system

Abstract

We provide the system. [Solution] A device including a sensor device for acquiring environmental information around the user, A processing unit that analyzes environmental information from the aforementioned device to determine the situation around the user, Based on the above circumstances, a control device controls the method of providing sensitive information, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the 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 recent years, with the spread of smart devices, the opportunity for personal information to be easily spoken has increased. However, since there is a risk that such speech may be heard by people around, the privacy of users may be violated. It is important to solve this problem.

Means for Solving the Problems

[0005] This invention provides a system that collects environmental information around a user by a sensor device, analyzes the information, and determines the surrounding situation. Based on the analysis result, it includes a control device that controls a method for providing sensitive information to protect the privacy of the user. Specifically, it utilizes a video acquisition device, an audio acquisition device, and a position information acquisition device to analyze the environment in detail, and has a mechanism to request confirmation from the user before voice output when providing information.

[0006] A "user" refers to an individual who uses this system and is the entity that receives information.

[0007] "Environmental information" refers to surrounding situation data, including video, audio, and location information, acquired through the device's sensor equipment.

[0008] A "sensor device" refers to hardware used to collect information about the user's surrounding environment, and includes devices such as video acquisition devices, audio acquisition devices, and location information acquisition devices.

[0009] "Device" refers to equipment that incorporates sensor devices and other related equipment and is carried or used by a user.

[0010] A "processing device" refers to a device that analyzes environmental information collected by a device and has the function of determining the situation around the user.

[0011] A "control device" refers to a device that has the function of controlling how sensitive information is provided based on the analyzed situation.

[0012] "Sensitive information" refers to highly confidential information related to an individual's privacy, and means information that requires careful handling.

[0013] A "video acquisition device" refers to a device with functions that include a camera for capturing visual information around the user.

[0014] A "voice acquisition device" refers to a device that includes a microphone and other functions for collecting acoustic information from the user's surroundings.

[0015] A "location information acquisition device" refers to a GPS module or a device with similar functionality for acquiring the user's current location information. [Brief explanation of the drawing]

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0018] First, let's explain the terminology used in the following explanation.

[0019] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0020] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a system that securely provides sensitive information while protecting user privacy. The system is implemented on the user's terminal and utilizes various sensor devices to monitor the user's surrounding environment in detail.

[0038] The device first uses a video acquisition device to detect people in its surroundings. This allows it to recognize faces and figures from the video captured by the camera and determine whether other people are nearby. Next, it analyzes ambient sounds with an audio acquisition device to detect voices and unusual changes in volume. This allows it to detect the possibility that other people are joining a conversation. In addition, it uses a location information acquisition device to determine the device's current location and whether it is a public place.

[0039] By analyzing this information using a processing unit, the terminal infers the possibility that other people are present around the user. Based on this, the control unit determines how to provide sensitive information. For example, if there are other people nearby, instead of speaking the information aloud, the terminal will display the information on the screen for the user and send a confirmation message to the user beforehand.

[0040] As a concrete example, consider a scenario where a user receives a balance notification from a financial institution. The terminal first uses sensors to assess the surrounding environment, and if it determines there is a privacy risk, it refrains from outputting audio. Then, it displays the balance information on the screen, allowing the user to check the details by touching the screen. In this way, it is possible to provide a flexible interface that adapts to the user's environment.

[0041] This system aims to protect user privacy on a daily basis while securely providing necessary information, and can be adapted in various ways depending on the target environment.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The device activates the video acquisition system and captures video of the user's surroundings through the camera. Using a video analysis algorithm, it detects human faces and figures from the acquired images. If people are detected, their number and location information are recorded.

[0045] Step 2:

[0046] The device uses a voice acquisition device to record ambient sounds. A voice analysis algorithm is applied to detect speech patterns and volume changes from the recorded audio. When voices suspected to belong to other people are recognized, the audio information is also recorded over time.

[0047] Step 3:

[0048] The device activates its location acquisition device and obtains current GPS data. Based on the acquired location information, it checks whether the user's current location is a public place and assesses the level of privacy risk.

[0049] Step 4:

[0050] The device integrates the results of analyzing video, audio, and location data to determine whether other people are present in the user's vicinity. If a high privacy risk is detected, the process proceeds to the next step.

[0051] Step 5:

[0052] The device displays a confirmation message on the screen before conveying sensitive information to the user via voice. It also provides the user with an option to ask whether they want to allow the information to be output aloud.

[0053] Step 6:

[0054] If the user refuses audio output, the device will provide sensitive information via screen display. Specifically, the device will display the information on the screen in text format so that the user can review the content.

[0055] Step 7:

[0056] Once the information provision is complete, the device will resume collecting environmental information and continue the process described above according to the surrounding conditions. This ensures that privacy protection is always tailored to the latest user environment.

[0057] (Example 1)

[0058] 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."

[0059] In today's data-driven society, safely providing sensitive information while protecting user privacy is a critical challenge. However, existing systems struggle to flexibly adapt to the surrounding environment and provide appropriate information accordingly. Therefore, there is a need to build systems that accurately assess the user's situation and minimize privacy risks.

[0060] 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.

[0061] In this invention, the server includes detection means for collecting physical conditions around the user, evaluation means for analyzing the physical conditions from the detection means and evaluating the risks around the user, and control means for determining a method for providing confidential information based on the risk evaluation. This enables the provision of safe and appropriate information according to the user's surrounding environment.

[0062] A "user" refers to an individual or group that uses the system, and is the entity that receives and manipulates information.

[0063] "Physical circumstances" refers to observable data in the user's surrounding environment, such as the presence of people, changes in volume, and location information.

[0064] "Detection means" refers to a collection of devices and equipment used to sense the physical conditions around the user.

[0065] "Evaluation means" refers to the process of analyzing data obtained from detection means and calculating and evaluating the privacy risks surrounding the user.

[0066] "Control means" refers to a mechanism for determining and implementing methods for providing confidential information based on risk assessments conducted by evaluation means.

[0067] "Confidential information" refers to information that requires user privacy protection, and includes, for example, personal information and financial data.

[0068] "Communication methods" refer to information transmission technologies and processes used to provide confirmations and notifications to users.

[0069] In embodiments of this invention, the aim is for the information processing system to provide sensitive information while protecting user privacy. The system mainly consists of terminals equipped with multiple sensor devices. Specifically, these include cameras for acquiring images, microphones for acquiring sound, and GPS modules for measuring location.

[0070] The device activates these sensors to collect information about the user's surroundings in real time. Video is analyzed by image processing algorithms to detect the presence of human faces and shapes. Audio data is processed by acoustic analysis software to detect speech and unusual volume changes. Location information is acquired via satellite communication and analyzed in conjunction with specific geographic information services.

[0071] The collected data is analyzed by a processing unit within the device, and the risk to user privacy is assessed. Based on this assessment, the method of providing the information is determined. If the risk is deemed high, a format is chosen that avoids voice output and displays the information on the device screen. This ensures that necessary information is provided appropriately while protecting the user's privacy.

[0072] As a concrete example, when a user receives a financial transaction alert, the device monitors the surrounding environment using the aforementioned sensors. If the system determines that there is a high privacy risk and that others are nearby, the financial information is displayed on the screen instead of being audible, and the user can manually check the details. By utilizing this system, users can receive information safely and appropriately according to their surrounding circumstances.

[0073] An example of a prompt for a generative AI model is, "Explain how the system monitors the user's surroundings and determines how to provide information." This makes it easier to understand how the system works.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The device first activates its sensor equipment and begins collecting environmental information. At this stage, the camera captures video, the microphone acquires audio data, and the GPS module acquires location information. The input data consists of video, audio, and location information, each of which is updated in real time. As output, each piece of data is stored in temporary storage. Specifically, the camera identifies people in the surroundings, the microphone records speech, and the GPS determines the current coordinates.

[0077] Step 2:

[0078] The terminal's processing unit analyzes the collected environmental data. In this analysis, image analysis software processes video data to recognize human faces and postures. Acoustic analysis software performs calculations to detect conversations and unusual volume changes from audio data. GPS data is compared with map information to determine if the current location is a public place. The input is the data set collected in step 1, and the output is risk assessment information regarding the user's surrounding environment.

[0079] Step 3:

[0080] Based on the evaluation results, the terminal's control unit determines how to provide information. If a high privacy risk is identified, it avoids audio presentation and switches to screen display. The input is the risk assessment information from step 2, and the output is the determination of the information provision method. Based on this information, the terminal takes specific actions to protect user privacy, such as displaying financial information only on the screen and suppressing audio output.

[0081] Step 4:

[0082] The terminal sends a message to the user requesting confirmation. This message includes confirmation that a predetermined information delivery method has been selected and instructions for confirmation. The input is the information delivery method determined in step 3, and the output is a confirmation message to the user. Specifically, it displays instructions on the screen such as "Information has been displayed. Please touch to confirm the contents."

[0083] (Application Example 1)

[0084] 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."

[0085] This invention relates to a technology that provides sensitive information while ensuring user privacy in public places and noisy environments. Conventional technologies are limited to simply conveying information by voice or displaying it on a screen, making it difficult to provide information while considering the surrounding environment. As a result, there is a risk of information being leaked to others, especially in public transportation and commercial facilities. This invention aims to solve these problems and realize a flexible means of providing information that is appropriate for the environment.

[0086] 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.

[0087] In this invention, the server includes means for a sensor device to acquire environmental information around the user; means for analyzing the environmental information from the device to determine the situation around the user; means for automatically switching the form of information provision from voice to visual display in public places; and means for transmitting information to the user via a bone conduction device according to the noise level of the environment. This makes it possible to provide information appropriate to the surrounding environment while protecting the user's privacy.

[0088] "User environment information" refers to data about the user's surroundings, including information such as video, audio, and location.

[0089] A "sensor device" is a device used to acquire various types of input data, and consists of devices such as video acquisition devices, audio acquisition devices, and location information acquisition devices.

[0090] A "processing device" is a device that analyzes acquired environmental information and performs information processing to determine the situation around the user.

[0091] A "control device" is a device that determines how to provide sensitive information based on the analysis results and controls the display format of that information.

[0092] A "public place" refers to a space that is accessible to the general public and is used by the general public, and includes public transportation and commercial facilities.

[0093] "Visual display" refers to a method of presenting information through human vision, and involves using display devices such as screens and smart glasses.

[0094] "Noise level" is an indicator that shows the intensity and noise level of sounds around the user, and is measured using a voice acquisition device.

[0095] A "bone conduction device" is a device that transmits sound vibrations to the inner ear through the bone, rather than sending sound directly to the ear, by utilizing vibrations.

[0096] "Sensitive information" is a term that refers to information relating to an individual's privacy or highly confidential information, and should be provided to users with particular care.

[0097] The present invention provides a system that flexibly switches the method of providing information according to the user's surrounding environment. Specific embodiments for carrying out the present invention are described below.

[0098] This system incorporates the following components into the user's device: The sensor device includes a video acquisition device, an audio acquisition device, a location information acquisition device, and an acoustic measurement function, collecting detailed information about the user's surroundings. This data is sent to a processing unit within the device and analyzed in real time. This allows the system to determine whether the user is currently in a public place or if the noise level is high.

[0099] The processing unit analyzes video data using the open-source library OpenCV to determine if a person is present in the video. Audio data is analyzed using general audio analysis software to measure the intensity of ambient noise. Location information is generated using a GPS module, and whether the location is a public place is confirmed through a third-party location service.

[0100] The control device decides whether to provide information via voice or visual display based on the analysis results from the processing unit. In cases of high noise levels, information can be transmitted to the user using a bone conduction device, allowing for efficient information delivery while protecting privacy.

[0101] As a concrete example, consider a scenario where a user receives a bank balance notification while on public transport. In noisy environments, the device would reduce the audio output, allowing the user to view the details by lightly touching the screen.

[0102] An example of a prompt message would be: "Design a real-time information delivery system that considers sensitive information delivery methods in public spaces while protecting privacy. Design a system that detects the number of people and the volume of voices and selects the optimal information display method."

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

[0104] Step 1:

[0105] The device acquires information about its surroundings using sensor devices. Inputs include video data from a camera, audio data from a microphone, and GPS data from a location information module. This data is collected and stored in internal memory.

[0106] Step 2:

[0107] The terminal's processing unit analyzes the acquired video data. Using the OpenCV library, it detects faces and the presence of people in the video. The output includes the number of detected people and their location information. This data is used for situational analysis within the terminal.

[0108] Step 3:

[0109] The terminal's processing unit analyzes the audio data. Using general audio analysis software, it measures the noise level from the obtained audio data. The input is audio data from the microphone, and the output is the noise level expressed in decibels (dB). This information is also used for situational analysis.

[0110] Step 4:

[0111] The device's processing unit analyzes location information. It sends GPS data to a third-party location service to determine if the location is a public place. The output is the location information and its attributes (whether it is public or not).

[0112] Step 5:

[0113] The terminal's control unit determines the information delivery method based on the analysis results from steps 2 to 4. The inputs are the number of people detected, the noise level, and location attributes. The output is a decision on whether to provide the information audibly or visually. For example, if the noise level is high in a public place, visual display is selected.

[0114] Step 6:

[0115] The user receives information according to the information delivery method selected by the user. Specifically, in noisy environments, the device transmits information near the ear using a bone conduction device, and if visual display is selected, the information is displayed on the device's screen. The user can check detailed information by operating the screen as needed.

[0116] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0117] This invention is a system that provides information flexibly based on the user's emotional state while ensuring user privacy. The system functions by integrating various sensor devices and an emotion engine on the user's terminal.

[0118] The device collects user facial expression data through a video acquisition device. This data is analyzed by an emotion engine to determine the user's emotional state (e.g., joy, sadness, anger, surprise, etc.). The tone and speed of speech obtained by the voice acquisition device are also used in emotion analysis, and changes in emotion can be read from the content of speech.

[0119] Furthermore, based on GPS data acquired by a location information acquisition device, the system determines whether the user's surroundings are a public space and assesses the privacy risks. This information, along with the results of the emotion engine's analysis, is used to select the most appropriate method of providing information to the user.

[0120] For example, if the device recognizes the user's agitated state and determines that it is in a public place, it can be controlled to display sensitive information on the screen instead of providing it verbally. Conversely, if the user is calm and at home, or if other conditions are met, verbal information provision may be permitted.

[0121] For example, when a user receives an important work-related message, the device attempts to read it aloud, but then detects that the user is in an office with other people present. Furthermore, if the emotion engine determines that the user's stress level is high, the device not only displays the message on the screen but also sends a notification message to encourage the user to check it themselves.

[0122] In this way, by using the analysis results of the emotion engine and environmental information, the device can autonomously adjust how it provides sensitive information, resulting in a more personalized user experience.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The device uses a video acquisition device to capture the user's facial expressions via a camera. The video data is sent to an emotion engine, where a facial expression analysis algorithm identifies the user's emotional state.

[0126] Step 2:

[0127] The device uses a voice acquisition device to collect the user's speech. A voice analysis algorithm is applied to evaluate the emotional state from the tone, pitch, and speed of the speech. This data is then integrated into the emotion engine.

[0128] Step 3:

[0129] The device activates its location acquisition device and obtains GPS data. The acquired location information is processed to determine whether the user's current location is a public place. This location data is used to assess the user's privacy risks.

[0130] Step 4:

[0131] The device integrates the analysis results from the emotion engine with location information to comprehensively evaluate the user's emotional state and surrounding environment. Based on this evaluation, it determines the information provision behavior of the interface.

[0132] Step 5:

[0133] When a device attempts to convey sensitive information to a user, it considers the user's emotional state and environmental conditions to determine the appropriateness of audio output. If the user is stressed or in a public place, screen display is recommended instead of audio.

[0134] Step 6:

[0135] If the user makes a selection in response to a confirmation message sent, the device will adjust how information is provided according to the user's choice. For example, if voice output is refused, the device will provide sensitive information visually on the screen.

[0136] Step 7:

[0137] Once the information provision is complete, the device will restart the collection and analysis of environmental and emotional information in preparation for any new information that may arise, and repeat the process described above. This cycle ensures that privacy protection is continuously tailored to the user's situation.

[0138] (Example 2)

[0139] 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".

[0140] Conventional information delivery systems sometimes provide sensitive information in an inappropriate manner without adequately considering the user's emotional state or surrounding environment. This can result in violations of user privacy or unpleasant experiences. Therefore, there is a need for a system that can flexibly adjust information delivery methods according to the user's emotional state and environment.

[0141] 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.

[0142] In this invention, the server includes data analysis means for analyzing the user's emotional state, location information acquisition means for acquiring the user's environmental information and determining whether it is a public place, and control means for flexibly selecting the method of providing information based on the information acquired by the data analysis means and the location information acquisition means. This makes it possible to provide information appropriately and flexibly while ensuring the user's privacy.

[0143] "Data analysis means" refers to a function or system that analyzes the user's collected video and audio data to determine their emotional state.

[0144] "Location information acquisition means" refers to a function or system that acquires the user's geographical location and uses that location to determine whether or not it is a public place.

[0145] A "control means" is a function or system that optimally selects and controls the method of providing information based on the user's emotional state and environmental information.

[0146] "Emotional state" refers to the user's psychological and emotional state, and includes various emotional elements such as joy, sadness, anger, and surprise.

[0147] "Environmental information" refers to data that indicates the user's surroundings, including location information, ambient sound environment, and visual environment.

[0148] "Information provision method" refers to the specific means by which information is presented to the user, and includes various forms of expression such as audio, text, and video.

[0149] This system is designed to analyze the user's emotional state and environmental information, and adjust the method of information delivery based on that analysis. Its main components are data analysis means, location information acquisition means, and control means.

[0150] First, the device collects the user's video and audio data using its built-in camera and microphone. For data analysis, this data is received and analyzed via an emotion engine using dedicated software. This emotion engine uses machine learning algorithms to determine the user's emotional state in real time, including emotions such as joy, anger, sadness, and stress levels.

[0151] Next, the device uses location information acquisition methods such as a GPS module to confirm the user's geographical location. This allows the device to determine whether the user is in a public place and assess privacy risks. In addition to location information, it may also use information from Wi-Fi or Bluetooth beacons as a supplementary tool in some cases.

[0152] The server integrates emotion analysis results and location information, and uses control mechanisms to determine the optimal method of information delivery. For example, if the user is agitated and in a public environment, the information will be displayed on the screen, and audio information will be withheld. Conversely, if the user is calm and at home, audio information will be permitted.

[0153] As a concrete example, consider a case where a user receives an important work-related notification. In this case, if the device's emotion engine determines that the user is in a high-stress state and the location information acquisition means detect that the user is in the office, it will prioritize visual notifications to safely deliver the information.

[0154] A concrete example of a prompt message for a generative AI model would be, "Please suggest ways to optimize information delivery methods when the user is under high stress." This allows the model to provide appropriate feedback regarding the selection of information delivery methods.

[0155] In this way, the system can provide flexible information tailored to the user's emotions and environment, enabling a more personalized user experience.

[0156] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0157] Step 1:

[0158] The device uses a camera and microphone to collect video and audio data from the user. This captures the user's facial expressions and voice tone and speed. The input is raw data acquired from the camera and microphone, and the output is data prepared in a format suitable for sentiment analysis. Specifically, the camera captures the user's face at a constant frame rate, and the microphone records audio in sync.

[0159] Step 2:

[0160] The device analyzes data collected via the emotion engine. The emotion engine uses machine learning algorithms to determine the user's emotional state, such as joy, anger, sadness, or happiness, from their image and voice data. The input is the formalized data prepared in step 1, and the output is a numerical value or category indicating the user's emotional state. Specifically, the emotion engine analyzes the movement of facial muscles and the frequency characteristics of the voice to determine, for example, that "the user is in a state of joy."

[0161] Step 3:

[0162] The device obtains location information using a GPS module and Wi-Fi data. This allows it to determine whether the user's current location is a public space. The input is location coordinates provided by GPS and supplementary Wi-Fi data, while the output is category information such as environmental characteristics, such as "public space" or "private space." Specifically, the device checks its current latitude and longitude every second and compares that location with an existing database to determine the environmental category.

[0163] Step 4:

[0164] The server integrates the sentiment analysis results obtained in Step 2 with the environmental information obtained in Step 3 to determine the optimal method of information delivery. The inputs are the user's emotional state and environmental characteristics, while the output is a guideline for information delivery, such as "avoid voice notifications" or "prioritize visual presentations." Specifically, the server evaluates the reliability and importance of each piece of information and selects a strategy to convey the information without burdening the user.

[0165] Step 5:

[0166] The terminal provides information based on instructions from the server. Specifically, it provides information via voice using a speech synthesizer or displays a notification on the screen. The input is the guideline for information provision from the server, and the output is the specific information conveyed to the user. For example, the terminal will display "You have a new message" on the screen and, if appropriate, explain the content via voice.

[0167] This allows the system to provide personalized information tailored to the user's emotions and environment.

[0168] (Application Example 2)

[0169] 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 device 14 will be referred to as the "terminal."

[0170] Providing personalized information to individual customers in physical stores is difficult with traditional methods, as they only offer uniform guidance, limiting the potential for improving the customer experience. Furthermore, it's challenging to respond flexibly to customers' emotional states and surrounding environments. Therefore, there is a need for technology that enables service delivery optimized for each customer's emotions and circumstances.

[0171] 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.

[0172] In this invention, the server includes detection means for acquiring environmental information around the user, processing means for analyzing the environmental information from the device to determine the situation around the user, control means for controlling the method of providing sensitive information based on the situation, emotion analysis means for analyzing the user's emotional state and optimizing information based thereon, and location-dependent means for optimizing the information provided using the user's location information. This makes it possible to provide optimal information based on the customer's emotional state and location information.

[0173] A "user" is an individual who utilizes this system and is a recipient of the information provided.

[0174] "Environmental information" refers to data about the user's surroundings, including sound, images, and location information.

[0175] A "detection device" is a device used to acquire environmental information and is equipped with various sensors.

[0176] A "processing mechanism" is a system that analyzes acquired environmental information to determine the user's situation and emotional state.

[0177] A "control device" is a device that has the function of adjusting the method of providing information based on the user's situation and emotions.

[0178] "Emotional analysis methods" are technologies that analyze a user's facial expressions and tone of voice to determine their emotional state.

[0179] "Location-dependent means" refers to a function that provides optimal information tailored to the user's location based on that information.

[0180] The system for implementing this invention acquires environmental information around the user, analyzes the user's emotional state, and provides information based on that analysis. The system mainly includes the following components.

[0181] First, the device uses sensor devices such as cameras and microphones to capture the user's facial expressions. This collects both acoustic and image data. Next, the processing unit uses software such as OpenCV and TENSORFLOW® to analyze this data and determine the user's emotional state.

[0182] The server uses Bluetooth beacon technology to obtain the user's location information and understand their surroundings. This allows the server to determine the environment in which the user is located. Based on the acquired data, the server selects the most appropriate method for providing information to the user, and then delivers that information.

[0183] A concrete example would be an application used in a physical store. If a customer shows interest in a product, the server displays detailed information about the product on their smartphone based on data acquired from the camera and microphone. Furthermore, if it is determined that the information the customer needs is not for a public place, the information is also provided via audio.

[0184] The following are examples of prompt statements for the generative AI model:

[0185] Input data: Image data (customer's facial expression), location information

[0186] Task: Design a way to provide customers with additional information about products they are interested in.

[0187] This allows the server to provide information optimized for the user, enabling a more personalized service.

[0188] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0189] Step 1:

[0190] The device acquires data from the user's face and voice. The camera and microphone are activated, capturing image and audio data. The input is the user's facial expression image and voice, and this raw data is taken into the system as output.

[0191] Step 2:

[0192] The system processes the image and audio data acquired by the device. At this stage, face recognition and emotion analysis are performed using OpenCV and TensorFlow. The input is the image and audio data collected in step 1, and the output is the analysis result indicating the user's emotional state. Specifically, feature points are extracted from the user's face, and emotional states such as joy, anger, sadness, and happiness are estimated using a pre-trained model.

[0193] Step 3:

[0194] The server determines the user's current location based on location information obtained from a Bluetooth beacon. The input is location data transmitted by the beacon, and the output is the user's location within the store. Specifically, the user's position is calculated using triangulation based on the received signal strength.

[0195] Step 4:

[0196] The server determines the information to provide to the user based on their emotional state and location. The input consists of the emotional analysis results obtained from steps 2 and 3, and the location information. The output is the selection of the most suitable information for the user. The generating AI model uses prompts to select the most suitable information and extracts information related to specific products within the store as the information to be provided.

[0197] Step 5:

[0198] The server selects information and sends it to the terminal, where it is displayed on the user's smartphone. The input is the information provided by the server, and the output is the information displayed on the smartphone screen. Specifically, information is sent to the terminal via a REST API and displayed in an appropriate format according to the user's browsing status.

[0199] 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.

[0200] 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.

[0201] 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.

[0202] [Second Embodiment]

[0203] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0204] 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.

[0205] 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).

[0206] 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.

[0207] 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.

[0208] 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).

[0209] 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.

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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".

[0215] This invention is a system that securely provides sensitive information while protecting user privacy. The system is implemented on the user's terminal and utilizes various sensor devices to monitor the user's surrounding environment in detail.

[0216] The device first uses a video acquisition device to detect people in its surroundings. This allows it to recognize faces and figures from the video captured by the camera and determine whether other people are nearby. Next, it analyzes ambient sounds with an audio acquisition device to detect voices and unusual changes in volume. This allows it to detect the possibility that other people are joining a conversation. In addition, it uses a location information acquisition device to determine the device's current location and whether it is a public place.

[0217] By analyzing this information using a processing unit, the terminal infers the possibility that other people are present around the user. Based on this, the control unit determines how to provide sensitive information. For example, if there are other people nearby, instead of speaking the information aloud, the terminal will display the information on the screen for the user and send a confirmation message to the user beforehand.

[0218] As a concrete example, consider a scenario where a user receives a balance notification from a financial institution. The terminal first uses sensors to assess the surrounding environment, and if it determines there is a privacy risk, it refrains from outputting audio. Then, it displays the balance information on the screen, allowing the user to check the details by touching the screen. In this way, it is possible to provide a flexible interface that adapts to the user's environment.

[0219] This system aims to protect user privacy on a daily basis while securely providing necessary information, and can be adapted in various ways depending on the target environment.

[0220] The following describes the processing flow.

[0221] Step 1:

[0222] The device activates the video acquisition system and captures video of the user's surroundings through the camera. Using a video analysis algorithm, it detects human faces and figures from the acquired images. If people are detected, their number and location information are recorded.

[0223] Step 2:

[0224] The device uses a voice acquisition device to record ambient sounds. A voice analysis algorithm is applied to detect speech patterns and volume changes from the recorded audio. When voices suspected to belong to other people are recognized, the audio information is also recorded over time.

[0225] Step 3:

[0226] The device activates its location acquisition device and obtains current GPS data. Based on the acquired location information, it checks whether the user's current location is a public place and assesses the level of privacy risk.

[0227] Step 4:

[0228] The device integrates the results of analyzing video, audio, and location data to determine whether other people are present in the user's vicinity. If a high privacy risk is detected, the process proceeds to the next step.

[0229] Step 5:

[0230] The device displays a confirmation message on the screen before conveying sensitive information to the user via voice. It also provides the user with an option to ask whether they want to allow the information to be output aloud.

[0231] Step 6:

[0232] If the user refuses audio output, the device will provide sensitive information via screen display. Specifically, the device will display the information on the screen in text format so that the user can review the content.

[0233] Step 7:

[0234] Once the information provision is complete, the device will resume collecting environmental information and continue the process described above according to the surrounding conditions. This ensures that privacy protection is always tailored to the latest user environment.

[0235] (Example 1)

[0236] 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."

[0237] In today's data-driven society, safely providing sensitive information while protecting user privacy is a critical challenge. However, existing systems struggle to flexibly adapt to the surrounding environment and provide appropriate information accordingly. Therefore, there is a need to build systems that accurately assess the user's situation and minimize privacy risks.

[0238] 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.

[0239] In this invention, the server includes detection means for collecting physical conditions around the user, evaluation means for analyzing the physical conditions from the detection means and evaluating the risks around the user, and control means for determining a method for providing confidential information based on the risk evaluation. This enables the provision of safe and appropriate information according to the user's surrounding environment.

[0240] A "user" refers to an individual or group that uses the system, and is the entity that receives and manipulates information.

[0241] "Physical circumstances" refers to observable data in the user's surrounding environment, such as the presence of people, changes in volume, and location information.

[0242] "Detection means" refers to a collection of devices and equipment used to sense the physical conditions around the user.

[0243] "Evaluation means" refers to the process of analyzing data obtained from detection means and calculating and evaluating the privacy risks surrounding the user.

[0244] "Control means" refers to a mechanism for determining and implementing methods for providing confidential information based on risk assessments conducted by evaluation means.

[0245] "Confidential information" refers to information that requires user privacy protection, and includes, for example, personal information and financial data.

[0246] "Communication methods" refer to information transmission technologies and processes used to provide confirmations and notifications to users.

[0247] In embodiments of this invention, the aim is for the information processing system to provide sensitive information while protecting user privacy. The system mainly consists of terminals equipped with multiple sensor devices. Specifically, these include cameras for acquiring images, microphones for acquiring sound, and GPS modules for measuring location.

[0248] The device activates these sensors to collect information about the user's surroundings in real time. Video is analyzed by image processing algorithms to detect the presence of human faces and shapes. Audio data is processed by acoustic analysis software to detect speech and unusual volume changes. Location information is acquired via satellite communication and analyzed in conjunction with specific geographic information services.

[0249] The collected data is analyzed by a processing unit within the device, and the risk to user privacy is assessed. Based on this assessment, the method of providing the information is determined. If the risk is deemed high, a format is chosen that avoids voice output and displays the information on the device screen. This ensures that necessary information is provided appropriately while protecting the user's privacy.

[0250] As a concrete example, when a user receives a financial transaction alert, the device monitors the surrounding environment using the aforementioned sensors. If the system determines that there is a high privacy risk and that others are nearby, the financial information is displayed on the screen instead of being audible, and the user can manually check the details. By utilizing this system, users can receive information safely and appropriately according to their surrounding circumstances.

[0251] An example of a prompt for a generative AI model is, "Explain how the system monitors the user's surroundings and determines how to provide information." This makes it easier to understand how the system works.

[0252] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0253] Step 1:

[0254] The device first activates its sensor equipment and begins collecting environmental information. At this stage, the camera captures video, the microphone acquires audio data, and the GPS module acquires location information. The input data consists of video, audio, and location information, each of which is updated in real time. As output, each piece of data is stored in temporary storage. Specifically, the camera identifies people in the surroundings, the microphone records speech, and the GPS determines the current coordinates.

[0255] Step 2:

[0256] The terminal's processing unit analyzes the collected environmental data. In this analysis, image analysis software processes video data to recognize human faces and postures. Acoustic analysis software performs calculations to detect conversations and unusual volume changes from audio data. GPS data is compared with map information to determine if the current location is a public place. The input is the data set collected in step 1, and the output is risk assessment information regarding the user's surrounding environment.

[0257] Step 3:

[0258] Based on the evaluation results, the terminal's control unit determines how to provide information. If a high privacy risk is identified, it avoids audio presentation and switches to screen display. The input is the risk assessment information from step 2, and the output is the determination of the information provision method. Based on this information, the terminal takes specific actions to protect user privacy, such as displaying financial information only on the screen and suppressing audio output.

[0259] Step 4:

[0260] The terminal sends a message to the user requesting confirmation. This message includes confirmation that a predetermined information delivery method has been selected and instructions for confirmation. The input is the information delivery method determined in step 3, and the output is a confirmation message to the user. Specifically, it displays instructions on the screen such as "Information has been displayed. Please touch to confirm the contents."

[0261] (Application Example 1)

[0262] 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."

[0263] This invention relates to a technology that provides sensitive information while ensuring user privacy in public places and noisy environments. Conventional technologies are limited to simply conveying information by voice or displaying it on a screen, making it difficult to provide information while considering the surrounding environment. As a result, there is a risk of information being leaked to others, especially in public transportation and commercial facilities. This invention aims to solve these problems and realize a flexible means of providing information that is appropriate for the environment.

[0264] 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.

[0265] In this invention, the server includes means for a sensor device to acquire environmental information around the user; means for analyzing the environmental information from the device to determine the situation around the user; means for automatically switching the form of information provision from voice to visual display in public places; and means for transmitting information to the user via a bone conduction device according to the noise level of the environment. This makes it possible to provide information appropriate to the surrounding environment while protecting the user's privacy.

[0266] "User environment information" refers to data about the user's surroundings, including information such as video, audio, and location.

[0267] A "sensor device" is a device used to acquire various types of input data, and consists of devices such as video acquisition devices, audio acquisition devices, and location information acquisition devices.

[0268] A "processing device" is a device that analyzes acquired environmental information and performs information processing to determine the situation around the user.

[0269] A "control device" is a device that determines how to provide sensitive information based on the analysis results and controls the display format of that information.

[0270] A "public place" refers to a space that is accessible to the general public and is used by the general public, and includes public transportation and commercial facilities.

[0271] "Visual display" refers to a method of presenting information through human vision, and involves using display devices such as screens and smart glasses.

[0272] "Noise level" is an indicator that shows the intensity and noise level of sounds around the user, and is measured using a voice acquisition device.

[0273] A "bone conduction device" is a device that transmits sound vibrations to the inner ear through the bone, rather than sending sound directly to the ear, by utilizing vibrations.

[0274] "Sensitive information" is a term that refers to information relating to an individual's privacy or highly confidential information, and should be provided to users with particular care.

[0275] The present invention provides a system that flexibly switches the method of providing information according to the user's surrounding environment. Specific embodiments for carrying out the present invention are described below.

[0276] This system incorporates the following components into the user's device: The sensor device includes a video acquisition device, an audio acquisition device, a location information acquisition device, and an acoustic measurement function, collecting detailed information about the user's surroundings. This data is sent to a processing unit within the device and analyzed in real time. This allows the system to determine whether the user is currently in a public place or if the noise level is high.

[0277] The processing unit analyzes video data using the open-source library OpenCV to determine if a person is present in the video. Audio data is analyzed using general audio analysis software to measure the intensity of ambient noise. Location information is generated using a GPS module, and whether the location is a public place is confirmed through a third-party location service.

[0278] The control device decides whether to provide information via voice or visual display based on the analysis results from the processing unit. In cases of high noise levels, information can be transmitted to the user using a bone conduction device, allowing for efficient information delivery while protecting privacy.

[0279] As a concrete example, consider a scenario where a user receives a bank balance notification while on public transport. In noisy environments, the device would reduce the audio output, allowing the user to view the details by lightly touching the screen.

[0280] Examples of prompt texts include "Please consider a real-time information provision system that takes into account sensitive information provision methods in public places while protecting privacy. Design a system that detects the number of people and voice volume and selects an optimal information display method."

[0281] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0282] Step 1:

[0283] The terminal acquires ambient environmental information using a sensor device. The inputs are video data from a camera, audio data from a microphone, and GPS data from a location information module. These data are collected and stored in an internal memory.

[0284] Step 2:

[0285] The processing device of the terminal analyzes the acquired video data. Using the OpenCV library, the presence of faces and people is detected from the video. The outputs are the number of detected people and location information. This data is used for situation analysis within the terminal.

[0286] Step 3:

[0287] The processing device of the terminal analyzes the audio data. Using general audio analysis software, the noise level is measured from the obtained audio data. The input is the audio data from the microphone, and the output is the noise level expressed in decibels (dB). This information is also utilized for situation analysis.

[0288] Step 4:

[0289] The processing device of the terminal analyzes the location information. The GPS data is sent to a third-party location information service to determine whether the location is a public place. The outputs are the location information and the attribute of that location (public or not).

[0290] Step 5:

[0291] The terminal's control unit determines the information delivery method based on the analysis results from steps 2 to 4. The inputs are the number of people detected, the noise level, and location attributes. The output is a decision on whether to provide the information audibly or visually. For example, if the noise level is high in a public place, visual display is selected.

[0292] Step 6:

[0293] The user receives information according to the information delivery method selected by the user. Specifically, in noisy environments, the device transmits information near the ear using a bone conduction device, and if visual display is selected, the information is displayed on the device's screen. The user can check detailed information by operating the screen as needed.

[0294] 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.

[0295] This invention is a system that provides information flexibly based on the user's emotional state while ensuring user privacy. The system functions by integrating various sensor devices and an emotion engine on the user's terminal.

[0296] The device collects user facial expression data through a video acquisition device. This data is analyzed by an emotion engine to determine the user's emotional state (e.g., joy, sadness, anger, surprise, etc.). The tone and speed of speech obtained by the voice acquisition device are also used in emotion analysis, and changes in emotion can be read from the content of speech.

[0297] Furthermore, based on GPS data acquired by a location information acquisition device, the system determines whether the user's surroundings are a public space and assesses the privacy risks. This information, along with the results of the emotion engine's analysis, is used to select the most appropriate method of providing information to the user.

[0298] For example, if the device recognizes the user's agitated state and determines that it is in a public place, it can be controlled to display sensitive information on the screen instead of providing it verbally. Conversely, if the user is calm and at home, or if other conditions are met, verbal information provision may be permitted.

[0299] For example, when a user receives an important work-related message, the device attempts to read it aloud, but then detects that the user is in an office with other people present. Furthermore, if the emotion engine determines that the user's stress level is high, the device not only displays the message on the screen but also sends a notification message to encourage the user to check it themselves.

[0300] In this way, by using the analysis results of the emotion engine and environmental information, the device can autonomously adjust how it provides sensitive information, resulting in a more personalized user experience.

[0301] The following describes the processing flow.

[0302] Step 1:

[0303] The device uses a video acquisition device to capture the user's facial expressions via a camera. The video data is sent to an emotion engine, where a facial expression analysis algorithm identifies the user's emotional state.

[0304] Step 2:

[0305] The device uses a voice acquisition device to collect the user's speech. A voice analysis algorithm is applied to evaluate the emotional state from the tone, pitch, and speed of the speech. This data is then integrated into the emotion engine.

[0306] Step 3:

[0307] The terminal activates the location information acquisition device and obtains GPS data. The acquired location information is processed to determine whether the user's current location is a public place. This location data is used for evaluating the user's privacy risk.

[0308] Step 4:

[0309] The terminal integrates the analysis result of the emotion engine and the location information to comprehensively evaluate the user's emotional state and the surrounding situation. Based on the evaluation, the information provision operation of the interface is determined.

[0310] Step 5:

[0311] When the terminal attempts to convey sensitive information to the user, it considers the user's emotional state and environmental conditions to determine the suitability of voice output. If the user is feeling stressed or is in a public place, screen display is recommended instead of voice.

[0312] Step 6:

[0313] When making a selection in response to the confirmation message sent by the user, the terminal adjusts the information provision method according to the user's selection. For example, if voice output is rejected, the terminal provides sensitive information visually on the screen.

[0314] Step 7:

[0315] When the information provision is completed, the terminal starts collecting and analyzing environmental information and emotional information again in preparation for new information, and repeats the above process. Through this cycle, continuous privacy protection suitable for the user's situation is realized.

[0316] (Example 2)

[0317] 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".

[0318] Conventional information delivery systems sometimes provide sensitive information in an inappropriate manner without adequately considering the user's emotional state or surrounding environment. This can result in violations of user privacy or unpleasant experiences. Therefore, there is a need for a system that can flexibly adjust information delivery methods according to the user's emotional state and environment.

[0319] 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.

[0320] In this invention, the server includes data analysis means for analyzing the user's emotional state, location information acquisition means for acquiring the user's environmental information and determining whether it is a public place, and control means for flexibly selecting the method of providing information based on the information acquired by the data analysis means and the location information acquisition means. This makes it possible to provide information appropriately and flexibly while ensuring the user's privacy.

[0321] "Data analysis means" refers to a function or system that analyzes the user's collected video and audio data to determine their emotional state.

[0322] "Location information acquisition means" refers to a function or system that acquires the user's geographical location and uses that location to determine whether or not it is a public place.

[0323] A "control means" is a function or system that optimally selects and controls the method of providing information based on the user's emotional state and environmental information.

[0324] "Emotional state" refers to the user's psychological and emotional state, and includes various emotional elements such as joy, sadness, anger, and surprise.

[0325] "Environmental information" refers to data that indicates the user's surroundings, including location information, ambient sound environment, and visual environment.

[0326] "Information provision method" refers to the specific means by which information is presented to the user, and includes various forms of expression such as audio, text, and video.

[0327] This system is designed to analyze the user's emotional state and environmental information, and adjust the method of information delivery based on that analysis. Its main components are data analysis means, location information acquisition means, and control means.

[0328] First, the device collects the user's video and audio data using its built-in camera and microphone. For data analysis, this data is received and analyzed via an emotion engine using dedicated software. This emotion engine uses machine learning algorithms to determine the user's emotional state in real time, including emotions such as joy, anger, sadness, and stress levels.

[0329] Next, the device uses location information acquisition methods such as a GPS module to confirm the user's geographical location. This allows the device to determine whether the user is in a public place and assess privacy risks. In addition to location information, it may also use information from Wi-Fi or Bluetooth beacons as a supplementary tool in some cases.

[0330] The server integrates emotion analysis results and location information, and uses control mechanisms to determine the optimal method of information delivery. For example, if the user is agitated and in a public environment, the information will be displayed on the screen, and audio information will be withheld. Conversely, if the user is calm and at home, audio information will be permitted.

[0331] As a concrete example, consider a case where a user receives an important work-related notification. In this case, if the device's emotion engine determines that the user is in a high-stress state and the location information acquisition means detect that the user is in the office, it will prioritize visual notifications to safely deliver the information.

[0332] A concrete example of a prompt message for a generative AI model would be, "Please suggest ways to optimize information delivery methods when the user is under high stress." This allows the model to provide appropriate feedback regarding the selection of information delivery methods.

[0333] In this way, the system can provide flexible information tailored to the user's emotions and environment, enabling a more personalized user experience.

[0334] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0335] Step 1:

[0336] The device uses a camera and microphone to collect video and audio data from the user. This captures the user's facial expressions and voice tone and speed. The input is raw data acquired from the camera and microphone, and the output is data prepared in a format suitable for sentiment analysis. Specifically, the camera captures the user's face at a constant frame rate, and the microphone records audio in sync.

[0337] Step 2:

[0338] The device analyzes data collected via the emotion engine. The emotion engine uses machine learning algorithms to determine the user's emotional state, such as joy, anger, sadness, or happiness, from their image and voice data. The input is the formalized data prepared in step 1, and the output is a numerical value or category indicating the user's emotional state. Specifically, the emotion engine analyzes the movement of facial muscles and the frequency characteristics of the voice to determine, for example, that "the user is in a state of joy."

[0339] Step 3:

[0340] The device obtains location information using a GPS module and Wi-Fi data. This allows it to determine whether the user's current location is a public space. The input is location coordinates provided by GPS and supplementary Wi-Fi data, while the output is category information such as environmental characteristics, such as "public space" or "private space." Specifically, the device checks its current latitude and longitude every second and compares that location with an existing database to determine the environmental category.

[0341] Step 4:

[0342] The server integrates the sentiment analysis results obtained in Step 2 with the environmental information obtained in Step 3 to determine the optimal method of information delivery. The inputs are the user's emotional state and environmental characteristics, while the output is a guideline for information delivery, such as "avoid voice notifications" or "prioritize visual presentations." Specifically, the server evaluates the reliability and importance of each piece of information and selects a strategy to convey the information without burdening the user.

[0343] Step 5:

[0344] The terminal provides information based on instructions from the server. Specifically, it provides information via voice using a speech synthesizer or displays a notification on the screen. The input is the guideline for information provision from the server, and the output is the specific information conveyed to the user. For example, the terminal will display "You have a new message" on the screen and, if appropriate, explain the content via voice.

[0345] This allows the system to provide personalized information tailored to the user's emotions and environment.

[0346] (Application Example 2)

[0347] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0348] Providing personalized information to individual customers in physical stores is difficult with traditional methods, as they only offer uniform guidance, limiting the potential for improving the customer experience. Furthermore, it's challenging to respond flexibly to customers' emotional states and surrounding environments. Therefore, there is a need for technology that enables service delivery optimized for each customer's emotions and circumstances.

[0349] 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.

[0350] In this invention, the server includes detection means for acquiring environmental information around the user, processing means for analyzing the environmental information from the device to determine the situation around the user, control means for controlling the method of providing sensitive information based on the situation, emotion analysis means for analyzing the user's emotional state and optimizing information based thereon, and location-dependent means for optimizing the information provided using the user's location information. This makes it possible to provide optimal information based on the customer's emotional state and location information.

[0351] A "user" is an individual who utilizes this system and is a recipient of the information provided.

[0352] "Environmental information" refers to data about the user's surroundings, including sound, images, and location information.

[0353] A "detection device" is a device used to acquire environmental information and is equipped with various sensors.

[0354] A "processing mechanism" is a system that analyzes acquired environmental information to determine the user's situation and emotional state.

[0355] A "control device" is a device that has the function of adjusting the method of providing information based on the user's situation and emotions.

[0356] "Emotional analysis methods" are technologies that analyze a user's facial expressions and tone of voice to determine their emotional state.

[0357] "Location-dependent means" refers to a function that provides optimal information tailored to the user's location based on that information.

[0358] The system for implementing this invention acquires environmental information around the user, analyzes the user's emotional state, and provides information based on that analysis. The system mainly includes the following components.

[0359] First, the device uses sensors such as cameras and microphones to capture the user's facial expressions. This collects both acoustic and image data. Next, the processing unit uses software such as OpenCV and TensorFlow to analyze this data and determine the user's emotional state.

[0360] The server uses Bluetooth beacon technology to obtain the user's location information and understand their surroundings. This allows the server to determine the environment in which the user is located. Based on the acquired data, the server selects the most appropriate method for providing information to the user, and then delivers that information.

[0361] A concrete example would be an application used in a physical store. If a customer shows interest in a product, the server displays detailed information about the product on their smartphone based on data acquired from the camera and microphone. Furthermore, if it is determined that the information the customer needs is not for a public place, the information is also provided via audio.

[0362] The following are examples of prompt statements for the generative AI model:

[0363] Input data: Image data (customer's facial expression), location information

[0364] Task: Design a way to provide customers with additional information about products they are interested in.

[0365] This allows the server to provide information optimized for the user, enabling a more personalized service.

[0366] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0367] Step 1:

[0368] The device acquires data from the user's face and voice. The camera and microphone are activated, capturing image and audio data. The input is the user's facial expression image and voice, and this raw data is taken into the system as output.

[0369] Step 2:

[0370] The system processes the image and audio data acquired by the device. At this stage, face recognition and emotion analysis are performed using OpenCV and TensorFlow. The input is the image and audio data collected in step 1, and the output is the analysis result indicating the user's emotional state. Specifically, feature points are extracted from the user's face, and emotional states such as joy, anger, sadness, and happiness are estimated using a pre-trained model.

[0371] Step 3:

[0372] The server determines the user's current location based on location information obtained from a Bluetooth beacon. The input is location data transmitted by the beacon, and the output is the user's location within the store. Specifically, the user's position is calculated using triangulation based on the received signal strength.

[0373] Step 4:

[0374] The server determines the information to provide to the user based on their emotional state and location. The input consists of the emotional analysis results obtained from steps 2 and 3, and the location information. The output is the selection of the most suitable information for the user. The generating AI model uses prompts to select the most suitable information and extracts information related to specific products within the store as the information to be provided.

[0375] Step 5:

[0376] The server selects information and sends it to the terminal, where it is displayed on the user's smartphone. The input is the information provided by the server, and the output is the information displayed on the smartphone screen. Specifically, information is sent to the terminal via a REST API and displayed in an appropriate format according to the user's browsing status.

[0377] 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.

[0378] 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.

[0379] 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.

[0380] [Third Embodiment]

[0381] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0382] 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.

[0383] 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).

[0384] 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.

[0385] 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.

[0386] 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).

[0387] 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.

[0388] 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.

[0389] 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.

[0390] 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.

[0391] 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.

[0392] 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".

[0393] This invention is a system that securely provides sensitive information while protecting user privacy. The system is implemented on the user's terminal and utilizes various sensor devices to monitor the user's surrounding environment in detail.

[0394] The device first uses a video acquisition device to detect people in its surroundings. This allows it to recognize faces and figures from the video captured by the camera and determine whether other people are nearby. Next, it analyzes ambient sounds with an audio acquisition device to detect voices and unusual changes in volume. This allows it to detect the possibility that other people are joining a conversation. In addition, it uses a location information acquisition device to determine the device's current location and whether it is a public place.

[0395] By analyzing this information using a processing unit, the terminal infers the possibility that other people are present around the user. Based on this, the control unit determines how to provide sensitive information. For example, if there are other people nearby, instead of speaking the information aloud, the terminal will display the information on the screen for the user and send a confirmation message to the user beforehand.

[0396] As a concrete example, consider a scenario where a user receives a balance notification from a financial institution. The terminal first uses sensors to assess the surrounding environment, and if it determines there is a privacy risk, it refrains from outputting audio. Then, it displays the balance information on the screen, allowing the user to check the details by touching the screen. In this way, it is possible to provide a flexible interface that adapts to the user's environment.

[0397] This system aims to protect user privacy on a daily basis while securely providing necessary information, and can be adapted in various ways depending on the target environment.

[0398] The following describes the processing flow.

[0399] Step 1:

[0400] The device activates the video acquisition system and captures video of the user's surroundings through the camera. Using a video analysis algorithm, it detects human faces and figures from the acquired images. If people are detected, their number and location information are recorded.

[0401] Step 2:

[0402] The device uses a voice acquisition device to record ambient sounds. A voice analysis algorithm is applied to detect speech patterns and volume changes from the recorded audio. When voices suspected to belong to other people are recognized, the audio information is also recorded over time.

[0403] Step 3:

[0404] The device activates its location acquisition device and obtains current GPS data. Based on the acquired location information, it checks whether the user's current location is a public place and assesses the level of privacy risk.

[0405] Step 4:

[0406] The device integrates the results of analyzing video, audio, and location data to determine whether other people are present in the user's vicinity. If a high privacy risk is detected, the process proceeds to the next step.

[0407] Step 5:

[0408] The device displays a confirmation message on the screen before conveying sensitive information to the user via voice. It also provides the user with an option to ask whether they want to allow the information to be output aloud.

[0409] Step 6:

[0410] If the user refuses audio output, the device will provide sensitive information via screen display. Specifically, the device will display the information on the screen in text format so that the user can review the content.

[0411] Step 7:

[0412] Once the information provision is complete, the device will resume collecting environmental information and continue the process described above according to the surrounding conditions. This ensures that privacy protection is always tailored to the latest user environment.

[0413] (Example 1)

[0414] 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."

[0415] In today's data-driven society, safely providing sensitive information while protecting user privacy is a critical challenge. However, existing systems struggle to flexibly adapt to the surrounding environment and provide appropriate information accordingly. Therefore, there is a need to build systems that accurately assess the user's situation and minimize privacy risks.

[0416] 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.

[0417] In this invention, the server includes detection means for collecting physical conditions around the user, evaluation means for analyzing the physical conditions from the detection means and evaluating the risks around the user, and control means for determining a method for providing confidential information based on the risk evaluation. This enables the provision of safe and appropriate information according to the user's surrounding environment.

[0418] A "user" refers to an individual or group that uses the system, and is the entity that receives and manipulates information.

[0419] "Physical circumstances" refers to observable data in the user's surrounding environment, such as the presence of people, changes in volume, and location information.

[0420] "Detection means" refers to a collection of devices and equipment used to sense the physical conditions around the user.

[0421] "Evaluation means" refers to the process of analyzing data obtained from detection means and calculating and evaluating the privacy risks surrounding the user.

[0422] "Control means" refers to a mechanism for determining and implementing methods for providing confidential information based on risk assessments conducted by evaluation means.

[0423] "Confidential information" refers to information that requires user privacy protection, and includes, for example, personal information and financial data.

[0424] "Communication methods" refer to information transmission technologies and processes used to provide confirmations and notifications to users.

[0425] In embodiments of this invention, the aim is for the information processing system to provide sensitive information while protecting user privacy. The system mainly consists of terminals equipped with multiple sensor devices. Specifically, these include cameras for acquiring images, microphones for acquiring sound, and GPS modules for measuring location.

[0426] The device activates these sensors to collect information about the user's surroundings in real time. Video is analyzed by image processing algorithms to detect the presence of human faces and shapes. Audio data is processed by acoustic analysis software to detect speech and unusual volume changes. Location information is acquired via satellite communication and analyzed in conjunction with specific geographic information services.

[0427] The collected data is analyzed by a processing unit within the device, and the risk to user privacy is assessed. Based on this assessment, the method of providing the information is determined. If the risk is deemed high, a format is chosen that avoids voice output and displays the information on the device screen. This ensures that necessary information is provided appropriately while protecting the user's privacy.

[0428] As a concrete example, when a user receives a financial transaction alert, the device monitors the surrounding environment using the aforementioned sensors. If the system determines that there is a high privacy risk and that others are nearby, the financial information is displayed on the screen instead of being audible, and the user can manually check the details. By utilizing this system, users can receive information safely and appropriately according to their surrounding circumstances.

[0429] An example of a prompt for a generative AI model is, "Explain how the system monitors the user's surroundings and determines how to provide information." This makes it easier to understand how the system works.

[0430] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0431] Step 1:

[0432] The device first activates its sensor equipment and begins collecting environmental information. At this stage, the camera captures video, the microphone acquires audio data, and the GPS module acquires location information. The input data consists of video, audio, and location information, each of which is updated in real time. As output, each piece of data is stored in temporary storage. Specifically, the camera identifies people in the surroundings, the microphone records speech, and the GPS determines the current coordinates.

[0433] Step 2:

[0434] The terminal's processing unit analyzes the collected environmental data. In this analysis, image analysis software processes video data to recognize human faces and postures. Acoustic analysis software performs calculations to detect conversations and unusual volume changes from audio data. GPS data is compared with map information to determine if the current location is a public place. The input is the data set collected in step 1, and the output is risk assessment information regarding the user's surrounding environment.

[0435] Step 3:

[0436] Based on the evaluation results, the terminal's control unit determines how to provide information. If a high privacy risk is identified, it avoids audio presentation and switches to screen display. The input is the risk assessment information from step 2, and the output is the determination of the information provision method. Based on this information, the terminal takes specific actions to protect user privacy, such as displaying financial information only on the screen and suppressing audio output.

[0437] Step 4:

[0438] The terminal sends a message to the user requesting confirmation. This message includes confirmation that a predetermined information delivery method has been selected and instructions for confirmation. The input is the information delivery method determined in step 3, and the output is a confirmation message to the user. Specifically, it displays instructions on the screen such as "Information has been displayed. Please touch to confirm the contents."

[0439] (Application Example 1)

[0440] 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."

[0441] This invention relates to a technology that provides sensitive information while ensuring user privacy in public places and noisy environments. Conventional technologies are limited to simply conveying information by voice or displaying it on a screen, making it difficult to provide information while considering the surrounding environment. As a result, there is a risk of information being leaked to others, especially in public transportation and commercial facilities. This invention aims to solve these problems and realize a flexible means of providing information that is appropriate for the environment.

[0442] 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.

[0443] In this invention, the server includes means for a sensor device to acquire environmental information around the user; means for analyzing the environmental information from the device to determine the situation around the user; means for automatically switching the form of information provision from voice to visual display in public places; and means for transmitting information to the user via a bone conduction device according to the noise level of the environment. This makes it possible to provide information appropriate to the surrounding environment while protecting the user's privacy.

[0444] "User environment information" refers to data about the user's surroundings, including information such as video, audio, and location.

[0445] A "sensor device" is a device used to acquire various types of input data, and consists of devices such as video acquisition devices, audio acquisition devices, and location information acquisition devices.

[0446] A "processing device" is a device that analyzes acquired environmental information and performs information processing to determine the situation around the user.

[0447] A "control device" is a device that determines how to provide sensitive information based on the analysis results and controls the display format of that information.

[0448] A "public place" refers to a space that is accessible to the general public and is used by the general public, and includes public transportation and commercial facilities.

[0449] "Visual display" refers to a method of presenting information through human vision, and involves using display devices such as screens and smart glasses.

[0450] "Noise level" is an indicator that shows the intensity and noise level of sounds around the user, and is measured using a voice acquisition device.

[0451] A "bone conduction device" is a device that transmits sound vibrations to the inner ear through the bone, rather than sending sound directly to the ear, by utilizing vibrations.

[0452] "Sensitive information" is a term that refers to information relating to an individual's privacy or highly confidential information, and should be provided to users with particular care.

[0453] The present invention provides a system that flexibly switches the method of providing information according to the user's surrounding environment. Specific embodiments for carrying out the present invention are described below.

[0454] This system incorporates the following components into the user's device: The sensor device includes a video acquisition device, an audio acquisition device, a location information acquisition device, and an acoustic measurement function, collecting detailed information about the user's surroundings. This data is sent to a processing unit within the device and analyzed in real time. This allows the system to determine whether the user is currently in a public place or if the noise level is high.

[0455] The processing unit analyzes video data using the open-source library OpenCV to determine if a person is present in the video. Audio data is analyzed using general audio analysis software to measure the intensity of ambient noise. Location information is generated using a GPS module, and whether the location is a public place is confirmed through a third-party location service.

[0456] The control device decides whether to provide information via voice or visual display based on the analysis results from the processing unit. In cases of high noise levels, information can be transmitted to the user using a bone conduction device, allowing for efficient information delivery while protecting privacy.

[0457] As a concrete example, consider a scenario where a user receives a bank balance notification while on public transport. In noisy environments, the device would reduce the audio output, allowing the user to view the details by lightly touching the screen.

[0458] An example of a prompt message would be: "Design a real-time information delivery system that considers sensitive information delivery methods in public spaces while protecting privacy. Design a system that detects the number of people and the volume of voices and selects the optimal information display method."

[0459] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0460] Step 1:

[0461] The device acquires information about its surroundings using sensor devices. Inputs include video data from a camera, audio data from a microphone, and GPS data from a location information module. This data is collected and stored in internal memory.

[0462] Step 2:

[0463] The terminal's processing unit analyzes the acquired video data. Using the OpenCV library, it detects faces and the presence of people in the video. The output includes the number of detected people and their location information. This data is used for situational analysis within the terminal.

[0464] Step 3:

[0465] The terminal's processing unit analyzes the audio data. Using general audio analysis software, it measures the noise level from the obtained audio data. The input is audio data from the microphone, and the output is the noise level expressed in decibels (dB). This information is also used for situational analysis.

[0466] Step 4:

[0467] The device's processing unit analyzes location information. It sends GPS data to a third-party location service to determine if the location is a public place. The output is the location information and its attributes (whether it is public or not).

[0468] Step 5:

[0469] The terminal's control unit determines the information delivery method based on the analysis results from steps 2 to 4. The inputs are the number of people detected, the noise level, and location attributes. The output is a decision on whether to provide the information audibly or visually. For example, if the noise level is high in a public place, visual display is selected.

[0470] Step 6:

[0471] The user receives information according to the information delivery method selected by the user. Specifically, in noisy environments, the device transmits information near the ear using a bone conduction device, and if visual display is selected, the information is displayed on the device's screen. The user can check detailed information by operating the screen as needed.

[0472] 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.

[0473] This invention is a system that provides information flexibly based on the user's emotional state while ensuring user privacy. The system functions by integrating various sensor devices and an emotion engine on the user's terminal.

[0474] The device collects user facial expression data through a video acquisition device. This data is analyzed by an emotion engine to determine the user's emotional state (e.g., joy, sadness, anger, surprise, etc.). The tone and speed of speech obtained by the voice acquisition device are also used in emotion analysis, and changes in emotion can be read from the content of speech.

[0475] Furthermore, based on GPS data acquired by a location information acquisition device, the system determines whether the user's surroundings are a public space and assesses the privacy risks. This information, along with the results of the emotion engine's analysis, is used to select the most appropriate method of providing information to the user.

[0476] For example, if the device recognizes the user's agitated state and determines that it is in a public place, it can be controlled to display sensitive information on the screen instead of providing it verbally. Conversely, if the user is calm and at home, or if other conditions are met, verbal information provision may be permitted.

[0477] For example, when a user receives an important work-related message, the device attempts to read it aloud, but then detects that the user is in an office with other people present. Furthermore, if the emotion engine determines that the user's stress level is high, the device not only displays the message on the screen but also sends a notification message to encourage the user to check it themselves.

[0478] In this way, by using the analysis results of the emotion engine and environmental information, the device can autonomously adjust how it provides sensitive information, resulting in a more personalized user experience.

[0479] The following describes the processing flow.

[0480] Step 1:

[0481] The device uses a video acquisition device to capture the user's facial expressions via a camera. The video data is sent to an emotion engine, where a facial expression analysis algorithm identifies the user's emotional state.

[0482] Step 2:

[0483] The device uses a voice acquisition device to collect the user's speech. A voice analysis algorithm is applied to evaluate the emotional state from the tone, pitch, and speed of the speech. This data is then integrated into the emotion engine.

[0484] Step 3:

[0485] The device activates its location acquisition device and obtains GPS data. The acquired location information is processed to determine whether the user's current location is a public place. This location data is used to assess the user's privacy risks.

[0486] Step 4:

[0487] The device integrates the analysis results from the emotion engine with location information to comprehensively evaluate the user's emotional state and surrounding environment. Based on this evaluation, it determines the information provision behavior of the interface.

[0488] Step 5:

[0489] When a device attempts to convey sensitive information to a user, it considers the user's emotional state and environmental conditions to determine the appropriateness of audio output. If the user is stressed or in a public place, screen display is recommended instead of audio.

[0490] Step 6:

[0491] If the user makes a selection in response to a confirmation message sent, the device will adjust how information is provided according to the user's choice. For example, if voice output is refused, the device will provide sensitive information visually on the screen.

[0492] Step 7:

[0493] Once the information provision is complete, the device will restart the collection and analysis of environmental and emotional information in preparation for any new information that may arise, and repeat the process described above. This cycle ensures that privacy protection is continuously tailored to the user's situation.

[0494] (Example 2)

[0495] 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."

[0496] Conventional information delivery systems sometimes provide sensitive information in an inappropriate manner without adequately considering the user's emotional state or surrounding environment. This can result in violations of user privacy or unpleasant experiences. Therefore, there is a need for a system that can flexibly adjust information delivery methods according to the user's emotional state and environment.

[0497] 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.

[0498] In this invention, the server includes data analysis means for analyzing the user's emotional state, location information acquisition means for acquiring the user's environmental information and determining whether it is a public place, and control means for flexibly selecting the method of providing information based on the information acquired by the data analysis means and the location information acquisition means. This makes it possible to provide information appropriately and flexibly while ensuring the user's privacy.

[0499] "Data analysis means" refers to a function or system that analyzes the user's collected video and audio data to determine their emotional state.

[0500] "Location information acquisition means" refers to a function or system that acquires the user's geographical location and uses that location to determine whether or not it is a public place.

[0501] A "control means" is a function or system that optimally selects and controls the method of providing information based on the user's emotional state and environmental information.

[0502] "Emotional state" refers to the user's psychological and emotional state, and includes various emotional elements such as joy, sadness, anger, and surprise.

[0503] "Environmental information" refers to data that indicates the user's surroundings, including location information, ambient sound environment, and visual environment.

[0504] "Information provision method" refers to the specific means by which information is presented to the user, and includes various forms of expression such as audio, text, and video.

[0505] This system is designed to analyze the user's emotional state and environmental information, and adjust the method of information delivery based on that analysis. Its main components are data analysis means, location information acquisition means, and control means.

[0506] First, the device collects the user's video and audio data using its built-in camera and microphone. For data analysis, this data is received and analyzed via an emotion engine using dedicated software. This emotion engine uses machine learning algorithms to determine the user's emotional state in real time, including emotions such as joy, anger, sadness, and stress levels.

[0507] Next, the device uses location information acquisition methods such as a GPS module to confirm the user's geographical location. This allows the device to determine whether the user is in a public place and assess privacy risks. In addition to location information, it may also use information from Wi-Fi or Bluetooth beacons as a supplementary tool in some cases.

[0508] The server integrates emotion analysis results and location information, and uses control mechanisms to determine the optimal method of information delivery. For example, if the user is agitated and in a public environment, the information will be displayed on the screen, and audio information will be withheld. Conversely, if the user is calm and at home, audio information will be permitted.

[0509] As a concrete example, consider a case where a user receives an important work-related notification. In this case, if the device's emotion engine determines that the user is in a high-stress state and the location information acquisition means detect that the user is in the office, it will prioritize visual notifications to safely deliver the information.

[0510] A concrete example of a prompt message for a generative AI model would be, "Please suggest ways to optimize information delivery methods when the user is under high stress." This allows the model to provide appropriate feedback regarding the selection of information delivery methods.

[0511] In this way, the system can provide flexible information tailored to the user's emotions and environment, enabling a more personalized user experience.

[0512] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0513] Step 1:

[0514] The device uses a camera and microphone to collect video and audio data from the user. This captures the user's facial expressions and voice tone and speed. The input is raw data acquired from the camera and microphone, and the output is data prepared in a format suitable for sentiment analysis. Specifically, the camera captures the user's face at a constant frame rate, and the microphone records audio in sync.

[0515] Step 2:

[0516] The device analyzes data collected via the emotion engine. The emotion engine uses machine learning algorithms to determine the user's emotional state, such as joy, anger, sadness, or happiness, from their image and voice data. The input is the formalized data prepared in step 1, and the output is a numerical value or category indicating the user's emotional state. Specifically, the emotion engine analyzes the movement of facial muscles and the frequency characteristics of the voice to determine, for example, that "the user is in a state of joy."

[0517] Step 3:

[0518] The device obtains location information using a GPS module and Wi-Fi data. This allows it to determine whether the user's current location is a public space. The input is location coordinates provided by GPS and supplementary Wi-Fi data, while the output is category information such as environmental characteristics, such as "public space" or "private space." Specifically, the device checks its current latitude and longitude every second and compares that location with an existing database to determine the environmental category.

[0519] Step 4:

[0520] The server integrates the sentiment analysis results obtained in Step 2 with the environmental information obtained in Step 3 to determine the optimal method of information delivery. The inputs are the user's emotional state and environmental characteristics, while the output is a guideline for information delivery, such as "avoid voice notifications" or "prioritize visual presentations." Specifically, the server evaluates the reliability and importance of each piece of information and selects a strategy to convey the information without burdening the user.

[0521] Step 5:

[0522] The terminal provides information based on instructions from the server. Specifically, it provides information via voice using a speech synthesizer or displays a notification on the screen. The input is the guideline for information provision from the server, and the output is the specific information conveyed to the user. For example, the terminal will display "You have a new message" on the screen and, if appropriate, explain the content via voice.

[0523] This allows the system to provide personalized information tailored to the user's emotions and environment.

[0524] (Application Example 2)

[0525] 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."

[0526] Providing personalized information to individual customers in physical stores is difficult with traditional methods, as they only offer uniform guidance, limiting the potential for improving the customer experience. Furthermore, it's challenging to respond flexibly to customers' emotional states and surrounding environments. Therefore, there is a need for technology that enables service delivery optimized for each customer's emotions and circumstances.

[0527] 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.

[0528] In this invention, the server includes detection means for acquiring environmental information around the user, processing means for analyzing the environmental information from the device to determine the situation around the user, control means for controlling the method of providing sensitive information based on the situation, emotion analysis means for analyzing the user's emotional state and optimizing information based thereon, and location-dependent means for optimizing the information provided using the user's location information. This makes it possible to provide optimal information based on the customer's emotional state and location information.

[0529] A "user" is an individual who utilizes this system and is a recipient of the information provided.

[0530] "Environmental information" refers to data about the user's surroundings, including sound, images, and location information.

[0531] A "detection device" is a device used to acquire environmental information and is equipped with various sensors.

[0532] A "processing mechanism" is a system that analyzes acquired environmental information to determine the user's situation and emotional state.

[0533] A "control device" is a device that has the function of adjusting the method of providing information based on the user's situation and emotions.

[0534] "Emotional analysis methods" are technologies that analyze a user's facial expressions and tone of voice to determine their emotional state.

[0535] "Location-dependent means" refers to a function that provides optimal information tailored to the user's location based on that information.

[0536] The system for implementing this invention acquires environmental information around the user, analyzes the user's emotional state, and provides information based on that analysis. The system mainly includes the following components.

[0537] First, the device uses sensors such as cameras and microphones to capture the user's facial expressions. This collects both acoustic and image data. Next, the processing unit uses software such as OpenCV and TensorFlow to analyze this data and determine the user's emotional state.

[0538] The server uses Bluetooth beacon technology to obtain the user's location information and understand their surroundings. This allows the server to determine the environment in which the user is located. Based on the acquired data, the server selects the most appropriate method for providing information to the user, and then delivers that information.

[0539] A concrete example would be an application used in a physical store. If a customer shows interest in a product, the server displays detailed information about the product on their smartphone based on data acquired from the camera and microphone. Furthermore, if it is determined that the information the customer needs is not for a public place, the information is also provided via audio.

[0540] The following are examples of prompt statements for the generative AI model:

[0541] Input data: Image data (customer's facial expression), location information

[0542] Task: Design a way to provide customers with additional information about products they are interested in.

[0543] This allows the server to provide information optimized for the user, enabling a more personalized service.

[0544] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0545] Step 1:

[0546] The device acquires data from the user's face and voice. The camera and microphone are activated, capturing image and audio data. The input is the user's facial expression image and voice, and this raw data is taken into the system as output.

[0547] Step 2:

[0548] The system processes the image and audio data acquired by the device. At this stage, face recognition and emotion analysis are performed using OpenCV and TensorFlow. The input is the image and audio data collected in step 1, and the output is the analysis result indicating the user's emotional state. Specifically, feature points are extracted from the user's face, and emotional states such as joy, anger, sadness, and happiness are estimated using a pre-trained model.

[0549] Step 3:

[0550] The server determines the user's current location based on location information obtained from a Bluetooth beacon. The input is location data transmitted by the beacon, and the output is the user's location within the store. Specifically, the user's position is calculated using triangulation based on the received signal strength.

[0551] Step 4:

[0552] The server determines the information to provide to the user based on their emotional state and location. The input consists of the emotional analysis results obtained from steps 2 and 3, and the location information. The output is the selection of the most suitable information for the user. The generating AI model uses prompts to select the most suitable information and extracts information related to specific products within the store as the information to be provided.

[0553] Step 5:

[0554] The server selects information and sends it to the terminal, where it is displayed on the user's smartphone. The input is the information provided by the server, and the output is the information displayed on the smartphone screen. Specifically, information is sent to the terminal via a REST API and displayed in an appropriate format according to the user's browsing status.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] [Fourth Embodiment]

[0559] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0560] 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.

[0561] 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).

[0562] 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.

[0563] 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.

[0564] 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).

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] 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.

[0571] 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".

[0572] This invention is a system that securely provides sensitive information while protecting user privacy. The system is implemented on the user's terminal and utilizes various sensor devices to monitor the user's surrounding environment in detail.

[0573] The device first uses a video acquisition device to detect people in its surroundings. This allows it to recognize faces and figures from the video captured by the camera and determine whether other people are nearby. Next, it analyzes ambient sounds with an audio acquisition device to detect voices and unusual changes in volume. This allows it to detect the possibility that other people are joining a conversation. In addition, it uses a location information acquisition device to determine the device's current location and whether it is a public place.

[0574] By analyzing this information using a processing unit, the terminal infers the possibility that other people are present around the user. Based on this, the control unit determines how to provide sensitive information. For example, if there are other people nearby, instead of speaking the information aloud, the terminal will display the information on the screen for the user and send a confirmation message to the user beforehand.

[0575] As a concrete example, consider a scenario where a user receives a balance notification from a financial institution. The terminal first uses sensors to assess the surrounding environment, and if it determines there is a privacy risk, it refrains from outputting audio. Then, it displays the balance information on the screen, allowing the user to check the details by touching the screen. In this way, it is possible to provide a flexible interface that adapts to the user's environment.

[0576] This system aims to protect user privacy on a daily basis while securely providing necessary information, and can be adapted in various ways depending on the target environment.

[0577] The following describes the processing flow.

[0578] Step 1:

[0579] The device activates the video acquisition system and captures video of the user's surroundings through the camera. Using a video analysis algorithm, it detects human faces and figures from the acquired images. If people are detected, their number and location information are recorded.

[0580] Step 2:

[0581] The device uses a voice acquisition device to record ambient sounds. A voice analysis algorithm is applied to detect speech patterns and volume changes from the recorded audio. When voices suspected to belong to other people are recognized, the audio information is also recorded over time.

[0582] Step 3:

[0583] The device activates its location acquisition device and obtains current GPS data. Based on the acquired location information, it checks whether the user's current location is a public place and assesses the level of privacy risk.

[0584] Step 4:

[0585] The device integrates the results of analyzing video, audio, and location data to determine whether other people are present in the user's vicinity. If a high privacy risk is detected, the process proceeds to the next step.

[0586] Step 5:

[0587] The device displays a confirmation message on the screen before conveying sensitive information to the user via voice. It also provides the user with an option to ask whether they want to allow the information to be output aloud.

[0588] Step 6:

[0589] If the user refuses audio output, the device will provide sensitive information via screen display. Specifically, the device will display the information on the screen in text format so that the user can review the content.

[0590] Step 7:

[0591] Once the information provision is complete, the device will resume collecting environmental information and continue the process described above according to the surrounding conditions. This ensures that privacy protection is always tailored to the latest user environment.

[0592] (Example 1)

[0593] 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".

[0594] In today's data-driven society, safely providing sensitive information while protecting user privacy is a critical challenge. However, existing systems struggle to flexibly adapt to the surrounding environment and provide appropriate information accordingly. Therefore, there is a need to build systems that accurately assess the user's situation and minimize privacy risks.

[0595] 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.

[0596] In this invention, the server includes detection means for collecting physical conditions around the user, evaluation means for analyzing the physical conditions from the detection means and evaluating the risks around the user, and control means for determining a method for providing confidential information based on the risk evaluation. This enables the provision of safe and appropriate information according to the user's surrounding environment.

[0597] A "user" refers to an individual or group that uses the system, and is the entity that receives and manipulates information.

[0598] "Physical circumstances" refers to observable data in the user's surrounding environment, such as the presence of people, changes in volume, and location information.

[0599] "Detection means" refers to a collection of devices and equipment used to sense the physical conditions around the user.

[0600] "Evaluation means" refers to the process of analyzing data obtained from detection means and calculating and evaluating the privacy risks surrounding the user.

[0601] "Control means" refers to a mechanism for determining and implementing methods for providing confidential information based on risk assessments conducted by evaluation means.

[0602] "Confidential information" refers to information that requires user privacy protection, and includes, for example, personal information and financial data.

[0603] "Communication methods" refer to information transmission technologies and processes used to provide confirmations and notifications to users.

[0604] In embodiments of this invention, the aim is for the information processing system to provide sensitive information while protecting user privacy. The system mainly consists of terminals equipped with multiple sensor devices. Specifically, these include cameras for acquiring images, microphones for acquiring sound, and GPS modules for measuring location.

[0605] The device activates these sensors to collect information about the user's surroundings in real time. Video is analyzed by image processing algorithms to detect the presence of human faces and shapes. Audio data is processed by acoustic analysis software to detect speech and unusual volume changes. Location information is acquired via satellite communication and analyzed in conjunction with specific geographic information services.

[0606] The collected data is analyzed by a processing unit within the device, and the risk to user privacy is assessed. Based on this assessment, the method of providing the information is determined. If the risk is deemed high, a format is chosen that avoids voice output and displays the information on the device screen. This ensures that necessary information is provided appropriately while protecting the user's privacy.

[0607] As a concrete example, when a user receives a financial transaction alert, the device monitors the surrounding environment using the aforementioned sensors. If the system determines that there is a high privacy risk and that others are nearby, the financial information is displayed on the screen instead of being audible, and the user can manually check the details. By utilizing this system, users can receive information safely and appropriately according to their surrounding circumstances.

[0608] An example of a prompt for a generative AI model is, "Explain how the system monitors the user's surroundings and determines how to provide information." This makes it easier to understand how the system works.

[0609] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0610] Step 1:

[0611] The device first activates its sensor equipment and begins collecting environmental information. At this stage, the camera captures video, the microphone acquires audio data, and the GPS module acquires location information. The input data consists of video, audio, and location information, each of which is updated in real time. As output, each piece of data is stored in temporary storage. Specifically, the camera identifies people in the surroundings, the microphone records speech, and the GPS determines the current coordinates.

[0612] Step 2:

[0613] The terminal's processing unit analyzes the collected environmental data. In this analysis, image analysis software processes video data to recognize human faces and postures. Acoustic analysis software performs calculations to detect conversations and unusual volume changes from audio data. GPS data is compared with map information to determine if the current location is a public place. The input is the data set collected in step 1, and the output is risk assessment information regarding the user's surrounding environment.

[0614] Step 3:

[0615] Based on the evaluation results, the terminal's control unit determines how to provide information. If a high privacy risk is identified, it avoids audio presentation and switches to screen display. The input is the risk assessment information from step 2, and the output is the determination of the information provision method. Based on this information, the terminal takes specific actions to protect user privacy, such as displaying financial information only on the screen and suppressing audio output.

[0616] Step 4:

[0617] The terminal sends a message to the user requesting confirmation. This message includes confirmation that a predetermined information delivery method has been selected and instructions for confirmation. The input is the information delivery method determined in step 3, and the output is a confirmation message to the user. Specifically, it displays instructions on the screen such as "Information has been displayed. Please touch to confirm the contents."

[0618] (Application Example 1)

[0619] 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".

[0620] This invention relates to a technology that provides sensitive information while ensuring user privacy in public places and noisy environments. Conventional technologies are limited to simply conveying information by voice or displaying it on a screen, making it difficult to provide information while considering the surrounding environment. As a result, there is a risk of information being leaked to others, especially in public transportation and commercial facilities. This invention aims to solve these problems and realize a flexible means of providing information that is appropriate for the environment.

[0621] 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.

[0622] In this invention, the server includes means for a sensor device to acquire environmental information around the user; means for analyzing the environmental information from the device to determine the situation around the user; means for automatically switching the form of information provision from voice to visual display in public places; and means for transmitting information to the user via a bone conduction device according to the noise level of the environment. This makes it possible to provide information appropriate to the surrounding environment while protecting the user's privacy.

[0623] "User environment information" refers to data about the user's surroundings, including information such as video, audio, and location.

[0624] A "sensor device" is a device used to acquire various types of input data, and consists of devices such as video acquisition devices, audio acquisition devices, and location information acquisition devices.

[0625] A "processing device" is a device that analyzes acquired environmental information and performs information processing to determine the situation around the user.

[0626] A "control device" is a device that determines how to provide sensitive information based on the analysis results and controls the display format of that information.

[0627] A "public place" refers to a space that is accessible to the general public and is used by the general public, and includes public transportation and commercial facilities.

[0628] "Visual display" refers to a method of presenting information through human vision, and involves using display devices such as screens and smart glasses.

[0629] "Noise level" is an indicator that shows the intensity and noise level of sounds around the user, and is measured using a voice acquisition device.

[0630] A "bone conduction device" is a device that transmits sound vibrations to the inner ear through the bone, rather than sending sound directly to the ear, by utilizing vibrations.

[0631] "Sensitive information" is a term that refers to information relating to an individual's privacy or highly confidential information, and should be provided to users with particular care.

[0632] The present invention provides a system that flexibly switches the method of providing information according to the user's surrounding environment. Specific embodiments for carrying out the present invention are described below.

[0633] This system incorporates the following components into the user's device: The sensor device includes a video acquisition device, an audio acquisition device, a location information acquisition device, and an acoustic measurement function, collecting detailed information about the user's surroundings. This data is sent to a processing unit within the device and analyzed in real time. This allows the system to determine whether the user is currently in a public place or if the noise level is high.

[0634] The processing unit analyzes video data using the open-source library OpenCV to determine if a person is present in the video. Audio data is analyzed using general audio analysis software to measure the intensity of ambient noise. Location information is generated using a GPS module, and whether the location is a public place is confirmed through a third-party location service.

[0635] The control device decides whether to provide information via voice or visual display based on the analysis results from the processing unit. In cases of high noise levels, information can be transmitted to the user using a bone conduction device, allowing for efficient information delivery while protecting privacy.

[0636] As a concrete example, consider a scenario where a user receives a bank balance notification while on public transport. In noisy environments, the device would reduce the audio output, allowing the user to view the details by lightly touching the screen.

[0637] An example of a prompt message would be: "Design a real-time information delivery system that considers sensitive information delivery methods in public spaces while protecting privacy. Design a system that detects the number of people and the volume of voices and selects the optimal information display method."

[0638] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0639] Step 1:

[0640] The device acquires information about its surroundings using sensor devices. Inputs include video data from a camera, audio data from a microphone, and GPS data from a location information module. This data is collected and stored in internal memory.

[0641] Step 2:

[0642] The terminal's processing unit analyzes the acquired video data. Using the OpenCV library, it detects faces and the presence of people in the video. The output includes the number of detected people and their location information. This data is used for situational analysis within the terminal.

[0643] Step 3:

[0644] The terminal's processing unit analyzes the audio data. Using general audio analysis software, it measures the noise level from the obtained audio data. The input is audio data from the microphone, and the output is the noise level expressed in decibels (dB). This information is also used for situational analysis.

[0645] Step 4:

[0646] The device's processing unit analyzes location information. It sends GPS data to a third-party location service to determine if the location is a public place. The output is the location information and its attributes (whether it is public or not).

[0647] Step 5:

[0648] The terminal's control unit determines the information delivery method based on the analysis results from steps 2 to 4. The inputs are the number of people detected, the noise level, and location attributes. The output is a decision on whether to provide the information audibly or visually. For example, if the noise level is high in a public place, visual display is selected.

[0649] Step 6:

[0650] The user receives information according to the information delivery method selected by the user. Specifically, in noisy environments, the device transmits information near the ear using a bone conduction device, and if visual display is selected, the information is displayed on the device's screen. The user can check detailed information by operating the screen as needed.

[0651] 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.

[0652] This invention is a system that provides information flexibly based on the user's emotional state while ensuring user privacy. The system functions by integrating various sensor devices and an emotion engine on the user's terminal.

[0653] The device collects user facial expression data through a video acquisition device. This data is analyzed by an emotion engine to determine the user's emotional state (e.g., joy, sadness, anger, surprise, etc.). The tone and speed of speech obtained by the voice acquisition device are also used in emotion analysis, and changes in emotion can be read from the content of speech.

[0654] Furthermore, based on GPS data acquired by a location information acquisition device, the system determines whether the user's surroundings are a public space and assesses the privacy risks. This information, along with the results of the emotion engine's analysis, is used to select the most appropriate method of providing information to the user.

[0655] For example, if the device recognizes the user's agitated state and determines that it is in a public place, it can be controlled to display sensitive information on the screen instead of providing it verbally. Conversely, if the user is calm and at home, or if other conditions are met, verbal information provision may be permitted.

[0656] For example, when a user receives an important work-related message, the device attempts to read it aloud, but then detects that the user is in an office with other people present. Furthermore, if the emotion engine determines that the user's stress level is high, the device not only displays the message on the screen but also sends a notification message to encourage the user to check it themselves.

[0657] In this way, by using the analysis results of the emotion engine and environmental information, the device can autonomously adjust how it provides sensitive information, resulting in a more personalized user experience.

[0658] The following describes the processing flow.

[0659] Step 1:

[0660] The device uses a video acquisition device to capture the user's facial expressions via a camera. The video data is sent to an emotion engine, where a facial expression analysis algorithm identifies the user's emotional state.

[0661] Step 2:

[0662] The device uses a voice acquisition device to collect the user's speech. A voice analysis algorithm is applied to evaluate the emotional state from the tone, pitch, and speed of the speech. This data is then integrated into the emotion engine.

[0663] Step 3:

[0664] The device activates its location acquisition device and obtains GPS data. The acquired location information is processed to determine whether the user's current location is a public place. This location data is used to assess the user's privacy risks.

[0665] Step 4:

[0666] The device integrates the analysis results from the emotion engine with location information to comprehensively evaluate the user's emotional state and surrounding environment. Based on this evaluation, it determines the information provision behavior of the interface.

[0667] Step 5:

[0668] When a device attempts to convey sensitive information to a user, it considers the user's emotional state and environmental conditions to determine the appropriateness of audio output. If the user is stressed or in a public place, screen display is recommended instead of audio.

[0669] Step 6:

[0670] If the user makes a selection in response to a confirmation message sent, the device will adjust how information is provided according to the user's choice. For example, if voice output is refused, the device will provide sensitive information visually on the screen.

[0671] Step 7:

[0672] Once the information provision is complete, the device will restart the collection and analysis of environmental and emotional information in preparation for any new information that may arise, and repeat the process described above. This cycle ensures that privacy protection is continuously tailored to the user's situation.

[0673] (Example 2)

[0674] 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".

[0675] Conventional information delivery systems sometimes provide sensitive information in an inappropriate manner without adequately considering the user's emotional state or surrounding environment. This can result in violations of user privacy or unpleasant experiences. Therefore, there is a need for a system that can flexibly adjust information delivery methods according to the user's emotional state and environment.

[0676] 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.

[0677] In this invention, the server includes data analysis means for analyzing the user's emotional state, location information acquisition means for acquiring the user's environmental information and determining whether it is a public place, and control means for flexibly selecting the method of providing information based on the information acquired by the data analysis means and the location information acquisition means. This makes it possible to provide information appropriately and flexibly while ensuring the user's privacy.

[0678] "Data analysis means" refers to a function or system that analyzes the user's collected video and audio data to determine their emotional state.

[0679] "Location information acquisition means" refers to a function or system that acquires the user's geographical location and uses that location to determine whether or not it is a public place.

[0680] A "control means" is a function or system that optimally selects and controls the method of providing information based on the user's emotional state and environmental information.

[0681] "Emotional state" refers to the user's psychological and emotional state, and includes various emotional elements such as joy, sadness, anger, and surprise.

[0682] "Environmental information" refers to data that indicates the user's surroundings, including location information, ambient sound environment, and visual environment.

[0683] "Information provision method" refers to the specific means by which information is presented to the user, and includes various forms of expression such as audio, text, and video.

[0684] This system is designed to analyze the user's emotional state and environmental information, and adjust the method of information delivery based on that analysis. Its main components are data analysis means, location information acquisition means, and control means.

[0685] First, the device collects the user's video and audio data using its built-in camera and microphone. For data analysis, this data is received and analyzed via an emotion engine using dedicated software. This emotion engine uses machine learning algorithms to determine the user's emotional state in real time, including emotions such as joy, anger, sadness, and stress levels.

[0686] Next, the device uses location information acquisition methods such as a GPS module to confirm the user's geographical location. This allows the device to determine whether the user is in a public place and assess privacy risks. In addition to location information, it may also use information from Wi-Fi or Bluetooth beacons as a supplementary tool in some cases.

[0687] The server integrates emotion analysis results and location information, and uses control mechanisms to determine the optimal method of information delivery. For example, if the user is agitated and in a public environment, the information will be displayed on the screen, and audio information will be withheld. Conversely, if the user is calm and at home, audio information will be permitted.

[0688] As a concrete example, consider a case where a user receives an important work-related notification. In this case, if the device's emotion engine determines that the user is in a high-stress state and the location information acquisition means detect that the user is in the office, it will prioritize visual notifications to safely deliver the information.

[0689] A concrete example of a prompt message for a generative AI model would be, "Please suggest ways to optimize information delivery methods when the user is under high stress." This allows the model to provide appropriate feedback regarding the selection of information delivery methods.

[0690] In this way, the system can provide flexible information tailored to the user's emotions and environment, enabling a more personalized user experience.

[0691] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0692] Step 1:

[0693] The device uses a camera and microphone to collect video and audio data from the user. This captures the user's facial expressions and voice tone and speed. The input is raw data acquired from the camera and microphone, and the output is data prepared in a format suitable for sentiment analysis. Specifically, the camera captures the user's face at a constant frame rate, and the microphone records audio in sync.

[0694] Step 2:

[0695] The device analyzes data collected via the emotion engine. The emotion engine uses machine learning algorithms to determine the user's emotional state, such as joy, anger, sadness, or happiness, from their image and voice data. The input is the formalized data prepared in step 1, and the output is a numerical value or category indicating the user's emotional state. Specifically, the emotion engine analyzes the movement of facial muscles and the frequency characteristics of the voice to determine, for example, that "the user is in a state of joy."

[0696] Step 3:

[0697] The device obtains location information using a GPS module and Wi-Fi data. This allows it to determine whether the user's current location is a public space. The input is location coordinates provided by GPS and supplementary Wi-Fi data, while the output is category information such as environmental characteristics, such as "public space" or "private space." Specifically, the device checks its current latitude and longitude every second and compares that location with an existing database to determine the environmental category.

[0698] Step 4:

[0699] The server integrates the sentiment analysis results obtained in Step 2 with the environmental information obtained in Step 3 to determine the optimal method of information delivery. The inputs are the user's emotional state and environmental characteristics, while the output is a guideline for information delivery, such as "avoid voice notifications" or "prioritize visual presentations." Specifically, the server evaluates the reliability and importance of each piece of information and selects a strategy to convey the information without burdening the user.

[0700] Step 5:

[0701] The terminal provides information based on instructions from the server. Specifically, it provides information via voice using a speech synthesizer or displays a notification on the screen. The input is the guideline for information provision from the server, and the output is the specific information conveyed to the user. For example, the terminal will display "You have a new message" on the screen and, if appropriate, explain the content via voice.

[0702] This allows the system to provide personalized information tailored to the user's emotions and environment.

[0703] (Application Example 2)

[0704] 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".

[0705] Providing personalized information to individual customers in physical stores is difficult with traditional methods, as they only offer uniform guidance, limiting the potential for improving the customer experience. Furthermore, it's challenging to respond flexibly to customers' emotional states and surrounding environments. Therefore, there is a need for technology that enables service delivery optimized for each customer's emotions and circumstances.

[0706] 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.

[0707] In this invention, the server includes detection means for acquiring environmental information around the user, processing means for analyzing the environmental information from the device to determine the situation around the user, control means for controlling the method of providing sensitive information based on the situation, emotion analysis means for analyzing the user's emotional state and optimizing information based thereon, and location-dependent means for optimizing the information provided using the user's location information. This makes it possible to provide optimal information based on the customer's emotional state and location information.

[0708] A "user" is an individual who utilizes this system and is a recipient of the information provided.

[0709] "Environmental information" refers to data about the user's surroundings, including sound, images, and location information.

[0710] A "detection device" is a device used to acquire environmental information and is equipped with various sensors.

[0711] A "processing mechanism" is a system that analyzes acquired environmental information to determine the user's situation and emotional state.

[0712] A "control device" is a device that has the function of adjusting the method of providing information based on the user's situation and emotions.

[0713] "Emotional analysis methods" are technologies that analyze a user's facial expressions and tone of voice to determine their emotional state.

[0714] "Location-dependent means" refers to a function that provides optimal information tailored to the user's location based on that information.

[0715] The system for implementing this invention acquires environmental information around the user, analyzes the user's emotional state, and provides information based on that analysis. The system mainly includes the following components.

[0716] First, the device uses sensors such as cameras and microphones to capture the user's facial expressions. This collects both acoustic and image data. Next, the processing unit uses software such as OpenCV and TensorFlow to analyze this data and determine the user's emotional state.

[0717] The server uses Bluetooth beacon technology to obtain the user's location information and understand their surroundings. This allows the server to determine the environment in which the user is located. Based on the acquired data, the server selects the most appropriate method for providing information to the user, and then delivers that information.

[0718] A concrete example would be an application used in a physical store. If a customer shows interest in a product, the server displays detailed information about the product on their smartphone based on data acquired from the camera and microphone. Furthermore, if it is determined that the information the customer needs is not for a public place, the information is also provided via audio.

[0719] The following are examples of prompt statements for the generative AI model:

[0720] Input data: Image data (customer's facial expression), location information

[0721] Task: Design a way to provide customers with additional information about products they are interested in.

[0722] This allows the server to provide information optimized for the user, enabling a more personalized service.

[0723] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0724] Step 1:

[0725] The device acquires data from the user's face and voice. The camera and microphone are activated, capturing image and audio data. The input is the user's facial expression image and voice, and this raw data is taken into the system as output.

[0726] Step 2:

[0727] The system processes the image and audio data acquired by the device. At this stage, face recognition and emotion analysis are performed using OpenCV and TensorFlow. The input is the image and audio data collected in step 1, and the output is the analysis result indicating the user's emotional state. Specifically, feature points are extracted from the user's face, and emotional states such as joy, anger, sadness, and happiness are estimated using a pre-trained model.

[0728] Step 3:

[0729] The server determines the user's current location based on location information obtained from a Bluetooth beacon. The input is location data transmitted by the beacon, and the output is the user's location within the store. Specifically, the user's position is calculated using triangulation based on the received signal strength.

[0730] Step 4:

[0731] The server determines the information to provide to the user based on their emotional state and location. The input consists of the emotional analysis results obtained from steps 2 and 3, and the location information. The output is the selection of the most suitable information for the user. The generating AI model uses prompts to select the most suitable information and extracts information related to specific products within the store as the information to be provided.

[0732] Step 5:

[0733] The server selects information and sends it to the terminal, where it is displayed on the user's smartphone. The input is the information provided by the server, and the output is the information displayed on the smartphone screen. Specifically, information is sent to the terminal via a REST API and displayed in an appropriate format according to the user's browsing status.

[0734] 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.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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."

[0743] 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.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] 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.

[0755] The following is further disclosed regarding the embodiments described above.

[0756] (Claim 1)

[0757] A device including a sensor device for acquiring environmental information around the user,

[0758] A processing unit that analyzes environmental information from the aforementioned device to determine the situation around the user,

[0759] Based on the above circumstances, a control device controls the method of providing sensitive information,

[0760] A system that includes this.

[0761] (Claim 2)

[0762] The system according to claim 1, characterized in that the sensor device includes a video acquisition device, an audio acquisition device, and a location information acquisition device.

[0763] (Claim 3)

[0764] The system according to claim 1, characterized in that the control device includes means for requesting user confirmation before speaking sensitive information aloud.

[0765] "Example 1"

[0766] (Claim 1)

[0767] A detection means for collecting physical information about the user's surroundings,

[0768] An evaluation means that analyzes the physical conditions from the detection means to evaluate the risks around the user,

[0769] A control means for determining the method of providing confidential information based on the aforementioned risk assessment,

[0770] A means of communication to send a confirmation message to the user,

[0771] A system that includes this.

[0772] (Claim 2)

[0773] The system according to claim 1, characterized in that the detection means includes an image acquisition device, an acoustic acquisition device, and a location information acquisition device.

[0774] (Claim 3)

[0775] The system according to claim 1, characterized in that the control means includes means for requesting user action when providing confidential information by non-voice means.

[0776] "Application Example 1"

[0777] (Claim 1)

[0778] A device including a sensor device for acquiring environmental information around the user,

[0779] A processing unit that analyzes environmental information from the aforementioned device to determine the situation around the user,

[0780] Based on the above circumstances, a control device controls the method of providing sensitive information,

[0781] A means of automatically switching the form of information provision from audio to visual display in public places,

[0782] A means of transmitting information to the user via a bone conduction device according to the noise level of the environment,

[0783] A system that includes this.

[0784] (Claim 2)

[0785] The system according to claim 1, characterized in that the sensor device includes, in addition to an image acquisition device, an audio acquisition device, and a location information acquisition device, an acoustic measurement function for measuring ambient noise.

[0786] (Claim 3)

[0787] The system according to claim 1, characterized in that the control device includes means for controlling the display means to select an appropriate method according to the surrounding circumstances when providing sensitive information.

[0788] "Example 2 of combining an emotion engine"

[0789] (Claim 1)

[0790] A data analysis method for analyzing the emotional state of users,

[0791] A means for acquiring location information to obtain user environment information and determine whether it is a public place,

[0792] Based on the information obtained by the data analysis means and location information acquisition means, a control means for flexibly selecting the method of providing information,

[0793] A system that includes this.

[0794] (Claim 2)

[0795] The system according to claim 1, wherein the data analysis means includes a video acquisition function and a voice acquisition function, and is characterized in that it determines the user's emotions from their facial expressions and voice.

[0796] (Claim 3)

[0797] The system according to claim 1, characterized in that the control means includes means for visually providing sensitive information when it is determined that the user is in an excited state and in a public environment.

[0798] "Application example 2 when combining with an emotional engine"

[0799] (Claim 1)

[0800] A device including a detection device for acquiring environmental information around the user,

[0801] A processing means that analyzes environmental information from the aforementioned device to determine the conditions around the user,

[0802] Based on the above circumstances, a control means for controlling the method of providing sensitive information,

[0803] A sentiment analysis means that analyzes the user's emotional state and optimizes information based on that analysis,

[0804] A location-dependent means that optimizes the information provided using the user's location information,

[0805] A system that includes this.

[0806] (Claim 2)

[0807] The system according to claim 1, characterized in that the detection device includes an image acquisition device, an acoustic acquisition device, and a position information acquisition device.

[0808] (Claim 3)

[0809] The system according to claim 1, characterized in that the control means includes means for requesting user confirmation before transmitting sensitive information acoustically. [Explanation of symbols]

[0810] 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 device including a sensor device for acquiring environmental information around the user, A processing unit that analyzes environmental information from the aforementioned device to determine the situation around the user, Based on the above circumstances, a control device controls the method of providing sensitive information, A system that includes this.

2. The system according to claim 1, characterized in that the sensor device includes an image acquisition device, an audio acquisition device, and a location information acquisition device.

3. The system according to claim 1, characterized in that the control device includes means for requesting user confirmation before speaking sensitive information aloud.

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