system

Abstract

We provide the system. [Solution] A computing device equipped with a storage medium for storing user attribute data and past connection history, and for collecting real-time communication quality information, Means for transmitting radio wave intensity and quality data measured at regular time intervals to a computing device, A means for monitoring the operational status of information processing and notifying the computing device of important data communication when such communication occurs, A means for selecting the optimal communication network by analyzing radio wave intensity, information processing operation status, and past connection data collected by a computing device, A means of automatically switching the connection of information terminals based on instructions from a computing device, A means for seamlessly switching between wireless networks and mobile data communication in real space, A system that includes this.

Description

Technical Field

[0005]

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a crowded transportation facility with many users, there is a problem that the use of the communication network is concentrated, and throughput degradation and connection instability are likely to occur. In such an environment, it is required to provide stable communication quality to specific communication network users.

Means for Solving the Problems

[0005] This invention utilizes a terminal that transmits measured signal strength and quality data to a server device, and another terminal equipped with a function to monitor the application being used and determine the necessity of communication. The server device is equipped with a database that stores user information and past communication history data, and network quality information is also collected in real time. Furthermore, the server device analyzes the collected data and sends instructions to the terminal to automatically connect to the optimal network, thereby providing an environment in which communication can be used comfortably. This enables stable communication connections even in environments with many users.

[0006] A "server device" is a computing device used to store and analyze user information, communication history data, and real-time network quality information.

[0007] "Signal strength" is an indicator that shows the received power of a signal measured by a communication terminal, and it is a value that affects the stability of the network connection.

[0008] "Quality data" refers to data that indicates the quality of received communication signals, and is information used to determine whether communication can be performed stably.

[0009] "Application usage" refers to information used to monitor applications currently running on a device and understand their data usage and required bandwidth.

[0010] A "database" is a storage device used to systematically store and manage information about users and past communication history data.

[0011] "Network quality information" refers to real-time data regarding the usage status of communication networks and the strength and quality of signals.

[0012] "Automatic switching" refers to a function that allows a communication terminal to change its network connection without manual operation, based on instructions from a server device.

[0013] A "communication terminal" is an electronic device, such as a mobile phone or tablet, used by a user to access a communication network. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

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

[0018] 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.

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

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention provides a system for optimizing communication quality in a specific network environment, in which the user's communication terminal and server device work together. The terminal enables the user to automatically select the most suitable communication environment at all times, even when the user is on the move.

[0036] The server stores user information and past communication history in a database and collects real-time network quality information. This information is used to analyze which network connection is optimal and to send instructions to the terminal to provide an appropriate communication environment.

[0037] The terminal measures signal strength and quality data at regular intervals and sends this data to the server. Furthermore, the terminal monitors the status of currently used applications and identifies applications that require high bandwidth. In this way, the terminal can smoothly switch automatically between public 4G / 5G networks and local 5G networks based on instructions from the server.

[0038] As a concrete example, consider a user streaming a video on a train during their commute. Because network usage is concentrated on trains, stable viewing may be difficult with a standard public 4G network. In this case, the device periodically sends signal strength and quality data to the server. The server, based on this data, confirms that the user is using a video streaming app, and considers past communication history to determine that using a local 5G network is more appropriate. The server then instructs the device to switch to local 5G, allowing the user to enjoy uninterrupted video viewing.

[0039] In this way, seamless collaboration between servers and terminals makes it possible to continuously provide users with an excellent communication experience.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The terminal measures signal strength and quality, including RSRP, RSRQ, and SINR, at regular intervals. This measurement data serves as fundamental information for evaluating communication stability.

[0043] Step 2:

[0044] The terminal sends the measured signal strength and quality data to the server. This data is used by the server to understand the real-time network conditions.

[0045] Step 3:

[0046] The device monitors the applications currently in use and identifies those that require high bandwidth (e.g., video streaming apps). This information helps determine the priority of communication needs.

[0047] Step 4:

[0048] The server analyzes received signal strength and quality data, application usage, and past communication history. This analysis helps determine the optimal network to select.

[0049] Step 5:

[0050] Based on the analysis results, the server evaluates whether a public 4G / 5G network or a local 5G network is appropriate and sends a network switching instruction to the terminal.

[0051] Step 6:

[0052] The terminal automatically switches networks upon receiving instructions from the server. This process is seamless, allowing users to continue using the service without experiencing any communication interruptions.

[0053] Step 7:

[0054] Users can utilize applications (e.g., video streaming) in a stable communication environment through the newly selected optimal communication path.

[0055] This series of processes allows users to receive high-quality communication services without stress, even in congested environments.

[0056] (Example 1)

[0057] 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."

[0058] In recent years, the use of mobile communication devices has increased, and many users require internet access while on the go. However, communication quality tends to be unstable, especially in certain travel environments such as trains and vehicles, which can cause problems when making important communications. The objective of this invention is to solve this problem and realize high-quality communication even while traveling.

[0059] 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.

[0060] In this invention, the server includes means for storing user data and past communication records, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to an information processing device; and means for monitoring the operating status of the application and notifying the information processing device when important communication occurs. This enables the automatic selection of the optimal communication environment even while on the move, resulting in uninterrupted, high-quality communication.

[0061] A "user" refers to an individual or legal entity that uses this system, and is the entity that uses the internet or data communication through a communication terminal.

[0062] "Data" refers to all information related to communication, including user information, past communication records, and application usage.

[0063] "Radio wave strength" is an indicator that shows the strength of the wireless signal received by a communication terminal, and it directly affects the quality of communication.

[0064] A "server" is an information processing device that stores user data, collects and analyzes network information, and acts as an intermediary between communication terminals and the network.

[0065] "Network quality information" refers to information necessary for evaluating communication status, and includes indicators such as signal strength, line stability, and latency.

[0066] "Communication equipment" refers to devices used by users, such as smartphones and tablets, that can connect to a network.

[0067] "Automatically switching connections" refers to the communication device automatically switching to a different network without requiring manual operation in order to maintain an optimal communication environment.

[0068] This system optimizes communication quality in a specific network environment through cooperation between the user's communication terminal and a server. The communication terminal is configured to automatically select the optimal network even when the user is on the move. Specifically, the terminal periodically measures signal strength and network quality using its built-in communication module and transmits this data to the server. Data security is ensured by using the SSL / TLS protocol during data transmission.

[0069] The server stores collected real-time network information and historical communication history in a database. To perform high-speed data analysis, the server utilizes analysis scripts built in Python and SQL queries to select the optimal communication network. Based on the analysis results, the server sends network switching instructions to the communication terminal as needed. This allows the terminal to smoothly switch connections between public 4G / 5G networks and local 5G networks.

[0070] As a concrete example, consider a scenario where a user is streaming a video on a train during their commute. In this case, the communication terminal detects a decrease in signal strength due to concentrated communication usage on the train and sends this data to the server. The server confirms that the video streaming app is running and, after comparing it with past communication history, determines that using local 5G is more appropriate. Following instructions from the server, the communication terminal switches to local 5G, allowing the user to enjoy watching the video without interruption.

[0071] An example of a prompt to input into a generative AI model is as follows: "Describe a system that maintains optimal network connectivity even when the user is on the move. Include specific examples, such as data handling during video streaming on a crowded train." This prompt is expected to generate detailed instructions and examples like the one above.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The terminal measures signal strength and network quality data at regular intervals. Based on this input information (indicators such as signal strength and SNR), the terminal sends the measurement results to the server. Specifically, the communication module installed in the terminal receives wireless signals and generates data measuring their strength and quality. This data is securely transmitted to the server using the SSL / TLS protocol.

[0075] Step 2:

[0076] The server uses data received from the terminal as input and analyzes it against historical communication records stored in the database and real-time network quality information. This process generates output information necessary for selecting the optimal communication network. Specifically, the server executes a data analysis script using Python, comparing the received data with past communication history.

[0077] Step 3:

[0078] The server selects an appropriate network connection based on the analysis results and sends the selection result as output to the terminal. The terminal receives this instruction as input and automatically switches from the current network to the selected network. Specifically, the terminal's network settings are dynamically changed and the appropriate profile is applied.

[0079] Step 4:

[0080] The terminal continuously monitors communication performance after the switch and outputs feedback to the server. Specifically, the terminal measures signal strength and latency on the new line as input information and sends this data to the server. This allows the server to continuously optimize the network selection criteria.

[0081] (Application Example 1)

[0082] 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."

[0083] To improve the user's communication experience within stores, seamless switching between wireless networks and mobile data communications is required. However, efficient systems for achieving this in real-world spaces have not yet been sufficiently developed, leading to communication failures and data delays. In particular, an inappropriate selection of communication network can impair the user experience.

[0084] 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.

[0085] In this invention, the server includes a computing device equipped with a storage medium for storing user attribute data and past connection history, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to the computing device; and means for monitoring the operational status of information processing and notifying the computing device of important data communication when it occurs. This makes it possible to seamlessly switch between wireless networks and mobile data communication within a store, providing a stable communication experience.

[0086] "User attribute data" refers to basic information about users, which is used to optimize communication environments and services.

[0087] "Past connection history" refers to a record of the communication networks a user has previously connected to and the conditions at the time, which is used to predict communication quality and select the optimal connection.

[0088] "Real-time communication quality information" refers to data such as signal strength and communication speed in the current communication environment, and is used for rapid network selection and switching.

[0089] A "storage medium" is hardware used to store data, and within a server device, it plays a role in maintaining user attribute data and past connection history.

[0090] A "computing device" is a device used for information processing, and servers and information terminals fulfill this role. It has the function of analyzing data related to communication networks and selecting the optimal network.

[0091] "Signal strength" is an indicator of the strength of a communication signal and is an important factor in selecting an appropriate network.

[0092] "Quality data" refers to data related to performance aspects such as stability and speed during communication, and is information that contributes to improving the communication experience.

[0093] "Information processing operational status" refers to the status of applications and processes running on communication terminals, and serves as a basis for determining communication priority.

[0094] "Important data communications" refer to communications of information of high importance to the user, and are prioritized and notified to the server device in situations where a high-quality communication environment is required.

[0095] A "communication network" refers to a collection of networks available to the user, and is what the system selects to provide the optimal communication experience.

[0096] "Information terminal" refers to communication devices owned by individual users, and typically includes mobile terminals and personal devices.

[0097] A "wireless network" is a technology that enables data communication without wired connections, and when used within a store, it allows for free movement.

[0098] "Mobile data communication" is a technology that enables stable communication even for terminals in motion, and involves sending and receiving data via a mobile network.

[0099] This invention provides a system for improving the user's communication experience in physical stores. This system consists of a server including a computing device and the cooperation of the user's mobile terminal as an information terminal.

[0100] The server first stores user attribute data and past connection history in a storage medium. Based on this data, the server collects communication quality information in real time and transmits signal strength and quality data to a computing device. The server monitors the operational status of information terminals and, when important data communication occurs, analyzes the optimal communication network based on that information.

[0101] The terminal is responsible for sending data collected at regular intervals to the server. This ensures that users can utilize information services in a suitable communication environment. For example, if a user is searching for product information in a store, the terminal will automatically switch to a more stable mobile data connection if the Wi-Fi connection is unstable. This ensures that the user experience is maintained without interruption.

[0102] Furthermore, the server analyzes network quality based on the data it collects and sends the optimal connection instructions to the user's terminal. During this process, the user is unaware of the network switching, ensuring a smooth and reliable connection.

[0103] A concrete example of a prompt might be, "Please provide an algorithm for designing a system where a smartphone app seamlessly switches between Wi-Fi and mobile data communication within a physical store, allowing users to smoothly access online services." By inputting this prompt into a generating AI model, it is possible to obtain design proposals for even more advanced communication control systems.

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The terminal measures signal strength and quality data at predetermined time intervals. This data is used as input information to evaluate the current network environment. The terminal prepares to send this measurement data to the server.

[0107] Step 2:

[0108] The terminal monitors application usage. The input here represents the application's operational status and serves as basic data for determining the importance of data communication. When important data communication is required, the terminal notifies the server of this information.

[0109] Step 3:

[0110] The server receives signal strength, quality data, and application usage information transmitted from the terminal. Based on this input data, the server uses past connection history and real-time communication quality information to perform calculations to select the optimal communication network. The server determines which communication network is best and prepares the result.

[0111] Step 4:

[0112] The server sends connection instructions to the terminal regarding the selected communication network. This output provides information for changing the terminal's communication settings. Based on the server's instructions, the terminal seamlessly switches between the wireless network and mobile data communication.

[0113] Step 5:

[0114] Users enjoy an optimal communication environment through the coordination between the server and the terminal. This allows users to comfortably use information services without interruptions. Specifically, they can continue operations such as searching for product information or placing online orders without any communication interruptions.

[0115] 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.

[0116] This invention optimizes the communication environment by combining an emotion engine with the communication system, taking into account the user's emotional state. The user's communication terminal, in addition to general network connectivity, is equipped with voice analysis and facial recognition capabilities via a camera. Using these functions, the user's emotional data can be collected and transmitted to a server.

[0117] The server stores user sentiment data in its database, along with signal strength and quality information related to normal connection conditions, application usage, and past communication history. The server comprehensively analyzes this data and selects the optimal network based on the results. It can also automatically adjust network settings to improve the communication experience based on the user's sentiment.

[0118] As a concrete example, consider a scenario where a user is watching a video and the device determines that the user is experiencing stress. Normally, in an environment where data communication is frequently interrupted, the stress level may increase. Therefore, the device sends emotional data to a server, and the server, based on the received data, determines that a stable communication environment is necessary.

[0119] This prompts the server to switch to the local 5G network, providing a stable communication environment. As a result, users can enjoy uninterrupted video streaming, contributing to reduced stress.

[0120] This system allows users to receive an emotionally-based, personalized user experience, which is expected to improve satisfaction with communication services.

[0121] The following describes the processing flow.

[0122] Step 1:

[0123] The device uses its built-in microphone and camera to collect voice and facial data while the user is using it, and analyzes the user's emotions. This allows it to determine emotional states such as joy, stress, and frustration.

[0124] Step 2:

[0125] The terminal sends the analyzed emotion data, along with signal strength and communication quality data, to the server. This transmission occurs at regular intervals, serving to convey real-time status to the server.

[0126] Step 3:

[0127] The server comprehensively analyzes received sentiment data, signal strength, communication quality information, application usage, and past communication history. This analysis helps to assess what kind of communication environment the user needs.

[0128] Step 4:

[0129] Based on the analysis of emotional data, the server determines that a particularly stable communication environment is necessary when the user is experiencing stress, and instructs the user to switch to an appropriate network. This instruction is sent to the terminal immediately.

[0130] Step 5:

[0131] The device automatically switches to the appropriate network, such as local 5G, based on instructions from the server. This operation is seamless, and care has been taken to ensure that users do not experience any interruptions in their communication.

[0132] Step 6:

[0133] Users can use applications without interruption by utilizing the selected optimal communication environment. For example, they can enjoy a comfortable video viewing experience.

[0134] This trend will lead to the realization of systems that provide a better user experience by utilizing user emotional data in the communication environment.

[0135] (Example 2)

[0136] 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".

[0137] In today's digital communication environment, a user's emotional state can significantly impact their communication experience. However, conventional communication systems have not optimized their networks to take user emotions into account, resulting in decreased user satisfaction, particularly under high load or unstable connection conditions. To solve these problems, it is necessary to consider the user's emotional state in real time and provide an optimal connection environment.

[0138] 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.

[0139] In this invention, the server includes means having a database for analyzing the user's emotional state and optimizing communication services; means for transmitting a digital signal containing emotional data to an information processing device; and means for analyzing the received emotional data, signal strength, and past activity logs in the information processing device and selecting an optimized communication network. This makes it possible to provide personalized network services that respond to the user's emotions and improve the communication experience.

[0140] "User" refers to an individual or group that accesses digital services using a communication device.

[0141] "Emotional state" refers to the emotional reactions and psychological state a user exhibits during their communication experience.

[0142] A "database" refers to an information management system that systematically stores user sentiment data and communication-related data, making it accessible as needed.

[0143] An "information processing device" refers to a computer system used for receiving, analyzing, and directing network optimization.

[0144] A "digital signal" refers to an electrical signal that represents a user's emotional data and other communication-related information and is transmitted to an information processing device.

[0145] "Emotional data" refers to information indicating a user's psychological state, obtained by analyzing their voice and facial expressions.

[0146] "Communication services" refer to the functions and processes of digital information exchange provided to users via the internet.

[0147] "Network optimization" refers to the adjustment of settings and reallocation of resources within a communication system to improve the efficiency and quality of data transmission.

[0148] "Automatic connection change" refers to the process by which a communication terminal switches its current network settings to other settings based on instructions from an information processing device.

[0149] This invention is a system that optimizes the communication environment based on emotional state. Its main components include a communication terminal used by the user, a server that processes data, and a network to support them.

[0150] The communication terminals used by users are equipped with hardware capable of voice analysis and facial recognition via cameras. This allows the terminals to collect user emotion data in real time and transmit it to a server. The software used includes voice recognition libraries and machine learning model execution environments.

[0151] The server stores the received sentiment data along with other communication-related data in a database and performs analysis. This analysis uses data analysis algorithms and network optimization algorithms. Based on the analysis results, the server calculates the optimal network settings and sends those settings to the communication terminals.

[0152] A concrete example is when a user is using a video streaming service. When the user experiences stress, emotional data is collected, and based on this data, the server determines that a more stable network environment is needed. By then instructing the server to switch to the local 5G network, the user can enjoy an uninterrupted viewing experience.

[0153] An example of a prompt this system might anticipate is, "Explain how to optimize the communication environment when the user is experiencing stress." This allows the AI ​​model to recognize the user's emotional state and gain guidance for developing an optimization strategy.

[0154] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0155] Step 1:

[0156] While a user is using a communication device, the device collects emotional data. The input consists of the user's voice and facial image. The device analyzes this data using a voice analysis module and a facial recognition algorithm, and outputs digital data indicating the user's emotional state. Specifically, it extracts voice tone and facial features and generates emotional tags such as "stress" and "relaxed."

[0157] Step 2:

[0158] The terminal sends the collected sentiment data to the server. The input is the sentiment tag generated in step 1 and the current communication metadata (e.g., signal strength, quality information). The terminal sends this information to the server over the network, and the server stores this data in a database. The output is the integrated dataset stored on the server.

[0159] Step 3:

[0160] The server analyzes the data it receives. The input consists of sentiment data and communication metadata stored in a database. The server uses an AI model to analyze this data and calculate the optimized network settings. Based on the data analysis, it outputs a judgment that "the network load is high, so we should switch to the local 5G network."

[0161] Step 4:

[0162] The server issues instructions to the communication terminal based on the analysis results. The input is the analysis results from step 3. The server sends instructions to the terminal to connect to a specific network and suggests settings to optimize communication quality. The output is the network configuration change instructions sent to the terminal.

[0163] Step 5:

[0164] The terminal changes its network settings according to instructions received from the server. The input is the network setting instruction from the server. The terminal automatically switches network connections and performs operations to ensure a more stable communication environment. The output is the new network settings that provide optimized communication quality.

[0165] (Application Example 2)

[0166] 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".

[0167] In elderly care settings, appropriate responses are required based on the emotional state of the user, but systems that can grasp this in real time and integrate it with communication services have not yet been fully realized. Furthermore, the impact of communication network quality on the user's emotions must also be considered. To solve this problem, it is necessary to accurately recognize the user's emotions and optimize the communication network accordingly.

[0168] 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.

[0169] In this invention, the server includes means for analyzing the user's facial expressions and voice to detect their emotional state, means for optimizing communication quality based on the user's emotional state and automatically switching the connection of communication terminals, and means for transmitting signal strength and quality data measured at regular time intervals to an information recording device. This makes it possible to provide a stable communication service that responds to the user's emotions.

[0170] "User information" refers to personal data and attribute information about individual users.

[0171] "Communication history data" refers to records of past network connections and communication activities.

[0172] An "information recording and ethics device" refers to a device that has server functionality for storing and analyzing user information and network quality information.

[0173] "Signal strength" is an indicator that shows the strength of the wireless signal received by a communication terminal.

[0174] "Quality data" refers to measurement information regarding the performance and stability of network connections.

[0175] "Application usage status" refers to information regarding the activity status of applications running on a communication terminal.

[0176] "Means of analyzing user facial expressions and voice" refers to technology that uses cameras and microphones to analyze a user's facial expressions and voice in real time.

[0177] "Means for detecting emotional state" refers to algorithms used to determine emotions inferred from a user's facial expressions and voice.

[0178] "Methods for optimizing communication quality and automatically switching the connection of communication terminals" refers to technologies that adjust network settings according to the communication environment and change the connection destination to provide a better communication experience.

[0179] The system for implementing this invention utilizes a communication terminal owned by the user and a server that functions as an information recording and ethics device. The communication terminal is equipped with a camera for recognizing the user's facial expressions and a microphone for analyzing the user's voice. Furthermore, the terminal has facial recognition software and a voice analysis algorithm installed, enabling real-time detection of the user's emotional state.

[0180] When a terminal detects an emotional state, it sends that data to the server at regular intervals. The server functions as an information recording and ethical device, comprehensively analyzing the received emotional data, signal strength, quality data, and application usage. This analysis process utilizes a database engine and statistical analysis algorithms. Based on the analysis results, the server determines the optimal network connection and automatically instructs the user's communication terminal to change the connection. This allows the user to enjoy an optimal communication environment tailored to their emotional state.

[0181] As a concrete example, this system could be used in elderly care settings. A care robot would analyze the elderly person's facial expressions and voice in real time, and when stress or loneliness is detected, it would provide appropriate verbal cues or play music. This is expected to improve the quality of life for the elderly.

[0182] An example of a prompt for a generative AI model is: "We are developing a care robot system that analyzes the facial expressions and voice of elderly people and plays relaxing music according to their emotional state. Please provide an algorithm for estimating emotions using the following image and audio."

[0183] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0184] Step 1:

[0185] The device uses a camera and microphone to capture the user's facial expressions and voice in real time. It acquires image data and audio data as input. This data is processed by facial recognition software and a voice analysis algorithm to estimate the user's emotional state. It generates estimated emotional state data as output.

[0186] Step 2:

[0187] The device sends estimated emotional state data to the server. Simultaneously, it also sends signal strength and quality data collected from the network, as well as application usage data, to the server. These are processed by the server as input data.

[0188] Step 3:

[0189] The server comprehensively analyzes received emotional state data, signal strength, quality data, and application usage. This analysis utilizes a database engine and statistical analysis algorithms to determine the optimal network connection. As output, it generates suggestions for appropriate network settings.

[0190] Step 4:

[0191] The server sends a suggested network configuration to the communication terminal. The terminal automatically switches the network connection based on these instructions. This allows the user to continue using the service in an optimal communication environment tailored to their needs.

[0192] 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.

[0193] 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.

[0194] 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.

[0195] [Second Embodiment]

[0196] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0197] 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.

[0198] 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).

[0199] 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.

[0200] 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.

[0201] 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).

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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".

[0208] This invention provides a system for optimizing communication quality in a specific network environment, in which the user's communication terminal and server device work together. The terminal enables the user to automatically select the most suitable communication environment at all times, even when the user is on the move.

[0209] The server stores user information and past communication history in a database and collects real-time network quality information. This information is used to analyze which network connection is optimal and to send instructions to the terminal to provide an appropriate communication environment.

[0210] The terminal measures signal strength and quality data at regular intervals and sends this data to the server. Furthermore, the terminal monitors the status of currently used applications and identifies applications that require high bandwidth. In this way, the terminal can smoothly switch automatically between public 4G / 5G networks and local 5G networks based on instructions from the server.

[0211] As a concrete example, consider a user streaming a video on a train during their commute. Because network usage is concentrated on trains, stable viewing may be difficult with a standard public 4G network. In this case, the device periodically sends signal strength and quality data to the server. The server, based on this data, confirms that the user is using a video streaming app, and considers past communication history to determine that using a local 5G network is more appropriate. The server then instructs the device to switch to local 5G, allowing the user to enjoy uninterrupted video viewing.

[0212] In this way, seamless collaboration between servers and terminals makes it possible to continuously provide users with an excellent communication experience.

[0213] The following describes the processing flow.

[0214] Step 1:

[0215] The terminal measures signal strength and quality, including RSRP, RSRQ, and SINR, at regular intervals. This measurement data serves as fundamental information for evaluating communication stability.

[0216] Step 2:

[0217] The terminal sends the measured signal strength and quality data to the server. This data is used by the server to understand the real-time network conditions.

[0218] Step 3:

[0219] The device monitors the applications currently in use and identifies those that require high bandwidth (e.g., video streaming apps). This information helps determine the priority of communication needs.

[0220] Step 4:

[0221] The server analyzes received signal strength and quality data, application usage, and past communication history. This analysis helps determine the optimal network to select.

[0222] Step 5:

[0223] Based on the analysis results, the server evaluates whether a public 4G / 5G network or a local 5G network is appropriate and sends a network switching instruction to the terminal.

[0224] Step 6:

[0225] The terminal automatically switches networks upon receiving instructions from the server. This process is seamless, allowing users to continue using the service without experiencing any communication interruptions.

[0226] Step 7:

[0227] Users can utilize applications (e.g., video streaming) in a stable communication environment through the newly selected optimal communication path.

[0228] This series of processes allows users to receive high-quality communication services without stress, even in congested environments.

[0229] (Example 1)

[0230] 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."

[0231] In recent years, the use of mobile communication devices has increased, and many users require internet access while on the go. However, communication quality tends to be unstable, especially in certain travel environments such as trains and vehicles, which can cause problems when making important communications. The objective of this invention is to solve this problem and realize high-quality communication even while traveling.

[0232] 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.

[0233] In this invention, the server includes means for storing user data and past communication records, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to an information processing device; and means for monitoring the operating status of the application and notifying the information processing device when important communication occurs. This enables the automatic selection of the optimal communication environment even while on the move, resulting in uninterrupted, high-quality communication.

[0234] A "user" refers to an individual or legal entity that uses this system, and is the entity that uses the internet or data communication through a communication terminal.

[0235] "Data" refers to all information related to communication, including user information, past communication records, and application usage.

[0236] "Radio wave strength" is an indicator that shows the strength of the wireless signal received by a communication terminal, and it directly affects the quality of communication.

[0237] A "server" is an information processing device that stores user data, collects and analyzes network information, and acts as an intermediary between communication terminals and the network.

[0238] "Network quality information" refers to information necessary for evaluating communication status, and includes indicators such as signal strength, line stability, and latency.

[0239] "Communication equipment" refers to devices used by users, such as smartphones and tablets, that can connect to a network.

[0240] "Automatically switching connections" refers to the communication device automatically switching to a different network without requiring manual operation in order to maintain an optimal communication environment.

[0241] This system optimizes communication quality in a specific network environment through cooperation between the user's communication terminal and a server. The communication terminal is configured to automatically select the optimal network even when the user is on the move. Specifically, the terminal periodically measures signal strength and network quality using its built-in communication module and transmits this data to the server. Data security is ensured by using the SSL / TLS protocol during data transmission.

[0242] The server stores collected real-time network information and historical communication history in a database. To perform high-speed data analysis, the server utilizes analysis scripts built in Python and SQL queries to select the optimal communication network. Based on the analysis results, the server sends network switching instructions to the communication terminal as needed. This allows the terminal to smoothly switch connections between public 4G / 5G networks and local 5G networks.

[0243] As a concrete example, consider a scenario where a user is streaming a video on a train during their commute. In this case, the communication terminal detects a decrease in signal strength due to concentrated communication usage on the train and sends this data to the server. The server confirms that the video streaming app is running and, after comparing it with past communication history, determines that using local 5G is more appropriate. Following instructions from the server, the communication terminal switches to local 5G, allowing the user to enjoy watching the video without interruption.

[0244] An example of a prompt to input into a generative AI model is as follows: "Describe a system that maintains optimal network connectivity even when the user is on the move. Include specific examples, such as data handling during video streaming on a crowded train." This prompt is expected to generate detailed instructions and examples like the one above.

[0245] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0246] Step 1:

[0247] The terminal measures signal strength and network quality data at regular intervals. Based on this input information (indicators such as signal strength and SNR), the terminal sends the measurement results to the server. Specifically, the communication module installed in the terminal receives wireless signals and generates data measuring their strength and quality. This data is securely transmitted to the server using the SSL / TLS protocol.

[0248] Step 2:

[0249] The server uses data received from the terminal as input and analyzes it against historical communication records stored in the database and real-time network quality information. This process generates output information necessary for selecting the optimal communication network. Specifically, the server executes a data analysis script using Python, comparing the received data with past communication history.

[0250] Step 3:

[0251] The server selects an appropriate network connection based on the analysis results and sends the selection result as output to the terminal. The terminal receives this instruction as input and automatically switches from the current network to the selected network. Specifically, the terminal's network settings are dynamically changed and the appropriate profile is applied.

[0252] Step 4:

[0253] The terminal continuously monitors communication performance after the switch and outputs feedback to the server. Specifically, the terminal measures signal strength and latency on the new line as input information and sends this data to the server. This allows the server to continuously optimize the network selection criteria.

[0254] (Application Example 1)

[0255] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0256] To improve the user's communication experience within stores, seamless switching between wireless networks and mobile data communications is required. However, efficient systems for achieving this in real-world spaces have not yet been sufficiently developed, leading to communication failures and data delays. In particular, an inappropriate selection of communication network can impair the user experience.

[0257] 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.

[0258] In this invention, the server includes a computing device equipped with a storage medium for storing user attribute data and past connection history, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to the computing device; and means for monitoring the operational status of information processing and notifying the computing device of important data communication when it occurs. This makes it possible to seamlessly switch between wireless networks and mobile data communication within a store, providing a stable communication experience.

[0259] "User attribute data" refers to basic information about users, which is used to optimize communication environments and services.

[0260] "Past connection history" refers to a record of the communication networks a user has previously connected to and the conditions at the time, which is used to predict communication quality and select the optimal connection.

[0261] "Real-time communication quality information" refers to data such as signal strength and communication speed in the current communication environment, and is used for rapid network selection and switching.

[0262] A "storage medium" is hardware used to store data, and within a server device, it plays a role in maintaining user attribute data and past connection history.

[0263] A "computing device" is a device used for information processing, and servers and information terminals fulfill this role. It has the function of analyzing data related to communication networks and selecting the optimal network.

[0264] "Signal strength" is an indicator of the strength of a communication signal and is an important factor in selecting an appropriate network.

[0265] "Quality data" refers to data related to performance aspects such as stability and speed during communication, and is information that contributes to improving the communication experience.

[0266] "Information processing operational status" refers to the status of applications and processes running on communication terminals, and serves as a basis for determining communication priority.

[0267] "Important data communications" refer to communications of information of high importance to the user, and are prioritized and notified to the server device in situations where a high-quality communication environment is required.

[0268] A "communication network" refers to a collection of networks available to the user, and is what the system selects to provide the optimal communication experience.

[0269] "Information terminal" refers to communication devices owned by individual users, and typically includes mobile terminals and personal devices.

[0270] A "wireless network" is a technology that enables data communication without wired connections, and when used within a store, it allows for free movement.

[0271] "Mobile data communication" is a technology that enables stable communication even for terminals in motion, and involves sending and receiving data via a mobile network.

[0272] This invention provides a system for improving the user's communication experience in physical stores. This system consists of a server including a computing device and the cooperation of the user's mobile terminal as an information terminal.

[0273] The server first stores user attribute data and past connection history in a storage medium. Based on this data, the server collects communication quality information in real time and transmits signal strength and quality data to a computing device. The server monitors the operational status of information terminals and, when important data communication occurs, analyzes the optimal communication network based on that information.

[0274] The terminal is responsible for sending data collected at regular intervals to the server. This ensures that users can utilize information services in a suitable communication environment. For example, if a user is searching for product information in a store, the terminal will automatically switch to a more stable mobile data connection if the Wi-Fi connection is unstable. This ensures that the user experience is maintained without interruption.

[0275] Furthermore, the server analyzes network quality based on the data it collects and sends the optimal connection instructions to the user's terminal. During this process, the user is unaware of the network switching, ensuring a smooth and reliable connection.

[0276] A concrete example of a prompt might be, "Please provide an algorithm for designing a system where a smartphone app seamlessly switches between Wi-Fi and mobile data communication within a physical store, allowing users to smoothly access online services." By inputting this prompt into a generating AI model, it is possible to obtain design proposals for even more advanced communication control systems.

[0277] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0278] Step 1:

[0279] The terminal measures signal strength and quality data at predetermined time intervals. This data is used as input information to evaluate the current network environment. The terminal prepares to send this measurement data to the server.

[0280] Step 2:

[0281] The terminal monitors the usage status of the application. The input here is the operating status of the application, which serves as the basic data for determining the importance of data communication. When important data communication is required, the terminal notifies the server of this information.

[0282] Step 3:

[0283] The server receives the radio wave intensity, quality data, and application usage status transmitted from the terminal. Based on these input data, the server utilizes the past connection history and real-time communication quality information to perform calculations for selecting the optimal communication network. The server determines which communication network is optimal and prepares the result.

[0284] Step 4:

[0285] The server transmits a connection instruction regarding the selected communication network to the terminal. This output serves as the information for changing the communication settings of the terminal. Based on the instruction content of the server, the terminal seamlessly switches the connection between the wireless network and mobile data communication.

[0286] Step 5:

[0287] The user enjoys an optimal communication environment through the cooperation between the server and the terminal. As a result, the user can comfortably use information services without communication interruption. Specifically, when searching for product information or placing an online order, the operation can continue without communication interruption.

[0288] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0289] This invention optimizes the communication environment by combining an emotion engine with the communication system, taking into account the user's emotional state. The user's communication terminal, in addition to general network connectivity, is equipped with voice analysis and facial recognition capabilities via a camera. Using these functions, the user's emotional data can be collected and transmitted to a server.

[0290] The server stores user sentiment data in its database, along with signal strength and quality information related to normal connection conditions, application usage, and past communication history. The server comprehensively analyzes this data and selects the optimal network based on the results. It can also automatically adjust network settings to improve the communication experience based on the user's sentiment.

[0291] As a concrete example, consider a scenario where a user is watching a video and the device determines that the user is experiencing stress. Normally, in an environment where data communication is frequently interrupted, the stress level may increase. Therefore, the device sends emotional data to a server, and the server, based on the received data, determines that a stable communication environment is necessary.

[0292] This prompts the server to switch to the local 5G network, providing a stable communication environment. As a result, users can enjoy uninterrupted video streaming, contributing to reduced stress.

[0293] This system allows users to receive an emotionally-based, personalized user experience, which is expected to improve satisfaction with communication services.

[0294] The following describes the processing flow.

[0295] Step 1:

[0296] The device uses its built-in microphone and camera to collect voice and facial data while the user is using it, and analyzes the user's emotions. This allows it to determine emotional states such as joy, stress, and frustration.

[0297] Step 2:

[0298] The terminal sends the analyzed emotion data, along with signal strength and communication quality data, to the server. This transmission occurs at regular intervals, serving to convey real-time status to the server.

[0299] Step 3:

[0300] The server comprehensively analyzes received sentiment data, signal strength, communication quality information, application usage, and past communication history. This analysis helps to assess what kind of communication environment the user needs.

[0301] Step 4:

[0302] Based on the analysis of emotional data, the server determines that a particularly stable communication environment is necessary when the user is experiencing stress, and instructs the user to switch to an appropriate network. This instruction is sent to the terminal immediately.

[0303] Step 5:

[0304] The device automatically switches to the appropriate network, such as local 5G, based on instructions from the server. This operation is seamless, and care has been taken to ensure that users do not experience any interruptions in their communication.

[0305] Step 6:

[0306] Users can use applications without interruption by utilizing the selected optimal communication environment. For example, they can enjoy a comfortable video viewing experience.

[0307] Through this process, a system that provides a better user experience is realized by utilizing the user's emotional data in the communication environment.

[0308] (Example 2)

[0309] Next, Example 2 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".

[0310] In the modern digital communication environment, the user's emotional state may significantly affect the communication experience. However, in conventional communication systems, network optimization considering the user's emotions has not been carried out, and there is a problem that the user satisfaction decreases particularly under high load or unstable connection environments. To solve such problems, it is necessary to consider the user's emotional state in real time and provide an optimal connection environment.

[0311] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0312] In this invention, the server includes means for analyzing the user's emotional state and having a database for optimizing communication services, means for transmitting a digital signal including emotional data to an information processing device, and means for analyzing the emotional data, signal strength, and past activity logs received by the information processing device and selecting an optimized communication network. Thereby, it becomes possible to provide a personalized network service according to the user's emotions and improve the communication experience.

[0313] The "user" refers to an individual or group who accesses digital services using a communication terminal.

[0314] The "emotional state" refers to the emotional reactions or psychological states shown by the user during the communication experience.

[0315] A "database" refers to an information management system that systematically stores user sentiment data and communication-related data, making it accessible as needed.

[0316] An "information processing device" refers to a computer system used for receiving, analyzing, and directing network optimization.

[0317] A "digital signal" refers to an electrical signal that represents a user's emotional data and other communication-related information and is transmitted to an information processing device.

[0318] "Emotional data" refers to information indicating a user's psychological state, obtained by analyzing their voice and facial expressions.

[0319] "Communication services" refer to the functions and processes of digital information exchange provided to users via the internet.

[0320] "Network optimization" refers to the adjustment of settings and reallocation of resources within a communication system to improve the efficiency and quality of data transmission.

[0321] "Automatic connection change" refers to the process by which a communication terminal switches its current network settings to other settings based on instructions from an information processing device.

[0322] This invention is a system that optimizes the communication environment based on emotional state. Its main components include a communication terminal used by the user, a server that processes data, and a network to support them.

[0323] The communication terminals used by users are equipped with hardware capable of voice analysis and facial recognition via cameras. This allows the terminals to collect user emotion data in real time and transmit it to a server. The software used includes voice recognition libraries and machine learning model execution environments.

[0324] The server stores the received sentiment data along with other communication-related data in a database and performs analysis. This analysis uses data analysis algorithms and network optimization algorithms. Based on the analysis results, the server calculates the optimal network settings and sends those settings to the communication terminals.

[0325] A concrete example is when a user is using a video streaming service. When the user experiences stress, emotional data is collected, and based on this data, the server determines that a more stable network environment is needed. By then instructing the server to switch to the local 5G network, the user can enjoy an uninterrupted viewing experience.

[0326] An example of a prompt this system might anticipate is, "Explain how to optimize the communication environment when the user is experiencing stress." This allows the AI ​​model to recognize the user's emotional state and gain guidance for developing an optimization strategy.

[0327] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0328] Step 1:

[0329] While a user is using a communication device, the device collects emotional data. The input consists of the user's voice and facial image. The device analyzes this data using a voice analysis module and a facial recognition algorithm, and outputs digital data indicating the user's emotional state. Specifically, it extracts voice tone and facial features and generates emotional tags such as "stress" and "relaxed."

[0330] Step 2:

[0331] The terminal sends the collected sentiment data to the server. The input is the sentiment tag generated in step 1 and the current communication metadata (e.g., signal strength, quality information). The terminal sends this information to the server over the network, and the server stores this data in a database. The output is the integrated dataset stored on the server.

[0332] Step 3:

[0333] The server analyzes the data it receives. The input consists of sentiment data and communication metadata stored in a database. The server uses an AI model to analyze this data and calculate the optimized network settings. Based on the data analysis, it outputs a judgment that "the network load is high, so we should switch to the local 5G network."

[0334] Step 4:

[0335] The server issues instructions to the communication terminal based on the analysis results. The input is the analysis results from step 3. The server sends instructions to the terminal to connect to a specific network and suggests settings to optimize communication quality. The output is the network configuration change instructions sent to the terminal.

[0336] Step 5:

[0337] The terminal changes its network settings according to instructions received from the server. The input is the network setting instruction from the server. The terminal automatically switches network connections and performs operations to ensure a more stable communication environment. The output is the new network settings that provide optimized communication quality.

[0338] (Application Example 2)

[0339] 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."

[0340] In elderly care settings, appropriate responses are required based on the emotional state of the user, but systems that can grasp this in real time and integrate it with communication services have not yet been fully realized. Furthermore, the impact of communication network quality on the user's emotions must also be considered. To solve this problem, it is necessary to accurately recognize the user's emotions and optimize the communication network accordingly.

[0341] 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.

[0342] In this invention, the server includes means for analyzing the user's facial expressions and voice to detect their emotional state, means for optimizing communication quality based on the user's emotional state and automatically switching the connection of communication terminals, and means for transmitting signal strength and quality data measured at regular time intervals to an information recording device. This makes it possible to provide a stable communication service that responds to the user's emotions.

[0343] "User information" refers to personal data and attribute information about individual users.

[0344] "Communication history data" refers to records of past network connections and communication activities.

[0345] An "information recording and ethics device" refers to a device that has server functionality for storing and analyzing user information and network quality information.

[0346] "Signal strength" is an indicator that shows the strength of the wireless signal received by a communication terminal.

[0347] "Quality data" refers to measurement information regarding the performance and stability of network connections.

[0348] "Application usage status" refers to information regarding the activity status of applications running on a communication terminal.

[0349] "Means of analyzing user facial expressions and voice" refers to technology that uses cameras and microphones to analyze a user's facial expressions and voice in real time.

[0350] "Means for detecting emotional state" refers to algorithms used to determine emotions inferred from a user's facial expressions and voice.

[0351] "Methods for optimizing communication quality and automatically switching the connection of communication terminals" refers to technologies that adjust network settings according to the communication environment and change the connection destination to provide a better communication experience.

[0352] The system for implementing this invention utilizes a communication terminal owned by the user and a server that functions as an information recording and ethics device. The communication terminal is equipped with a camera for recognizing the user's facial expressions and a microphone for analyzing the user's voice. Furthermore, the terminal has facial recognition software and a voice analysis algorithm installed, enabling real-time detection of the user's emotional state.

[0353] When a terminal detects an emotional state, it sends that data to the server at regular intervals. The server functions as an information recording and ethical device, comprehensively analyzing the received emotional data, signal strength, quality data, and application usage. This analysis process utilizes a database engine and statistical analysis algorithms. Based on the analysis results, the server determines the optimal network connection and automatically instructs the user's communication terminal to change the connection. This allows the user to enjoy an optimal communication environment tailored to their emotional state.

[0354] As a concrete example, this system could be used in elderly care settings. A care robot would analyze the elderly person's facial expressions and voice in real time, and when stress or loneliness is detected, it would provide appropriate verbal cues or play music. This is expected to improve the quality of life for the elderly.

[0355] An example of a prompt for a generative AI model is: "We are developing a care robot system that analyzes the facial expressions and voice of elderly people and plays relaxing music according to their emotional state. Please provide an algorithm for estimating emotions using the following image and audio."

[0356] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0357] Step 1:

[0358] The device uses a camera and microphone to capture the user's facial expressions and voice in real time. It acquires image data and audio data as input. This data is processed by facial recognition software and a voice analysis algorithm to estimate the user's emotional state. It generates estimated emotional state data as output.

[0359] Step 2:

[0360] The device sends estimated emotional state data to the server. Simultaneously, it also sends signal strength and quality data collected from the network, as well as application usage data, to the server. These are processed by the server as input data.

[0361] Step 3:

[0362] The server comprehensively analyzes received emotional state data, signal strength, quality data, and application usage. This analysis utilizes a database engine and statistical analysis algorithms to determine the optimal network connection. As output, it generates suggestions for appropriate network settings.

[0363] Step 4:

[0364] The server sends a suggested network configuration to the communication terminal. The terminal automatically switches the network connection based on these instructions. This allows the user to continue using the service in an optimal communication environment tailored to their needs.

[0365] 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.

[0366] 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.

[0367] 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.

[0368] [Third Embodiment]

[0369] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0370] 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.

[0371] 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).

[0372] 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.

[0373] 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.

[0374] 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).

[0375] 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.

[0376] 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.

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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".

[0381] This invention provides a system for optimizing communication quality in a specific network environment, in which the user's communication terminal and server device work together. The terminal enables the user to automatically select the most suitable communication environment at all times, even when the user is on the move.

[0382] The server stores user information and past communication history in a database and collects real-time network quality information. This information is used to analyze which network connection is optimal and to send instructions to the terminal to provide an appropriate communication environment.

[0383] The terminal measures signal strength and quality data at regular intervals and sends this data to the server. Furthermore, the terminal monitors the status of currently used applications and identifies applications that require high bandwidth. In this way, the terminal can smoothly switch automatically between public 4G / 5G networks and local 5G networks based on instructions from the server.

[0384] As a concrete example, consider a user streaming a video on a train during their commute. Because network usage is concentrated on trains, stable viewing may be difficult with a standard public 4G network. In this case, the device periodically sends signal strength and quality data to the server. The server, based on this data, confirms that the user is using a video streaming app, and considers past communication history to determine that using a local 5G network is more appropriate. The server then instructs the device to switch to local 5G, allowing the user to enjoy uninterrupted video viewing.

[0385] In this way, seamless collaboration between servers and terminals makes it possible to continuously provide users with an excellent communication experience.

[0386] The following describes the processing flow.

[0387] Step 1:

[0388] The terminal measures signal strength and quality, including RSRP, RSRQ, and SINR, at regular intervals. This measurement data serves as fundamental information for evaluating communication stability.

[0389] Step 2:

[0390] The terminal sends the measured signal strength and quality data to the server. This data is used by the server to understand the real-time network conditions.

[0391] Step 3:

[0392] The device monitors the applications currently in use and identifies those that require high bandwidth (e.g., video streaming apps). This information helps determine the priority of communication needs.

[0393] Step 4:

[0394] The server analyzes received signal strength and quality data, application usage, and past communication history. This analysis helps determine the optimal network to select.

[0395] Step 5:

[0396] Based on the analysis results, the server evaluates whether a public 4G / 5G network or a local 5G network is appropriate and sends a network switching instruction to the terminal.

[0397] Step 6:

[0398] The terminal automatically switches networks upon receiving instructions from the server. This process is seamless, allowing users to continue using the service without experiencing any communication interruptions.

[0399] Step 7:

[0400] Users can utilize applications (e.g., video streaming) in a stable communication environment through the newly selected optimal communication path.

[0401] This series of processes allows users to receive high-quality communication services without stress, even in congested environments.

[0402] (Example 1)

[0403] 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."

[0404] In recent years, the use of mobile communication devices has increased, and many users require internet access while on the go. However, communication quality tends to be unstable, especially in certain travel environments such as trains and vehicles, which can cause problems when making important communications. The objective of this invention is to solve this problem and realize high-quality communication even while traveling.

[0405] 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.

[0406] In this invention, the server includes means for storing user data and past communication records, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to an information processing device; and means for monitoring the operating status of the application and notifying the information processing device when important communication occurs. This enables the automatic selection of the optimal communication environment even while on the move, resulting in uninterrupted, high-quality communication.

[0407] A "user" refers to an individual or legal entity that uses this system, and is the entity that uses the internet or data communication through a communication terminal.

[0408] "Data" refers to all information related to communication, including user information, past communication records, and application usage.

[0409] "Radio wave strength" is an indicator that shows the strength of the wireless signal received by a communication terminal, and it directly affects the quality of communication.

[0410] A "server" is an information processing device that stores user data, collects and analyzes network information, and acts as an intermediary between communication terminals and the network.

[0411] "Network quality information" refers to information necessary for evaluating communication status, and includes indicators such as signal strength, line stability, and latency.

[0412] "Communication equipment" refers to devices used by users, such as smartphones and tablets, that can connect to a network.

[0413] "Automatically switching connections" refers to the communication device automatically switching to a different network without requiring manual operation in order to maintain an optimal communication environment.

[0414] This system optimizes communication quality in a specific network environment through cooperation between the user's communication terminal and a server. The communication terminal is configured to automatically select the optimal network even when the user is on the move. Specifically, the terminal periodically measures signal strength and network quality using its built-in communication module and transmits this data to the server. Data security is ensured by using the SSL / TLS protocol during data transmission.

[0415] The server stores collected real-time network information and historical communication history in a database. To perform high-speed data analysis, the server utilizes analysis scripts built in Python and SQL queries to select the optimal communication network. Based on the analysis results, the server sends network switching instructions to the communication terminal as needed. This allows the terminal to smoothly switch connections between public 4G / 5G networks and local 5G networks.

[0416] As a concrete example, consider a scenario where a user is streaming a video on a train during their commute. In this case, the communication terminal detects a decrease in signal strength due to concentrated communication usage on the train and sends this data to the server. The server confirms that the video streaming app is running and, after comparing it with past communication history, determines that using local 5G is more appropriate. Following instructions from the server, the communication terminal switches to local 5G, allowing the user to enjoy watching the video without interruption.

[0417] An example of a prompt to input into a generative AI model is as follows: "Describe a system that maintains optimal network connectivity even when the user is on the move. Include specific examples, such as data handling during video streaming on a crowded train." This prompt is expected to generate detailed instructions and examples like the one above.

[0418] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0419] Step 1:

[0420] The terminal measures signal strength and network quality data at regular intervals. Based on this input information (indicators such as signal strength and SNR), the terminal sends the measurement results to the server. Specifically, the communication module installed in the terminal receives wireless signals and generates data measuring their strength and quality. This data is securely transmitted to the server using the SSL / TLS protocol.

[0421] Step 2:

[0422] The server uses data received from the terminal as input and analyzes it against historical communication records stored in the database and real-time network quality information. This process generates output information necessary for selecting the optimal communication network. Specifically, the server executes a data analysis script using Python, comparing the received data with past communication history.

[0423] Step 3:

[0424] The server selects an appropriate network connection based on the analysis results and sends the selection result as output to the terminal. The terminal receives this instruction as input and automatically switches from the current network to the selected network. Specifically, the terminal's network settings are dynamically changed and the appropriate profile is applied.

[0425] Step 4:

[0426] The terminal continuously monitors communication performance after the switch and outputs feedback to the server. Specifically, the terminal measures signal strength and latency on the new line as input information and sends this data to the server. This allows the server to continuously optimize the network selection criteria.

[0427] (Application Example 1)

[0428] 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."

[0429] To improve the user's communication experience within stores, seamless switching between wireless networks and mobile data communications is required. However, efficient systems for achieving this in real-world spaces have not yet been sufficiently developed, leading to communication failures and data delays. In particular, an inappropriate selection of communication network can impair the user experience.

[0430] 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.

[0431] In this invention, the server includes a computing device equipped with a storage medium for storing user attribute data and past connection history, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to the computing device; and means for monitoring the operational status of information processing and notifying the computing device of important data communication when it occurs. This makes it possible to seamlessly switch between wireless networks and mobile data communication within a store, providing a stable communication experience.

[0432] "User attribute data" refers to basic information about users, which is used to optimize communication environments and services.

[0433] "Past connection history" refers to a record of the communication networks a user has previously connected to and the conditions at the time, which is used to predict communication quality and select the optimal connection.

[0434] "Real-time communication quality information" refers to data such as signal strength and communication speed in the current communication environment, and is used for rapid network selection and switching.

[0435] A "storage medium" is hardware used to store data, and within a server device, it plays a role in maintaining user attribute data and past connection history.

[0436] A "computing device" is a device used for information processing, and servers and information terminals fulfill this role. It has the function of analyzing data related to communication networks and selecting the optimal network.

[0437] "Signal strength" is an indicator of the strength of a communication signal and is an important factor in selecting an appropriate network.

[0438] "Quality data" refers to data related to performance aspects such as stability and speed during communication, and is information that contributes to improving the communication experience.

[0439] "Information processing operational status" refers to the status of applications and processes running on communication terminals, and serves as a basis for determining communication priority.

[0440] "Important data communications" refer to communications of information of high importance to the user, and are prioritized and notified to the server device in situations where a high-quality communication environment is required.

[0441] A "communication network" refers to a collection of networks available to the user, and is what the system selects to provide the optimal communication experience.

[0442] "Information terminal" refers to communication devices owned by individual users, and typically includes mobile terminals and personal devices.

[0443] A "wireless network" is a technology that enables data communication without wired connections, and when used within a store, it allows for free movement.

[0444] "Mobile data communication" is a technology that enables stable communication even for terminals in motion, and involves sending and receiving data via a mobile network.

[0445] This invention provides a system for improving the user's communication experience in physical stores. This system consists of a server including a computing device and the cooperation of the user's mobile terminal as an information terminal.

[0446] The server first stores user attribute data and past connection history in a storage medium. Based on this data, the server collects communication quality information in real time and transmits signal strength and quality data to a computing device. The server monitors the operational status of information terminals and, when important data communication occurs, analyzes the optimal communication network based on that information.

[0447] The terminal is responsible for sending data collected at regular intervals to the server. This ensures that users can utilize information services in a suitable communication environment. For example, if a user is searching for product information in a store, the terminal will automatically switch to a more stable mobile data connection if the Wi-Fi connection is unstable. This ensures that the user experience is maintained without interruption.

[0448] Furthermore, the server analyzes network quality based on the data it collects and sends the optimal connection instructions to the user's terminal. During this process, the user is unaware of the network switching, ensuring a smooth and reliable connection.

[0449] A concrete example of a prompt might be, "Please provide an algorithm for designing a system where a smartphone app seamlessly switches between Wi-Fi and mobile data communication within a physical store, allowing users to smoothly access online services." By inputting this prompt into a generating AI model, it is possible to obtain design proposals for even more advanced communication control systems.

[0450] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0451] Step 1:

[0452] The terminal measures signal strength and quality data at predetermined time intervals. This data is used as input information to evaluate the current network environment. The terminal prepares to send this measurement data to the server.

[0453] Step 2:

[0454] The terminal monitors application usage. The input here represents the application's operational status and serves as basic data for determining the importance of data communication. When important data communication is required, the terminal notifies the server of this information.

[0455] Step 3:

[0456] The server receives signal strength, quality data, and application usage information transmitted from the terminal. Based on this input data, the server uses past connection history and real-time communication quality information to perform calculations to select the optimal communication network. The server determines which communication network is best and prepares the result.

[0457] Step 4:

[0458] The server sends connection instructions to the terminal regarding the selected communication network. This output provides information for changing the terminal's communication settings. Based on the server's instructions, the terminal seamlessly switches between the wireless network and mobile data communication.

[0459] Step 5:

[0460] Users enjoy an optimal communication environment through the coordination between the server and the terminal. This allows users to comfortably use information services without interruptions. Specifically, they can continue operations such as searching for product information or placing online orders without any communication interruptions.

[0461] 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.

[0462] This invention optimizes the communication environment by combining an emotion engine with the communication system, taking into account the user's emotional state. The user's communication terminal, in addition to general network connectivity, is equipped with voice analysis and facial recognition capabilities via a camera. Using these functions, the user's emotional data can be collected and transmitted to a server.

[0463] The server stores user sentiment data in its database, along with signal strength and quality information related to normal connection conditions, application usage, and past communication history. The server comprehensively analyzes this data and selects the optimal network based on the results. It can also automatically adjust network settings to improve the communication experience based on the user's sentiment.

[0464] As a concrete example, consider a scenario where a user is watching a video and the device determines that the user is experiencing stress. Normally, in an environment where data communication is frequently interrupted, the stress level may increase. Therefore, the device sends emotional data to a server, and the server, based on the received data, determines that a stable communication environment is necessary.

[0465] This prompts the server to switch to the local 5G network, providing a stable communication environment. As a result, users can enjoy uninterrupted video streaming, contributing to reduced stress.

[0466] This system allows users to receive an emotionally-based, personalized user experience, which is expected to improve satisfaction with communication services.

[0467] The following describes the processing flow.

[0468] Step 1:

[0469] The device uses its built-in microphone and camera to collect voice and facial data while the user is using it, and analyzes the user's emotions. This allows it to determine emotional states such as joy, stress, and frustration.

[0470] Step 2:

[0471] The terminal sends the analyzed emotion data, along with signal strength and communication quality data, to the server. This transmission occurs at regular intervals, serving to convey real-time status to the server.

[0472] Step 3:

[0473] The server comprehensively analyzes received sentiment data, signal strength, communication quality information, application usage, and past communication history. This analysis helps to assess what kind of communication environment the user needs.

[0474] Step 4:

[0475] Based on the analysis of emotional data, the server determines that a particularly stable communication environment is necessary when the user is experiencing stress, and instructs the user to switch to an appropriate network. This instruction is sent to the terminal immediately.

[0476] Step 5:

[0477] The device automatically switches to the appropriate network, such as local 5G, based on instructions from the server. This operation is seamless, and care has been taken to ensure that users do not experience any interruptions in their communication.

[0478] Step 6:

[0479] Users can use applications without interruption by utilizing the selected optimal communication environment. For example, they can enjoy a comfortable video viewing experience.

[0480] This trend will lead to the realization of systems that provide a better user experience by utilizing user emotional data in the communication environment.

[0481] (Example 2)

[0482] 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."

[0483] In today's digital communication environment, a user's emotional state can significantly impact their communication experience. However, conventional communication systems have not optimized their networks to take user emotions into account, resulting in decreased user satisfaction, particularly under high load or unstable connection conditions. To solve these problems, it is necessary to consider the user's emotional state in real time and provide an optimal connection environment.

[0484] 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.

[0485] In this invention, the server includes means having a database for analyzing the user's emotional state and optimizing communication services; means for transmitting a digital signal containing emotional data to an information processing device; and means for analyzing the received emotional data, signal strength, and past activity logs in the information processing device and selecting an optimized communication network. This makes it possible to provide personalized network services that respond to the user's emotions and improve the communication experience.

[0486] "User" refers to an individual or group that accesses digital services using a communication device.

[0487] "Emotional state" refers to the emotional reactions and psychological state a user exhibits during their communication experience.

[0488] A "database" refers to an information management system that systematically stores user sentiment data and communication-related data, making it accessible as needed.

[0489] An "information processing device" refers to a computer system used for receiving, analyzing, and directing network optimization.

[0490] A "digital signal" refers to an electrical signal that represents a user's emotional data and other communication-related information and is transmitted to an information processing device.

[0491] "Emotional data" refers to information indicating a user's psychological state, obtained by analyzing their voice and facial expressions.

[0492] "Communication services" refer to the functions and processes of digital information exchange provided to users via the internet.

[0493] "Network optimization" refers to the adjustment of settings and reallocation of resources within a communication system to improve the efficiency and quality of data transmission.

[0494] "Automatic connection change" refers to the process by which a communication terminal switches its current network settings to other settings based on instructions from an information processing device.

[0495] This invention is a system that optimizes the communication environment based on emotional state. Its main components include a communication terminal used by the user, a server that processes data, and a network to support them.

[0496] The communication terminals used by users are equipped with hardware capable of voice analysis and facial recognition via cameras. This allows the terminals to collect user emotion data in real time and transmit it to a server. The software used includes voice recognition libraries and machine learning model execution environments.

[0497] The server stores the received sentiment data along with other communication-related data in a database and performs analysis. This analysis uses data analysis algorithms and network optimization algorithms. Based on the analysis results, the server calculates the optimal network settings and sends those settings to the communication terminals.

[0498] A concrete example is when a user is using a video streaming service. When the user experiences stress, emotional data is collected, and based on this data, the server determines that a more stable network environment is needed. By then instructing the server to switch to the local 5G network, the user can enjoy an uninterrupted viewing experience.

[0499] An example of a prompt this system might anticipate is, "Explain how to optimize the communication environment when the user is experiencing stress." This allows the AI ​​model to recognize the user's emotional state and gain guidance for developing an optimization strategy.

[0500] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0501] Step 1:

[0502] While a user is using a communication device, the device collects emotional data. The input consists of the user's voice and facial image. The device analyzes this data using a voice analysis module and a facial recognition algorithm, and outputs digital data indicating the user's emotional state. Specifically, it extracts voice tone and facial features and generates emotional tags such as "stress" and "relaxed."

[0503] Step 2:

[0504] The terminal sends the collected sentiment data to the server. The input is the sentiment tag generated in step 1 and the current communication metadata (e.g., signal strength, quality information). The terminal sends this information to the server over the network, and the server stores this data in a database. The output is the integrated dataset stored on the server.

[0505] Step 3:

[0506] The server analyzes the data it receives. The input consists of sentiment data and communication metadata stored in a database. The server uses an AI model to analyze this data and calculate the optimized network settings. Based on the data analysis, it outputs a judgment that "the network load is high, so we should switch to the local 5G network."

[0507] Step 4:

[0508] The server issues instructions to the communication terminal based on the analysis results. The input is the analysis results from step 3. The server sends instructions to the terminal to connect to a specific network and suggests settings to optimize communication quality. The output is the network configuration change instructions sent to the terminal.

[0509] Step 5:

[0510] The terminal changes its network settings according to instructions received from the server. The input is the network setting instruction from the server. The terminal automatically switches network connections and performs operations to ensure a more stable communication environment. The output is the new network settings that provide optimized communication quality.

[0511] (Application Example 2)

[0512] 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."

[0513] In elderly care settings, appropriate responses are required based on the emotional state of the user, but systems that can grasp this in real time and integrate it with communication services have not yet been fully realized. Furthermore, the impact of communication network quality on the user's emotions must also be considered. To solve this problem, it is necessary to accurately recognize the user's emotions and optimize the communication network accordingly.

[0514] 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.

[0515] In this invention, the server includes means for analyzing the user's facial expressions and voice to detect their emotional state, means for optimizing communication quality based on the user's emotional state and automatically switching the connection of communication terminals, and means for transmitting signal strength and quality data measured at regular time intervals to an information recording device. This makes it possible to provide a stable communication service that responds to the user's emotions.

[0516] "User information" refers to personal data and attribute information about individual users.

[0517] "Communication history data" refers to records of past network connections and communication activities.

[0518] An "information recording and ethics device" refers to a device that has server functionality for storing and analyzing user information and network quality information.

[0519] "Signal strength" is an indicator that shows the strength of the wireless signal received by a communication terminal.

[0520] "Quality data" refers to measurement information regarding the performance and stability of network connections.

[0521] "Application usage status" refers to information regarding the activity status of applications running on a communication terminal.

[0522] "Means of analyzing user facial expressions and voice" refers to technology that uses cameras and microphones to analyze a user's facial expressions and voice in real time.

[0523] "Means for detecting emotional state" refers to algorithms used to determine emotions inferred from a user's facial expressions and voice.

[0524] "Methods for optimizing communication quality and automatically switching the connection of communication terminals" refers to technologies that adjust network settings according to the communication environment and change the connection destination to provide a better communication experience.

[0525] The system for implementing this invention utilizes a communication terminal owned by the user and a server that functions as an information recording and ethics device. The communication terminal is equipped with a camera for recognizing the user's facial expressions and a microphone for analyzing the user's voice. Furthermore, the terminal has facial recognition software and a voice analysis algorithm installed, enabling real-time detection of the user's emotional state.

[0526] When a terminal detects an emotional state, it sends that data to the server at regular intervals. The server functions as an information recording and ethical device, comprehensively analyzing the received emotional data, signal strength, quality data, and application usage. This analysis process utilizes a database engine and statistical analysis algorithms. Based on the analysis results, the server determines the optimal network connection and automatically instructs the user's communication terminal to change the connection. This allows the user to enjoy an optimal communication environment tailored to their emotional state.

[0527] As a concrete example, this system could be used in elderly care settings. A care robot would analyze the elderly person's facial expressions and voice in real time, and when stress or loneliness is detected, it would provide appropriate verbal cues or play music. This is expected to improve the quality of life for the elderly.

[0528] An example of a prompt for a generative AI model is: "We are developing a care robot system that analyzes the facial expressions and voice of elderly people and plays relaxing music according to their emotional state. Please provide an algorithm for estimating emotions using the following image and audio."

[0529] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0530] Step 1:

[0531] The device uses a camera and microphone to capture the user's facial expressions and voice in real time. It acquires image data and audio data as input. This data is processed by facial recognition software and a voice analysis algorithm to estimate the user's emotional state. It generates estimated emotional state data as output.

[0532] Step 2:

[0533] The device sends estimated emotional state data to the server. Simultaneously, it also sends signal strength and quality data collected from the network, as well as application usage data, to the server. These are processed by the server as input data.

[0534] Step 3:

[0535] The server comprehensively analyzes received emotional state data, signal strength, quality data, and application usage. This analysis utilizes a database engine and statistical analysis algorithms to determine the optimal network connection. As output, it generates suggestions for appropriate network settings.

[0536] Step 4:

[0537] The server sends a suggested network configuration to the communication terminal. The terminal automatically switches the network connection based on these instructions. This allows the user to continue using the service in an optimal communication environment tailored to their needs.

[0538] 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.

[0539] 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.

[0540] 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.

[0541] [Fourth Embodiment]

[0542] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0543] 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.

[0544] 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).

[0545] 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.

[0546] 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.

[0547] 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).

[0548] 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.

[0549] 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.

[0550] 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.

[0551] 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.

[0552] 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.

[0553] 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.

[0554] 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".

[0555] This invention provides a system for optimizing communication quality in a specific network environment, in which the user's communication terminal and server device work together. The terminal enables the user to automatically select the most suitable communication environment at all times, even when the user is on the move.

[0556] The server stores user information and past communication history in a database and collects real-time network quality information. This information is used to analyze which network connection is optimal and to send instructions to the terminal to provide an appropriate communication environment.

[0557] The terminal measures signal strength and quality data at regular intervals and sends this data to the server. Furthermore, the terminal monitors the status of currently used applications and identifies applications that require high bandwidth. In this way, the terminal can smoothly switch automatically between public 4G / 5G networks and local 5G networks based on instructions from the server.

[0558] As a concrete example, consider a user streaming a video on a train during their commute. Because network usage is concentrated on trains, stable viewing may be difficult with a standard public 4G network. In this case, the device periodically sends signal strength and quality data to the server. The server, based on this data, confirms that the user is using a video streaming app, and considers past communication history to determine that using a local 5G network is more appropriate. The server then instructs the device to switch to local 5G, allowing the user to enjoy uninterrupted video viewing.

[0559] In this way, seamless collaboration between servers and terminals makes it possible to continuously provide users with an excellent communication experience.

[0560] The following describes the processing flow.

[0561] Step 1:

[0562] The terminal measures signal strength and quality, including RSRP, RSRQ, and SINR, at regular intervals. This measurement data serves as fundamental information for evaluating communication stability.

[0563] Step 2:

[0564] The terminal sends the measured signal strength and quality data to the server. This data is used by the server to understand the real-time network conditions.

[0565] Step 3:

[0566] The device monitors the applications currently in use and identifies those that require high bandwidth (e.g., video streaming apps). This information helps determine the priority of communication needs.

[0567] Step 4:

[0568] The server analyzes received signal strength and quality data, application usage, and past communication history. This analysis helps determine the optimal network to select.

[0569] Step 5:

[0570] Based on the analysis results, the server evaluates whether a public 4G / 5G network or a local 5G network is appropriate and sends a network switching instruction to the terminal.

[0571] Step 6:

[0572] The terminal automatically switches networks upon receiving instructions from the server. This process is seamless, allowing users to continue using the service without experiencing any communication interruptions.

[0573] Step 7:

[0574] Users can utilize applications (e.g., video streaming) in a stable communication environment through the newly selected optimal communication path.

[0575] This series of processes allows users to receive high-quality communication services without stress, even in congested environments.

[0576] (Example 1)

[0577] 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".

[0578] In recent years, the use of mobile communication devices has increased, and many users require internet access while on the go. However, communication quality tends to be unstable, especially in certain travel environments such as trains and vehicles, which can cause problems when making important communications. The objective of this invention is to solve this problem and realize high-quality communication even while traveling.

[0579] 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.

[0580] In this invention, the server includes means for storing user data and past communication records, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to an information processing device; and means for monitoring the operating status of the application and notifying the information processing device when important communication occurs. This enables the automatic selection of the optimal communication environment even while on the move, resulting in uninterrupted, high-quality communication.

[0581] A "user" refers to an individual or legal entity that uses this system, and is the entity that uses the internet or data communication through a communication terminal.

[0582] "Data" refers to all information related to communication, including user information, past communication records, and application usage.

[0583] "Radio wave strength" is an indicator that shows the strength of the wireless signal received by a communication terminal, and it directly affects the quality of communication.

[0584] A "server" is an information processing device that stores user data, collects and analyzes network information, and acts as an intermediary between communication terminals and the network.

[0585] "Network quality information" refers to information necessary for evaluating communication status, and includes indicators such as signal strength, line stability, and latency.

[0586] "Communication equipment" refers to devices used by users, such as smartphones and tablets, that can connect to a network.

[0587] "Automatically switching connections" refers to the communication device automatically switching to a different network without requiring manual operation in order to maintain an optimal communication environment.

[0588] This system optimizes communication quality in a specific network environment through cooperation between the user's communication terminal and a server. The communication terminal is configured to automatically select the optimal network even when the user is on the move. Specifically, the terminal periodically measures signal strength and network quality using its built-in communication module and transmits this data to the server. Data security is ensured by using the SSL / TLS protocol during data transmission.

[0589] The server stores collected real-time network information and historical communication history in a database. To perform high-speed data analysis, the server utilizes analysis scripts built in Python and SQL queries to select the optimal communication network. Based on the analysis results, the server sends network switching instructions to the communication terminal as needed. This allows the terminal to smoothly switch connections between public 4G / 5G networks and local 5G networks.

[0590] As a concrete example, consider a scenario where a user is streaming a video on a train during their commute. In this case, the communication terminal detects a decrease in signal strength due to concentrated communication usage on the train and sends this data to the server. The server confirms that the video streaming app is running and, after comparing it with past communication history, determines that using local 5G is more appropriate. Following instructions from the server, the communication terminal switches to local 5G, allowing the user to enjoy watching the video without interruption.

[0591] An example of a prompt to input into a generative AI model is as follows: "Describe a system that maintains optimal network connectivity even when the user is on the move. Include specific examples, such as data handling during video streaming on a crowded train." This prompt is expected to generate detailed instructions and examples like the one above.

[0592] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0593] Step 1:

[0594] The terminal measures signal strength and network quality data at regular intervals. Based on this input information (indicators such as signal strength and SNR), the terminal sends the measurement results to the server. Specifically, the communication module installed in the terminal receives wireless signals and generates data measuring their strength and quality. This data is securely transmitted to the server using the SSL / TLS protocol.

[0595] Step 2:

[0596] The server uses data received from the terminal as input and analyzes it against historical communication records stored in the database and real-time network quality information. This process generates output information necessary for selecting the optimal communication network. Specifically, the server executes a data analysis script using Python, comparing the received data with past communication history.

[0597] Step 3:

[0598] The server selects an appropriate network connection based on the analysis results and sends the selection result as output to the terminal. The terminal receives this instruction as input and automatically switches from the current network to the selected network. Specifically, the terminal's network settings are dynamically changed and the appropriate profile is applied.

[0599] Step 4:

[0600] The terminal continuously monitors communication performance after the switch and outputs feedback to the server. Specifically, the terminal measures signal strength and latency on the new line as input information and sends this data to the server. This allows the server to continuously optimize the network selection criteria.

[0601] (Application Example 1)

[0602] 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".

[0603] To improve the user's communication experience within stores, seamless switching between wireless networks and mobile data communications is required. However, efficient systems for achieving this in real-world spaces have not yet been sufficiently developed, leading to communication failures and data delays. In particular, an inappropriate selection of communication network can impair the user experience.

[0604] 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.

[0605] In this invention, the server includes a computing device equipped with a storage medium for storing user attribute data and past connection history, and for collecting real-time communication quality information; means for transmitting radio wave strength and quality data measured at regular time intervals to the computing device; and means for monitoring the operational status of information processing and notifying the computing device of important data communication when it occurs. This makes it possible to seamlessly switch between wireless networks and mobile data communication within a store, providing a stable communication experience.

[0606] "User attribute data" refers to basic information about users, which is used to optimize communication environments and services.

[0607] "Past connection history" refers to a record of the communication networks a user has previously connected to and the conditions at the time, which is used to predict communication quality and select the optimal connection.

[0608] "Real-time communication quality information" refers to data such as signal strength and communication speed in the current communication environment, and is used for rapid network selection and switching.

[0609] A "storage medium" is hardware used to store data, and within a server device, it plays a role in maintaining user attribute data and past connection history.

[0610] A "computing device" is a device used for information processing, and servers and information terminals fulfill this role. It has the function of analyzing data related to communication networks and selecting the optimal network.

[0611] "Signal strength" is an indicator of the strength of a communication signal and is an important factor in selecting an appropriate network.

[0612] "Quality data" refers to data related to performance aspects such as stability and speed during communication, and is information that contributes to improving the communication experience.

[0613] "Information processing operational status" refers to the status of applications and processes running on communication terminals, and serves as a basis for determining communication priority.

[0614] "Important data communications" refer to communications of information of high importance to the user, and are prioritized and notified to the server device in situations where a high-quality communication environment is required.

[0615] A "communication network" refers to a collection of networks available to the user, and is what the system selects to provide the optimal communication experience.

[0616] "Information terminal" refers to communication devices owned by individual users, and typically includes mobile terminals and personal devices.

[0617] A "wireless network" is a technology that enables data communication without wired connections, and when used within a store, it allows for free movement.

[0618] "Mobile data communication" is a technology that enables stable communication even for terminals in motion, and involves sending and receiving data via a mobile network.

[0619] This invention provides a system for improving the user's communication experience in physical stores. This system consists of a server including a computing device and the cooperation of the user's mobile terminal as an information terminal.

[0620] The server first stores user attribute data and past connection history in a storage medium. Based on this data, the server collects communication quality information in real time and transmits signal strength and quality data to a computing device. The server monitors the operational status of information terminals and, when important data communication occurs, analyzes the optimal communication network based on that information.

[0621] The terminal is responsible for sending data collected at regular intervals to the server. This ensures that users can utilize information services in a suitable communication environment. For example, if a user is searching for product information in a store, the terminal will automatically switch to a more stable mobile data connection if the Wi-Fi connection is unstable. This ensures that the user experience is maintained without interruption.

[0622] Furthermore, the server analyzes network quality based on the data it collects and sends the optimal connection instructions to the user's terminal. During this process, the user is unaware of the network switching, ensuring a smooth and reliable connection.

[0623] A concrete example of a prompt might be, "Please provide an algorithm for designing a system where a smartphone app seamlessly switches between Wi-Fi and mobile data communication within a physical store, allowing users to smoothly access online services." By inputting this prompt into a generating AI model, it is possible to obtain design proposals for even more advanced communication control systems.

[0624] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0625] Step 1:

[0626] The terminal measures signal strength and quality data at predetermined time intervals. This data is used as input information to evaluate the current network environment. The terminal prepares to send this measurement data to the server.

[0627] Step 2:

[0628] The terminal monitors application usage. The input here represents the application's operational status and serves as basic data for determining the importance of data communication. When important data communication is required, the terminal notifies the server of this information.

[0629] Step 3:

[0630] The server receives signal strength, quality data, and application usage information transmitted from the terminal. Based on this input data, the server uses past connection history and real-time communication quality information to perform calculations to select the optimal communication network. The server determines which communication network is best and prepares the result.

[0631] Step 4:

[0632] The server sends connection instructions to the terminal regarding the selected communication network. This output provides information for changing the terminal's communication settings. Based on the server's instructions, the terminal seamlessly switches between the wireless network and mobile data communication.

[0633] Step 5:

[0634] Users enjoy an optimal communication environment through the coordination between the server and the terminal. This allows users to comfortably use information services without interruptions. Specifically, they can continue operations such as searching for product information or placing online orders without any communication interruptions.

[0635] 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.

[0636] This invention optimizes the communication environment by combining an emotion engine with the communication system, taking into account the user's emotional state. The user's communication terminal, in addition to general network connectivity, is equipped with voice analysis and facial recognition capabilities via a camera. Using these functions, the user's emotional data can be collected and transmitted to a server.

[0637] The server stores user sentiment data in its database, along with signal strength and quality information related to normal connection conditions, application usage, and past communication history. The server comprehensively analyzes this data and selects the optimal network based on the results. It can also automatically adjust network settings to improve the communication experience based on the user's sentiment.

[0638] As a concrete example, consider a scenario where a user is watching a video and the device determines that the user is experiencing stress. Normally, in an environment where data communication is frequently interrupted, the stress level may increase. Therefore, the device sends emotional data to a server, and the server, based on the received data, determines that a stable communication environment is necessary.

[0639] This prompts the server to switch to the local 5G network, providing a stable communication environment. As a result, users can enjoy uninterrupted video streaming, contributing to reduced stress.

[0640] This system allows users to receive an emotionally-based, personalized user experience, which is expected to improve satisfaction with communication services.

[0641] The following describes the processing flow.

[0642] Step 1:

[0643] The device uses its built-in microphone and camera to collect voice and facial data while the user is using it, and analyzes the user's emotions. This allows it to determine emotional states such as joy, stress, and frustration.

[0644] Step 2:

[0645] The terminal sends the analyzed emotion data, along with signal strength and communication quality data, to the server. This transmission occurs at regular intervals, serving to convey real-time status to the server.

[0646] Step 3:

[0647] The server comprehensively analyzes received sentiment data, signal strength, communication quality information, application usage, and past communication history. This analysis helps to assess what kind of communication environment the user needs.

[0648] Step 4:

[0649] Based on the analysis of emotional data, the server determines that a particularly stable communication environment is necessary when the user is experiencing stress, and instructs the user to switch to an appropriate network. This instruction is sent to the terminal immediately.

[0650] Step 5:

[0651] The device automatically switches to the appropriate network, such as local 5G, based on instructions from the server. This operation is seamless, and care has been taken to ensure that users do not experience any interruptions in their communication.

[0652] Step 6:

[0653] Users can use applications without interruption by utilizing the selected optimal communication environment. For example, they can enjoy a comfortable video viewing experience.

[0654] This trend will lead to the realization of systems that provide a better user experience by utilizing user emotional data in the communication environment.

[0655] (Example 2)

[0656] 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".

[0657] In today's digital communication environment, a user's emotional state can significantly impact their communication experience. However, conventional communication systems have not optimized their networks to take user emotions into account, resulting in decreased user satisfaction, particularly under high load or unstable connection conditions. To solve these problems, it is necessary to consider the user's emotional state in real time and provide an optimal connection environment.

[0658] 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.

[0659] In this invention, the server includes means having a database for analyzing the user's emotional state and optimizing communication services; means for transmitting a digital signal containing emotional data to an information processing device; and means for analyzing the received emotional data, signal strength, and past activity logs in the information processing device and selecting an optimized communication network. This makes it possible to provide personalized network services that respond to the user's emotions and improve the communication experience.

[0660] "User" refers to an individual or group that accesses digital services using a communication device.

[0661] "Emotional state" refers to the emotional reactions and psychological state a user exhibits during their communication experience.

[0662] A "database" refers to an information management system that systematically stores user sentiment data and communication-related data, making it accessible as needed.

[0663] An "information processing device" refers to a computer system used for receiving, analyzing, and directing network optimization.

[0664] A "digital signal" refers to an electrical signal that represents a user's emotional data and other communication-related information and is transmitted to an information processing device.

[0665] "Emotional data" refers to information indicating a user's psychological state, obtained by analyzing their voice and facial expressions.

[0666] "Communication services" refer to the functions and processes of digital information exchange provided to users via the internet.

[0667] "Network optimization" refers to the adjustment of settings and reallocation of resources within a communication system to improve the efficiency and quality of data transmission.

[0668] "Automatic connection change" refers to the process by which a communication terminal switches its current network settings to other settings based on instructions from an information processing device.

[0669] This invention is a system that optimizes the communication environment based on emotional state. Its main components include a communication terminal used by the user, a server that processes data, and a network to support them.

[0670] The communication terminals used by users are equipped with hardware capable of voice analysis and facial recognition via cameras. This allows the terminals to collect user emotion data in real time and transmit it to a server. The software used includes voice recognition libraries and machine learning model execution environments.

[0671] The server stores the received sentiment data along with other communication-related data in a database and performs analysis. This analysis uses data analysis algorithms and network optimization algorithms. Based on the analysis results, the server calculates the optimal network settings and sends those settings to the communication terminals.

[0672] A concrete example is when a user is using a video streaming service. When the user experiences stress, emotional data is collected, and based on this data, the server determines that a more stable network environment is needed. By then instructing the server to switch to the local 5G network, the user can enjoy an uninterrupted viewing experience.

[0673] An example of a prompt this system might anticipate is, "Explain how to optimize the communication environment when the user is experiencing stress." This allows the AI ​​model to recognize the user's emotional state and gain guidance for developing an optimization strategy.

[0674] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0675] Step 1:

[0676] While a user is using a communication device, the device collects emotional data. The input consists of the user's voice and facial image. The device analyzes this data using a voice analysis module and a facial recognition algorithm, and outputs digital data indicating the user's emotional state. Specifically, it extracts voice tone and facial features and generates emotional tags such as "stress" and "relaxed."

[0677] Step 2:

[0678] The terminal sends the collected sentiment data to the server. The input is the sentiment tag generated in step 1 and the current communication metadata (e.g., signal strength, quality information). The terminal sends this information to the server over the network, and the server stores this data in a database. The output is the integrated dataset stored on the server.

[0679] Step 3:

[0680] The server analyzes the data it receives. The input consists of sentiment data and communication metadata stored in a database. The server uses an AI model to analyze this data and calculate the optimized network settings. Based on the data analysis, it outputs a judgment that "the network load is high, so we should switch to the local 5G network."

[0681] Step 4:

[0682] The server issues instructions to the communication terminal based on the analysis results. The input is the analysis results from step 3. The server sends instructions to the terminal to connect to a specific network and suggests settings to optimize communication quality. The output is the network configuration change instructions sent to the terminal.

[0683] Step 5:

[0684] The terminal changes its network settings according to instructions received from the server. The input is the network setting instruction from the server. The terminal automatically switches network connections and performs operations to ensure a more stable communication environment. The output is the new network settings that provide optimized communication quality.

[0685] (Application Example 2)

[0686] 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".

[0687] In elderly care settings, appropriate responses are required based on the emotional state of the user, but systems that can grasp this in real time and integrate it with communication services have not yet been fully realized. Furthermore, the impact of communication network quality on the user's emotions must also be considered. To solve this problem, it is necessary to accurately recognize the user's emotions and optimize the communication network accordingly.

[0688] 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.

[0689] In this invention, the server includes means for analyzing the user's facial expressions and voice to detect their emotional state, means for optimizing communication quality based on the user's emotional state and automatically switching the connection of communication terminals, and means for transmitting signal strength and quality data measured at regular time intervals to an information recording device. This makes it possible to provide a stable communication service that responds to the user's emotions.

[0690] "User information" refers to personal data and attribute information about individual users.

[0691] "Communication history data" refers to records of past network connections and communication activities.

[0692] An "information recording and ethics device" refers to a device that has server functionality for storing and analyzing user information and network quality information.

[0693] "Signal strength" is an indicator that shows the strength of the wireless signal received by a communication terminal.

[0694] "Quality data" refers to measurement information regarding the performance and stability of network connections.

[0695] "Application usage status" refers to information regarding the activity status of applications running on a communication terminal.

[0696] "Means of analyzing user facial expressions and voice" refers to technology that uses cameras and microphones to analyze a user's facial expressions and voice in real time.

[0697] "Means for detecting emotional state" refers to algorithms used to determine emotions inferred from a user's facial expressions and voice.

[0698] "Methods for optimizing communication quality and automatically switching the connection of communication terminals" refers to technologies that adjust network settings according to the communication environment and change the connection destination to provide a better communication experience.

[0699] The system for implementing this invention utilizes a communication terminal owned by the user and a server that functions as an information recording and ethics device. The communication terminal is equipped with a camera for recognizing the user's facial expressions and a microphone for analyzing the user's voice. Furthermore, the terminal has facial recognition software and a voice analysis algorithm installed, enabling real-time detection of the user's emotional state.

[0700] When a terminal detects an emotional state, it sends that data to the server at regular intervals. The server functions as an information recording and ethical device, comprehensively analyzing the received emotional data, signal strength, quality data, and application usage. This analysis process utilizes a database engine and statistical analysis algorithms. Based on the analysis results, the server determines the optimal network connection and automatically instructs the user's communication terminal to change the connection. This allows the user to enjoy an optimal communication environment tailored to their emotional state.

[0701] As a concrete example, this system could be used in elderly care settings. A care robot would analyze the elderly person's facial expressions and voice in real time, and when stress or loneliness is detected, it would provide appropriate verbal cues or play music. This is expected to improve the quality of life for the elderly.

[0702] An example of a prompt for a generative AI model is: "We are developing a care robot system that analyzes the facial expressions and voice of elderly people and plays relaxing music according to their emotional state. Please provide an algorithm for estimating emotions using the following image and audio."

[0703] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0704] Step 1:

[0705] The device uses a camera and microphone to capture the user's facial expressions and voice in real time. It acquires image data and audio data as input. This data is processed by facial recognition software and a voice analysis algorithm to estimate the user's emotional state. It generates estimated emotional state data as output.

[0706] Step 2:

[0707] The device sends estimated emotional state data to the server. Simultaneously, it also sends signal strength and quality data collected from the network, as well as application usage data, to the server. These are processed by the server as input data.

[0708] Step 3:

[0709] The server comprehensively analyzes received emotional state data, signal strength, quality data, and application usage. This analysis utilizes a database engine and statistical analysis algorithms to determine the optimal network connection. As output, it generates suggestions for appropriate network settings.

[0710] Step 4:

[0711] The server sends a suggested network configuration to the communication terminal. The terminal automatically switches the network connection based on these instructions. This allows the user to continue using the service in an optimal communication environment tailored to their needs.

[0712] 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.

[0713] 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.

[0714] 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.

[0715] 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.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] 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.

[0720] 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."

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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.

[0728] 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.

[0729] 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.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] The following is further disclosed regarding the embodiments described above.

[0734] (Claim 1)

[0735] A server device equipped with a database for storing user information and past communication history data, and for collecting real-time network quality information,

[0736] Means for transmitting signal strength and quality data measured at regular time intervals to a server device,

[0737] A means for monitoring application usage and notifying the server device of important communications when they occur,

[0738] A means of selecting the optimal network by analyzing signal strength, application usage, and historical communication data collected by the server device.

[0739] A means of automatically switching the connection of communication terminals based on instructions from the server device,

[0740] A system that includes this.

[0741] (Claim 2)

[0742] The system according to claim 1, further comprising means for continuously monitoring changes in communication performance when a network switch occurs and for sending feedback to a server device.

[0743] (Claim 3)

[0744] The system according to claim 1, further comprising means for ensuring stable communication connectivity even in specific mobile environments such as trains.

[0745] "Example 1"

[0746] (Claim 1)

[0747] An information processing device equipped with a storage device for storing user data and past communication records, and for collecting real-time communication quality information,

[0748] A means for transmitting radio wave intensity and quality data measured at regular time intervals to an information processing device,

[0749] A means of monitoring the operational status of an application and notifying information processing equipment when important communications occur,

[0750] A means of selecting the optimal communication environment by analyzing radio wave strength, application operating status, and past communication records collected by information processing equipment.

[0751] A means of automatically switching the connection of communication devices based on instructions from information processing equipment,

[0752] A means of identifying when an application in use requires a high amount of data,

[0753] A system that includes this.

[0754] (Claim 2)

[0755] The system according to claim 1, further comprising means for continuously observing changes in communication performance when a network switch occurs and transmitting feedback to an information processing device.

[0756] (Claim 3)

[0757] The system according to claim 1, further comprising means for ensuring stable communication connectivity even within specific mobile environments such as transportation systems.

[0758] "Application Example 1"

[0759] (Claim 1)

[0760] A computing device equipped with a storage medium for storing user attribute data and past connection history, and for collecting real-time communication quality information,

[0761] Means for transmitting radio wave intensity and quality data measured at regular time intervals to a computing device,

[0762] A means for monitoring the operational status of information processing and notifying the computing device of important data communication when such communication occurs,

[0763] A means for selecting the optimal communication network by analyzing radio wave intensity, information processing operation status, and past connection data collected by a computing device,

[0764] A means of automatically switching the connection of information terminals based on instructions from a computing device,

[0765] A means for seamlessly switching between wireless networks and mobile data communication in real space,

[0766] A system that includes this.

[0767] (Claim 2)

[0768] The system according to claim 1, further comprising means for continuously monitoring changes in communication performance after a switch in the communication network and transmitting feedback to a computing device.

[0769] (Claim 3)

[0770] The system according to claim 1, further comprising means for ensuring stable communication connectivity even in specific mobile environments such as vehicles.

[0771] "Example 2 of combining an emotion engine"

[0772] (Claim 1)

[0773] An information processing device having a database for analyzing the emotional state of users and optimizing communication services,

[0774] A means for transmitting a digital signal containing emotional data to an information processing device,

[0775] A means for monitoring application activity and transmitting information to an information processing device when important communication activity occurs,

[0776] A means for analyzing received emotional data, signal strength, and past activity logs in an information processing device and selecting an optimized communication network,

[0777] A means for automatically changing the connection of digital devices based on instructions from an information processing device,

[0778] A system that includes this.

[0779] (Claim 2)

[0780] The system according to claim 1, further comprising means for continuously monitoring fluctuations in communication quality when a change is made to the digital network and for transmitting feedback data to an information processing device.

[0781] (Claim 3)

[0782] The system according to claim 1, comprising means for ensuring a stable digital communication connection even in a mobile environment.

[0783] "Application example 2 when combining with an emotional engine"

[0784] (Claim 1)

[0785] An information recording device for storing user information and past communication history data in a general information recording device, and for collecting immediate network quality information,

[0786] Means for transmitting signal intensity and quality data measured at regular time intervals to an information recording device,

[0787] A means of monitoring application usage and notifying an information recording ethics device of important communications occurring,

[0788] A means of selecting the optimal network by analyzing signal strength, application usage, and past communication data collected by an information recording and ethics device.

[0789] A means for analyzing the user's facial expressions and voice to detect their emotional state,

[0790] A means to optimize communication quality based on the user's emotional state and automatically switch the connection of communication terminals,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, further comprising means for continuously monitoring changes in communication performance when a network switch occurs and transmitting feedback to an information recording device.

[0794] (Claim 3)

[0795] The system according to claim 1, further comprising means for ensuring a stable communication connection in accordance with the user's emotional state, even in a specific mobile environment. [Explanation of Symbols]

[0796] 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 computing device equipped with a storage medium for storing user attribute data and past connection history, and for collecting real-time communication quality information, Means for transmitting radio wave intensity and quality data measured at regular time intervals to a computing device, A means for monitoring the operational status of information processing and notifying the computing device of important data communication when such communication occurs, A means for selecting the optimal communication network by analyzing radio wave intensity, information processing operation status, and past connection data collected by a computing device, A means of automatically switching the connection of information terminals based on instructions from a computing device, A means for seamlessly switching between wireless networks and mobile data communication in real space, A system that includes this.

2. The system according to claim 1, further comprising means for continuously monitoring changes in communication performance after a switch in the communication network and transmitting feedback to a computing device.

3. The system according to claim 1, further comprising means for ensuring stable communication connectivity even in specific mobile environments such as vehicles.

Images