booking.

[0075] The server also monitors potentially unused reservations in real time and automatically cancels them if no action is taken by the user. Finally, the server can generate optimization suggestions for the facility's structure based on usage data. This information is communicated to users and administrators via terminals to promote efficient operation.

[0076] Implementing this system will significantly improve the efficiency of meeting facility utilization, allowing users to access the optimal facility in a stress-free environment. As a result, human effort will be reduced, providing added value through more efficient use of time.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The server retrieves information from various information management and reservation management systems. Information is retrieved via APIs, with raw data transmitted from each system as input. The server aggregates this data and preprocesses it to extract only the necessary items. The output is an integrated dataset.

[0080] Step 2:

[0081] The server anonymizes the acquired data. The input is an integrated dataset, and the server applies an algorithm to remove or replace personally identifiable information. This ensures the protection of personal information. The output is an anonymized dataset.

[0082] Step 3:

[0083] The server analyzes facility usage patterns based on anonymized data. It uses machine learning algorithms to analyze the data and identify periods of low utilization. The input here is an anonymized dataset, and the server uses algorithms to derive trends and patterns. The output is the analysis results of the usage patterns.

[0084] Step 4:

[0085] The terminal receives a reservation request from the user. The input is the details of the reservation request entered by the user into the terminal, including the date, time, and the number of participants required. The terminal sends this request to the server. The output is the user's reservation request.

[0086] Step 5:

[0087] The server selects the most suitable facility based on the user's reservation request and the analyzed usage patterns. The input consists of the user's reservation preference and the results of the usage pattern analysis. The server then matches this information against its database and selects the most suitable available facility and time slot. The output is a list of suggested facilities and time slots.

[0088] Step 6:

[0089] The server notifies the user of the most suitable facility reservation options. The input is information about the optimized facility and time slot. The server sends this information as a message to the terminal. The output provides the user with the suggested reservation information.

[0090] Step 7:

[0091] The server monitors reservations that may become unused and automatically cancels them if there is no response. Inputs are the current reservation status data and user responses. The server cancels reservations deemed unused and notifies the relevant systems of this information. The output is the updated reservation status.

[0092] Step 8:

[0093] The server generates optimization suggestions based on facility usage data. The input is accumulated usage data. The server generates suggestions for efficient space use and sends them to the terminal. The optimization suggestions are then notified to users and administrators as output.

[0094] (Application Example 1)

[0095] 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."

[0096] In modern society, improving the efficiency of shared facilities is crucial for maximizing the use of time and resources. However, many current reservation systems have problems with efficient reservation management, as checking whether a suitable facility is available when a user desires it is cumbersome. Furthermore, there is a lack of systems that automatically make appropriate layout changes or suggestions based on facility usage, resulting in inefficient use of space. Therefore, there is a need for a system that can quickly and automatically optimize facility reservations and flexibly utilize space based on usage trends.

[0097] 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.

[0098] In this invention, the server includes means for proposing the optimal facility and time based on user requests for collective facilities within a city area, means for immediately proposing the optimal facility when a user inputs their usage request via a terminal device, and means for providing information including proposed changes to the facility arrangement based on usage trends. This enables the optimization of facility reservations in response to user requests quickly. Furthermore, it improves the efficiency of facility utilization and makes effective use of time and resources.

[0099] A "data processing device" is a device that has the function of acquiring data from various electronic schedule systems and reservation management systems and anonymizing that data.

[0100] "Anonymization" is a technology that securely processes data by removing or transforming information that could identify an individual.

[0101] "Collective facilities" refers to all spaces used for holding meetings and events.

[0102] "Usage status" refers to information about how a particular facility or system is being used.

[0103] "Optimization" is the process of making adjustments or changes to achieve maximum or minimum efficiency under specified conditions.

[0104] "Automatic adjustment" refers to a system's ability to autonomously adjust itself according to the situation and conditions without user intervention.

[0105] "Usage data" refers to information regarding the frequency, duration, and number of users of facilities and services.

[0106] "Urban area" refers to the entire area within a specific region where urban planning and service provision take place.

[0107] A "terminal device" is a device used by a user to interact with and operate a system.

[0108] "Usage trends" refer to data and analysis results based on the behavior and patterns of typical users.

[0109] "Arrangement change proposal" refers to specific suggestions for optimizing the layout within a facility.

[0110] This invention constructs a system to improve the utilization efficiency of collective facilities. The server first uses a data processing device to acquire data from various electronic schedule systems and reservation management systems, and then anonymizes it. This makes it possible to manage reservations efficiently while protecting user privacy.

[0111] Based on the anonymized data it acquires, the server instantly monitors the usage status of the facilities and detects available reservations. The detected available reservation information is provided in a format that users can easily access from their terminal devices. Furthermore, the server can instantly suggest the most suitable facilities and times based on the user's input.

[0112] The terminal functions as the user interface and is used when users enter their usage requests. Users can make facility reservations through the terminal and receive optimized notifications once the reservation is complete.

[0113] The server can also analyze usage trends and generate proposed changes to the facility layout. This information is provided to users and administrators via terminals, resulting in a real-time, optimized user environment.

[0114] As a concrete example, a user might enter a prompt like this: "We have a meeting scheduled for next Tuesday at a community center in the city with five people. Please suggest the best venue." The system can then use a generative AI model to provide the user with the most suitable suggestion. These processes may utilize software such as Python or Flask.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server retrieves data from the electronic schedule system and the reservation management system. It receives access information to the APIs and databases of each system as input, and outputs raw reservation data. This data includes information such as date, time, number of participants, and facility name.

[0118] Step 2:

[0119] The server anonymizes the raw reservation data it retrieves. It receives the reservation data obtained in the previous step as input and outputs anonymized data by removing or transforming personally identifiable information. This process involves data processing to protect privacy.

[0120] Step 3:

[0121] The server monitors the usage status of collective facilities using anonymized data. It receives anonymized data as input and performs real-time analysis to output facility usage and availability information. Usage status is represented by the facility name and available time slots.

[0122] Step 4:

[0123] The terminal receives usage request data from users. It receives information such as the user's desired date, time, and number of participants as input, and sends it to the server. This clarifies the conditions the user is looking for.

[0124] Step 5:

[0125] The server suggests the most suitable facility and time based on the user's request data. Using user request data and availability information from the terminal as input, it generates the optimal suggestion through an optimization algorithm. The output is the name of the facility and time slot immediately available to the user.

[0126] Step 6:

[0127] The user receives and reviews suggestions from the server. They receive suggestions for the most suitable facilities and time slots as input, and take action to confirm them as a reservation if necessary. The output is a reservation confirmation notification.

[0128] Step 7:

[0129] The server generates and provides administrators with proposed facility layouts based on usage trends. It uses historical usage data and trend analysis results as input, and a generative AI model to create optimized layouts. The output is presented as a concrete, efficient facility layout plan.

[0130] 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.

[0131] This invention provides a system that combines an emotion engine to enable efficient and comfortable use of conference facilities. This system collects and anonymizes data from multiple electronic scheduling and reservation management systems via a data processing device, and a server monitors the usage status of conference facilities in real time based on this data. Furthermore, the server uses sensor information and data from IoT devices to detect available reservations and propose optimizations.

[0132] In particular, this invention incorporates an emotion engine that can detect the user's emotional state. The emotion engine analyzes the user's emotions from their voice, facial expression data, and operation history, and generates suggestions to adjust the optimal reservation and layout according to emotions such as stress and anxiety. If the user is satisfied with the success of their reservation, the system will provide services that reflect their individual emotions, such as prioritizing the provision of a similar meeting environment.

[0133] For example, when a user fails to book a meeting, the emotion engine detects the user's stress level. Based on this information, the server prioritizes suggesting alternative time slots or more convenient meeting facilities. The terminal also suggests the possibility of being put on a waiting list or other options to the user, aiming to improve satisfaction.

[0134] Furthermore, the analyzed emotional data can be applied to suggesting layouts for meeting facilities. To provide a less stressful environment, it can suggest the installation of more private phone booths and the creation of relaxing spaces. The terminal notifies the users and facility managers who receive these suggestions, supporting their final decision-making.

[0135] The system of this invention makes it possible not only to efficiently utilize meeting facilities but also to create a stress-free and comfortable meeting environment that takes into account the emotional state of users. This provides work style support optimized for individual needs and improves overall work efficiency.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] The server retrieves data from the electronic scheduling and reservation management systems and anonymizes it. This prepares the system to track reservation status while protecting personal information.

[0139] Step 2:

[0140] The server monitors facility usage in real time based on information from sensors and IoT devices installed in the conference facility, and continuously updates the database.

[0141] Step 3:

[0142] The emotion engine recognizes emotions from the user's voice input and operation history. This allows for the evaluation of user stress and satisfaction levels, and provides insights.

[0143] Step 4:

[0144] The server analyzes anonymized data and feedback from the emotion engine to identify available reservations and present an optimized reservation plan. At this stage, optimization is applied based on the user's emotional state.

[0145] Step 5:

[0146] The terminal notifies the user of reservation suggestions provided by the server. From the suggested reservations, the user can select the meeting schedule that best suits their needs.

[0147] Step 6:

[0148] If an available reservation is detected, the server sends a notification to the user of that reservation, and if there is no response within a certain period of time, it initiates a procedure to automatically cancel the reservation.

[0149] Step 7:

[0150] The server generates meeting facility layout suggestions based on data obtained from the emotion engine. This includes specific improvement measures to create a more comfortable environment for users.

[0151] Step 8:

[0152] The terminal notifies the conference facility operator of layout suggestions from the server. The operator evaluates the suggestions and makes changes to the facility settings as needed.

[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] In conventional use of meeting and other facilities, monitoring of usage and optimization of reservations are insufficient, leading to problems such as inefficient use of space and decreased user satisfaction. Furthermore, reservations and seating arrangements are often made without considering user emotions or stress levels, making it difficult to ensure a comfortable user environment. There is a need for a system that integrates real-time reservation optimization with personalized recommendations based on user emotions.

[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 means for acquiring data from various information management systems and reservation management systems from a data processing device and anonymizing the data; means for monitoring the usage status of the facility in real time using the anonymized data and detecting available reservations; and means for analyzing the emotional state using the user's voice, facial expressions, or operation history and generating optimal suggestions according to the user's emotions. This enables efficient use of the facility and the provision of a comfortable environment that takes into account the user's emotions.

[0158] A "data processing device" is hardware or software used to collect, analyze, anonymize, and process various types of data.

[0159] "Anonymization" is a process that protects privacy by converting personally identifiable information into a form that makes it impossible to identify an individual.

[0160] "Usage status" refers to information that indicates how facilities and resources are being used.

[0161] "Real-time monitoring" refers to the ability to instantly acquire current conditions and data, and to immediately evaluate and display them.

[0162] An "available reservation" refers to a reservation slot that is not currently being used and is available for free use.

[0163] "Optimization" refers to adjusting a system or process to its most efficient or effective state for a specific purpose.

[0164] "Emotional state" refers to data that indicates the user's psychological state and feelings.

[0165] A "suggestion" is the presentation of recommended actions or options based on a specific situation.

[0166] "Layout" is a concept that refers to the arrangement and structure of elements in a physical space.

[0167] A "user" is an individual or legal entity that uses a system or service.

[0168] This invention is a system for supporting the efficient and comfortable use of conference facilities and other various facilities. This system includes a data processing unit, an emotion engine, a server, and terminal devices.

[0169] The server retrieves data from information management systems and reservation management systems and anonymizes this data. A hash algorithm is used to anonymize the data and protect personal information. Using this anonymized data, the server monitors facility usage in real time. Specifically, the server uses a database management system to organize and store the collected information, enabling real-time access.

[0170] Furthermore, the server aggregates data from sensors and IoT devices installed within the facility and uses this data to detect available reservations. The server analyzes the obtained data and proposes the optimal reservation plan. This allows users to utilize the facility more effectively.

[0171] The emotion engine combines voice analysis software and facial recognition software to analyze the user's emotional state. It analyzes the user's voice tone and infers emotions based on data acquired by a facial recognition camera. Based on these analysis results, the server suggests reservations and layouts that are suitable for the user.

[0172] The terminal notifies the user of suggestions provided by the server. The user can review reservations through the terminal and make adjustments as needed. The terminal's interface is intuitive and interactive, ensuring high user convenience.

[0173] For example, if a user fails to book a meeting, the emotion engine detects their stress level. Based on this information, the server suggests alternative meeting rooms or available time slots to the user's device. The device then reviews these suggestions and provides the best option for the user.

[0174] An example of a prompt based on sentiment analysis using a generative AI model is, "Please suggest the best option to alleviate the user's stress caused by a booking failure." This allows the system to always consider the user's emotions and support a comfortable and effective user experience.

[0175] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0176] Step 1:

[0177] The server retrieves data from information management systems and reservation management systems. It receives schedule data and reservation lists via APIs as input and stores them in a database. After retrieving the data, it anonymizes it using a hash algorithm to protect personal information. This makes it possible to generate anonymous data that cannot be used for personal identification.

[0178] Step 2:

[0179] The server uses anonymized data to monitor facility usage in real time. It collects input data from sensors and IoT devices and generates status reports on usage. Specifically, it executes database queries to identify which facilities are in use and which are available. As output, it updates the usage dashboard to visualize the monitoring information.

[0180] Step 3:

[0181] The server analyzes real-time usage data to detect available reservations. It compares the current facility reservation status with user reservation requests as input. Statistical algorithms are used to calculate the most efficient reservation schedule. As output, it identifies the optimal reservation time slot and provides it to the user.

[0182] Step 4:

[0183] The emotion engine receives user voice data and facial expression data as input. It uses voice analysis and facial recognition technologies to evaluate the user's emotional state. Specifically, it performs voice tone analysis and monitors changes in facial expressions. As output, it quantifies the user's stress and anxiety levels and records their emotional state.

[0184] Step 5:

[0185] The server provides user-friendly booking and layout suggestions based on analyzed sentiment data. It receives the user's sentiment state and booking request as input, and uses an analytics model to calculate optimal suggestions. Specifically, it suggests environments and time slots predicted to be more comfortable based on the sentiment analysis results. The output provides the user with personalized booking guidance.

[0186] Step 6:

[0187] The terminal notifies the user of suggested information received from the server. The user reviews the suggestions via the terminal's interface and makes an appropriate selection. As output, the user sends the final selected reservation details to the server to confirm the reservation. This ensures efficient facility use and improves user satisfaction.

[0188] (Application Example 2)

[0189] 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".

[0190] Providing an efficient and comfortable environment that takes into account the emotional state of users in physical stores and meeting facilities presents challenges. Traditional reservation systems and methods for understanding user stress levels are insufficient, resulting in a lack of expected improvements in customer satisfaction.

[0191] 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.

[0192] In this invention, the server includes means for acquiring and anonymizing information from an information management system and a reservation management system, means for monitoring usage status in real time and detecting available time, and means for analyzing the customer's emotional state using an emotion analysis engine and making optimal suggestions. This makes it possible to provide an optimal reservation environment tailored to the user's emotional state.

[0193] A "data processing device" is a device that acquires information from various information management systems and reservation management systems, and processes this information after anonymizing it.

[0194] "Anonymization" is a technique that transforms information into a form that does not identify individuals, thereby making data usable while protecting privacy.

[0195] An "emotion analysis engine" is a technology that analyzes a customer's emotional state from data such as their voice and facial expressions to detect stress, anxiety, and other emotional states.

[0196] "Real-time monitoring" is a technology that allows for immediate monitoring of ongoing situations and instantaneous action to be taken as needed.

[0197] "Optimization" is the process of adjusting conditions to suit a specific objective in order to obtain efficient and effective results.

[0198] "Notification" refers to the process of sending information from a system to a user and providing them with necessary actions or information.

[0199] An "alternative service" is a service that offers alternative options to the original service, tailored to the user's preferences and circumstances.

[0200] The system according to the present invention enables reservation management that takes into account the emotional state of users in physical stores and meeting facilities. This system consists of the following elements.

[0201] The server retrieves and anonymizes information from the information management system and reservation management system. This allows for efficient processing of necessary data while protecting user privacy. The server also monitors facility usage in real time, detects available time slots, and provides users with the most suitable reservation options. Furthermore, the server uses an emotion analysis engine to analyze users' voices and facial expressions to determine their stress levels and emotional states. Based on these analysis results, it suggests available time slots and alternative services to provide users with the best possible environment.

[0202] The terminal receives notifications from the server and presents optimized reservation information based on the user's emotional state. These notifications help users reduce stress and frustration, allowing them to enjoy a more comfortable reservation experience. For example, if a customer visits a crowded store, the terminal can suggest less busy times and notify them of benefits for future visits, thereby increasing customer satisfaction.

[0203] For example, if a customer attempts to book a meeting but fails, the system automatically analyzes the customer's emotions, detects that the user is experiencing high stress levels, and then suggests available times. A possible prompt in this case would be, "Detect the customer's stress level and suggest what services should be provided."

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The server retrieves information from the information management system and reservation management system, and anonymizes the received raw data. The input is raw data containing user identification information, and the output is anonymized data. Data anonymization protects privacy by transforming the data into a form that does not identify individuals, while still making it possible to perform data analysis.

[0207] Step 2:

[0208] The server monitors anonymized data in real time to detect facility vacancies. The input is anonymized usage data, and the output is vacancy information. Monitoring analyzes current usage and identifies the next available time slots, optimizing facility operations.

[0209] Step 3:

[0210] The server uses an emotion analysis engine to analyze the user's voice and facial expression data. The input is voice and image data obtained from the user, and the output is the analyzed emotional state. The server processes this data to identify emotions such as stress and anxiety. The emotion analysis engine achieves this by analyzing fluctuation patterns in voice and image data.

[0211] Step 4:

[0212] The server calculates and suggests the most suitable booking options and alternative services to the user based on availability information and emotional state. The input is availability information and emotional state data, and the output is the suggested booking options. The server uses a generative AI model to present the optimal time slots and services tailored to the emotional state.

[0213] Step 5:

[0214] The terminal notifies the user of suggestions received from the server. The input is the suggestion information sent from the server, and the output is the notification on the user's terminal. The terminal uses its notification function to display reservation information and alternatives optimized for the user. This makes it easy for the user to make the best choice.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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).

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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".

[0231] The system according to the present invention is based on the principle of acquiring data from multiple electronic scheduling systems and reservation management systems using a data processing device, anonymizing that data, and then analyzing it, in order to achieve efficient management of conference facilities. The server uses this data to monitor the usage status of conference facilities in real time and automatically detect available reservations.

[0232] This system uses a server to analyze user schedule data and identify underutilized time slots and trends in available bookings. This enables the optimization and automatic adjustment of appropriate meeting facility reservations. Based on the analysis results from the server, users can receive information on which meeting facilities are available and what the optimal dates and times are.

[0233] As a concrete example, suppose a user wants to hold a meeting the following Tuesday and sends a reservation request via their device. The server first receives the request and, considering existing reservation data and the availability of meeting facilities on that day from the electronic scheduling system, suggests the most suitable meeting room and time. If a reservation becomes available, the server automatically cancels it and offers the user the opportunity.

[0234] Furthermore, the server generates optimization suggestions for the meeting facility layout based on the analysis. For example, for a meeting room frequently used by two people, it suggests changing it to a phone booth to help utilize the space more efficiently. This suggestion is notified to users and operators via terminals, and a final decision is made based on their feedback.

[0235] This system significantly improves the operational efficiency of meeting facilities, creating an environment where users can use meeting rooms when needed without stress. Because these processes are automated, human resources are drastically reduced, allowing for more efficient use of time.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] The server periodically retrieves meeting facility reservation data via APIs from multiple electronic scheduling and reservation management systems. The retrieved data is stored in a database on the server.

[0239] Step 2:

[0240] The server anonymizes the acquired data. Specifically, it replaces personally identifiable information such as user IDs and personal names with random identifiers and stores it in a database in a format that protects privacy.

[0241] Step 3:

[0242] The server monitors the real-time usage status of meeting facilities based on anonymized data. Using input from sensors and IoT devices installed in meeting rooms, it verifies actual usage and identifies available reservations.

[0243] Step 4:

[0244] The server analyzes usage and reservation data to calculate the optimal reservation schedule. It analyzes reservation imbalances and trends in available reservations to generate an efficient usage schedule.

[0245] Step 5:

[0246] The terminal notifies the user of optimized reservation information provided by the server. The user reviews the proposal presented through the terminal and approves or modifies the reservation as needed.

[0247] Step 6:

[0248] When the server detects an available reservation, it sends a confirmation notification to the user. If the user does not respond within a certain period of time, the server automatically initiates a procedure to cancel the reservation.

[0249] Step 7:

[0250] The server analyzes the usage data of meeting facilities and, if meetings with only two people occur frequently, generates suggestions for layout improvements, such as moving to smaller spaces like phone booths.

[0251] Step 8:

[0252] The terminal notifies the facility administrator of the layout proposal from the server and receives feedback. Based on this feedback, the final layout changes are decided.

[0253] (Example 1)

[0254] 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."

[0255] Efficiently managing the booking status of meeting facilities and event spaces and minimizing unused time slots is a major challenge for many companies and organizations. Currently, duplicate bookings and unused bookings are frequent, reducing the operational efficiency of facilities. Furthermore, a lack of information necessary for users to select appropriate facilities is hindering a smooth booking process.

[0256] 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.

[0257] In this invention, the server includes means for acquiring information from various information management systems and reservation management systems from an information processing device and anonymizing the information; means for optimizing and automatically adjusting facility reservations based on the usage status; and means for analyzing usage patterns using a machine learning algorithm and identifying time periods with low utilization rates. This makes it possible to improve the efficiency of facility utilization and to quickly provide appropriate facility information to users.

[0258] An "information processing device" is a device that acquires and processes information from various information management systems and reservation management systems.

[0259] "Anonymization" is a process that transforms information so that personal information cannot be identified, thereby protecting privacy.

[0260] A "facility" is a space or building used for holding meetings or events.

[0261] An "unused reservation" is a reservation that has been made but has not actually been used.

[0262] "Optimization" is the process of adjusting and improving how resources are used and allocated in order to increase their efficiency.

[0263] A "machine learning algorithm" is a computational method that analyzes data and learns patterns to improve future predictions and decisions.

[0264] "Usage patterns" refer to the tendencies and habits that indicate how facility users utilize the facility.

[0265] A "user terminal" is a computer device used by a user to receive and input information.

[0266] This invention relates to a system that efficiently and automatically optimizes the use of conference facilities. The server operates as an information processing device and is connected to various information management and reservation management systems. This allows the server to acquire necessary information and anonymize it. The server uses machine learning algorithms to analyze the collected data and learn patterns of facility usage. This enables the identification of time slots with low utilization rates and the optimization of facility reservations.

[0267] Furthermore, the server provides users with information on the most suitable facility for booking via their terminals. For example, if a user wants to use a facility next Tuesday, they can simply type "I would like to have a two-hour meeting next Tuesday. Please find and book the most suitable meeting facility" into their terminal, and the server will suggest the most suitable facility and automatically process the booking.

[0268] The server also monitors potentially unused reservations in real time and automatically cancels them if no action is taken by the user. Finally, the server can generate optimization suggestions for the facility's structure based on usage data. This information is communicated to users and administrators via terminals to promote efficient operation.

[0269] Implementing this system will significantly improve the efficiency of meeting facility utilization, allowing users to access the optimal facility in a stress-free environment. As a result, human effort will be reduced, providing added value through more efficient use of time.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] The server retrieves information from various information management and reservation management systems. Information is retrieved via APIs, with raw data transmitted from each system as input. The server aggregates this data and preprocesses it to extract only the necessary items. The output is an integrated dataset.

[0273] Step 2:

[0274] The server anonymizes the acquired data. The input is an integrated dataset, and the server applies an algorithm to remove or replace personally identifiable information. This ensures the protection of personal information. The output is an anonymized dataset.

[0275] Step 3:

[0276] The server analyzes the facility usage patterns based on the anonymized data. It uses machine learning algorithms to analyze the data and identify time periods with low utilization rates. The input here is the anonymized dataset, and the server derives trends and patterns through the algorithms. As output, the analysis results of the usage patterns are obtained.

[0277] Step 4:

[0278] The terminal receives a reservation request from the user. The input is the details of the reservation desired by the user entered into the terminal. This includes the date, time, required number of participants, etc. The terminal sends this request to the server. As output, the user's reservation desire is obtained.

[0279] Step 5:

[0280] The server selects the optimal facility based on the user's reservation request and the analyzed usage patterns. The input is the user's reservation desire and the analysis results of the usage patterns. The server checks the database and selects the optimal available facility and time. As output, a list of the proposed facilities and time periods is obtained.

[0281] Step 6:

[0282] The server notifies the user of the candidates for the optimal facility reservation. The input is the information on the optimized facility and time period. The server sends this information to the terminal as a message. As output, the reservation information proposed to the user is provided.

[0283] Step 7:

[0284] The server monitors reservations that may become unused and automatically cancels the reservation in case of no response. The input is the current reservation status data and the user's response. The server cancels the reservation judged to be unused and notifies that information to the relevant system. As output, the updated reservation status is obtained.

[0285] Step 8:

[0286] The server generates optimization proposals based on the usage data of the facility. The input is the accumulated usage data. The server generates proposals regarding the efficient use of space and transmits them to the terminal. As output, the optimization proposals are notified to the user or administrator.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] In modern society, improving the utilization efficiency of collective facilities is important for maximizing the use of time and resources. However, many current reservation systems have the problem that it is cumbersome to check whether a facility suitable for the time desired by the user is available, and it is difficult to manage reservations efficiently. In addition, there is a lack of a system that automatically makes appropriate layout changes or proposals based on the usage status of the facility, so the space cannot be optimally utilized. For this reason, there is a need for a system that can quickly and automatically optimize facility reservations and flexibly utilize space based on usage trends.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0291] In this invention, the server includes means for proposing an optimal facility and time based on the user's request for a collective facility within the urban area, means for immediately proposing an optimal facility when the user inputs a usage desire via the terminal device, and means for providing information including a facility arrangement change plan based on usage trends. Thereby, it becomes possible to optimize facility reservations in response to the user's request quickly. Also, the utilization efficiency of the facility is improved, and it becomes possible to effectively utilize time and resources.

[0292] The "data processing device" is a device that has the function of acquiring data from various electronic progress table systems and reservation management systems and anonymizing it.

[0293] "Anonymization" is a technology that securely processes data by removing or transforming information that could identify an individual.

[0294] "Collective facilities" refers to all spaces used for holding meetings and events.

[0295] "Usage status" refers to information about how a particular facility or system is being used.

[0296] "Optimization" is the process of making adjustments or changes to achieve maximum or minimum efficiency under specified conditions.

[0297] "Automatic adjustment" refers to a system's ability to autonomously adjust itself according to the situation and conditions without user intervention.

[0298] "Usage data" refers to information regarding the frequency, duration, and number of users of facilities and services.

[0299] "Urban area" refers to the entire area within a specific region where urban planning and service provision take place.

[0300] A "terminal device" is a device used by a user to interact with and operate a system.

[0301] "Usage trends" refer to data and analysis results based on the behavior and patterns of typical users.

[0302] "Arrangement change proposal" refers to specific suggestions for optimizing the layout within a facility.

[0303] This invention constructs a system for improving the utilization efficiency of collective facilities. First, the server uses a data processing device to obtain data from various electronic schedule systems and reservation management systems, and anonymizes it. This enables efficient reservation management while protecting the privacy of users.

[0304] Based on the obtained anonymized data, the server immediately monitors the usage status of the collective facilities and detects available reservations. The detected available reservation information is provided in a state where it can be easily accessed by users from the terminal device. Furthermore, the server can immediately propose the optimal facility and time according to the user's input request.

[0305] The terminal functions as an interface for users and is used when users input their usage requests. Users can make reservations for facilities through the terminal and receive optimized notifications when the reservation is completed.

[0306] The server can also analyze usage trends and generate proposals for changing the layout of the facilities. This information is provided to users and administrators via the terminal, realizing an optimized usage environment in real time.

[0307] As a specific example, it is conceivable that a user inputs the following prompt. "I am planning a meeting for 5 people at a collective facility in the city next Tuesday. Please propose the optimal facility." Thereby, the system can utilize the generative AI model to provide an optimal proposal to the user. Software such as Python and Flask may be used in these processes.

[0308] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The server retrieves data from the electronic schedule system and the reservation management system. It receives access information to the APIs and databases of each system as input, and outputs raw reservation data. This data includes information such as date, time, number of participants, and facility name.

[0311] Step 2:

[0312] The server anonymizes the raw reservation data it retrieves. It receives the reservation data obtained in the previous step as input and outputs anonymized data by removing or transforming personally identifiable information. This process involves data processing to protect privacy.

[0313] Step 3:

[0314] The server monitors the usage status of collective facilities using anonymized data. It receives anonymized data as input and performs real-time analysis to output facility usage and availability information. Usage status is represented by the facility name and available time slots.

[0315] Step 4:

[0316] The terminal receives usage request data from users. It receives information such as the user's desired date, time, and number of participants as input, and sends it to the server. This clarifies the conditions the user is looking for.

[0317] Step 5:

[0318] The server suggests the most suitable facility and time based on the user's request data. Using user request data and availability information from the terminal as input, it generates the optimal suggestion through an optimization algorithm. The output is the name of the facility and time slot immediately available to the user.

[0319] Step 6:

[0320] The user receives and reviews suggestions from the server. They receive suggestions for the most suitable facilities and time slots as input, and take action to confirm them as a reservation if necessary. The output is a reservation confirmation notification.

[0321] Step 7:

[0322] The server generates and provides administrators with proposed facility layouts based on usage trends. It uses historical usage data and trend analysis results as input, and a generative AI model to create optimized layouts. The output is presented as a concrete, efficient facility layout plan.

[0323] 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.

[0324] This invention provides a system that combines an emotion engine to enable efficient and comfortable use of conference facilities. This system collects and anonymizes data from multiple electronic scheduling and reservation management systems via a data processing device, and a server monitors the usage status of conference facilities in real time based on this data. Furthermore, the server uses sensor information and data from IoT devices to detect available reservations and propose optimizations.

[0325] In particular, this invention incorporates an emotion engine that can detect the user's emotional state. The emotion engine analyzes the user's emotions from their voice, facial expression data, and operation history, and generates suggestions to adjust the optimal reservation and layout according to emotions such as stress and anxiety. If the user is satisfied with the success of their reservation, the system will provide services that reflect their individual emotions, such as prioritizing the provision of a similar meeting environment.

[0326] For example, when a user fails to book a meeting, the emotion engine detects the user's stress level. Based on this information, the server prioritizes suggesting alternative time slots or more convenient meeting facilities. The terminal also suggests the possibility of being put on a waiting list or other options to the user, aiming to improve satisfaction.

[0327] Furthermore, the analyzed emotional data can be applied to suggesting layouts for meeting facilities. To provide a less stressful environment, it can suggest the installation of more private phone booths and the creation of relaxing spaces. The terminal notifies the users and facility managers who receive these suggestions, supporting their final decision-making.

[0328] The system of this invention makes it possible not only to efficiently utilize meeting facilities but also to create a stress-free and comfortable meeting environment that takes into account the emotional state of users. This provides work style support optimized for individual needs and improves overall work efficiency.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] The server retrieves data from the electronic scheduling and reservation management systems and anonymizes it. This prepares the system to track reservation status while protecting personal information.

[0332] Step 2:

[0333] The server monitors facility usage in real time based on information from sensors and IoT devices installed in the conference facility, and continuously updates the database.

[0334] Step 3:

[0335] The emotion engine recognizes emotions from the user's voice input and operation history. This allows for the evaluation of user stress and satisfaction levels, and provides insights.

[0336] Step 4:

[0337] The server analyzes anonymized data and feedback from the emotion engine to identify available reservations and present an optimized reservation plan. At this stage, optimization is applied based on the user's emotional state.

[0338] Step 5:

[0339] The terminal notifies the user of reservation suggestions provided by the server. From the suggested reservations, the user can select the meeting schedule that best suits their needs.

[0340] Step 6:

[0341] If an available reservation is detected, the server sends a notification to the user of that reservation, and if there is no response within a certain period of time, it initiates a procedure to automatically cancel the reservation.

[0342] Step 7:

[0343] The server generates meeting facility layout suggestions based on data obtained from the emotion engine. This includes specific improvement measures to create a more comfortable environment for users.

[0344] Step 8:

[0345] The terminal notifies the conference facility operator of layout suggestions from the server. The operator evaluates the suggestions and makes changes to the facility settings as needed.

[0346] (Example 2)

[0347] 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".

[0348] In conventional use of meeting and other facilities, monitoring of usage and optimization of reservations are insufficient, leading to problems such as inefficient use of space and decreased user satisfaction. Furthermore, reservations and seating arrangements are often made without considering user emotions or stress levels, making it difficult to ensure a comfortable user environment. There is a need for a system that integrates real-time reservation optimization with personalized recommendations based on user emotions.

[0349] 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.

[0350] In this invention, the server includes means for acquiring data from various information management systems and reservation management systems from a data processing device and anonymizing the data; means for monitoring the usage status of the facility in real time using the anonymized data and detecting available reservations; and means for analyzing the emotional state using the user's voice, facial expressions, or operation history and generating optimal suggestions according to the user's emotions. This enables efficient use of the facility and the provision of a comfortable environment that takes into account the user's emotions.

[0351] A "data processing device" is hardware or software used to collect, analyze, anonymize, and process various types of data.

[0352] "Anonymization" is a process that protects privacy by converting personally identifiable information into a form that makes it impossible to identify an individual.

[0353] "Usage status" refers to information that indicates how facilities and resources are being used.

[0354] "Real-time monitoring" refers to the ability to instantly acquire current conditions and data, and to immediately evaluate and display them.

[0355] An "available reservation" refers to a reservation slot that is not currently being used and is available for free use.

[0356] "Optimization" refers to adjusting a system or process to its most efficient or effective state for a specific purpose.

[0357] "Emotional state" refers to data that indicates the user's psychological state and feelings.

[0358] A "suggestion" is the presentation of recommended actions or options based on a specific situation.

[0359] "Layout" is a concept that refers to the arrangement and structure of elements in a physical space.

[0360] A "user" is an individual or legal entity that uses a system or service.

[0361] This invention is a system for supporting the efficient and comfortable use of conference facilities and other various facilities. This system includes a data processing unit, an emotion engine, a server, and terminal devices.

[0362] The server retrieves data from information management systems and reservation management systems and anonymizes this data. A hash algorithm is used to anonymize the data and protect personal information. Using this anonymized data, the server monitors facility usage in real time. Specifically, the server uses a database management system to organize and store the collected information, enabling real-time access.

[0363] Furthermore, the server aggregates data from sensors and IoT devices installed within the facility and uses this data to detect available reservations. The server analyzes the obtained data and proposes the optimal reservation plan. This allows users to utilize the facility more effectively.

[0364] The emotion engine combines voice analysis software and facial recognition software to analyze the user's emotional state. It analyzes the user's voice tone and infers emotions based on data acquired by a facial recognition camera. Based on these analysis results, the server suggests reservations and layouts that are suitable for the user.

[0365] The terminal notifies the user of suggestions provided by the server. The user can review reservations through the terminal and make adjustments as needed. The terminal's interface is intuitive and interactive, ensuring high user convenience.

[0366] For example, if a user fails to book a meeting, the emotion engine detects their stress level. Based on this information, the server suggests alternative meeting rooms or available time slots to the user's device. The device then reviews these suggestions and provides the best option for the user.

[0367] An example of a prompt based on sentiment analysis using a generative AI model is, "Please suggest the best option to alleviate the user's stress caused by a booking failure." This allows the system to always consider the user's emotions and support a comfortable and effective user experience.

[0368] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0369] Step 1:

[0370] The server retrieves data from information management systems and reservation management systems. It receives schedule data and reservation lists via APIs as input and stores them in a database. After retrieving the data, it anonymizes it using a hash algorithm to protect personal information. This makes it possible to generate anonymous data that cannot be used for personal identification.

[0371] Step 2:

[0372] The server uses anonymized data to monitor facility usage in real time. It collects input data from sensors and IoT devices and generates status reports on usage. Specifically, it executes database queries to identify which facilities are in use and which are available. As output, it updates the usage dashboard to visualize the monitoring information.

[0373] Step 3:

[0374] The server analyzes real-time usage data to detect available reservations. It compares the current facility reservation status with user reservation requests as input. Statistical algorithms are used to calculate the most efficient reservation schedule. As output, it identifies the optimal reservation time slot and provides it to the user.

[0375] Step 4:

[0376] The emotion engine receives user voice data and facial expression data as input. It uses voice analysis and facial recognition technologies to evaluate the user's emotional state. Specifically, it performs voice tone analysis and monitors changes in facial expressions. As output, it quantifies the user's stress and anxiety levels and records their emotional state.

[0377] Step 5:

[0378] The server provides user-friendly booking and layout suggestions based on analyzed sentiment data. It receives the user's sentiment state and booking request as input, and uses an analytics model to calculate optimal suggestions. Specifically, it suggests environments and time slots predicted to be more comfortable based on the sentiment analysis results. The output provides the user with personalized booking guidance.

[0379] Step 6:

[0380] The terminal notifies the user of suggested information received from the server. The user reviews the suggestions via the terminal's interface and makes an appropriate selection. As output, the user sends the final selected reservation details to the server to confirm the reservation. This ensures efficient facility use and improves user satisfaction.

[0381] (Application Example 2)

[0382] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0383] Providing an efficient and comfortable environment that takes into account the emotional state of users in physical stores and meeting facilities presents challenges. Traditional reservation systems and methods for understanding user stress levels are insufficient, resulting in a lack of expected improvements in customer satisfaction.

[0384] 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.

[0385] In this invention, the server includes means for acquiring and anonymizing information from an information management system and a reservation management system, means for monitoring usage status in real time and detecting available time, and means for analyzing the customer's emotional state using an emotion analysis engine and making optimal suggestions. This makes it possible to provide an optimal reservation environment tailored to the user's emotional state.

[0386] A "data processing device" is a device that acquires information from various information management systems and reservation management systems, and processes this information after anonymizing it.

[0387] "Anonymization" is a technique that transforms information into a form that does not identify individuals, thereby making data usable while protecting privacy.

[0388] An "emotion analysis engine" is a technology that analyzes a customer's emotional state from data such as their voice and facial expressions to detect stress, anxiety, and other emotional states.

[0389] "Real-time monitoring" is a technology that allows for immediate monitoring of ongoing situations and instantaneous action to be taken as needed.

[0390] "Optimization" is the process of adjusting conditions to suit a specific objective in order to obtain efficient and effective results.

[0391] "Notification" refers to the process of sending information from a system to a user and providing them with necessary actions or information.

[0392] An "alternative service" is a service that offers alternative options to the original service, tailored to the user's preferences and circumstances.

[0393] The system according to the present invention enables reservation management that takes into account the emotional state of users in physical stores and meeting facilities. This system consists of the following elements.

[0394] The server retrieves and anonymizes information from the information management system and reservation management system. This allows for efficient processing of necessary data while protecting user privacy. The server also monitors facility usage in real time, detects available time slots, and provides users with the most suitable reservation options. Furthermore, the server uses an emotion analysis engine to analyze users' voices and facial expressions to determine their stress levels and emotional states. Based on these analysis results, it suggests available time slots and alternative services to provide users with the best possible environment.

[0395] The terminal receives notifications from the server and presents optimized reservation information based on the user's emotional state. These notifications help users reduce stress and frustration, allowing them to enjoy a more comfortable reservation experience. For example, if a customer visits a crowded store, the terminal can suggest less busy times and notify them of benefits for future visits, thereby increasing customer satisfaction.

[0396] For example, if a customer attempts to book a meeting but fails, the system automatically analyzes the customer's emotions, detects that the user is experiencing high stress levels, and then suggests available times. A possible prompt in this case would be, "Detect the customer's stress level and suggest what services should be provided."

[0397] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0398] Step 1:

[0399] The server retrieves information from the information management system and reservation management system, and anonymizes the received raw data. The input is raw data containing user identification information, and the output is anonymized data. Data anonymization protects privacy by transforming the data into a form that does not identify individuals, while still making it possible to perform data analysis.

[0400] Step 2:

[0401] The server monitors anonymized data in real time to detect facility vacancies. The input is anonymized usage data, and the output is vacancy information. Monitoring analyzes current usage and identifies the next available time slots, optimizing facility operations.

[0402] Step 3:

[0403] The server uses an emotion analysis engine to analyze the user's voice and facial expression data. The input is voice and image data obtained from the user, and the output is the analyzed emotional state. The server processes this data to identify emotions such as stress and anxiety. The emotion analysis engine achieves this by analyzing fluctuation patterns in voice and image data.

[0404] Step 4:

[0405] The server calculates and suggests the most suitable booking options and alternative services to the user based on availability information and emotional state. The input is availability information and emotional state data, and the output is the suggested booking options. The server uses a generative AI model to present the optimal time slots and services tailored to the emotional state.

[0406] Step 5:

[0407] The terminal notifies the user of suggestions received from the server. The input is the suggestion information sent from the server, and the output is the notification on the user's terminal. The terminal uses its notification function to display reservation information and alternatives optimized for the user. This makes it easy for the user to make the best choice.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] [Third Embodiment]

[0412] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0413] 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.

[0414] 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).

[0415] 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.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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".

[0424] The system according to the present invention is based on the principle of acquiring data from multiple electronic scheduling systems and reservation management systems using a data processing device, anonymizing that data, and then analyzing it, in order to achieve efficient management of conference facilities. The server uses this data to monitor the usage status of conference facilities in real time and automatically detect available reservations.

[0425] This system uses a server to analyze user schedule data and identify underutilized time slots and trends in available bookings. This enables the optimization and automatic adjustment of appropriate meeting facility reservations. Based on the analysis results from the server, users can receive information on which meeting facilities are available and what the optimal dates and times are.

[0426] As a concrete example, suppose a user wants to hold a meeting the following Tuesday and sends a reservation request via their device. The server first receives the request and, considering existing reservation data and the availability of meeting facilities on that day from the electronic scheduling system, suggests the most suitable meeting room and time. If a reservation becomes available, the server automatically cancels it and offers the user the opportunity.

[0427] Furthermore, the server generates optimization suggestions for the meeting facility layout based on the analysis. For example, for a meeting room frequently used by two people, it suggests changing it to a phone booth to help utilize the space more efficiently. This suggestion is notified to users and operators via terminals, and a final decision is made based on their feedback.

[0428] This system significantly improves the operational efficiency of meeting facilities, creating an environment where users can use meeting rooms when needed without stress. Because these processes are automated, human resources are drastically reduced, allowing for more efficient use of time.

[0429] The following describes the processing flow.

[0430] Step 1:

[0431] The server periodically retrieves meeting facility reservation data via APIs from multiple electronic scheduling and reservation management systems. The retrieved data is stored in a database on the server.

[0432] Step 2:

[0433] The server anonymizes the acquired data. Specifically, it replaces personally identifiable information such as user IDs and personal names with random identifiers and stores it in a database in a format that protects privacy.

[0434] Step 3:

[0435] The server monitors the real-time usage status of meeting facilities based on anonymized data. Using input from sensors and IoT devices installed in meeting rooms, it verifies actual usage and identifies available reservations.

[0436] Step 4:

[0437] The server analyzes usage and reservation data to calculate the optimal reservation schedule. It analyzes reservation imbalances and trends in available reservations to generate an efficient usage schedule.

[0438] Step 5:

[0439] The terminal notifies the user of optimized reservation information provided by the server. The user reviews the proposal presented through the terminal and approves or modifies the reservation as needed.

[0440] Step 6:

[0441] When the server detects an available reservation, it sends a confirmation notification to the user. If the user does not respond within a certain period of time, the server automatically initiates a procedure to cancel the reservation.

[0442] Step 7:

[0443] The server analyzes the usage data of meeting facilities and, if meetings with only two people occur frequently, generates suggestions for layout improvements, such as moving to smaller spaces like phone booths.

[0444] Step 8:

[0445] The terminal notifies the facility administrator of the layout proposal from the server and receives feedback. Based on this feedback, the final layout changes are decided.

[0446] (Example 1)

[0447] 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."

[0448] Efficiently managing the booking status of meeting facilities and event spaces and minimizing unused time slots is a major challenge for many companies and organizations. Currently, duplicate bookings and unused bookings are frequent, reducing the operational efficiency of facilities. Furthermore, a lack of information necessary for users to select appropriate facilities is hindering a smooth booking process.

[0449] 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.

[0450] In this invention, the server includes means for acquiring information from various information management systems and reservation management systems from an information processing device and anonymizing the information; means for optimizing and automatically adjusting facility reservations based on the usage status; and means for analyzing usage patterns using a machine learning algorithm and identifying time periods with low utilization rates. This makes it possible to improve the efficiency of facility utilization and to quickly provide appropriate facility information to users.

[0451] An "information processing device" is a device that acquires and processes information from various information management systems and reservation management systems.

[0452] "Anonymization" is a process that transforms information so that personal information cannot be identified, thereby protecting privacy.

[0453] A "facility" is a space or building used for holding meetings or events.

[0454] An "unused reservation" is a reservation that has been made but has not actually been used.

[0455] "Optimization" is the process of adjusting and improving how resources are used and allocated in order to increase their efficiency.

[0456] A "machine learning algorithm" is a computational method that analyzes data and learns patterns to improve future predictions and decisions.

[0457] "Usage patterns" refer to the tendencies and habits that indicate how facility users utilize the facility.

[0458] A "user terminal" is a computer device used by a user to receive and input information.

[0459] This invention relates to a system that efficiently and automatically optimizes the use of conference facilities. The server operates as an information processing device and is connected to various information management and reservation management systems. This allows the server to acquire necessary information and anonymize it. The server uses machine learning algorithms to analyze the collected data and learn patterns of facility usage. This enables the identification of time slots with low utilization rates and the optimization of facility reservations.

[0460] Furthermore, the server provides users with information on the most suitable facility for booking via their terminals. For example, if a user wants to use a facility next Tuesday, they can simply type "I would like to have a two-hour meeting next Tuesday. Please find and book the most suitable meeting facility" into their terminal, and the server will suggest the most suitable facility and automatically process the booking.

[0461] The server also monitors potentially unused reservations in real time and automatically cancels them if no action is taken by the user. Finally, the server can generate optimization suggestions for the facility's structure based on usage data. This information is communicated to users and administrators via terminals to promote efficient operation.

[0462] Implementing this system will significantly improve the efficiency of meeting facility utilization, allowing users to access the optimal facility in a stress-free environment. As a result, human effort will be reduced, providing added value through more efficient use of time.

[0463] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0464] Step 1:

[0465] The server retrieves information from various information management and reservation management systems. Information is retrieved via APIs, with raw data transmitted from each system as input. The server aggregates this data and preprocesses it to extract only the necessary items. The output is an integrated dataset.

[0466] Step 2:

[0467] The server anonymizes the acquired data. The input is an integrated dataset, and the server applies an algorithm to remove or replace personally identifiable information. This ensures the protection of personal information. The output is an anonymized dataset.

[0468] Step 3:

[0469] The server analyzes facility usage patterns based on anonymized data. It uses machine learning algorithms to analyze the data and identify periods of low utilization. The input here is an anonymized dataset, and the server uses algorithms to derive trends and patterns. The output is the analysis results of the usage patterns.

[0470] Step 4:

[0471] The terminal receives a reservation request from the user. The input is the details of the reservation request entered by the user into the terminal, including the date, time, and the number of participants required. The terminal sends this request to the server. The output is the user's reservation request.

[0472] Step 5:

[0473] The server selects the most suitable facility based on the user's reservation request and the analyzed usage patterns. The input consists of the user's reservation preference and the results of the usage pattern analysis. The server then matches this information against its database and selects the most suitable available facility and time slot. The output is a list of suggested facilities and time slots.

[0474] Step 6:

[0475] The server notifies the user of the most suitable facility reservation options. The input is information about the optimized facility and time slot. The server sends this information as a message to the terminal. The output provides the user with the suggested reservation information.

[0476] Step 7:

[0477] The server monitors reservations that may become unused and automatically cancels them if there is no response. Inputs are the current reservation status data and user responses. The server cancels reservations deemed unused and notifies the relevant systems of this information. The output is the updated reservation status.

[0478] Step 8:

[0479] The server generates optimization suggestions based on facility usage data. The input is accumulated usage data. The server generates suggestions for efficient space use and sends them to the terminal. The optimization suggestions are then notified to users and administrators as output.

[0480] (Application Example 1)

[0481] 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."

[0482] In modern society, improving the efficiency of shared facilities is crucial for maximizing the use of time and resources. However, many current reservation systems have problems with efficient reservation management, as checking whether a suitable facility is available when a user desires it is cumbersome. Furthermore, there is a lack of systems that automatically make appropriate layout changes or suggestions based on facility usage, resulting in inefficient use of space. Therefore, there is a need for a system that can quickly and automatically optimize facility reservations and flexibly utilize space based on usage trends.

[0483] 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.

[0484] In this invention, the server includes means for proposing the optimal facility and time based on user requests for collective facilities within a city area, means for immediately proposing the optimal facility when a user inputs their usage request via a terminal device, and means for providing information including proposed changes to the facility arrangement based on usage trends. This enables the optimization of facility reservations in response to user requests quickly. Furthermore, it improves the efficiency of facility utilization and makes effective use of time and resources.

[0485] A "data processing device" is a device that has the function of acquiring data from various electronic schedule systems and reservation management systems and anonymizing that data.

[0486] "Anonymization" is a technology that securely processes data by removing or transforming information that could identify an individual.

[0487] "Collective facilities" refers to all spaces used for holding meetings and events.

[0488] "Usage status" refers to information about how a particular facility or system is being used.

[0489] "Optimization" is the process of making adjustments or changes to achieve maximum or minimum efficiency under specified conditions.

[0490] "Automatic adjustment" refers to a system's ability to autonomously adjust itself according to the situation and conditions without user intervention.

[0491] "Usage data" refers to information regarding the frequency, duration, and number of users of facilities and services.

[0492] "Urban area" refers to the entire area within a specific region where urban planning and service provision take place.

[0493] A "terminal device" is a device used by a user to interact with and operate a system.

[0494] "Usage trends" refer to data and analysis results based on the behavior and patterns of typical users.

[0495] "Arrangement change proposal" refers to specific suggestions for optimizing the layout within a facility.

[0496] This invention constructs a system to improve the utilization efficiency of collective facilities. The server first uses a data processing device to acquire data from various electronic schedule systems and reservation management systems, and then anonymizes it. This makes it possible to manage reservations efficiently while protecting user privacy.

[0497] Based on the anonymized data it acquires, the server instantly monitors the usage status of the facilities and detects available reservations. The detected available reservation information is provided in a format that users can easily access from their terminal devices. Furthermore, the server can instantly suggest the most suitable facilities and times based on the user's input.

[0498] The terminal functions as the user interface and is used when users enter their usage requests. Users can make facility reservations through the terminal and receive optimized notifications once the reservation is complete.

[0499] The server can also analyze usage trends and generate proposed changes to the facility layout. This information is provided to users and administrators via terminals, resulting in a real-time, optimized user environment.

[0500] As a concrete example, a user might enter a prompt like this: "We have a meeting scheduled for next Tuesday at a community center in the city with five people. Please suggest the best venue." The system can then use a generative AI model to provide the user with the most suitable suggestion. These processes may utilize software such as Python or Flask.

[0501] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0502] Step 1:

[0503] The server retrieves data from the electronic schedule system and the reservation management system. It receives access information to the APIs and databases of each system as input, and outputs raw reservation data. This data includes information such as date, time, number of participants, and facility name.

[0504] Step 2:

[0505] The server anonymizes the raw reservation data it retrieves. It receives the reservation data obtained in the previous step as input and outputs anonymized data by removing or transforming personally identifiable information. This process involves data processing to protect privacy.

[0506] Step 3:

[0507] The server monitors the usage status of collective facilities using anonymized data. It receives anonymized data as input and performs real-time analysis to output facility usage and availability information. Usage status is represented by the facility name and available time slots.

[0508] Step 4:

[0509] The terminal receives usage request data from users. It receives information such as the user's desired date, time, and number of participants as input, and sends it to the server. This clarifies the conditions the user is looking for.

[0510] Step 5:

[0511] The server suggests the most suitable facility and time based on the user's request data. Using user request data and availability information from the terminal as input, it generates the optimal suggestion through an optimization algorithm. The output is the name of the facility and time slot immediately available to the user.

[0512] Step 6:

[0513] The user receives and reviews suggestions from the server. They receive suggestions for the most suitable facilities and time slots as input, and take action to confirm them as a reservation if necessary. The output is a reservation confirmation notification.

[0514] Step 7:

[0515] The server generates and provides administrators with proposed facility layouts based on usage trends. It uses historical usage data and trend analysis results as input, and a generative AI model to create optimized layouts. The output is presented as a concrete, efficient facility layout plan.

[0516] 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.

[0517] This invention provides a system that combines an emotion engine to enable efficient and comfortable use of conference facilities. This system collects and anonymizes data from multiple electronic scheduling and reservation management systems via a data processing device, and a server monitors the usage status of conference facilities in real time based on this data. Furthermore, the server uses sensor information and data from IoT devices to detect available reservations and propose optimizations.

[0518] In particular, this invention incorporates an emotion engine that can detect the user's emotional state. The emotion engine analyzes the user's emotions from their voice, facial expression data, and operation history, and generates suggestions to adjust the optimal reservation and layout according to emotions such as stress and anxiety. If the user is satisfied with the success of their reservation, the system will provide services that reflect their individual emotions, such as prioritizing the provision of a similar meeting environment.

[0519] For example, when a user fails to book a meeting, the emotion engine detects the user's stress level. Based on this information, the server prioritizes suggesting alternative time slots or more convenient meeting facilities. The terminal also suggests the possibility of being put on a waiting list or other options to the user, aiming to improve satisfaction.

[0520] Furthermore, the analyzed emotional data can be applied to suggesting layouts for meeting facilities. To provide a less stressful environment, it can suggest the installation of more private phone booths and the creation of relaxing spaces. The terminal notifies the users and facility managers who receive these suggestions, supporting their final decision-making.

[0521] The system of this invention makes it possible not only to efficiently utilize meeting facilities but also to create a stress-free and comfortable meeting environment that takes into account the emotional state of users. This provides work style support optimized for individual needs and improves overall work efficiency.

[0522] The following describes the processing flow.

[0523] Step 1:

[0524] The server retrieves data from the electronic scheduling and reservation management systems and anonymizes it. This prepares the system to track reservation status while protecting personal information.

[0525] Step 2:

[0526] The server monitors facility usage in real time based on information from sensors and IoT devices installed in the conference facility, and continuously updates the database.

[0527] Step 3:

[0528] The emotion engine recognizes emotions from the user's voice input and operation history. This allows for the evaluation of user stress and satisfaction levels, and provides insights.

[0529] Step 4:

[0530] The server analyzes anonymized data and feedback from the emotion engine to identify available reservations and present an optimized reservation plan. At this stage, optimization is applied based on the user's emotional state.

[0531] Step 5:

[0532] The terminal notifies the user of reservation suggestions provided by the server. From the suggested reservations, the user can select the meeting schedule that best suits their needs.

[0533] Step 6:

[0534] If an available reservation is detected, the server sends a notification to the user of that reservation, and if there is no response within a certain period of time, it initiates a procedure to automatically cancel the reservation.

[0535] Step 7:

[0536] The server generates meeting facility layout suggestions based on data obtained from the emotion engine. This includes specific improvement measures to create a more comfortable environment for users.

[0537] Step 8:

[0538] The terminal notifies the conference facility operator of layout suggestions from the server. The operator evaluates the suggestions and makes changes to the facility settings as needed.

[0539] (Example 2)

[0540] 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."

[0541] In conventional use of meeting and other facilities, monitoring of usage and optimization of reservations are insufficient, leading to problems such as inefficient use of space and decreased user satisfaction. Furthermore, reservations and seating arrangements are often made without considering user emotions or stress levels, making it difficult to ensure a comfortable user environment. There is a need for a system that integrates real-time reservation optimization with personalized recommendations based on user emotions.

[0542] 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.

[0543] In this invention, the server includes means for acquiring data from various information management systems and reservation management systems from a data processing device and anonymizing the data; means for monitoring the usage status of the facility in real time using the anonymized data and detecting available reservations; and means for analyzing the emotional state using the user's voice, facial expressions, or operation history and generating optimal suggestions according to the user's emotions. This enables efficient use of the facility and the provision of a comfortable environment that takes into account the user's emotions.

[0544] A "data processing device" is hardware or software used to collect, analyze, anonymize, and process various types of data.

[0545] "Anonymization" is a process that protects privacy by converting personally identifiable information into a form that makes it impossible to identify an individual.

[0546] "Usage status" refers to information that indicates how facilities and resources are being used.

[0547] "Real-time monitoring" refers to the ability to instantly acquire current conditions and data, and to immediately evaluate and display them.

[0548] An "available reservation" refers to a reservation slot that is not currently being used and is available for free use.

[0549] "Optimization" refers to adjusting a system or process to its most efficient or effective state for a specific purpose.

[0550] "Emotional state" refers to data that indicates the user's psychological state and feelings.

[0551] A "suggestion" is the presentation of recommended actions or options based on a specific situation.

[0552] "Layout" is a concept that refers to the arrangement and structure of elements in a physical space.

[0553] A "user" is an individual or legal entity that uses a system or service.

[0554] This invention is a system for supporting the efficient and comfortable use of conference facilities and other various facilities. This system includes a data processing unit, an emotion engine, a server, and terminal devices.

[0555] The server retrieves data from information management systems and reservation management systems and anonymizes this data. A hash algorithm is used to anonymize the data and protect personal information. Using this anonymized data, the server monitors facility usage in real time. Specifically, the server uses a database management system to organize and store the collected information, enabling real-time access.

[0556] Furthermore, the server aggregates data from sensors and IoT devices installed within the facility and uses this data to detect available reservations. The server analyzes the obtained data and proposes the optimal reservation plan. This allows users to utilize the facility more effectively.

[0557] The emotion engine combines voice analysis software and facial recognition software to analyze the user's emotional state. It analyzes the user's voice tone and infers emotions based on data acquired by a facial recognition camera. Based on these analysis results, the server suggests reservations and layouts that are suitable for the user.

[0558] The terminal notifies the user of suggestions provided by the server. The user can review reservations through the terminal and make adjustments as needed. The terminal's interface is intuitive and interactive, ensuring high user convenience.

[0559] For example, if a user fails to book a meeting, the emotion engine detects their stress level. Based on this information, the server suggests alternative meeting rooms or available time slots to the user's device. The device then reviews these suggestions and provides the best option for the user.

[0560] An example of a prompt based on sentiment analysis using a generative AI model is, "Please suggest the best option to alleviate the user's stress caused by a booking failure." This allows the system to always consider the user's emotions and support a comfortable and effective user experience.

[0561] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0562] Step 1:

[0563] The server retrieves data from information management systems and reservation management systems. It receives schedule data and reservation lists via APIs as input and stores them in a database. After retrieving the data, it anonymizes it using a hash algorithm to protect personal information. This makes it possible to generate anonymous data that cannot be used for personal identification.

[0564] Step 2:

[0565] The server uses anonymized data to monitor facility usage in real time. It collects input data from sensors and IoT devices and generates status reports on usage. Specifically, it executes database queries to identify which facilities are in use and which are available. As output, it updates the usage dashboard to visualize the monitoring information.

[0566] Step 3:

[0567] The server analyzes real-time usage data to detect available reservations. It compares the current facility reservation status with user reservation requests as input. Statistical algorithms are used to calculate the most efficient reservation schedule. As output, it identifies the optimal reservation time slot and provides it to the user.

[0568] Step 4:

[0569] The emotion engine receives user voice data and facial expression data as input. It uses voice analysis and facial recognition technologies to evaluate the user's emotional state. Specifically, it performs voice tone analysis and monitors changes in facial expressions. As output, it quantifies the user's stress and anxiety levels and records their emotional state.

[0570] Step 5:

[0571] The server provides user-friendly booking and layout suggestions based on analyzed sentiment data. It receives the user's sentiment state and booking request as input, and uses an analytics model to calculate optimal suggestions. Specifically, it suggests environments and time slots predicted to be more comfortable based on the sentiment analysis results. The output provides the user with personalized booking guidance.

[0572] Step 6:

[0573] The terminal notifies the user of suggested information received from the server. The user reviews the suggestions via the terminal's interface and makes an appropriate selection. As output, the user sends the final selected reservation details to the server to confirm the reservation. This ensures efficient facility use and improves user satisfaction.

[0574] (Application Example 2)

[0575] 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."

[0576] Providing an efficient and comfortable environment that takes into account the emotional state of users in physical stores and meeting facilities presents challenges. Traditional reservation systems and methods for understanding user stress levels are insufficient, resulting in a lack of expected improvements in customer satisfaction.

[0577] 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.

[0578] In this invention, the server includes means for acquiring and anonymizing information from an information management system and a reservation management system, means for monitoring usage status in real time and detecting available time, and means for analyzing the customer's emotional state using an emotion analysis engine and making optimal suggestions. This makes it possible to provide an optimal reservation environment tailored to the user's emotional state.

[0579] A "data processing device" is a device that acquires information from various information management systems and reservation management systems, and processes this information after anonymizing it.

[0580] "Anonymization" is a technique that transforms information into a form that does not identify individuals, thereby making data usable while protecting privacy.

[0581] An "emotion analysis engine" is a technology that analyzes a customer's emotional state from data such as their voice and facial expressions to detect stress, anxiety, and other emotional states.

[0582] "Real-time monitoring" is a technology that allows for immediate monitoring of ongoing situations and instantaneous action to be taken as needed.

[0583] "Optimization" is the process of adjusting conditions to suit a specific objective in order to obtain efficient and effective results.

[0584] "Notification" refers to the process of sending information from a system to a user and providing them with necessary actions or information.

[0585] An "alternative service" is a service that offers alternative options to the original service, tailored to the user's preferences and circumstances.

[0586] The system according to the present invention enables reservation management that takes into account the emotional state of users in physical stores and meeting facilities. This system consists of the following elements.

[0587] The server retrieves and anonymizes information from the information management system and reservation management system. This allows for efficient processing of necessary data while protecting user privacy. The server also monitors facility usage in real time, detects available time slots, and provides users with the most suitable reservation options. Furthermore, the server uses an emotion analysis engine to analyze users' voices and facial expressions to determine their stress levels and emotional states. Based on these analysis results, it suggests available time slots and alternative services to provide users with the best possible environment.

[0588] The terminal receives notifications from the server and presents optimized reservation information based on the user's emotional state. These notifications help users reduce stress and frustration, allowing them to enjoy a more comfortable reservation experience. For example, if a customer visits a crowded store, the terminal can suggest less busy times and notify them of benefits for future visits, thereby increasing customer satisfaction.

[0589] For example, if a customer attempts to book a meeting but fails, the system automatically analyzes the customer's emotions, detects that the user is experiencing high stress levels, and then suggests available times. A possible prompt in this case would be, "Detect the customer's stress level and suggest what services should be provided."

[0590] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0591] Step 1:

[0592] The server retrieves information from the information management system and reservation management system, and anonymizes the received raw data. The input is raw data containing user identification information, and the output is anonymized data. Data anonymization protects privacy by transforming the data into a form that does not identify individuals, while still making it possible to perform data analysis.

[0593] Step 2:

[0594] The server monitors anonymized data in real time to detect facility vacancies. The input is anonymized usage data, and the output is vacancy information. Monitoring analyzes current usage and identifies the next available time slots, optimizing facility operations.

[0595] Step 3:

[0596] The server uses an emotion analysis engine to analyze the user's voice and facial expression data. The input is voice and image data obtained from the user, and the output is the analyzed emotional state. The server processes this data to identify emotions such as stress and anxiety. The emotion analysis engine achieves this by analyzing fluctuation patterns in voice and image data.

[0597] Step 4:

[0598] The server calculates and suggests the most suitable booking options and alternative services to the user based on availability information and emotional state. The input is availability information and emotional state data, and the output is the suggested booking options. The server uses a generative AI model to present the optimal time slots and services tailored to the emotional state.

[0599] Step 5:

[0600] The terminal notifies the user of suggestions received from the server. The input is the suggestion information sent from the server, and the output is the notification on the user's terminal. The terminal uses its notification function to display reservation information and alternatives optimized for the user. This makes it easy for the user to make the best choice.

[0601] 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.

[0602] 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.

[0603] 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.

[0604] [Fourth Embodiment]

[0605] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0606] 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.

[0607] 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).

[0608] 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.

[0609] 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.

[0610] 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).

[0611] 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.

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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".

[0618] The system according to the present invention is based on the principle of acquiring data from multiple electronic scheduling systems and reservation management systems using a data processing device, anonymizing that data, and then analyzing it, in order to achieve efficient management of conference facilities. The server uses this data to monitor the usage status of conference facilities in real time and automatically detect available reservations.

[0619] This system uses a server to analyze user schedule data and identify underutilized time slots and trends in available bookings. This enables the optimization and automatic adjustment of appropriate meeting facility reservations. Based on the analysis results from the server, users can receive information on which meeting facilities are available and what the optimal dates and times are.

[0620] As a concrete example, suppose a user wants to hold a meeting the following Tuesday and sends a reservation request via their device. The server first receives the request and, considering existing reservation data and the availability of meeting facilities on that day from the electronic scheduling system, suggests the most suitable meeting room and time. If a reservation becomes available, the server automatically cancels it and offers the user the opportunity.

[0621] Furthermore, the server generates optimization suggestions for the meeting facility layout based on the analysis. For example, for a meeting room frequently used by two people, it suggests changing it to a phone booth to help utilize the space more efficiently. This suggestion is notified to users and operators via terminals, and a final decision is made based on their feedback.

[0622] This system significantly improves the operational efficiency of meeting facilities, creating an environment where users can use meeting rooms when needed without stress. Because these processes are automated, human resources are drastically reduced, allowing for more efficient use of time.

[0623] The following describes the processing flow.

[0624] Step 1:

[0625] The server periodically retrieves meeting facility reservation data via APIs from multiple electronic scheduling and reservation management systems. The retrieved data is stored in a database on the server.

[0626] Step 2:

[0627] The server anonymizes the acquired data. Specifically, it replaces personally identifiable information such as user IDs and personal names with random identifiers and stores it in a database in a format that protects privacy.

[0628] Step 3:

[0629] The server monitors the real-time usage status of meeting facilities based on anonymized data. Using input from sensors and IoT devices installed in meeting rooms, it verifies actual usage and identifies available reservations.

[0630] Step 4:

[0631] The server analyzes usage and reservation data to calculate the optimal reservation schedule. It analyzes reservation imbalances and trends in available reservations to generate an efficient usage schedule.

[0632] Step 5:

[0633] The terminal notifies the user of optimized reservation information provided by the server. The user reviews the proposal presented through the terminal and approves or modifies the reservation as needed.

[0634] Step 6:

[0635] When the server detects an available reservation, it sends a confirmation notification to the user. If the user does not respond within a certain period of time, the server automatically initiates a procedure to cancel the reservation.

[0636] Step 7:

[0637] The server analyzes the usage data of meeting facilities and, if meetings with only two people occur frequently, generates suggestions for layout improvements, such as moving to smaller spaces like phone booths.

[0638] Step 8:

[0639] The terminal notifies the facility administrator of the layout proposal from the server and receives feedback. Based on this feedback, the final layout changes are decided.

[0640] (Example 1)

[0641] 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".

[0642] Efficiently managing the booking status of meeting facilities and event spaces and minimizing unused time slots is a major challenge for many companies and organizations. Currently, duplicate bookings and unused bookings are frequent, reducing the operational efficiency of facilities. Furthermore, a lack of information necessary for users to select appropriate facilities is hindering a smooth booking process.

[0643] 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.

[0644] In this invention, the server includes means for acquiring information from various information management systems and reservation management systems from an information processing device and anonymizing the information; means for optimizing and automatically adjusting facility reservations based on the usage status; and means for analyzing usage patterns using a machine learning algorithm and identifying time periods with low utilization rates. This makes it possible to improve the efficiency of facility utilization and to quickly provide appropriate facility information to users.

[0645] An "information processing device" is a device that acquires and processes information from various information management systems and reservation management systems.

[0646] "Anonymization" is a process that transforms information so that personal information cannot be identified, thereby protecting privacy.

[0647] A "facility" is a space or building used for holding meetings or events.

[0648] An "unused reservation" is a reservation that has been made but has not actually been used.

[0649] "Optimization" is the process of adjusting and improving how resources are used and allocated in order to increase their efficiency.

[0650] A "machine learning algorithm" is a computational method that analyzes data and learns patterns to improve future predictions and decisions.

[0651] "Usage patterns" refer to the tendencies and habits that indicate how facility users utilize the facility.

[0652] A "user terminal" is a computer device used by a user to receive and input information.

[0653] This invention relates to a system that efficiently and automatically optimizes the use of conference facilities. The server operates as an information processing device and is connected to various information management and reservation management systems. This allows the server to acquire necessary information and anonymize it. The server uses machine learning algorithms to analyze the collected data and learn patterns of facility usage. This enables the identification of time slots with low utilization rates and the optimization of facility reservations.

[0654] Furthermore, the server provides users with information on the most suitable facility for booking via their terminals. For example, if a user wants to use a facility next Tuesday, they can simply type "I would like to have a two-hour meeting next Tuesday. Please find and book the most suitable meeting facility" into their terminal, and the server will suggest the most suitable facility and automatically process the booking.

[0655] The server also monitors potentially unused reservations in real time and automatically cancels them if no action is taken by the user. Finally, the server can generate optimization suggestions for the facility's structure based on usage data. This information is communicated to users and administrators via terminals to promote efficient operation.

[0656] Implementing this system will significantly improve the efficiency of meeting facility utilization, allowing users to access the optimal facility in a stress-free environment. As a result, human effort will be reduced, providing added value through more efficient use of time.

[0657] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0658] Step 1:

[0659] The server retrieves information from various information management and reservation management systems. Information is retrieved via APIs, with raw data transmitted from each system as input. The server aggregates this data and preprocesses it to extract only the necessary items. The output is an integrated dataset.

[0660] Step 2:

[0661] The server anonymizes the acquired data. The input is an integrated dataset, and the server applies an algorithm to remove or replace personally identifiable information. This ensures the protection of personal information. The output is an anonymized dataset.

[0662] Step 3:

[0663] The server analyzes facility usage patterns based on anonymized data. It uses machine learning algorithms to analyze the data and identify periods of low utilization. The input here is an anonymized dataset, and the server uses algorithms to derive trends and patterns. The output is the analysis results of the usage patterns.

[0664] Step 4:

[0665] The terminal receives a reservation request from the user. The input is the details of the reservation request entered by the user into the terminal, including the date, time, and the number of participants required. The terminal sends this request to the server. The output is the user's reservation request.

[0666] Step 5:

[0667] The server selects the most suitable facility based on the user's reservation request and the analyzed usage patterns. The input consists of the user's reservation preference and the results of the usage pattern analysis. The server then matches this information against its database and selects the most suitable available facility and time slot. The output is a list of suggested facilities and time slots.

[0668] Step 6:

[0669] The server notifies the user of the most suitable facility reservation options. The input is information about the optimized facility and time slot. The server sends this information as a message to the terminal. The output provides the user with the suggested reservation information.

[0670] Step 7:

[0671] The server monitors reservations that may become unused and automatically cancels them if there is no response. Inputs are the current reservation status data and user responses. The server cancels reservations deemed unused and notifies the relevant systems of this information. The output is the updated reservation status.

[0672] Step 8:

[0673] The server generates optimization suggestions based on facility usage data. The input is accumulated usage data. The server generates suggestions for efficient space use and sends them to the terminal. The optimization suggestions are then notified to users and administrators as output.

[0674] (Application Example 1)

[0675] 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".

[0676] In modern society, improving the efficiency of shared facilities is crucial for maximizing the use of time and resources. However, many current reservation systems have problems with efficient reservation management, as checking whether a suitable facility is available when a user desires it is cumbersome. Furthermore, there is a lack of systems that automatically make appropriate layout changes or suggestions based on facility usage, resulting in inefficient use of space. Therefore, there is a need for a system that can quickly and automatically optimize facility reservations and flexibly utilize space based on usage trends.

[0677] 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.

[0678] In this invention, the server includes means for proposing the optimal facility and time based on user requests for collective facilities within a city area, means for immediately proposing the optimal facility when a user inputs their usage request via a terminal device, and means for providing information including proposed changes to the facility arrangement based on usage trends. This enables the optimization of facility reservations in response to user requests quickly. Furthermore, it improves the efficiency of facility utilization and makes effective use of time and resources.

[0679] A "data processing device" is a device that has the function of acquiring data from various electronic schedule systems and reservation management systems and anonymizing that data.

[0680] "Anonymization" is a technology that securely processes data by removing or transforming information that could identify an individual.

[0681] "Collective facilities" refers to all spaces used for holding meetings and events.

[0682] "Usage status" refers to information about how a particular facility or system is being used.

[0683] "Optimization" is the process of making adjustments or changes to achieve maximum or minimum efficiency under specified conditions.

[0684] "Automatic adjustment" refers to a system's ability to autonomously adjust itself according to the situation and conditions without user intervention.

[0685] "Usage data" refers to information regarding the frequency, duration, and number of users of facilities and services.

[0686] "Urban area" refers to the entire area within a specific region where urban planning and service provision take place.

[0687] A "terminal device" is a device used by a user to interact with and operate a system.

[0688] "Usage trends" refer to data and analysis results based on the behavior and patterns of typical users.

[0689] "Arrangement change proposal" refers to specific suggestions for optimizing the layout within a facility.

[0690] This invention constructs a system to improve the utilization efficiency of collective facilities. The server first uses a data processing device to acquire data from various electronic schedule systems and reservation management systems, and then anonymizes it. This makes it possible to manage reservations efficiently while protecting user privacy.

[0691] Based on the anonymized data it acquires, the server instantly monitors the usage status of the facilities and detects available reservations. The detected available reservation information is provided in a format that users can easily access from their terminal devices. Furthermore, the server can instantly suggest the most suitable facilities and times based on the user's input.

[0692] The terminal functions as the user interface and is used when users enter their usage requests. Users can make facility reservations through the terminal and receive optimized notifications once the reservation is complete.

[0693] The server can also analyze usage trends and generate proposed changes to the facility layout. This information is provided to users and administrators via terminals, resulting in a real-time, optimized user environment.

[0694] As a concrete example, a user might enter a prompt like this: "We have a meeting scheduled for next Tuesday at a community center in the city with five people. Please suggest the best venue." The system can then use a generative AI model to provide the user with the most suitable suggestion. These processes may utilize software such as Python or Flask.

[0695] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0696] Step 1:

[0697] The server retrieves data from the electronic schedule system and the reservation management system. It receives access information to the APIs and databases of each system as input, and outputs raw reservation data. This data includes information such as date, time, number of participants, and facility name.

[0698] Step 2:

[0699] The server anonymizes the raw reservation data it retrieves. It receives the reservation data obtained in the previous step as input and outputs anonymized data by removing or transforming personally identifiable information. This process involves data processing to protect privacy.

[0700] Step 3:

[0701] The server monitors the usage status of collective facilities using anonymized data. It receives anonymized data as input and performs real-time analysis to output facility usage and availability information. Usage status is represented by the facility name and available time slots.

[0702] Step 4:

[0703] The terminal receives usage request data from users. It receives information such as the user's desired date, time, and number of participants as input, and sends it to the server. This clarifies the conditions the user is looking for.

[0704] Step 5:

[0705] The server suggests the most suitable facility and time based on the user's request data. Using user request data and availability information from the terminal as input, it generates the optimal suggestion through an optimization algorithm. The output is the name of the facility and time slot immediately available to the user.

[0706] Step 6:

[0707] The user receives and reviews suggestions from the server. They receive suggestions for the most suitable facilities and time slots as input, and take action to confirm them as a reservation if necessary. The output is a reservation confirmation notification.

[0708] Step 7:

[0709] The server generates and provides administrators with proposed facility layouts based on usage trends. It uses historical usage data and trend analysis results as input, and a generative AI model to create optimized layouts. The output is presented as a concrete, efficient facility layout plan.

[0710] 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.

[0711] This invention provides a system that combines an emotion engine to enable efficient and comfortable use of conference facilities. This system collects and anonymizes data from multiple electronic scheduling and reservation management systems via a data processing device, and a server monitors the usage status of conference facilities in real time based on this data. Furthermore, the server uses sensor information and data from IoT devices to detect available reservations and propose optimizations.

[0712] In particular, this invention incorporates an emotion engine that can detect the user's emotional state. The emotion engine analyzes the user's emotions from their voice, facial expression data, and operation history, and generates suggestions to adjust the optimal reservation and layout according to emotions such as stress and anxiety. If the user is satisfied with the success of their reservation, the system will provide services that reflect their individual emotions, such as prioritizing the provision of a similar meeting environment.

[0713] For example, when a user fails to book a meeting, the emotion engine detects the user's stress level. Based on this information, the server prioritizes suggesting alternative time slots or more convenient meeting facilities. The terminal also suggests the possibility of being put on a waiting list or other options to the user, aiming to improve satisfaction.

[0714] Furthermore, the analyzed emotional data can be applied to suggesting layouts for meeting facilities. To provide a less stressful environment, it can suggest the installation of more private phone booths and the creation of relaxing spaces. The terminal notifies the users and facility managers who receive these suggestions, supporting their final decision-making.

[0715] The system of this invention makes it possible not only to efficiently utilize meeting facilities but also to create a stress-free and comfortable meeting environment that takes into account the emotional state of users. This provides work style support optimized for individual needs and improves overall work efficiency.

[0716] The following describes the processing flow.

[0717] Step 1:

[0718] The server retrieves data from the electronic scheduling and reservation management systems and anonymizes it. This prepares the system to track reservation status while protecting personal information.

[0719] Step 2:

[0720] The server monitors facility usage in real time based on information from sensors and IoT devices installed in the conference facility, and continuously updates the database.

[0721] Step 3:

[0722] The emotion engine recognizes emotions from the user's voice input and operation history. This allows for the evaluation of user stress and satisfaction levels, and provides insights.

[0723] Step 4:

[0724] The server analyzes anonymized data and feedback from the emotion engine to identify available reservations and present an optimized reservation plan. At this stage, optimization is applied based on the user's emotional state.

[0725] Step 5:

[0726] The terminal notifies the user of reservation suggestions provided by the server. From the suggested reservations, the user can select the meeting schedule that best suits their needs.

[0727] Step 6:

[0728] If an available reservation is detected, the server sends a notification to the user of that reservation, and if there is no response within a certain period of time, it initiates a procedure to automatically cancel the reservation.

[0729] Step 7:

[0730] The server generates meeting facility layout suggestions based on data obtained from the emotion engine. This includes specific improvement measures to create a more comfortable environment for users.

[0731] Step 8:

[0732] The terminal notifies the conference facility operator of layout suggestions from the server. The operator evaluates the suggestions and makes changes to the facility settings as needed.

[0733] (Example 2)

[0734] 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".

[0735] In conventional use of meeting and other facilities, monitoring of usage and optimization of reservations are insufficient, leading to problems such as inefficient use of space and decreased user satisfaction. Furthermore, reservations and seating arrangements are often made without considering user emotions or stress levels, making it difficult to ensure a comfortable user environment. There is a need for a system that integrates real-time reservation optimization with personalized recommendations based on user emotions.

[0736] 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.

[0737] In this invention, the server includes means for acquiring data from various information management systems and reservation management systems from a data processing device and anonymizing the data; means for monitoring the usage status of the facility in real time using the anonymized data and detecting available reservations; and means for analyzing the emotional state using the user's voice, facial expressions, or operation history and generating optimal suggestions according to the user's emotions. This enables efficient use of the facility and the provision of a comfortable environment that takes into account the user's emotions.

[0738] A "data processing device" is hardware or software used to collect, analyze, anonymize, and process various types of data.

[0739] "Anonymization" is a process that protects privacy by converting personally identifiable information into a form that makes it impossible to identify an individual.

[0740] "Usage status" refers to information that indicates how facilities and resources are being used.

[0741] "Real-time monitoring" refers to the ability to instantly acquire current conditions and data, and to immediately evaluate and display them.

[0742] An "available reservation" refers to a reservation slot that is not currently being used and is available for free use.

[0743] "Optimization" refers to adjusting a system or process to its most efficient or effective state for a specific purpose.

[0744] "Emotional state" refers to data that indicates the user's psychological state and feelings.

[0745] A "suggestion" is the presentation of recommended actions or options based on a specific situation.

[0746] "Layout" is a concept that refers to the arrangement and structure of elements in a physical space.

[0747] A "user" is an individual or legal entity that uses a system or service.

[0748] This invention is a system for supporting the efficient and comfortable use of conference facilities and other various facilities. This system includes a data processing unit, an emotion engine, a server, and terminal devices.

[0749] The server retrieves data from information management systems and reservation management systems and anonymizes this data. A hash algorithm is used to anonymize the data and protect personal information. Using this anonymized data, the server monitors facility usage in real time. Specifically, the server uses a database management system to organize and store the collected information, enabling real-time access.

[0750] Furthermore, the server aggregates data from sensors and IoT devices installed within the facility and uses this data to detect available reservations. The server analyzes the obtained data and proposes the optimal reservation plan. This allows users to utilize the facility more effectively.

[0751] The emotion engine combines voice analysis software and facial recognition software to analyze the user's emotional state. It analyzes the user's voice tone and infers emotions based on data acquired by a facial recognition camera. Based on these analysis results, the server suggests reservations and layouts that are suitable for the user.

[0752] The terminal notifies the user of suggestions provided by the server. The user can review reservations through the terminal and make adjustments as needed. The terminal's interface is intuitive and interactive, ensuring high user convenience.

[0753] For example, if a user fails to book a meeting, the emotion engine detects their stress level. Based on this information, the server suggests alternative meeting rooms or available time slots to the user's device. The device then reviews these suggestions and provides the best option for the user.

[0754] An example of a prompt based on sentiment analysis using a generative AI model is, "Please suggest the best option to alleviate the user's stress caused by a booking failure." This allows the system to always consider the user's emotions and support a comfortable and effective user experience.

[0755] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0756] Step 1:

[0757] The server retrieves data from information management systems and reservation management systems. It receives schedule data and reservation lists via APIs as input and stores them in a database. After retrieving the data, it anonymizes it using a hash algorithm to protect personal information. This makes it possible to generate anonymous data that cannot be used for personal identification.

[0758] Step 2:

[0759] The server uses anonymized data to monitor facility usage in real time. It collects input data from sensors and IoT devices and generates status reports on usage. Specifically, it executes database queries to identify which facilities are in use and which are available. As output, it updates the usage dashboard to visualize the monitoring information.

[0760] Step 3:

[0761] The server analyzes real-time usage data to detect available reservations. It compares the current facility reservation status with user reservation requests as input. Statistical algorithms are used to calculate the most efficient reservation schedule. As output, it identifies the optimal reservation time slot and provides it to the user.

[0762] Step 4:

[0763] The emotion engine receives user voice data and facial expression data as input. It uses voice analysis and facial recognition technologies to evaluate the user's emotional state. Specifically, it performs voice tone analysis and monitors changes in facial expressions. As output, it quantifies the user's stress and anxiety levels and records their emotional state.

[0764] Step 5:

[0765] The server provides user-friendly booking and layout suggestions based on analyzed sentiment data. It receives the user's sentiment state and booking request as input, and uses an analytics model to calculate optimal suggestions. Specifically, it suggests environments and time slots predicted to be more comfortable based on the sentiment analysis results. The output provides the user with personalized booking guidance.

[0766] Step 6:

[0767] The terminal notifies the user of suggested information received from the server. The user reviews the suggestions via the terminal's interface and makes an appropriate selection. As output, the user sends the final selected reservation details to the server to confirm the reservation. This ensures efficient facility use and improves user satisfaction.

[0768] (Application Example 2)

[0769] 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".

[0770] Providing an efficient and comfortable environment that takes into account the emotional state of users in physical stores and meeting facilities presents challenges. Traditional reservation systems and methods for understanding user stress levels are insufficient, resulting in a lack of expected improvements in customer satisfaction.

[0771] 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.

[0772] In this invention, the server includes means for acquiring and anonymizing information from an information management system and a reservation management system, means for monitoring usage status in real time and detecting available time, and means for analyzing the customer's emotional state using an emotion analysis engine and making optimal suggestions. This makes it possible to provide an optimal reservation environment tailored to the user's emotional state.

[0773] A "data processing device" is a device that acquires information from various information management systems and reservation management systems, and processes this information after anonymizing it.

[0774] "Anonymization" is a technique that transforms information into a form that does not identify individuals, thereby making data usable while protecting privacy.

[0775] An "emotion analysis engine" is a technology that analyzes a customer's emotional state from data such as their voice and facial expressions to detect stress, anxiety, and other emotional states.

[0776] "Real-time monitoring" is a technology that allows for immediate monitoring of ongoing situations and instantaneous action to be taken as needed.

[0777] "Optimization" is the process of adjusting conditions to suit a specific objective in order to obtain efficient and effective results.

[0778] "Notification" refers to the process of sending information from a system to a user and providing them with necessary actions or information.

[0779] An "alternative service" is a service that offers alternative options to the original service, tailored to the user's preferences and circumstances.

[0780] The system according to the present invention enables reservation management that takes into account the emotional state of users in physical stores and meeting facilities. This system consists of the following elements.

[0781] The server retrieves and anonymizes information from the information management system and reservation management system. This allows for efficient processing of necessary data while protecting user privacy. The server also monitors facility usage in real time, detects available time slots, and provides users with the most suitable reservation options. Furthermore, the server uses an emotion analysis engine to analyze users' voices and facial expressions to determine their stress levels and emotional states. Based on these analysis results, it suggests available time slots and alternative services to provide users with the best possible environment.

[0782] The terminal receives notifications from the server and presents optimized reservation information based on the user's emotional state. These notifications help users reduce stress and frustration, allowing them to enjoy a more comfortable reservation experience. For example, if a customer visits a crowded store, the terminal can suggest less busy times and notify them of benefits for future visits, thereby increasing customer satisfaction.

[0783] For example, if a customer attempts to book a meeting but fails, the system automatically analyzes the customer's emotions, detects that the user is experiencing high stress levels, and then suggests available times. A possible prompt in this case would be, "Detect the customer's stress level and suggest what services should be provided."

[0784] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0785] Step 1:

[0786] The server retrieves information from the information management system and reservation management system, and anonymizes the received raw data. The input is raw data containing user identification information, and the output is anonymized data. Data anonymization protects privacy by transforming the data into a form that does not identify individuals, while still making it possible to perform data analysis.

[0787] Step 2:

[0788] The server monitors anonymized data in real time to detect facility vacancies. The input is anonymized usage data, and the output is vacancy information. Monitoring analyzes current usage and identifies the next available time slots, optimizing facility operations.

[0789] Step 3:

[0790] The server uses an emotion analysis engine to analyze the user's voice and facial expression data. The input is voice and image data obtained from the user, and the output is the analyzed emotional state. The server processes this data to identify emotions such as stress and anxiety. The emotion analysis engine achieves this by analyzing fluctuation patterns in voice and image data.

[0791] Step 4:

[0792] The server calculates and suggests the most suitable booking options and alternative services to the user based on availability information and emotional state. The input is availability information and emotional state data, and the output is the suggested booking options. The server uses a generative AI model to present the optimal time slots and services tailored to the emotional state.

[0793] Step 5:

[0794] The terminal notifies the user of suggestions received from the server. The input is the suggestion information sent from the server, and the output is the notification on the user's terminal. The terminal uses its notification function to display reservation information and alternatives optimized for the user. This makes it easy for the user to make the best choice.

[0795] 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.

[0796] 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.

[0797] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0798] 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.

[0799] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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."

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] The following is further disclosed regarding the embodiments described above.

[0817] (Claim 1)

[0818] A data processing device acquires data from various electronic scheduling systems and reservation management systems, and a means for anonymizing said data.

[0819] A means for monitoring the usage status of meeting facilities in real time using the anonymized data and detecting available reservations,

[0820] A means for optimizing and automatically adjusting the reservation of meeting facilities based on the aforementioned usage status,

[0821] A means to notify the user when the aforementioned vacant reservation is detected, and to automatically cancel the reservation if no response is received,

[0822] A system that includes means for performing analysis based on usage data in order to propose an appropriate layout for the aforementioned conference facility.

[0823] (Claim 2)

[0824] The system according to claim 1, which performs an analysis to identify time periods when the utilization rate of the conference facility is low.

[0825] (Claim 3)

[0826] The system according to claim 1, which notifies a user of optimized meeting reservation information via a terminal device.

[0827] "Example 1"

[0828] (Claim 1)

[0829] An information processing device acquires information from various information management systems and reservation management systems, and a means for anonymizing said information.

[0830] A means for monitoring the usage status of the facility in real time using the anonymized information and detecting unused reservations,

[0831] A means for optimizing and automatically adjusting facility reservations based on the aforementioned usage status,

[0832] A means to notify the user when an unused reservation is detected, and to automatically cancel the reservation if no response is received,

[0833] In order to propose an appropriate structure for the aforementioned facility, a means of performing analysis based on usage information,

[0834] A method for analyzing usage patterns using machine learning algorithms and identifying time periods with low utilization rates,

[0835] A means of notifying users of optimized reservation information via their terminals and presenting the most suitable reservation options,

[0836] A means to support final decisions regarding facility operations based on feedback.

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, which provides suggestions for optimizing the layout of facilities.

[0840] (Claim 3)

[0841] The system according to claim 1, which notifies the user of unused time in order to provide opportunities.

[0842] "Application Example 1"

[0843] (Claim 1)

[0844] A data processing device acquires data from various electronic schedule systems and reservation management systems, and a means for anonymizing said data.

[0845] A means for immediately monitoring the usage status of a collective facility using the anonymized data and detecting available reservations,

[0846] A means for optimizing and automatically adjusting reservations for group facilities based on the aforementioned usage status,

[0847] A means to notify the user when the aforementioned vacant reservation is detected, and to automatically cancel the reservation if no response is received,

[0848] In order to propose an appropriate arrangement of the aforementioned group facilities, a means for performing analysis based on usage status data,

[0849] A means of proposing the optimal facility and time based on user requests for collective facilities within the city area,

[0850] A means of immediately suggesting the most suitable facility when a user inputs their desired facility via a terminal device,

[0851] A system that includes means for providing information, including proposed changes to the arrangement of facilities, based on usage trends.

[0852] (Claim 2)

[0853] The system according to claim 1, which performs an analysis to identify time periods when the utilization rate of the aforementioned collective facility is low.

[0854] (Claim 3)

[0855] The system according to claim 1, which notifies users of optimized group reservation information via a terminal device.

[0856] "Example 2 of combining an emotion engine"

[0857] (Claim 1)

[0858] A data processing device acquires data from various information management systems and reservation management systems, and a means for anonymizing said data.

[0859] A means for monitoring the usage status of the facility in real time using the anonymized data and detecting available reservations,

[0860] A means for optimizing and automatically adjusting facility reservations based on the aforementioned usage status,

[0861] A means for analyzing the user's emotional state using their voice, facial expressions, or operation history, and generating optimal suggestions that correspond to the user's emotions,

[0862] By notifying users of the aforementioned proposal and presenting additional options if users do not respond, this is a means of improving reservation satisfaction.

[0863] A system that includes means for proposing an appropriate layout for the aforementioned facility and for proposing adjustments to the spatial design within the facility.

[0864] (Claim 2)

[0865] The system according to claim 1, which identifies time periods when the utilization rate of the facility is low and proposes the installation of a relaxing environment.

[0866] (Claim 3)

[0867] The system according to claim 1, which notifies a user of optimized reservation information based on sentiment analysis via a terminal device.

[0868] "Application example 2 of combining emotional engines"

[0869] (Claim 1)

[0870] A data processing device acquires information from various information management systems and reservation management systems, and a means for anonymizing said information.

[0871] A means for monitoring the usage status of meeting facilities in real time using the anonymized information and detecting available time slots,

[0872] A means for optimizing and automatically adjusting reservations for meeting facilities based on the aforementioned usage status,

[0873] A method that uses an emotion analysis engine to analyze the customer's emotional state and propose the optimal reservation time or alternative service,

[0874] A means to notify the user when the aforementioned free time is detected, and to automatically cancel the reservation if no response is received,

[0875] A system including means for performing analysis based on analyzed emotional information in order to propose the appropriate arrangement of the aforementioned conference facilities.

[0876] (Claim 2)

[0877] The system according to claim 1, which identifies time slots with low utilization rates for the aforementioned meeting facilities and performs analysis to notify alternative time slots.

[0878] (Claim 3)

[0879] The system according to claim 1, which notifies a user of optimized reservation information based on their emotional state via an information terminal device. [Explanation of Symbols]

[0880] 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 processing device acquires data from various electronic scheduling systems and reservation management systems, and a means for anonymizing said data. A means for monitoring the usage status of meeting facilities in real time using the anonymized data and detecting available reservations, A means for optimizing and automatically adjusting the reservation of meeting facilities based on the aforementioned usage status, A means to notify the user when the aforementioned vacant reservation is detected, and to automatically cancel the reservation if no response is received, A system that includes means for performing analysis based on usage data in order to propose an appropriate layout for the aforementioned conference facility.

2. The system according to claim 1, which performs an analysis to identify time periods when the utilization rate of the conference facility is low.

3. The system according to claim 1, which notifies a user of optimized meeting reservation information via a terminal device.

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