system

Abstract

システムを提供する。【解決手段】ユーザーの周囲環境を検知するためのデータを取得する手段と、環境音を取得する手段と、位置情報を取得する手段と、前記データ、環境音、及び位置情報を解析し、周囲に他者が存在するかを判断する手段と、センシティブ情報の提供方法を、前記判断に基づいて変更する手段と、前記センシティブ情報の提供前に、ユーザーに確認を求める手段と、メッセージ内容を暗号化して提供する手段と、を含むシステム。

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When an AI agent provides sensitive information, there is a risk that the information may leak to third parties around. Specifically, when a voice assistant or the like speaks information related to privacy, there is a possibility that the information may be transmitted to others who do not want to hear it. Furthermore, when a user is in a public place, the risk of information leakage is even higher. Such a risk is an issue that should be solved in order to protect the privacy of users and enable them to use the technology with confidence.

Means for Solving the Problems

[0005] To solve this problem, the present invention provides a system equipped with means for acquiring image data, acoustic data, and location data to detect the user's surrounding environment. By analyzing this data and using means to determine whether other people are present in the vicinity, the system selects a method for providing sensitive information. Furthermore, by implementing means to request confirmation from the user before providing sensitive information, the risk of privacy leakage can be reduced. In addition, this system can flexibly change how information is handled by providing information audibly or visually. By using a face detection algorithm and an acoustic analysis algorithm, high-precision environmental analysis is performed, enabling the provision of appropriate information.

[0006] "Image data" refers to information that visually records the user's surroundings using cameras and sensors.

[0007] "Acoustic data" refers to audio-related information recorded using microphones or other means to capture ambient sounds.

[0008] "Location data" refers to information used to determine a user's current location using technologies such as GPS.

[0009] "Analysis" refers to the process of analyzing collected data and processing the information.

[0010] "Sensitive information" refers to information that relates to users' personal information and privacy and requires careful handling.

[0011] "Method of provision" refers to the means or format chosen when presenting collected information to users.

[0012] A "face detection algorithm" is a computational method for detecting and identifying human faces from image data.

[0013] An "acoustic analysis algorithm" is a computational method for analyzing acoustic data and extracting characteristics of sound.

[0014] "Means of requesting confirmation" refers to an interface used to confirm the user's consent to provide information. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

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

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

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

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

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

[0023] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0036] This invention is a system that appropriately adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, the terminal monitors the user's surrounding environment using a camera and microphone. Face detection is performed from video data acquired through the front camera to determine if other people are present in the vicinity. In addition, ambient sounds are collected as acoustic data, and voice analysis algorithms are used to detect the voices of others and background noise. Furthermore, GPS information is acquired to confirm whether the user's current location is a public place.

[0037] The server aggregates and analyzes this data transmitted from the terminal. Based on the analysis results, it assesses the risks associated with providing sensitive information. If the risk is deemed high, the server adjusts the system so that sensitive information is not provided via voice, but instead displayed visually as text on the terminal's screen.

[0038] On the other hand, users can choose how information is provided in response to prompts from the device. For example, if there is a possibility of other people being nearby, the device will ask the user, "Is it okay to display this information on the screen?" If the user grants permission, the system will display and provide the sensitive information on the screen.

[0039] As a concrete example, suppose a user checks their personal financial information on a terminal in a public cafe. In this case, the terminal analyzes the surrounding environment and detects the presence of other customers. The server receives this information and recognizes that providing the information verbally is risky, so the terminal suggests displaying the information on the screen. By allowing the user to view the information on the screen, the financial information is provided visually, avoiding the risk of leakage to others. This process ensures safe and reliable information provision.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The device activates its front camera and captures video data of the user's surroundings. It also uses its microphone to record ambient sound data.

[0043] Step 2:

[0044] The device uses GPS functionality to obtain the user's current location and record the location data.

[0045] Step 3:

[0046] The device transmits the acquired video data, audio data, and location data to the server.

[0047] Step 4:

[0048] The server analyzes the received video data and applies a face detection algorithm to determine if there are other people around the user.

[0049] Step 5:

[0050] The server uses an acoustic analysis algorithm to analyze acoustic data and detect whether there are other people's voices or noise in the surrounding area.

[0051] Step 6:

[0052] The server analyzes GPS data to determine whether the user's current location is a public place.

[0053] Step 7:

[0054] Based on these analysis results, the server assesses the risks of providing sensitive information via voice.

[0055] Step 8:

[0056] The server sends the evaluation results to the terminal and provides instructions on how to provide sensitive information.

[0057] Step 9:

[0058] The terminal, following instructions from the server, displays a confirmation message to the user, allowing them to choose whether to receive information via voice or on the screen.

[0059] Step 10:

[0060] Users will select or authorize the method of providing information in response to the confirmation message.

[0061] Step 11:

[0062] The device prevents information leaks by providing sensitive information in an appropriate format according to the user's choice.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In modern society, as opportunities to access sensitive information using mobile devices increase, the risk of information being leaked to those around the user is also rising. In this context, a system that can dynamically adjust the information delivery method according to the surrounding environment is desirable to ensure that users receive sensitive information safely and with their privacy protected.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for acquiring image data to detect the user's surrounding environment, means for acquiring acoustic data, and means for acquiring location data. This makes it possible to individually assess the risk of leakage of sensitive information and provide information by switching between audio and visual formats.

[0068] A "user" refers to a person who uses a system to receive information.

[0069] "Surrounding environment" refers to the physical space surrounding the user, as well as other people, sounds, and other elements present within that space.

[0070] "Image data" refers to a collection of visual information acquired through video input devices such as cameras.

[0071] "Audio data" refers to information about sound acquired through audio input devices such as microphones.

[0072] "Location data" refers to geographical location information obtained using GPS or other location measurement technologies.

[0073] "Sensitive information" refers to information where an individual's privacy and confidentiality should be given priority.

[0074] A "face detection algorithm" refers to a computational method for identifying and recognizing a person's face from image data.

[0075] A "speech analysis algorithm" refers to a computational method that analyzes acoustic data to detect specific sounds or patterns.

[0076] A "noise-canceling algorithm" refers to a technique that removes unwanted sounds from audio data and extracts important audio.

[0077] "Visual display" refers to showing information in text and images through displays or screens.

[0078] "Control means" refers to a mechanism for managing each element of a system and generating commands.

[0079] "Audio delivery" refers to a method of conveying information to users through audio.

[0080] This invention is a system that dynamically adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, it is configured as follows:

[0081] First, the device uses a front camera and microphone to monitor the user's surroundings. The camera captures images of the user's front and acquires video data. Face detection algorithms are executed on this video data using image processing libraries such as OpenCV and TENSORFLOW® to determine if there are other people nearby. Simultaneously, acoustic data is collected from the microphone, and voice analysis algorithms recognize other people's voices and environmental noise. GPS functionality is also active to acquire the user's location data, helping to determine if the user is in a public place.

[0082] At this time, the server aggregates and analyzes the environmental data transmitted from the terminal. The server evaluates whether it is necessary to provide information that respects the user's privacy based on the received face detection results, voice analysis results, and GPS information. If the evaluation determines that providing information via voice poses a risk, the server sends an instruction to provide sensitive information visually.

[0083] Furthermore, users can choose how information is presented based on prompts from their device. For example, a confirmation prompt such as "Do you want to display the information on the screen?" may appear, and the user can select an option to visualize the information.

[0084] As a concrete example, suppose a user wants to access their personal financial information using their smartphone in a public cafe. In this case, the device uses its front camera and microphone to analyze the surrounding environment, and the server uses this information to determine that providing the information via voice is risky. The device then prompts the user, "Do you want to display this information on the screen?" If the user grants permission, the information is displayed visually on the screen, reducing the risk of the information being leaked to others.

[0085] The system functions effectively by inputting prompts such as, "The user is viewing sensitive information in a public place. Please suggest a safe way to provide this information in this situation," into the AI ​​model that generates the prompts.

[0086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0087] Step 1:

[0088] The device activates its front camera to capture images of the user's surroundings and acquire video data. The input is real-time video obtained through the camera, and the output is image data used for analysis. Specifically, the device acquires a high-resolution video stream and extracts the necessary frames.

[0089] Step 2:

[0090] The device uses a microphone to record ambient sounds and acquires acoustic data. The input is raw audio data captured by the microphone, and the output is acoustic data for speech analysis. Specifically, the device samples the audio at regular intervals and performs digital signal processing.

[0091] Step 3:

[0092] The device uses GPS functionality to obtain its current location data. The input is satellite data from the GPS chip, and the output is geographic coordinates indicating the user's location. The device periodically receives signals to calculate highly accurate location information.

[0093] Step 4:

[0094] The device applies a face detection algorithm to the acquired image data. The input is the image data obtained in step 1, and the output is information regarding the presence or absence of faces detected in the image. Specifically, the device uses libraries such as OpenCV to extract facial features through pattern matching.

[0095] Step 5:

[0096] The device executes a speech analysis algorithm on acoustic data to detect other people's voices. The input is the acoustic data obtained in step 2, and the output is the characteristics of the detected voices. The device performs frequency analysis using FFT (Fast Fourier Transform) to identify specific voice patterns.

[0097] Step 6:

[0098] The server aggregates environmental information sent from terminals and performs a risk assessment. The input consists of data obtained in steps 4 and 5, and step 3, and the output is a guideline for selecting information provision methods. The server uses a machine learning model to determine whether information provision involves risk.

[0099] Step 7:

[0100] The terminal receives instructions from the server and prompts the user for information. The input is the instructions received from the server in step 6, and the output is the selection prompt displayed to the user. The terminal uses a user interface to display clear and intuitive choices.

[0101] Step 8:

[0102] The user selects a method for providing information and grants permission in response to prompts on the device. The input is the prompt obtained in step 7, and the output is the result of the user's selection. The user makes selections using taps or voice commands.

[0103] Step 9:

[0104] The device provides sensitive information verbally or visually based on the user's selection. The input is the user's selection in step 8, and the output is the information provided on the screen or verbally. Specifically, the device displays information on the screen or reads text aloud.

[0105] (Application Example 1)

[0106] 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."

[0107] In recent years, the leakage of personal information has become a serious problem, and there is always a risk of information being leaked to others, especially when handling sensitive information in public places. This issue is a widespread concern for users of portable information processing devices such as smartphones. Furthermore, there is a need to further enhance the security of sensitive information management and provide users with means to communicate with peace of mind.

[0108] 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.

[0109] In this invention, the server includes means for acquiring data to detect the user's surrounding environment, means for acquiring ambient sounds, and means for acquiring location information. This makes it possible to flexibly adjust the method of providing sensitive information according to the environment and to enhance the protection of information through encryption technology.

[0110] A "user" is an individual who uses the system or provides information about their surrounding environment.

[0111] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, and is the subject of information acquisition and analysis.

[0112] "Sensitive information" refers to information that, if disclosed to others, could potentially threaten a user's privacy or safety.

[0113] "Means of acquiring data" refers to the devices and technologies used to gather necessary information from the user's surrounding environment.

[0114] "Environmental sounds" refer to sounds and voices that occur around the user, and are elements that allow the presence of others to be confirmed through voice analysis.

[0115] "Location information" refers to geographical data obtained to identify where a user is currently located.

[0116] "Encryption technology" is a technical method that transforms data to maintain its confidentiality and protect it from unauthorized access.

[0117] "Facial recognition technology" is a technology that detects and recognizes specific faces by analyzing camera video data.

[0118] "Voice analysis technology" is a technique that extracts characteristics of voices by analyzing voice data, and uses this to distinguish between other people's voices and background noise.

[0119] To implement this invention, the system operates through a dedicated application installed on the user's portable information processing device. The hardware used is a smartphone, with the camera, microphone, and GPS being its primary data acquisition devices. The software utilizes OpenCV for facial recognition, Google® Cloud Speech-to-Text for speech analysis, and the Google Maps API for location management.

[0120] The server receives and comprehensively analyzes video, audio, and location data continuously acquired from the terminal. From the video data, facial recognition technology is used to detect the presence of others, and audio analysis technology is used to identify human voices and noises from ambient sounds. Based on location data, it determines whether the user is in a public place. Based on this data, the server performs a risk assessment regarding how to provide sensitive information.

[0121] As an example, consider a scenario where a user tries to check a message on a train. In this case, the server detects other passengers using facial recognition and decides to refrain from reading the message aloud. It can then propose to the user that the message be displayed on the screen and provided as an encrypted message. Specifically, the terminal would display a prompt to the user asking, "Is it alright to provide the information visually?"

[0122] When using a generative AI model, an example prompt might be: "Monitor the surrounding environment and suggest a safe way to provide information. If it is a public place and other people are present, please select text display." This allows users to receive information while maintaining their privacy, even in public places.

[0123] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0124] Step 1:

[0125] The device uses a camera and microphone to acquire data about the user's surrounding environment. Specifically, the camera collects video data, and the microphone records ambient sounds. In this case, the input is the surrounding environment itself, and the output is video data and audio data.

[0126] Step 2:

[0127] The device uses location services to obtain the user's current location. The input is location information obtained from GPS, and the output is specific geographical location data. This prepares the device to determine whether the user is in a public place.

[0128] Step 3:

[0129] The terminal sends the acquired data to the server. Video data, audio data, and location data are sent to the server as input. The expected output is the data analysis results from the server.

[0130] Step 4:

[0131] The server begins data analysis, using facial recognition technology for video data and speech analysis technology for audio data. Facial information is extracted from the video data, and characteristics of speech and noise are identified from the audio data. The output provides a determination of whether or not other people are present in the surrounding area.

[0132] Step 5:

[0133] The server analyzes the location data to determine whether the user is in a public place. The input to this process is the geographical location data obtained earlier, and the output is the result of the determination of whether or not it is a public place.

[0134] Step 6:

[0135] The server determines how to provide sensitive information based on the analysis results and performs a risk assessment. It receives all data analysis results as input and generates proposed adjustments regarding information provision methods as output.

[0136] Step 7:

[0137] Based on the server's decision, the terminal will present the user with a choice of whether to provide information visually or audibly. The input for this process is the server's suggested options, and the output is a confirmation prompt displayed to the user. Specifically, the terminal screen will display a prompt message such as, "Is it alright to provide the information visually?"

[0138] Step 8:

[0139] The user selects the information delivery method in response to prompts on the device. User actions are the input, and the output is the decision of the selected information delivery method. Sensitive information is provided to the user according to the selected method.

[0140] In scenarios utilizing the generative AI model, the prompt "Monitor the surrounding environment and suggest a safe method of providing information. If it is a public place and other people are present, select text display." is used as input to ensure safe and appropriate information provision.

[0141] 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.

[0142] This invention is a system that optimizes the delivery of sensitive information by taking into account the user's environment and emotions. This system begins with the terminal collecting environmental data using a camera, microphone, and GPS sensor. The terminal uses this data to determine the user's surrounding environment and emotional state.

[0143] First, the device uses image data from the camera to apply a face detection algorithm to determine if there are other people nearby. It also uses an acoustic analysis algorithm based on acoustic data from the microphone to assess the surrounding environment. Furthermore, it analyzes GPS information acquired by the device to evaluate whether the user is in a public place.

[0144] The server comprehensively analyzes this data transmitted from the terminal. It also uses an emotion engine to recognize the user's emotional state from the collected image and sound data. The emotion engine analyzes the user's facial expressions and voice tone to determine whether the user is calm or tense.

[0145] Based on these analysis results, the server determines how to provide sensitive information. If the user is in a public place with other people around and the server determines that the user's emotional state is tense, sensitive information will be provided via screen display. If the server determines that the user is calm and their privacy is maintained, sensitive information can be provided via audio.

[0146] For example, when a user is in a confined office, this system allows for verbal communication. On the other hand, if a user is on a train and feels like they are being watched by others, the server prioritizes providing information on a screen, thereby reducing the risk of the user's information being overheard by others. In this way, the present invention realizes information provision that balances user safety and privacy.

[0147] The following describes the processing flow.

[0148] Step 1:

[0149] The device activates its front camera and acquires image data to visually record the user's surroundings. It also uses a microphone to collect ambient acoustic data.

[0150] Step 2:

[0151] The device uses GPS functionality to obtain location data and determine the user's location. This data is used as a factor in determining whether or not the user is in a public place.

[0152] Step 3:

[0153] The device transmits acquired image data, audio data, and location data to the server. This transmitted data is used for analysis.

[0154] Step 4:

[0155] The server applies a face detection algorithm to the received image data to determine if other people are present in the vicinity. This algorithm confirms the presence of people in the surrounding area.

[0156] Step 5:

[0157] The server uses an acoustic analysis algorithm to analyze acoustic data, detect ambient noise levels and human voices, and use these as clues to determine the presence of other people.

[0158] Step 6:

[0159] The server analyzes GPS data to assess whether the user is in a public place or in a private environment. This assessment helps determine the appropriateness of providing the information.

[0160] Step 7:

[0161] The server activates an emotion engine, which analyzes image and sound data to recognize the user's emotional state. The emotion engine determines whether the user is tense or calm based on their facial expressions and tone of voice.

[0162] Step 8:

[0163] The server integrates the analysis results described above and determines how to provide sensitive information. If it determines that the risk is high, it selects a method to display the information on the screen.

[0164] Step 9:

[0165] Based on instructions from the server, the terminal displays a confirmation message to the user and allows the user to choose a secure method of providing information.

[0166] Step 10:

[0167] Users can choose to receive information via audio or visual means in response to presentations from their device.

[0168] Step 11:

[0169] The device will provide sensitive information in an appropriate format according to the user's choice, ensuring the user's privacy and safety.

[0170] (Example 2)

[0171] 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".

[0172] In modern times, the problem of personal information being unintentionally overheard by third parties in public is a serious issue from the perspective of protecting individual privacy. In particular, when providing sensitive information via mobile devices, the risk of information leakage increases if the information is provided in a uniform manner without considering the surrounding circumstances or the individual's emotional state. This invention aims to solve such problems and provide sensitive information in a way that protects the user's safety and privacy.

[0173] 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.

[0174] In this invention, the server includes means for acquiring photographic data to detect the user's surrounding conditions, means for acquiring audio data, and means for acquiring location information. This enables the provision of information in a safer and more privacy-conscious manner, taking into account both surrounding conditions and emotional state.

[0175] A "user" is the entity that operates this system and receives information from it.

[0176] "Surrounding conditions" refers to the state of the environment in which the user is currently located, and includes sound, visual information, location information, etc.

[0177] "Shooting data" refers to image information acquired from a camera or other shooting device.

[0178] "Audio data" refers to information about ambient sounds obtained through audio acquisition devices such as microphones.

[0179] "Location information" refers to data on the user's current location, identified using location detection devices such as GPS.

[0180] "Emotion analysis function" refers to a set of algorithms that analyze captured image data and audio data in order to recognize the user's emotional state.

[0181] "Sensitive information" refers to important and sensitive information about an individual, including information that the individual does not want to be known to third parties.

[0182] "Means of adjustment" refers to a process or function that allows a system to change how it provides information depending on the situation.

[0183] This invention is a system that optimizes the provision of sensitive information according to the user's environment and emotional state. Users can acquire different data via their terminal and receive information in a safe and privacy-conscious manner. The terminal is equipped with a camera, microphone, and GPS sensor, and data is collected using this hardware.

[0184] The device uses a camera to acquire real-time image data and applies a face detection algorithm (e.g., the OpenCV library). This allows it to determine if other people are present in the vicinity. It also uses a microphone to acquire audio data and analyzes the surrounding sound environment using acoustic analysis algorithms (e.g., noise cancellation and speech recognition technologies). Furthermore, a GPS sensor acquires location information and uses a map application to determine whether the user is in a public place.

[0185] The server uses image and audio data transmitted from the terminal to perform sentiment analysis and recognize the user's emotional state. This sentiment analysis utilizes facial expression recognition technology (e.g., OpenPose and Dlib) and voice tone analysis. After the server determines the user's state and environment, it adjusts how sensitive information is provided.

[0186] For example, if a user is in a confined office, the server can safely provide sensitive information via voice. On the other hand, if the user is on a train and feels the gaze of others, the server chooses to provide the information via screen display. In this way, the present invention realizes context-appropriate information provision while protecting the user's privacy.

[0187] An example of a prompt to a generative AI model might be, "If the user is in a public place, such as a train station, but it is quiet and calm, please tell me how to provide sensitive information in a way that respects privacy." This prompt is used to specifically show how the system evaluates the situation and adjusts how information is provided.

[0188] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0189] Step 1:

[0190] The device activates its camera, microphone, and GPS sensor, and begins data collection. As input, the camera acquires real-time image data, the microphone collects ambient audio data, and the GPS sensor obtains location information. As output, this data is prepared for subsequent analysis.

[0191] Step 2:

[0192] The device applies a face detection algorithm to the collected image data. The image data is processed using tools such as the OpenCV library as input, and face presence information is obtained as output. Through this process, the device determines whether other people are present in its vicinity.

[0193] Step 3:

[0194] The device applies an acoustic analysis algorithm to the collected audio data. As input, the audio data is processed using noise cancellation and speech recognition technology, and as output, information about the surrounding sound environment is obtained. Through this analysis, the device determines whether the user's surroundings are quiet or noisy.

[0195] Step 4:

[0196] The device analyzes the acquired GPS data. As input, it compares the location data with a map application, and as output, it obtains a result evaluating whether the user is in a public place.

[0197] Step 5:

[0198] The terminal sends the results of steps 2-4 to the server. It combines face detection results, acoustic analysis results, and location determination results as input, and sends data as output to prepare for analysis on the server side.

[0199] Step 6:

[0200] The server activates its emotion analysis function based on the received data. It uses face detection information and audio environment information as input to perform facial recognition and tone analysis. This analysis then outputs the user's emotional state (e.g., calm, tense).

[0201] Step 7:

[0202] The server determines the optimal method for providing sensitive information based on acquired environmental information and emotional state. As input, it comprehensively assesses the surrounding environment and the user's emotions, and as output, it sends a command to the terminal to provide the information in audio or visual format.

[0203] Step 8:

[0204] The terminal provides sensitive information in a predetermined manner according to instructions from the server. It receives instructions from the server as input and communicates the information to the user as output, either through screen display or audio via the speaker.

[0205] (Application Example 2)

[0206] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0207] It is necessary to ensure that users can receive information appropriately and safely, according to their environment and emotional state. In particular, when users are in a dangerous situation, it is essential to provide prompt and effective warnings. However, existing technologies have not adequately analyzed the user's surrounding environment and emotional state in detail and dynamically adjusted the information delivery method based on that analysis. As a result, there have been problems in which the privacy and safety of users when receiving information are not guaranteed.

[0208] 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.

[0209] In this invention, the server includes means for acquiring image information to detect the user's surrounding environment, means for acquiring acoustic information, means for acquiring location information, and means for analyzing the user's emotional state and providing emergency notifications in an appropriate manner. This enables the user to receive information customized according to their environment and emotions. Furthermore, if the user is in a dangerous situation, an automatic warning can be issued to encourage a quick response.

[0210] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, which are detected by cameras and microphones.

[0211] "Image information" refers to visual data acquired using a camera, and is used as material for analyzing the user and their surroundings.

[0212] "Acoustic information" refers to audio data acquired through a microphone, which is used to analyze ambient sounds and voices.

[0213] "Location information" refers to data obtained through GPS and other location acquisition technologies, and is used to determine the user's physical location.

[0214] "Emotional state" refers to the user's psychological and emotional condition, and is determined through analysis of facial expressions and voice tone.

[0215] An "emergency notification" refers to important information or warnings that need to be conveyed to the user quickly, and is delivered using voice, vibration, and visual effects.

[0216] A "warning" is information intended to alert users to danger or require caution, and is automatically issued depending on the situation.

[0217] The system that realizes this invention is designed to optimally provide information based on the user's surrounding environment and emotional state. The system mainly consists of a terminal held by the user and a server that performs data analysis.

[0218] The device uses a camera, microphone, and GPS sensor to monitor the user's surroundings in real time. Specifically, it uses the camera to acquire image information and detects people and objects in the surroundings through facial recognition technology (e.g., the OpenCV library). Acoustic information acquired by the microphone is processed by a speech analysis algorithm (e.g., the TensorFlow library) to analyze ambient sounds. The GPS sensor acquires the user's location information, determining their current position.

[0219] This collected data is sent from the device to the server, where it is analyzed and evaluated. The server uses a generative AI model to identify the user's emotional state from their facial expressions and tone of voice. For example, if the user appears anxious, the server will choose a means to quickly issue an emergency notification.

[0220] Based on the analysis results, the server determines how to provide information. For example, if it determines that the user is in a public place with other people present or is in a dangerous situation, it automatically sends a warning to the device and notifies the user in an appropriate way, such as by voice or vibration. If it determines that the user is relaxed and their privacy is protected, it provides sensitive information by voice.

[0221] For example, when a user is traveling through an area where they feel uneasy at night, the device's camera and microphone detect surrounding sounds and people. If the server analyzes the data and determines that an abnormal situation is occurring, it immediately issues a warning. This helps the user sense danger and move to a safe location.

[0222] An example of a prompt for a generating AI model is, "Explain how to issue an appropriate alert when a user is in a situation that causes anxiety."

[0223] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0224] Step 1:

[0225] The device collects data about its surroundings. Specifically, it acquires image information with a camera, collects acoustic information with a microphone, and obtains location information with a GPS sensor. This raw data is used as input data for the next processing step.

[0226] Step 2:

[0227] The device uses the acquired image information to apply a face recognition algorithm and detect whether other people are present in the vicinity. This algorithm converts the image data into data in the form of a face detection result. The output is the result of determining whether or not other people are present in the vicinity.

[0228] Step 3:

[0229] The device inputs acoustic information into an acoustic analysis algorithm to analyze the characteristics of the surrounding sound. Through this data processing, the acoustic data is converted into analytical information such as sound patterns, volume, and sound source direction. The output is the meaning of the sound and the results of abnormal sound detection.

[0230] Step 4:

[0231] The device analyzes GPS information to evaluate the user's current location and movement patterns. This converts location data into information indicating whether the user is in a public place or a safe location. The output is a location evaluation related to safety and public accessibility.

[0232] Step 5:

[0233] The server integrates face detection results, acoustic analysis information, and location evaluation information transmitted from the terminal, and uses a generative AI model to recognize the user's emotional state. The input is the integrated analysis data, and the output is the estimated result of the user's emotional state (e.g., calm, tense, anxious).

[0234] Step 6:

[0235] The server comprehensively evaluates these results and determines the means of providing sensitive information. Specifically, if it is determined that the user is in a stressful state in a public place, the information will be quietly provided via a screen display. The output is the selection of the information provision method.

[0236] Step 7:

[0237] The server automatically issues an emergency warning via voice and vibration through the terminal if it determines that the user's situation is dangerous. The action taken is to sound a warning and vibrate the terminal. The output is the execution of the emergency notification.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] [Second Embodiment]

[0242] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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).

[0248] 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.

[0249] 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.

[0250] 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.

[0251] 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.

[0252] 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.

[0253] 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".

[0254] This invention is a system that appropriately adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, the terminal monitors the user's surrounding environment using a camera and microphone. Face detection is performed from video data acquired through the front camera to determine if other people are present in the vicinity. In addition, ambient sounds are collected as acoustic data, and voice analysis algorithms are used to detect the voices of others and background noise. Furthermore, GPS information is acquired to confirm whether the user's current location is a public place.

[0255] The server aggregates and analyzes this data transmitted from the terminal. Based on the analysis results, it assesses the risks associated with providing sensitive information. If the risk is deemed high, the server adjusts the system so that sensitive information is not provided via voice, but instead displayed visually as text on the terminal's screen.

[0256] On the other hand, users can choose how information is provided in response to prompts from the device. For example, if there is a possibility of other people being nearby, the device will ask the user, "Is it okay to display this information on the screen?" If the user grants permission, the system will display and provide the sensitive information on the screen.

[0257] As a concrete example, suppose a user checks their personal financial information on a terminal in a public cafe. In this case, the terminal analyzes the surrounding environment and detects the presence of other customers. The server receives this information and recognizes that providing the information verbally is risky, so the terminal suggests displaying the information on the screen. By allowing the user to view the information on the screen, the financial information is provided visually, avoiding the risk of leakage to others. This process ensures safe and reliable information provision.

[0258] The following describes the processing flow.

[0259] Step 1:

[0260] The device activates its front camera and captures video data of the user's surroundings. It also uses its microphone to record ambient sound data.

[0261] Step 2:

[0262] The device uses GPS functionality to obtain the user's current location and record the location data.

[0263] Step 3:

[0264] The device transmits the acquired video data, audio data, and location data to the server.

[0265] Step 4:

[0266] The server analyzes the received video data and applies a face detection algorithm to determine if there are other people around the user.

[0267] Step 5:

[0268] The server uses an acoustic analysis algorithm to analyze acoustic data and detect whether there are other people's voices or noise in the surrounding area.

[0269] Step 6:

[0270] The server analyzes GPS data to determine whether the user's current location is a public place.

[0271] Step 7:

[0272] Based on these analysis results, the server assesses the risks of providing sensitive information via voice.

[0273] Step 8:

[0274] The server sends the evaluation results to the terminal and provides instructions on how to provide sensitive information.

[0275] Step 9:

[0276] The terminal, following instructions from the server, displays a confirmation message to the user, allowing them to choose whether to receive information via voice or on the screen.

[0277] Step 10:

[0278] Users will select or authorize the method of providing information in response to the confirmation message.

[0279] Step 11:

[0280] The terminal prevents information leakage by providing sensitive information in an appropriate format according to the user's selection.

[0281] (Example 1)

[0282] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0283] In modern society, as the opportunity to access sensitive information using mobile devices increases, the risk of information leakage to people around is rising. In such a situation, in order for users to receive sensitive information in a safe and privacy-protected state, a system that can dynamically adjust the information-providing method according to the surrounding environment is desired.

[0284] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0285] In this invention, the server includes means for acquiring image data for detecting the user's surrounding environment, means for acquiring acoustic data, and means for acquiring position data. Thereby, it becomes possible to individually evaluate the risk of leakage of sensitive information and provide information by switching it audibly or visually.

[0286] "User" refers to a person who receives information using the system.

[0287] "Surrounding environment" refers to the physical space surrounding the user and elements such as other people and sounds existing in that space.

[0288] "Image data" refers to a set of visual information acquired through a video input device such as a camera.

[0289] "Acoustic data" refers to information related to sounds acquired through a voice input device such as a microphone.

[0290] "Location data" refers to geographical location information obtained using GPS or other location measurement technologies.

[0291] "Sensitive information" refers to information where an individual's privacy and confidentiality should be given priority.

[0292] A "face detection algorithm" refers to a computational method for identifying and recognizing a person's face from image data.

[0293] A "speech analysis algorithm" refers to a computational method that analyzes acoustic data to detect specific sounds or patterns.

[0294] A "noise-canceling algorithm" refers to a technique that removes unwanted sounds from audio data and extracts important audio.

[0295] "Visual display" refers to showing information in text and images through displays or screens.

[0296] "Control means" refers to a mechanism for managing each element of a system and generating commands.

[0297] "Audio delivery" refers to a method of conveying information to users through audio.

[0298] This invention is a system that dynamically adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, it is configured as follows:

[0299] First, the device uses a front camera and microphone to monitor the user's surroundings. The camera captures images of the user's front and acquires video data. Face detection algorithms are then executed on this video data using image processing libraries such as OpenCV or TensorFlow to determine if other people are nearby. Simultaneously, acoustic data is collected from the microphone, and voice analysis algorithms are used to recognize other people's voices and environmental noise. GPS functionality is also active to acquire the user's location data, helping to determine if the user is in a public place.

[0300] At this time, the server aggregates and analyzes the environmental data transmitted from the terminal. The server evaluates whether it is necessary to provide information that respects the user's privacy based on the received face detection results, voice analysis results, and GPS information. If the evaluation determines that providing information via voice poses a risk, the server sends an instruction to provide sensitive information visually.

[0301] Furthermore, users can choose how information is presented based on prompts from their device. For example, a confirmation prompt such as "Do you want to display the information on the screen?" may appear, and the user can select an option to visualize the information.

[0302] As a concrete example, suppose a user wants to access their personal financial information using their smartphone in a public cafe. In this case, the device uses its front camera and microphone to analyze the surrounding environment, and the server uses this information to determine that providing the information via voice is risky. The device then prompts the user, "Do you want to display this information on the screen?" If the user grants permission, the information is displayed visually on the screen, reducing the risk of the information being leaked to others.

[0303] The system functions effectively by inputting prompts such as, "The user is viewing sensitive information in a public place. Please suggest a safe way to provide this information in this situation," into the AI ​​model that generates the prompts.

[0304] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0305] Step 1:

[0306] The terminal activates the front camera to capture the surroundings of the user and obtains video data. The input is real-time video obtained through the camera, and the output is image data used for analysis. As a specific operation, the terminal acquires a video stream at a high resolution and extracts the necessary frames.

[0307] Step 2:

[0308] The terminal uses the microphone to record the surrounding sounds and obtains acoustic data. The input is raw audio data captured by the microphone, and the output is acoustic data for voice analysis. Specifically, the terminal samples the voice at regular intervals and performs digital signal processing.

[0309] Step 3:

[0310] The terminal uses the GPS function to obtain the current location data. The input is satellite data from the GPS chip, and the output is geographical coordinates indicating the user's location. The terminal receives signals periodically and calculates highly accurate location information.

[0311] Step 4:

[0312] The terminal applies a face detection algorithm to the acquired image data. The input is the image data obtained in Step 1, and the output is information regarding the presence or absence of a face detected in the image. Specifically, the terminal uses libraries such as the OpenCV library to extract face features through pattern matching.

[0313] Step 5:

[0314] The device executes a speech analysis algorithm on acoustic data to detect other people's voices. The input is the acoustic data obtained in step 2, and the output is the characteristics of the detected voices. The device performs frequency analysis using FFT (Fast Fourier Transform) to identify specific voice patterns.

[0315] Step 6:

[0316] The server aggregates environmental information sent from terminals and performs a risk assessment. The input consists of data obtained in steps 4 and 5, and step 3, and the output is a guideline for selecting information provision methods. The server uses a machine learning model to determine whether information provision involves risk.

[0317] Step 7:

[0318] The terminal receives instructions from the server and prompts the user for information. The input is the instructions received from the server in step 6, and the output is the selection prompt displayed to the user. The terminal uses a user interface to display clear and intuitive choices.

[0319] Step 8:

[0320] The user selects a method for providing information and grants permission in response to prompts on the device. The input is the prompt obtained in step 7, and the output is the result of the user's selection. The user makes selections using taps or voice commands.

[0321] Step 9:

[0322] The device provides sensitive information verbally or visually based on the user's selection. The input is the user's selection in step 8, and the output is the information provided on the screen or verbally. Specifically, the device displays information on the screen or reads text aloud.

[0323] (Application Example 1)

[0324] 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."

[0325] In recent years, the leakage of personal information has become a serious problem, and there is always a risk of information being leaked to others, especially when handling sensitive information in public places. This issue is a widespread concern for users of portable information processing devices such as smartphones. Furthermore, there is a need to further enhance the security of sensitive information management and provide users with means to communicate with peace of mind.

[0326] 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.

[0327] In this invention, the server includes means for acquiring data to detect the user's surrounding environment, means for acquiring ambient sounds, and means for acquiring location information. This makes it possible to flexibly adjust the method of providing sensitive information according to the environment and to enhance the protection of information through encryption technology.

[0328] A "user" is an individual who uses the system or provides information about their surrounding environment.

[0329] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, and is the subject of information acquisition and analysis.

[0330] "Sensitive information" refers to information that, if disclosed to others, could potentially threaten a user's privacy or safety.

[0331] "Means of acquiring data" refers to the devices and technologies used to gather necessary information from the user's surrounding environment.

[0332] "Environmental sounds" refer to sounds and voices that occur around the user, and are elements that allow the presence of others to be confirmed through voice analysis.

[0333] "Location information" refers to geographical data obtained to identify where a user is currently located.

[0334] "Encryption technology" is a technical method that transforms data to maintain its confidentiality and protect it from unauthorized access.

[0335] "Facial recognition technology" is a technology that detects and recognizes specific faces by analyzing camera video data.

[0336] "Voice analysis technology" is a technique that extracts characteristics of voices by analyzing voice data, and uses this to distinguish between other people's voices and background noise.

[0337] To implement this invention, the system operates through a dedicated application installed on the user's portable information processing device. The hardware used is a smartphone, with the camera, microphone, and GPS being its primary data acquisition devices. The software utilizes OpenCV for facial recognition, Google Cloud Speech-to-Text for speech analysis, and the Google Maps API for location management.

[0338] The server receives and comprehensively analyzes video, audio, and location data continuously acquired from the terminal. From the video data, facial recognition technology is used to detect the presence of others, and audio analysis technology is used to identify human voices and noises from ambient sounds. Based on location data, it determines whether the user is in a public place. Based on this data, the server performs a risk assessment regarding how to provide sensitive information.

[0339] As an example, consider a scenario where a user tries to check a message on a train. In this case, the server detects other passengers using facial recognition and decides to refrain from reading the message aloud. It can then propose to the user that the message be displayed on the screen and provided as an encrypted message. Specifically, the terminal would display a prompt to the user asking, "Is it alright to provide the information visually?"

[0340] When using a generative AI model, an example prompt might be: "Monitor the surrounding environment and suggest a safe way to provide information. If it is a public place and other people are present, please select text display." This allows users to receive information while maintaining their privacy, even in public places.

[0341] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0342] Step 1:

[0343] The device uses a camera and microphone to acquire data about the user's surrounding environment. Specifically, the camera collects video data, and the microphone records ambient sounds. In this case, the input is the surrounding environment itself, and the output is video data and audio data.

[0344] Step 2:

[0345] The device uses location services to obtain the user's current location. The input is location information obtained from GPS, and the output is specific geographical location data. This prepares the device to determine whether the user is in a public place.

[0346] Step 3:

[0347] The terminal sends the acquired data to the server. Video data, audio data, and location data are sent to the server as input. The expected output is the data analysis results from the server.

[0348] Step 4:

[0349] The server begins data analysis, using facial recognition technology for video data and speech analysis technology for audio data. Facial information is extracted from the video data, and characteristics of speech and noise are identified from the audio data. The output provides a determination of whether or not other people are present in the surrounding area.

[0350] Step 5:

[0351] The server analyzes the location data to determine whether the user is in a public place. The input to this process is the geographical location data obtained earlier, and the output is the result of the determination of whether or not it is a public place.

[0352] Step 6:

[0353] The server determines how to provide sensitive information based on the analysis results and performs a risk assessment. It receives all data analysis results as input and generates proposed adjustments regarding information provision methods as output.

[0354] Step 7:

[0355] Based on the server's decision, the terminal will present the user with a choice of whether to provide information visually or audibly. The input for this process is the server's suggested options, and the output is a confirmation prompt displayed to the user. Specifically, the terminal screen will display a prompt message such as, "Is it alright to provide the information visually?"

[0356] Step 8:

[0357] The user selects the information delivery method in response to prompts on the device. User actions are the input, and the output is the decision of the selected information delivery method. Sensitive information is provided to the user according to the selected method.

[0358] In scenarios utilizing the generative AI model, the prompt "Monitor the surrounding environment and suggest a safe method of providing information. If it is a public place and other people are present, select text display." is used as input to ensure safe and appropriate information provision.

[0359] 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.

[0360] This invention is a system that optimizes the delivery of sensitive information by taking into account the user's environment and emotions. This system begins with the terminal collecting environmental data using a camera, microphone, and GPS sensor. The terminal uses this data to determine the user's surrounding environment and emotional state.

[0361] First, the device uses image data from the camera to apply a face detection algorithm to determine if there are other people nearby. It also uses an acoustic analysis algorithm based on acoustic data from the microphone to assess the surrounding environment. Furthermore, it analyzes GPS information acquired by the device to evaluate whether the user is in a public place.

[0362] The server comprehensively analyzes this data transmitted from the terminal. It also uses an emotion engine to recognize the user's emotional state from the collected image and sound data. The emotion engine analyzes the user's facial expressions and voice tone to determine whether the user is calm or tense.

[0363] Based on these analysis results, the server determines how to provide sensitive information. If the user is in a public place with other people around and the server determines that the user's emotional state is tense, sensitive information will be provided via screen display. If the server determines that the user is calm and their privacy is maintained, sensitive information can be provided via audio.

[0364] For example, when a user is in a confined office, this system allows for verbal communication. On the other hand, if a user is on a train and feels like they are being watched by others, the server prioritizes providing information on a screen, thereby reducing the risk of the user's information being overheard by others. In this way, the present invention realizes information provision that balances user safety and privacy.

[0365] The following describes the processing flow.

[0366] Step 1:

[0367] The device activates its front camera and acquires image data to visually record the user's surroundings. It also uses a microphone to collect ambient acoustic data.

[0368] Step 2:

[0369] The device uses GPS functionality to obtain location data and determine the user's location. This data is used as a factor in determining whether or not the user is in a public place.

[0370] Step 3:

[0371] The device transmits acquired image data, audio data, and location data to the server. This transmitted data is used for analysis.

[0372] Step 4:

[0373] The server applies a face detection algorithm to the received image data to determine if other people are present in the vicinity. This algorithm confirms the presence of people in the surrounding area.

[0374] Step 5:

[0375] The server uses an acoustic analysis algorithm to analyze acoustic data, detect ambient noise levels and human voices, and use these as clues to determine the presence of other people.

[0376] Step 6:

[0377] The server analyzes GPS data to assess whether the user is in a public place or in a private environment. This assessment helps determine the appropriateness of providing the information.

[0378] Step 7:

[0379] The server activates an emotion engine, which analyzes image and sound data to recognize the user's emotional state. The emotion engine determines whether the user is tense or calm based on their facial expressions and tone of voice.

[0380] Step 8:

[0381] The server integrates the analysis results described above and determines how to provide sensitive information. If it determines that the risk is high, it selects a method to display the information on the screen.

[0382] Step 9:

[0383] Based on instructions from the server, the terminal displays a confirmation message to the user and allows the user to choose a secure method of providing information.

[0384] Step 10:

[0385] Users can choose to receive information via audio or visual means in response to presentations from their device.

[0386] Step 11:

[0387] The device will provide sensitive information in an appropriate format according to the user's choice, ensuring the user's privacy and safety.

[0388] (Example 2)

[0389] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0390] In modern times, the problem of personal information being unintentionally overheard by third parties in public is a serious issue from the perspective of protecting individual privacy. In particular, when providing sensitive information via mobile devices, the risk of information leakage increases if the information is provided in a uniform manner without considering the surrounding circumstances or the individual's emotional state. This invention aims to solve such problems and provide sensitive information in a way that protects the user's safety and privacy.

[0391] 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.

[0392] In this invention, the server includes means for acquiring photographic data to detect the user's surrounding conditions, means for acquiring audio data, and means for acquiring location information. This enables the provision of information in a safer and more privacy-conscious manner, taking into account both surrounding conditions and emotional state.

[0393] A "user" is the entity that operates this system and receives information from it.

[0394] "Surrounding conditions" refers to the state of the environment in which the user is currently located, and includes sound, visual information, location information, etc.

[0395] "Shooting data" refers to image information acquired from a camera or other shooting device.

[0396] "Audio data" refers to information about ambient sounds obtained through audio acquisition devices such as microphones.

[0397] "Location information" refers to data on the user's current location, identified using location detection devices such as GPS.

[0398] "Emotion analysis function" refers to a set of algorithms that analyze captured image data and audio data in order to recognize the user's emotional state.

[0399] "Sensitive information" refers to important and sensitive information about an individual, including information that the individual does not want to be known to third parties.

[0400] "Means of adjustment" refers to a process or function that allows a system to change how it provides information depending on the situation.

[0401] This invention is a system that optimizes the provision of sensitive information according to the user's environment and emotional state. Users can acquire different data via their terminal and receive information in a safe and privacy-conscious manner. The terminal is equipped with a camera, microphone, and GPS sensor, and data is collected using this hardware.

[0402] The device uses a camera to acquire real-time image data and applies a face detection algorithm (e.g., the OpenCV library). This allows it to determine if other people are present in the vicinity. It also uses a microphone to acquire audio data and analyzes the surrounding sound environment using acoustic analysis algorithms (e.g., noise cancellation and speech recognition technologies). Furthermore, a GPS sensor acquires location information and uses a map application to determine whether the user is in a public place.

[0403] The server uses image and audio data transmitted from the terminal to perform sentiment analysis and recognize the user's emotional state. This sentiment analysis utilizes facial expression recognition technology (e.g., OpenPose and Dlib) and voice tone analysis. After the server determines the user's state and environment, it adjusts how sensitive information is provided.

[0404] For example, if a user is in a confined office, the server can safely provide sensitive information via voice. On the other hand, if the user is on a train and feels the gaze of others, the server chooses to provide the information via screen display. In this way, the present invention realizes context-appropriate information provision while protecting the user's privacy.

[0405] An example of a prompt to a generative AI model might be, "If the user is in a public place, such as a train station, but it is quiet and calm, please tell me how to provide sensitive information in a way that respects privacy." This prompt is used to specifically show how the system evaluates the situation and adjusts how information is provided.

[0406] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0407] Step 1:

[0408] The device activates its camera, microphone, and GPS sensor, and begins data collection. As input, the camera acquires real-time image data, the microphone collects ambient audio data, and the GPS sensor obtains location information. As output, this data is prepared for subsequent analysis.

[0409] Step 2:

[0410] The device applies a face detection algorithm to the collected image data. The image data is processed using tools such as the OpenCV library as input, and face presence information is obtained as output. Through this process, the device determines whether other people are present in its vicinity.

[0411] Step 3:

[0412] The device applies an acoustic analysis algorithm to the collected audio data. As input, the audio data is processed using noise cancellation and speech recognition technology, and as output, information about the surrounding sound environment is obtained. Through this analysis, the device determines whether the user's surroundings are quiet or noisy.

[0413] Step 4:

[0414] The device analyzes the acquired GPS data. As input, it compares the location data with a map application, and as output, it obtains a result evaluating whether the user is in a public place.

[0415] Step 5:

[0416] The terminal sends the results of steps 2-4 to the server. It combines face detection results, acoustic analysis results, and location determination results as input, and sends data as output to prepare for analysis on the server side.

[0417] Step 6:

[0418] The server activates its emotion analysis function based on the received data. It uses face detection information and audio environment information as input to perform facial recognition and tone analysis. This analysis then outputs the user's emotional state (e.g., calm, tense).

[0419] Step 7:

[0420] The server determines the optimal method for providing sensitive information based on acquired environmental information and emotional state. As input, it comprehensively assesses the surrounding environment and the user's emotions, and as output, it sends a command to the terminal to provide the information in audio or visual format.

[0421] Step 8:

[0422] The terminal provides sensitive information in a predetermined manner according to instructions from the server. It receives instructions from the server as input and communicates the information to the user as output, either through screen display or audio via the speaker.

[0423] (Application Example 2)

[0424] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0425] It is necessary to ensure that users can receive information appropriately and safely, according to their environment and emotional state. In particular, when users are in a dangerous situation, it is essential to provide prompt and effective warnings. However, existing technologies have not adequately analyzed the user's surrounding environment and emotional state in detail and dynamically adjusted the information delivery method based on that analysis. As a result, there have been problems in which the privacy and safety of users when receiving information are not guaranteed.

[0426] 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.

[0427] In this invention, the server includes means for acquiring image information to detect the user's surrounding environment, means for acquiring acoustic information, means for acquiring location information, and means for analyzing the user's emotional state and providing emergency notifications in an appropriate manner. This enables the user to receive information customized according to their environment and emotions. Furthermore, if the user is in a dangerous situation, an automatic warning can be issued to encourage a quick response.

[0428] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, which are detected by cameras and microphones.

[0429] "Image information" refers to visual data acquired using a camera, and is used as material for analyzing the user and their surroundings.

[0430] "Acoustic information" refers to audio data acquired through a microphone, which is used to analyze ambient sounds and voices.

[0431] "Location information" refers to data obtained through GPS and other location acquisition technologies, and is used to determine the user's physical location.

[0432] "Emotional state" refers to the user's psychological and emotional condition, and is determined through analysis of facial expressions and voice tone.

[0433] An "emergency notification" refers to important information or warnings that need to be conveyed to the user quickly, and is delivered using voice, vibration, and visual effects.

[0434] A "warning" is information intended to alert users to danger or require caution, and is automatically issued depending on the situation.

[0435] The system that realizes this invention is designed to optimally provide information based on the user's surrounding environment and emotional state. The system mainly consists of a terminal held by the user and a server that performs data analysis.

[0436] The device uses a camera, microphone, and GPS sensor to monitor the user's surroundings in real time. Specifically, it uses the camera to acquire image information and detects people and objects in the surroundings through facial recognition technology (e.g., the OpenCV library). Acoustic information acquired by the microphone is processed by a speech analysis algorithm (e.g., the TensorFlow library) to analyze ambient sounds. The GPS sensor acquires the user's location information, determining their current position.

[0437] This collected data is sent from the device to the server, where it is analyzed and evaluated. The server uses a generative AI model to identify the user's emotional state from their facial expressions and tone of voice. For example, if the user appears anxious, the server will choose a means to quickly issue an emergency notification.

[0438] Based on the analysis results, the server determines how to provide information. For example, if it determines that the user is in a public place with other people present or is in a dangerous situation, it automatically sends a warning to the device and notifies the user in an appropriate way, such as by voice or vibration. If it determines that the user is relaxed and their privacy is protected, it provides sensitive information by voice.

[0439] For example, when a user is traveling through an area where they feel uneasy at night, the device's camera and microphone detect surrounding sounds and people. If the server analyzes the data and determines that an abnormal situation is occurring, it immediately issues a warning. This helps the user sense danger and move to a safe location.

[0440] An example of a prompt for a generating AI model is, "Explain how to issue an appropriate alert when a user is in a situation that causes anxiety."

[0441] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0442] Step 1:

[0443] The device collects data about its surroundings. Specifically, it acquires image information with a camera, collects acoustic information with a microphone, and obtains location information with a GPS sensor. This raw data is used as input data for the next processing step.

[0444] Step 2:

[0445] The device uses the acquired image information to apply a face recognition algorithm and detect whether other people are present in the vicinity. This algorithm converts the image data into data in the form of a face detection result. The output is the result of determining whether or not other people are present in the vicinity.

[0446] Step 3:

[0447] The device inputs acoustic information into an acoustic analysis algorithm to analyze the characteristics of the surrounding sound. Through this data processing, the acoustic data is converted into analytical information such as sound patterns, volume, and sound source direction. The output is the meaning of the sound and the results of abnormal sound detection.

[0448] Step 4:

[0449] The device analyzes GPS information to evaluate the user's current location and movement patterns. This converts location data into information indicating whether the user is in a public place or a safe location. The output is a location evaluation related to safety and public accessibility.

[0450] Step 5:

[0451] The server integrates face detection results, acoustic analysis information, and location evaluation information transmitted from the terminal, and uses a generative AI model to recognize the user's emotional state. The input is the integrated analysis data, and the output is the estimated result of the user's emotional state (e.g., calm, tense, anxious).

[0452] Step 6:

[0453] The server comprehensively evaluates these results and determines the means of providing sensitive information. Specifically, if it is determined that the user is in a stressful state in a public place, the information will be quietly provided via a screen display. The output is the selection of the information provision method.

[0454] Step 7:

[0455] The server automatically issues an emergency warning via voice and vibration through the terminal if it determines that the user's situation is dangerous. The action taken is to sound a warning and vibrate the terminal. The output is the execution of the emergency notification.

[0456] 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.

[0457] 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.

[0458] 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.

[0459] [Third Embodiment]

[0460] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0461] 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.

[0462] 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).

[0463] 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.

[0464] 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.

[0465] 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).

[0466] 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.

[0467] 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.

[0468] 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.

[0469] 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.

[0470] 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.

[0471] 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".

[0472] This invention is a system that appropriately adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, the terminal monitors the user's surrounding environment using a camera and microphone. Face detection is performed from video data acquired through the front camera to determine if other people are present in the vicinity. In addition, ambient sounds are collected as acoustic data, and voice analysis algorithms are used to detect the voices of others and background noise. Furthermore, GPS information is acquired to confirm whether the user's current location is a public place.

[0473] The server aggregates and analyzes this data transmitted from the terminal. Based on the analysis results, it assesses the risks associated with providing sensitive information. If the risk is deemed high, the server adjusts the system so that sensitive information is not provided via voice, but instead displayed visually as text on the terminal's screen.

[0474] On the other hand, users can choose how information is provided in response to prompts from the device. For example, if there is a possibility of other people being nearby, the device will ask the user, "Is it okay to display this information on the screen?" If the user grants permission, the system will display and provide the sensitive information on the screen.

[0475] As a concrete example, suppose a user checks their personal financial information on a terminal in a public cafe. In this case, the terminal analyzes the surrounding environment and detects the presence of other customers. The server receives this information and recognizes that providing the information verbally is risky, so the terminal suggests displaying the information on the screen. By allowing the user to view the information on the screen, the financial information is provided visually, avoiding the risk of leakage to others. This process ensures safe and reliable information provision.

[0476] The following describes the processing flow.

[0477] Step 1:

[0478] The device activates its front camera and captures video data of the user's surroundings. It also uses its microphone to record ambient sound data.

[0479] Step 2:

[0480] The device uses GPS functionality to obtain the user's current location and record the location data.

[0481] Step 3:

[0482] The device transmits the acquired video data, audio data, and location data to the server.

[0483] Step 4:

[0484] The server analyzes the received video data and applies a face detection algorithm to determine if there are other people around the user.

[0485] Step 5:

[0486] The server uses an acoustic analysis algorithm to analyze acoustic data and detect whether there are other people's voices or noise in the surrounding area.

[0487] Step 6:

[0488] The server analyzes GPS data to determine whether the user's current location is a public place.

[0489] Step 7:

[0490] Based on these analysis results, the server assesses the risks of providing sensitive information via voice.

[0491] Step 8:

[0492] The server sends the evaluation results to the terminal and provides instructions on how to provide sensitive information.

[0493] Step 9:

[0494] The terminal, following instructions from the server, displays a confirmation message to the user, allowing them to choose whether to receive information via voice or on the screen.

[0495] Step 10:

[0496] Users will select or authorize the method of providing information in response to the confirmation message.

[0497] Step 11:

[0498] The device prevents information leaks by providing sensitive information in an appropriate format according to the user's choice.

[0499] (Example 1)

[0500] 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."

[0501] In modern society, as opportunities to access sensitive information using mobile devices increase, the risk of information being leaked to those around the user is also rising. In this context, a system that can dynamically adjust the information delivery method according to the surrounding environment is desirable to ensure that users receive sensitive information safely and with their privacy protected.

[0502] 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.

[0503] In this invention, the server includes means for acquiring image data to detect the user's surrounding environment, means for acquiring acoustic data, and means for acquiring location data. This makes it possible to individually assess the risk of leakage of sensitive information and provide information by switching between audio and visual formats.

[0504] A "user" refers to a person who uses a system to receive information.

[0505] "Surrounding environment" refers to the physical space surrounding the user, as well as other people, sounds, and other elements present within that space.

[0506] "Image data" refers to a collection of visual information acquired through video input devices such as cameras.

[0507] "Audio data" refers to information about sound acquired through audio input devices such as microphones.

[0508] "Location data" refers to geographical location information obtained using GPS or other location measurement technologies.

[0509] "Sensitive information" refers to information where an individual's privacy and confidentiality should be given priority.

[0510] A "face detection algorithm" refers to a computational method for identifying and recognizing a person's face from image data.

[0511] A "speech analysis algorithm" refers to a computational method that analyzes acoustic data to detect specific sounds or patterns.

[0512] A "noise-canceling algorithm" refers to a technique that removes unwanted sounds from audio data and extracts important audio.

[0513] "Visual display" refers to showing information in text and images through displays or screens.

[0514] "Control means" refers to a mechanism for managing each element of a system and generating commands.

[0515] "Audio delivery" refers to a method of conveying information to users through audio.

[0516] This invention is a system that dynamically adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, it is configured as follows:

[0517] First, the device uses a front camera and microphone to monitor the user's surroundings. The camera captures images of the user's front and acquires video data. Face detection algorithms are then executed on this video data using image processing libraries such as OpenCV or TensorFlow to determine if other people are nearby. Simultaneously, acoustic data is collected from the microphone, and voice analysis algorithms are used to recognize other people's voices and environmental noise. GPS functionality is also active to acquire the user's location data, helping to determine if the user is in a public place.

[0518] At this time, the server aggregates and analyzes the environmental data transmitted from the terminal. The server evaluates whether it is necessary to provide information that respects the user's privacy based on the received face detection results, voice analysis results, and GPS information. If the evaluation determines that providing information via voice poses a risk, the server sends an instruction to provide sensitive information visually.

[0519] Furthermore, users can choose how information is presented based on prompts from their device. For example, a confirmation prompt such as "Do you want to display the information on the screen?" may appear, and the user can select an option to visualize the information.

[0520] As a concrete example, suppose a user wants to access their personal financial information using their smartphone in a public cafe. In this case, the device uses its front camera and microphone to analyze the surrounding environment, and the server uses this information to determine that providing the information via voice is risky. The device then prompts the user, "Do you want to display this information on the screen?" If the user grants permission, the information is displayed visually on the screen, reducing the risk of the information being leaked to others.

[0521] The system functions effectively by inputting prompts such as, "The user is viewing sensitive information in a public place. Please suggest a safe way to provide this information in this situation," into the AI ​​model that generates the prompts.

[0522] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0523] Step 1:

[0524] The device activates its front camera to capture images of the user's surroundings and acquire video data. The input is real-time video obtained through the camera, and the output is image data used for analysis. Specifically, the device acquires a high-resolution video stream and extracts the necessary frames.

[0525] Step 2:

[0526] The device uses a microphone to record ambient sounds and acquires acoustic data. The input is raw audio data captured by the microphone, and the output is acoustic data for speech analysis. Specifically, the device samples the audio at regular intervals and performs digital signal processing.

[0527] Step 3:

[0528] The device uses GPS functionality to obtain its current location data. The input is satellite data from the GPS chip, and the output is geographic coordinates indicating the user's location. The device periodically receives signals to calculate highly accurate location information.

[0529] Step 4:

[0530] The device applies a face detection algorithm to the acquired image data. The input is the image data obtained in step 1, and the output is information regarding the presence or absence of faces detected in the image. Specifically, the device uses libraries such as OpenCV to extract facial features through pattern matching.

[0531] Step 5:

[0532] The device executes a speech analysis algorithm on acoustic data to detect other people's voices. The input is the acoustic data obtained in step 2, and the output is the characteristics of the detected voices. The device performs frequency analysis using FFT (Fast Fourier Transform) to identify specific voice patterns.

[0533] Step 6:

[0534] The server aggregates environmental information sent from terminals and performs a risk assessment. The input consists of data obtained in steps 4 and 5, and step 3, and the output is a guideline for selecting information provision methods. The server uses a machine learning model to determine whether information provision involves risk.

[0535] Step 7:

[0536] The terminal receives instructions from the server and prompts the user for information. The input is the instructions received from the server in step 6, and the output is the selection prompt displayed to the user. The terminal uses a user interface to display clear and intuitive choices.

[0537] Step 8:

[0538] The user selects a method for providing information and grants permission in response to prompts on the device. The input is the prompt obtained in step 7, and the output is the result of the user's selection. The user makes selections using taps or voice commands.

[0539] Step 9:

[0540] The device provides sensitive information verbally or visually based on the user's selection. The input is the user's selection in step 8, and the output is the information provided on the screen or verbally. Specifically, the device displays information on the screen or reads text aloud.

[0541] (Application Example 1)

[0542] 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."

[0543] In recent years, the leakage of personal information has become a serious problem, and there is always a risk of information being leaked to others, especially when handling sensitive information in public places. This issue is a widespread concern for users of portable information processing devices such as smartphones. Furthermore, there is a need to further enhance the security of sensitive information management and provide users with means to communicate with peace of mind.

[0544] 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.

[0545] In this invention, the server includes means for acquiring data to detect the user's surrounding environment, means for acquiring ambient sounds, and means for acquiring location information. This makes it possible to flexibly adjust the method of providing sensitive information according to the environment and to enhance the protection of information through encryption technology.

[0546] A "user" is an individual who uses the system or provides information about their surrounding environment.

[0547] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, and is the subject of information acquisition and analysis.

[0548] "Sensitive information" refers to information that, if disclosed to others, could potentially threaten a user's privacy or safety.

[0549] "Means of acquiring data" refers to the devices and technologies used to gather necessary information from the user's surrounding environment.

[0550] "Environmental sounds" refer to sounds and voices that occur around the user, and are elements that allow the presence of others to be confirmed through voice analysis.

[0551] "Location information" refers to geographical data obtained to identify where a user is currently located.

[0552] "Encryption technology" is a technical method that transforms data to maintain its confidentiality and protect it from unauthorized access.

[0553] "Facial recognition technology" is a technology that detects and recognizes specific faces by analyzing camera video data.

[0554] "Voice analysis technology" is a technique that extracts characteristics of voices by analyzing voice data, and uses this to distinguish between other people's voices and background noise.

[0555] To implement this invention, the system operates through a dedicated application installed on the user's portable information processing device. The hardware used is a smartphone, with the camera, microphone, and GPS being its primary data acquisition devices. The software utilizes OpenCV for facial recognition, Google Cloud Speech-to-Text for speech analysis, and the Google Maps API for location management.

[0556] The server receives and comprehensively analyzes video, audio, and location data continuously acquired from the terminal. From the video data, facial recognition technology is used to detect the presence of others, and audio analysis technology is used to identify human voices and noises from ambient sounds. Based on location data, it determines whether the user is in a public place. Based on this data, the server performs a risk assessment regarding how to provide sensitive information.

[0557] As an example, consider a scenario where a user tries to check a message on a train. In this case, the server detects other passengers using facial recognition and decides to refrain from reading the message aloud. It can then propose to the user that the message be displayed on the screen and provided as an encrypted message. Specifically, the terminal would display a prompt to the user asking, "Is it alright to provide the information visually?"

[0558] When using a generative AI model, an example prompt might be: "Monitor the surrounding environment and suggest a safe way to provide information. If it is a public place and other people are present, please select text display." This allows users to receive information while maintaining their privacy, even in public places.

[0559] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0560] Step 1:

[0561] The device uses a camera and microphone to acquire data about the user's surrounding environment. Specifically, the camera collects video data, and the microphone records ambient sounds. In this case, the input is the surrounding environment itself, and the output is video data and audio data.

[0562] Step 2:

[0563] The device uses location services to obtain the user's current location. The input is location information obtained from GPS, and the output is specific geographical location data. This prepares the device to determine whether the user is in a public place.

[0564] Step 3:

[0565] The terminal sends the acquired data to the server. Video data, audio data, and location data are sent to the server as input. The expected output is the data analysis results from the server.

[0566] Step 4:

[0567] The server begins data analysis, using facial recognition technology for video data and speech analysis technology for audio data. Facial information is extracted from the video data, and characteristics of speech and noise are identified from the audio data. The output provides a determination of whether or not other people are present in the surrounding area.

[0568] Step 5:

[0569] The server analyzes the location data to determine whether the user is in a public place. The input to this process is the geographical location data obtained earlier, and the output is the result of the determination of whether or not it is a public place.

[0570] Step 6:

[0571] The server determines how to provide sensitive information based on the analysis results and performs a risk assessment. It receives all data analysis results as input and generates proposed adjustments regarding information provision methods as output.

[0572] Step 7:

[0573] Based on the server's decision, the terminal will present the user with a choice of whether to provide information visually or audibly. The input for this process is the server's suggested options, and the output is a confirmation prompt displayed to the user. Specifically, the terminal screen will display a prompt message such as, "Is it alright to provide the information visually?"

[0574] Step 8:

[0575] The user selects the information delivery method in response to prompts on the device. User actions are the input, and the output is the decision of the selected information delivery method. Sensitive information is provided to the user according to the selected method.

[0576] In scenarios utilizing the generative AI model, the prompt "Monitor the surrounding environment and suggest a safe method of providing information. If it is a public place and other people are present, select text display." is used as input to ensure safe and appropriate information provision.

[0577] 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.

[0578] This invention is a system that optimizes the delivery of sensitive information by taking into account the user's environment and emotions. This system begins with the terminal collecting environmental data using a camera, microphone, and GPS sensor. The terminal uses this data to determine the user's surrounding environment and emotional state.

[0579] First, the device uses image data from the camera to apply a face detection algorithm to determine if there are other people nearby. It also uses an acoustic analysis algorithm based on acoustic data from the microphone to assess the surrounding environment. Furthermore, it analyzes GPS information acquired by the device to evaluate whether the user is in a public place.

[0580] The server comprehensively analyzes this data transmitted from the terminal. It also uses an emotion engine to recognize the user's emotional state from the collected image and sound data. The emotion engine analyzes the user's facial expressions and voice tone to determine whether the user is calm or tense.

[0581] Based on these analysis results, the server determines how to provide sensitive information. If the user is in a public place with other people around and the server determines that the user's emotional state is tense, sensitive information will be provided via screen display. If the server determines that the user is calm and their privacy is maintained, sensitive information can be provided via audio.

[0582] For example, when a user is in a confined office, this system allows for verbal communication. On the other hand, if a user is on a train and feels like they are being watched by others, the server prioritizes providing information on a screen, thereby reducing the risk of the user's information being overheard by others. In this way, the present invention realizes information provision that balances user safety and privacy.

[0583] The following describes the processing flow.

[0584] Step 1:

[0585] The device activates its front camera and acquires image data to visually record the user's surroundings. It also uses a microphone to collect ambient acoustic data.

[0586] Step 2:

[0587] The device uses GPS functionality to obtain location data and determine the user's location. This data is used as a factor in determining whether or not the user is in a public place.

[0588] Step 3:

[0589] The device transmits acquired image data, audio data, and location data to the server. This transmitted data is used for analysis.

[0590] Step 4:

[0591] The server applies a face detection algorithm to the received image data to determine if other people are present in the vicinity. This algorithm confirms the presence of people in the surrounding area.

[0592] Step 5:

[0593] The server uses an acoustic analysis algorithm to analyze acoustic data, detect ambient noise levels and human voices, and use these as clues to determine the presence of other people.

[0594] Step 6:

[0595] The server analyzes GPS data to assess whether the user is in a public place or in a private environment. This assessment helps determine the appropriateness of providing the information.

[0596] Step 7:

[0597] The server activates an emotion engine, which analyzes image and sound data to recognize the user's emotional state. The emotion engine determines whether the user is tense or calm based on their facial expressions and tone of voice.

[0598] Step 8:

[0599] The server integrates the analysis results described above and determines how to provide sensitive information. If it determines that the risk is high, it selects a method to display the information on the screen.

[0600] Step 9:

[0601] Based on instructions from the server, the terminal displays a confirmation message to the user and allows the user to choose a secure method of providing information.

[0602] Step 10:

[0603] Users can choose to receive information via audio or visual means in response to presentations from their device.

[0604] Step 11:

[0605] The device will provide sensitive information in an appropriate format according to the user's choice, ensuring the user's privacy and safety.

[0606] (Example 2)

[0607] 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."

[0608] In modern times, the problem of personal information being unintentionally overheard by third parties in public is a serious issue from the perspective of protecting individual privacy. In particular, when providing sensitive information via mobile devices, the risk of information leakage increases if the information is provided in a uniform manner without considering the surrounding circumstances or the individual's emotional state. This invention aims to solve such problems and provide sensitive information in a way that protects the user's safety and privacy.

[0609] 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.

[0610] In this invention, the server includes means for acquiring photographic data to detect the user's surrounding conditions, means for acquiring audio data, and means for acquiring location information. This enables the provision of information in a safer and more privacy-conscious manner, taking into account both surrounding conditions and emotional state.

[0611] A "user" is the entity that operates this system and receives information from it.

[0612] "Surrounding conditions" refers to the state of the environment in which the user is currently located, and includes sound, visual information, location information, etc.

[0613] "Shooting data" refers to image information acquired from a camera or other shooting device.

[0614] "Audio data" refers to information about ambient sounds obtained through audio acquisition devices such as microphones.

[0615] "Location information" refers to data on the user's current location, identified using location detection devices such as GPS.

[0616] "Emotion analysis function" refers to a set of algorithms that analyze captured image data and audio data in order to recognize the user's emotional state.

[0617] "Sensitive information" refers to important and sensitive information about an individual, including information that the individual does not want to be known to third parties.

[0618] "Means of adjustment" refers to a process or function that allows a system to change how it provides information depending on the situation.

[0619] This invention is a system that optimizes the provision of sensitive information according to the user's environment and emotional state. Users can acquire different data via their terminal and receive information in a safe and privacy-conscious manner. The terminal is equipped with a camera, microphone, and GPS sensor, and data is collected using this hardware.

[0620] The device uses a camera to acquire real-time image data and applies a face detection algorithm (e.g., the OpenCV library). This allows it to determine if other people are present in the vicinity. It also uses a microphone to acquire audio data and analyzes the surrounding sound environment using acoustic analysis algorithms (e.g., noise cancellation and speech recognition technologies). Furthermore, a GPS sensor acquires location information and uses a map application to determine whether the user is in a public place.

[0621] The server uses image and audio data transmitted from the terminal to perform sentiment analysis and recognize the user's emotional state. This sentiment analysis utilizes facial expression recognition technology (e.g., OpenPose and Dlib) and voice tone analysis. After the server determines the user's state and environment, it adjusts how sensitive information is provided.

[0622] For example, if a user is in a confined office, the server can safely provide sensitive information via voice. On the other hand, if the user is on a train and feels the gaze of others, the server chooses to provide the information via screen display. In this way, the present invention realizes context-appropriate information provision while protecting the user's privacy.

[0623] An example of a prompt to a generative AI model might be, "If the user is in a public place, such as a train station, but it is quiet and calm, please tell me how to provide sensitive information in a way that respects privacy." This prompt is used to specifically show how the system evaluates the situation and adjusts how information is provided.

[0624] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0625] Step 1:

[0626] The device activates its camera, microphone, and GPS sensor, and begins data collection. As input, the camera acquires real-time image data, the microphone collects ambient audio data, and the GPS sensor obtains location information. As output, this data is prepared for subsequent analysis.

[0627] Step 2:

[0628] The device applies a face detection algorithm to the collected image data. The image data is processed using tools such as the OpenCV library as input, and face presence information is obtained as output. Through this process, the device determines whether other people are present in its vicinity.

[0629] Step 3:

[0630] The device applies an acoustic analysis algorithm to the collected audio data. As input, the audio data is processed using noise cancellation and speech recognition technology, and as output, information about the surrounding sound environment is obtained. Through this analysis, the device determines whether the user's surroundings are quiet or noisy.

[0631] Step 4:

[0632] The device analyzes the acquired GPS data. As input, it compares the location data with a map application, and as output, it obtains a result evaluating whether the user is in a public place.

[0633] Step 5:

[0634] The terminal sends the results of steps 2-4 to the server. It combines face detection results, acoustic analysis results, and location determination results as input, and sends data as output to prepare for analysis on the server side.

[0635] Step 6:

[0636] The server activates its emotion analysis function based on the received data. It uses face detection information and audio environment information as input to perform facial recognition and tone analysis. This analysis then outputs the user's emotional state (e.g., calm, tense).

[0637] Step 7:

[0638] The server determines the optimal method for providing sensitive information based on acquired environmental information and emotional state. As input, it comprehensively assesses the surrounding environment and the user's emotions, and as output, it sends a command to the terminal to provide the information in audio or visual format.

[0639] Step 8:

[0640] The terminal provides sensitive information in a predetermined manner according to instructions from the server. It receives instructions from the server as input and communicates the information to the user as output, either through screen display or audio via the speaker.

[0641] (Application Example 2)

[0642] 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."

[0643] It is necessary to ensure that users can receive information appropriately and safely, according to their environment and emotional state. In particular, when users are in a dangerous situation, it is essential to provide prompt and effective warnings. However, existing technologies have not adequately analyzed the user's surrounding environment and emotional state in detail and dynamically adjusted the information delivery method based on that analysis. As a result, there have been problems in which the privacy and safety of users when receiving information are not guaranteed.

[0644] 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.

[0645] In this invention, the server includes means for acquiring image information to detect the user's surrounding environment, means for acquiring acoustic information, means for acquiring location information, and means for analyzing the user's emotional state and providing emergency notifications in an appropriate manner. This enables the user to receive information customized according to their environment and emotions. Furthermore, if the user is in a dangerous situation, an automatic warning can be issued to encourage a quick response.

[0646] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, which are detected by cameras and microphones.

[0647] "Image information" refers to visual data acquired using a camera, and is used as material for analyzing the user and their surroundings.

[0648] "Acoustic information" refers to audio data acquired through a microphone, which is used to analyze ambient sounds and voices.

[0649] "Location information" refers to data obtained through GPS and other location acquisition technologies, and is used to determine the user's physical location.

[0650] "Emotional state" refers to the user's psychological and emotional condition, and is determined through analysis of facial expressions and voice tone.

[0651] An "emergency notification" refers to important information or warnings that need to be conveyed to the user quickly, and is delivered using voice, vibration, and visual effects.

[0652] A "warning" is information intended to alert users to danger or require caution, and is automatically issued depending on the situation.

[0653] The system that realizes this invention is designed to optimally provide information based on the user's surrounding environment and emotional state. The system mainly consists of a terminal held by the user and a server that performs data analysis.

[0654] The device uses a camera, microphone, and GPS sensor to monitor the user's surroundings in real time. Specifically, it uses the camera to acquire image information and detects people and objects in the surroundings through facial recognition technology (e.g., the OpenCV library). Acoustic information acquired by the microphone is processed by a speech analysis algorithm (e.g., the TensorFlow library) to analyze ambient sounds. The GPS sensor acquires the user's location information, determining their current position.

[0655] This collected data is sent from the device to the server, where it is analyzed and evaluated. The server uses a generative AI model to identify the user's emotional state from their facial expressions and tone of voice. For example, if the user appears anxious, the server will choose a means to quickly issue an emergency notification.

[0656] Based on the analysis results, the server determines how to provide information. For example, if it determines that the user is in a public place with other people present or is in a dangerous situation, it automatically sends a warning to the device and notifies the user in an appropriate way, such as by voice or vibration. If it determines that the user is relaxed and their privacy is protected, it provides sensitive information by voice.

[0657] For example, when a user is traveling through an area where they feel uneasy at night, the device's camera and microphone detect surrounding sounds and people. If the server analyzes the data and determines that an abnormal situation is occurring, it immediately issues a warning. This helps the user sense danger and move to a safe location.

[0658] An example of a prompt for a generating AI model is, "Explain how to issue an appropriate alert when a user is in a situation that causes anxiety."

[0659] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0660] Step 1:

[0661] The device collects data about its surroundings. Specifically, it acquires image information with a camera, collects acoustic information with a microphone, and obtains location information with a GPS sensor. This raw data is used as input data for the next processing step.

[0662] Step 2:

[0663] The device uses the acquired image information to apply a face recognition algorithm and detect whether other people are present in the vicinity. This algorithm converts the image data into data in the form of a face detection result. The output is the result of determining whether or not other people are present in the vicinity.

[0664] Step 3:

[0665] The device inputs acoustic information into an acoustic analysis algorithm to analyze the characteristics of the surrounding sound. Through this data processing, the acoustic data is converted into analytical information such as sound patterns, volume, and sound source direction. The output is the meaning of the sound and the results of abnormal sound detection.

[0666] Step 4:

[0667] The device analyzes GPS information to evaluate the user's current location and movement patterns. This converts location data into information indicating whether the user is in a public place or a safe location. The output is a location evaluation related to safety and public accessibility.

[0668] Step 5:

[0669] The server integrates face detection results, acoustic analysis information, and location evaluation information transmitted from the terminal, and uses a generative AI model to recognize the user's emotional state. The input is the integrated analysis data, and the output is the estimated result of the user's emotional state (e.g., calm, tense, anxious).

[0670] Step 6:

[0671] The server comprehensively evaluates these results and determines the means of providing sensitive information. Specifically, if it is determined that the user is in a stressful state in a public place, the information will be quietly provided via a screen display. The output is the selection of the information provision method.

[0672] Step 7:

[0673] The server automatically issues an emergency warning via voice and vibration through the terminal if it determines that the user's situation is dangerous. The action taken is to sound a warning and vibrate the terminal. The output is the execution of the emergency notification.

[0674] 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.

[0675] 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.

[0676] 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.

[0677] [Fourth Embodiment]

[0678] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0679] 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.

[0680] 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).

[0681] 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.

[0682] 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.

[0683] 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).

[0684] 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.

[0685] 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.

[0686] 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.

[0687] 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.

[0688] 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.

[0689] 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.

[0690] 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".

[0691] This invention is a system that appropriately adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, the terminal monitors the user's surrounding environment using a camera and microphone. Face detection is performed from video data acquired through the front camera to determine if other people are present in the vicinity. In addition, ambient sounds are collected as acoustic data, and voice analysis algorithms are used to detect the voices of others and background noise. Furthermore, GPS information is acquired to confirm whether the user's current location is a public place.

[0692] The server aggregates and analyzes this data transmitted from the terminal. Based on the analysis results, it assesses the risks associated with providing sensitive information. If the risk is deemed high, the server adjusts the system so that sensitive information is not provided via voice, but instead displayed visually as text on the terminal's screen.

[0693] On the other hand, users can choose how information is provided in response to prompts from the device. For example, if there is a possibility of other people being nearby, the device will ask the user, "Is it okay to display this information on the screen?" If the user grants permission, the system will display and provide the sensitive information on the screen.

[0694] As a concrete example, suppose a user checks their personal financial information on a terminal in a public cafe. In this case, the terminal analyzes the surrounding environment and detects the presence of other customers. The server receives this information and recognizes that providing the information verbally is risky, so the terminal suggests displaying the information on the screen. By allowing the user to view the information on the screen, the financial information is provided visually, avoiding the risk of leakage to others. This process ensures safe and reliable information provision.

[0695] The following describes the processing flow.

[0696] Step 1:

[0697] The device activates its front camera and captures video data of the user's surroundings. It also uses its microphone to record ambient sound data.

[0698] Step 2:

[0699] The device uses GPS functionality to obtain the user's current location and record the location data.

[0700] Step 3:

[0701] The device transmits the acquired video data, audio data, and location data to the server.

[0702] Step 4:

[0703] The server analyzes the received video data and applies a face detection algorithm to determine if there are other people around the user.

[0704] Step 5:

[0705] The server uses an acoustic analysis algorithm to analyze acoustic data and detect whether there are other people's voices or noise in the surrounding area.

[0706] Step 6:

[0707] The server analyzes GPS data to determine whether the user's current location is a public place.

[0708] Step 7:

[0709] Based on these analysis results, the server assesses the risks of providing sensitive information via voice.

[0710] Step 8:

[0711] The server sends the evaluation results to the terminal and provides instructions on how to provide sensitive information.

[0712] Step 9:

[0713] The terminal, following instructions from the server, displays a confirmation message to the user, allowing them to choose whether to receive information via voice or on the screen.

[0714] Step 10:

[0715] Users will select or authorize the method of providing information in response to the confirmation message.

[0716] Step 11:

[0717] The device prevents information leaks by providing sensitive information in an appropriate format according to the user's choice.

[0718] (Example 1)

[0719] 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".

[0720] In modern society, as opportunities to access sensitive information using mobile devices increase, the risk of information being leaked to those around the user is also rising. In this context, a system that can dynamically adjust the information delivery method according to the surrounding environment is desirable to ensure that users receive sensitive information safely and with their privacy protected.

[0721] 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.

[0722] In this invention, the server includes means for acquiring image data to detect the user's surrounding environment, means for acquiring acoustic data, and means for acquiring location data. This makes it possible to individually assess the risk of leakage of sensitive information and provide information by switching between audio and visual formats.

[0723] A "user" refers to a person who uses a system to receive information.

[0724] "Surrounding environment" refers to the physical space surrounding the user, as well as other people, sounds, and other elements present within that space.

[0725] "Image data" refers to a collection of visual information acquired through video input devices such as cameras.

[0726] "Audio data" refers to information about sound acquired through audio input devices such as microphones.

[0727] "Location data" refers to geographical location information obtained using GPS or other location measurement technologies.

[0728] "Sensitive information" refers to information where an individual's privacy and confidentiality should be given priority.

[0729] A "face detection algorithm" refers to a computational method for identifying and recognizing a person's face from image data.

[0730] A "speech analysis algorithm" refers to a computational method that analyzes acoustic data to detect specific sounds or patterns.

[0731] A "noise-canceling algorithm" refers to a technique that removes unwanted sounds from audio data and extracts important audio.

[0732] "Visual display" refers to showing information in text and images through displays or screens.

[0733] "Control means" refers to a mechanism for managing each element of a system and generating commands.

[0734] "Audio delivery" refers to a method of conveying information to users through audio.

[0735] This invention is a system that dynamically adjusts the method of providing sensitive information based on the user's surrounding environment. Specifically, it is configured as follows:

[0736] First, the device uses a front camera and microphone to monitor the user's surroundings. The camera captures images of the user's front and acquires video data. Face detection algorithms are then executed on this video data using image processing libraries such as OpenCV or TensorFlow to determine if other people are nearby. Simultaneously, acoustic data is collected from the microphone, and voice analysis algorithms are used to recognize other people's voices and environmental noise. GPS functionality is also active to acquire the user's location data, helping to determine if the user is in a public place.

[0737] At this time, the server aggregates and analyzes the environmental data transmitted from the terminal. The server evaluates whether it is necessary to provide information that respects the user's privacy based on the received face detection results, voice analysis results, and GPS information. If the evaluation determines that providing information via voice poses a risk, the server sends an instruction to provide sensitive information visually.

[0738] Furthermore, users can choose how information is presented based on prompts from their device. For example, a confirmation prompt such as "Do you want to display the information on the screen?" may appear, and the user can select an option to visualize the information.

[0739] As a concrete example, suppose a user wants to access their personal financial information using their smartphone in a public cafe. In this case, the device uses its front camera and microphone to analyze the surrounding environment, and the server uses this information to determine that providing the information via voice is risky. The device then prompts the user, "Do you want to display this information on the screen?" If the user grants permission, the information is displayed visually on the screen, reducing the risk of the information being leaked to others.

[0740] The system functions effectively by inputting prompts such as, "The user is viewing sensitive information in a public place. Please suggest a safe way to provide this information in this situation," into the AI ​​model that generates the prompts.

[0741] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0742] Step 1:

[0743] The device activates its front camera to capture images of the user's surroundings and acquire video data. The input is real-time video obtained through the camera, and the output is image data used for analysis. Specifically, the device acquires a high-resolution video stream and extracts the necessary frames.

[0744] Step 2:

[0745] The device uses a microphone to record ambient sounds and acquires acoustic data. The input is raw audio data captured by the microphone, and the output is acoustic data for speech analysis. Specifically, the device samples the audio at regular intervals and performs digital signal processing.

[0746] Step 3:

[0747] The device uses GPS functionality to obtain its current location data. The input is satellite data from the GPS chip, and the output is geographic coordinates indicating the user's location. The device periodically receives signals to calculate highly accurate location information.

[0748] Step 4:

[0749] The device applies a face detection algorithm to the acquired image data. The input is the image data obtained in step 1, and the output is information regarding the presence or absence of faces detected in the image. Specifically, the device uses libraries such as OpenCV to extract facial features through pattern matching.

[0750] Step 5:

[0751] The device executes a speech analysis algorithm on acoustic data to detect other people's voices. The input is the acoustic data obtained in step 2, and the output is the characteristics of the detected voices. The device performs frequency analysis using FFT (Fast Fourier Transform) to identify specific voice patterns.

[0752] Step 6:

[0753] The server aggregates environmental information sent from terminals and performs a risk assessment. The input consists of data obtained in steps 4 and 5, and step 3, and the output is a guideline for selecting information provision methods. The server uses a machine learning model to determine whether information provision involves risk.

[0754] Step 7:

[0755] The terminal receives instructions from the server and prompts the user for information. The input is the instructions received from the server in step 6, and the output is the selection prompt displayed to the user. The terminal uses a user interface to display clear and intuitive choices.

[0756] Step 8:

[0757] The user selects a method for providing information and grants permission in response to prompts on the device. The input is the prompt obtained in step 7, and the output is the result of the user's selection. The user makes selections using taps or voice commands.

[0758] Step 9:

[0759] The device provides sensitive information verbally or visually based on the user's selection. The input is the user's selection in step 8, and the output is the information provided on the screen or verbally. Specifically, the device displays information on the screen or reads text aloud.

[0760] (Application Example 1)

[0761] 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".

[0762] In recent years, the leakage of personal information has become a serious problem, and there is always a risk of information being leaked to others, especially when handling sensitive information in public places. This issue is a widespread concern for users of portable information processing devices such as smartphones. Furthermore, there is a need to further enhance the security of sensitive information management and provide users with means to communicate with peace of mind.

[0763] 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.

[0764] In this invention, the server includes means for acquiring data to detect the user's surrounding environment, means for acquiring ambient sounds, and means for acquiring location information. This makes it possible to flexibly adjust the method of providing sensitive information according to the environment and to enhance the protection of information through encryption technology.

[0765] A "user" is an individual who uses the system or provides information about their surrounding environment.

[0766] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, and is the subject of information acquisition and analysis.

[0767] "Sensitive information" refers to information that, if disclosed to others, could potentially threaten a user's privacy or safety.

[0768] "Means of acquiring data" refers to the devices and technologies used to gather necessary information from the user's surrounding environment.

[0769] "Environmental sounds" refer to sounds and voices that occur around the user, and are elements that allow the presence of others to be confirmed through voice analysis.

[0770] "Location information" refers to geographical data obtained to identify where a user is currently located.

[0771] "Encryption technology" is a technical method that transforms data to maintain its confidentiality and protect it from unauthorized access.

[0772] "Facial recognition technology" is a technology that detects and recognizes specific faces by analyzing camera video data.

[0773] "Voice analysis technology" is a technique that extracts characteristics of voices by analyzing voice data, and uses this to distinguish between other people's voices and background noise.

[0774] To implement this invention, the system operates through a dedicated application installed on the user's portable information processing device. The hardware used is a smartphone, with the camera, microphone, and GPS being its primary data acquisition devices. The software utilizes OpenCV for facial recognition, Google Cloud Speech-to-Text for speech analysis, and the Google Maps API for location management.

[0775] The server receives and comprehensively analyzes video, audio, and location data continuously acquired from the terminal. From the video data, facial recognition technology is used to detect the presence of others, and audio analysis technology is used to identify human voices and noises from ambient sounds. Based on location data, it determines whether the user is in a public place. Based on this data, the server performs a risk assessment regarding how to provide sensitive information.

[0776] As an example, consider a scenario where a user tries to check a message on a train. In this case, the server detects other passengers using facial recognition and decides to refrain from reading the message aloud. It can then propose to the user that the message be displayed on the screen and provided as an encrypted message. Specifically, the terminal would display a prompt to the user asking, "Is it alright to provide the information visually?"

[0777] When using a generative AI model, an example prompt might be: "Monitor the surrounding environment and suggest a safe way to provide information. If it is a public place and other people are present, please select text display." This allows users to receive information while maintaining their privacy, even in public places.

[0778] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0779] Step 1:

[0780] The device uses a camera and microphone to acquire data about the user's surrounding environment. Specifically, the camera collects video data, and the microphone records ambient sounds. In this case, the input is the surrounding environment itself, and the output is video data and audio data.

[0781] Step 2:

[0782] The device uses location services to obtain the user's current location. The input is location information obtained from GPS, and the output is specific geographical location data. This prepares the device to determine whether the user is in a public place.

[0783] Step 3:

[0784] The terminal sends the acquired data to the server. Video data, audio data, and location data are sent to the server as input. The expected output is the data analysis results from the server.

[0785] Step 4:

[0786] The server begins data analysis, using facial recognition technology for video data and speech analysis technology for audio data. Facial information is extracted from the video data, and characteristics of speech and noise are identified from the audio data. The output provides a determination of whether or not other people are present in the surrounding area.

[0787] Step 5:

[0788] The server analyzes the location data to determine whether the user is in a public place. The input to this process is the geographical location data obtained earlier, and the output is the result of the determination of whether or not it is a public place.

[0789] Step 6:

[0790] The server determines how to provide sensitive information based on the analysis results and performs a risk assessment. It receives all data analysis results as input and generates proposed adjustments regarding information provision methods as output.

[0791] Step 7:

[0792] Based on the server's decision, the terminal will present the user with a choice of whether to provide information visually or audibly. The input for this process is the server's suggested options, and the output is a confirmation prompt displayed to the user. Specifically, the terminal screen will display a prompt message such as, "Is it alright to provide the information visually?"

[0793] Step 8:

[0794] The user selects the information delivery method in response to prompts on the device. User actions are the input, and the output is the decision of the selected information delivery method. Sensitive information is provided to the user according to the selected method.

[0795] In scenarios utilizing the generative AI model, the prompt "Monitor the surrounding environment and suggest a safe method of providing information. If it is a public place and other people are present, select text display." is used as input to ensure safe and appropriate information provision.

[0796] 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.

[0797] This invention is a system that optimizes the delivery of sensitive information by taking into account the user's environment and emotions. This system begins with the terminal collecting environmental data using a camera, microphone, and GPS sensor. The terminal uses this data to determine the user's surrounding environment and emotional state.

[0798] First, the device uses image data from the camera to apply a face detection algorithm to determine if there are other people nearby. It also uses an acoustic analysis algorithm based on acoustic data from the microphone to assess the surrounding environment. Furthermore, it analyzes GPS information acquired by the device to evaluate whether the user is in a public place.

[0799] The server comprehensively analyzes this data transmitted from the terminal. It also uses an emotion engine to recognize the user's emotional state from the collected image and sound data. The emotion engine analyzes the user's facial expressions and voice tone to determine whether the user is calm or tense.

[0800] Based on these analysis results, the server determines how to provide sensitive information. If the user is in a public place with other people around and the server determines that the user's emotional state is tense, sensitive information will be provided via screen display. If the server determines that the user is calm and their privacy is maintained, sensitive information can be provided via audio.

[0801] For example, when a user is in a confined office, this system allows for verbal communication. On the other hand, if a user is on a train and feels like they are being watched by others, the server prioritizes providing information on a screen, thereby reducing the risk of the user's information being overheard by others. In this way, the present invention realizes information provision that balances user safety and privacy.

[0802] The following describes the processing flow.

[0803] Step 1:

[0804] The device activates its front camera and acquires image data to visually record the user's surroundings. It also uses a microphone to collect ambient acoustic data.

[0805] Step 2:

[0806] The device uses GPS functionality to obtain location data and determine the user's location. This data is used as a factor in determining whether or not the user is in a public place.

[0807] Step 3:

[0808] The device transmits acquired image data, audio data, and location data to the server. This transmitted data is used for analysis.

[0809] Step 4:

[0810] The server applies a face detection algorithm to the received image data to determine if other people are present in the vicinity. This algorithm confirms the presence of people in the surrounding area.

[0811] Step 5:

[0812] The server uses an acoustic analysis algorithm to analyze acoustic data, detect ambient noise levels and human voices, and use these as clues to determine the presence of other people.

[0813] Step 6:

[0814] The server analyzes GPS data to assess whether the user is in a public place or in a private environment. This assessment helps determine the appropriateness of providing the information.

[0815] Step 7:

[0816] The server activates an emotion engine, which analyzes image and sound data to recognize the user's emotional state. The emotion engine determines whether the user is tense or calm based on their facial expressions and tone of voice.

[0817] Step 8:

[0818] The server integrates the analysis results described above and determines how to provide sensitive information. If it determines that the risk is high, it selects a method to display the information on the screen.

[0819] Step 9:

[0820] Based on instructions from the server, the terminal displays a confirmation message to the user and allows the user to choose a secure method of providing information.

[0821] Step 10:

[0822] Users can choose to receive information via audio or visual means in response to presentations from their device.

[0823] Step 11:

[0824] The device will provide sensitive information in an appropriate format according to the user's choice, ensuring the user's privacy and safety.

[0825] (Example 2)

[0826] 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".

[0827] In modern times, the problem of personal information being unintentionally overheard by third parties in public is a serious issue from the perspective of protecting individual privacy. In particular, when providing sensitive information via mobile devices, the risk of information leakage increases if the information is provided in a uniform manner without considering the surrounding circumstances or the individual's emotional state. This invention aims to solve such problems and provide sensitive information in a way that protects the user's safety and privacy.

[0828] 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.

[0829] In this invention, the server includes means for acquiring photographic data to detect the user's surrounding conditions, means for acquiring audio data, and means for acquiring location information. This enables the provision of information in a safer and more privacy-conscious manner, taking into account both surrounding conditions and emotional state.

[0830] A "user" is the entity that operates this system and receives information from it.

[0831] "Surrounding conditions" refers to the state of the environment in which the user is currently located, and includes sound, visual information, location information, etc.

[0832] "Shooting data" refers to image information acquired from a camera or other shooting device.

[0833] "Audio data" refers to information about ambient sounds obtained through audio acquisition devices such as microphones.

[0834] "Location information" refers to data on the user's current location, identified using location detection devices such as GPS.

[0835] "Emotion analysis function" refers to a set of algorithms that analyze captured image data and audio data in order to recognize the user's emotional state.

[0836] "Sensitive information" refers to important and sensitive information about an individual, including information that the individual does not want to be known to third parties.

[0837] "Means of adjustment" refers to a process or function that allows a system to change how it provides information depending on the situation.

[0838] This invention is a system that optimizes the provision of sensitive information according to the user's environment and emotional state. Users can acquire different data via their terminal and receive information in a safe and privacy-conscious manner. The terminal is equipped with a camera, microphone, and GPS sensor, and data is collected using this hardware.

[0839] The device uses a camera to acquire real-time image data and applies a face detection algorithm (e.g., the OpenCV library). This allows it to determine if other people are present in the vicinity. It also uses a microphone to acquire audio data and analyzes the surrounding sound environment using acoustic analysis algorithms (e.g., noise cancellation and speech recognition technologies). Furthermore, a GPS sensor acquires location information and uses a map application to determine whether the user is in a public place.

[0840] The server uses image and audio data transmitted from the terminal to perform sentiment analysis and recognize the user's emotional state. This sentiment analysis utilizes facial expression recognition technology (e.g., OpenPose and Dlib) and voice tone analysis. After the server determines the user's state and environment, it adjusts how sensitive information is provided.

[0841] For example, if a user is in a confined office, the server can safely provide sensitive information via voice. On the other hand, if the user is on a train and feels the gaze of others, the server chooses to provide the information via screen display. In this way, the present invention realizes context-appropriate information provision while protecting the user's privacy.

[0842] An example of a prompt to a generative AI model might be, "If the user is in a public place, such as a train station, but it is quiet and calm, please tell me how to provide sensitive information in a way that respects privacy." This prompt is used to specifically show how the system evaluates the situation and adjusts how information is provided.

[0843] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0844] Step 1:

[0845] The device activates its camera, microphone, and GPS sensor, and begins data collection. As input, the camera acquires real-time image data, the microphone collects ambient audio data, and the GPS sensor obtains location information. As output, this data is prepared for subsequent analysis.

[0846] Step 2:

[0847] The device applies a face detection algorithm to the collected image data. The image data is processed using tools such as the OpenCV library as input, and face presence information is obtained as output. Through this process, the device determines whether other people are present in its vicinity.

[0848] Step 3:

[0849] The device applies an acoustic analysis algorithm to the collected audio data. As input, the audio data is processed using noise cancellation and speech recognition technology, and as output, information about the surrounding sound environment is obtained. Through this analysis, the device determines whether the user's surroundings are quiet or noisy.

[0850] Step 4:

[0851] The device analyzes the acquired GPS data. As input, it compares the location data with a map application, and as output, it obtains a result evaluating whether the user is in a public place.

[0852] Step 5:

[0853] The terminal sends the results of steps 2-4 to the server. It combines face detection results, acoustic analysis results, and location determination results as input, and sends data as output to prepare for analysis on the server side.

[0854] Step 6:

[0855] The server activates its emotion analysis function based on the received data. It uses face detection information and audio environment information as input to perform facial recognition and tone analysis. This analysis then outputs the user's emotional state (e.g., calm, tense).

[0856] Step 7:

[0857] The server determines the optimal method for providing sensitive information based on acquired environmental information and emotional state. As input, it comprehensively assesses the surrounding environment and the user's emotions, and as output, it sends a command to the terminal to provide the information in audio or visual format.

[0858] Step 8:

[0859] The terminal provides sensitive information in a predetermined manner according to instructions from the server. It receives instructions from the server as input and communicates the information to the user as output, either through screen display or audio via the speaker.

[0860] (Application Example 2)

[0861] 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".

[0862] It is necessary to ensure that users can receive information appropriately and safely, according to their environment and emotional state. In particular, when users are in a dangerous situation, it is essential to provide prompt and effective warnings. However, existing technologies have not adequately analyzed the user's surrounding environment and emotional state in detail and dynamically adjusted the information delivery method based on that analysis. As a result, there have been problems in which the privacy and safety of users when receiving information are not guaranteed.

[0863] 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.

[0864] In this invention, the server includes means for acquiring image information to detect the user's surrounding environment, means for acquiring acoustic information, means for acquiring location information, and means for analyzing the user's emotional state and providing emergency notifications in an appropriate manner. This enables the user to receive information customized according to their environment and emotions. Furthermore, if the user is in a dangerous situation, an automatic warning can be issued to encourage a quick response.

[0865] "Surrounding environment" refers to the physical and acoustic conditions surrounding the user, which are detected by cameras and microphones.

[0866] "Image information" refers to visual data acquired using a camera, and is used as material for analyzing the user and their surroundings.

[0867] "Acoustic information" refers to audio data acquired through a microphone, which is used to analyze ambient sounds and voices.

[0868] "Location information" refers to data obtained through GPS and other location acquisition technologies, and is used to determine the user's physical location.

[0869] "Emotional state" refers to the user's psychological and emotional condition, and is determined through analysis of facial expressions and voice tone.

[0870] An "emergency notification" refers to important information or warnings that need to be conveyed to the user quickly, and is delivered using voice, vibration, and visual effects.

[0871] A "warning" is information intended to alert users to danger or require caution, and is automatically issued depending on the situation.

[0872] The system that realizes this invention is designed to optimally provide information based on the user's surrounding environment and emotional state. The system mainly consists of a terminal held by the user and a server that performs data analysis.

[0873] The device uses a camera, microphone, and GPS sensor to monitor the user's surroundings in real time. Specifically, it uses the camera to acquire image information and detects people and objects in the surroundings through facial recognition technology (e.g., the OpenCV library). Acoustic information acquired by the microphone is processed by a speech analysis algorithm (e.g., the TensorFlow library) to analyze ambient sounds. The GPS sensor acquires the user's location information, determining their current position.

[0874] This collected data is sent from the device to the server, where it is analyzed and evaluated. The server uses a generative AI model to identify the user's emotional state from their facial expressions and tone of voice. For example, if the user appears anxious, the server will choose a means to quickly issue an emergency notification.

[0875] Based on the analysis results, the server determines how to provide information. For example, if it determines that the user is in a public place with other people present or is in a dangerous situation, it automatically sends a warning to the device and notifies the user in an appropriate way, such as by voice or vibration. If it determines that the user is relaxed and their privacy is protected, it provides sensitive information by voice.

[0876] For example, when a user is traveling through an area where they feel uneasy at night, the device's camera and microphone detect surrounding sounds and people. If the server analyzes the data and determines that an abnormal situation is occurring, it immediately issues a warning. This helps the user sense danger and move to a safe location.

[0877] An example of a prompt for a generating AI model is, "Explain how to issue an appropriate alert when a user is in a situation that causes anxiety."

[0878] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0879] Step 1:

[0880] The device collects data about its surroundings. Specifically, it acquires image information with a camera, collects acoustic information with a microphone, and obtains location information with a GPS sensor. This raw data is used as input data for the next processing step.

[0881] Step 2:

[0882] The device uses the acquired image information to apply a face recognition algorithm and detect whether other people are present in the vicinity. This algorithm converts the image data into data in the form of a face detection result. The output is the result of determining whether or not other people are present in the vicinity.

[0883] Step 3:

[0884] The device inputs acoustic information into an acoustic analysis algorithm to analyze the characteristics of the surrounding sound. Through this data processing, the acoustic data is converted into analytical information such as sound patterns, volume, and sound source direction. The output is the meaning of the sound and the results of abnormal sound detection.

[0885] Step 4:

[0886] The device analyzes GPS information to evaluate the user's current location and movement patterns. This converts location data into information indicating whether the user is in a public place or a safe location. The output is a location evaluation related to safety and public accessibility.

[0887] Step 5:

[0888] The server integrates face detection results, acoustic analysis information, and location evaluation information transmitted from the terminal, and uses a generative AI model to recognize the user's emotional state. The input is the integrated analysis data, and the output is the estimated result of the user's emotional state (e.g., calm, tense, anxious).

[0889] Step 6:

[0890] The server comprehensively evaluates these results and determines the means of providing sensitive information. Specifically, if it is determined that the user is in a stressful state in a public place, the information will be quietly provided via a screen display. The output is the selection of the information provision method.

[0891] Step 7:

[0892] The server automatically issues an emergency warning via voice and vibration through the terminal if it determines that the user's situation is dangerous. The action taken is to sound a warning and vibrate the terminal. The output is the execution of the emergency notification.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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."

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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.

[0911] 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.

[0912] 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.

[0913] 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.

[0914] The following is further disclosed regarding the embodiments described above.

[0915] (Claim 1)

[0916] A means of acquiring image data to detect the user's surrounding environment,

[0917] Means for acquiring acoustic data,

[0918] Means for obtaining location data,

[0919] A means for analyzing the aforementioned image data, acoustic data, and location data to determine whether other people are present in the vicinity,

[0920] Means for changing the method of providing sensitive information based on the aforementioned determination,

[0921] Before providing the aforementioned sensitive information, a means of requesting confirmation from the user,

[0922] A system that includes this.

[0923] (Claim 2)

[0924] The system according to claim 1, which provides the sensitive information by voice or visual means.

[0925] (Claim 3)

[0926] The system according to claim 1, wherein a face detection algorithm and an acoustic analysis algorithm are used in the analysis of the environmental data.

[0927] "Example 1"

[0928] (Claim 1)

[0929] A means of acquiring image data to detect the user's surrounding environment,

[0930] Means for acquiring acoustic data,

[0931] Means for obtaining location data,

[0932] A means for analyzing the aforementioned image data, acoustic data, and location data to determine whether other people are present in the vicinity,

[0933] Means for changing the method of providing sensitive information based on the aforementioned determination,

[0934] Before providing the aforementioned sensitive information, a means of requesting confirmation from the user,

[0935] A control means for assessing the risk of personal information leakage and switching from audio to visual display,

[0936] A providing means that provides sensitive information based on the control means,

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, which provides the sensitive information by voice or visual means.

[0940] (Claim 3)

[0941] The system according to claim 1, which uses a face detection algorithm and an acoustic analysis algorithm in the analysis of the environmental data, and includes an algorithm for removing excessive noise.

[0942] "Application Example 1"

[0943] (Claim 1)

[0944] A means of acquiring data to detect the user's surrounding environment,

[0945] Means for acquiring ambient sounds,

[0946] Means for obtaining location information,

[0947] A means for analyzing the aforementioned data, ambient sounds, and location information to determine whether other people are present in the vicinity,

[0948] Means for changing the method of providing sensitive information based on the aforementioned determination,

[0949] Before providing the aforementioned sensitive information, a means of requesting confirmation from the user,

[0950] A means of encrypting and providing message content,

[0951] A system that includes this.

[0952] (Claim 2)

[0953] The system according to claim 1, which securely provides the aforementioned sensitive information.

[0954] (Claim 3)

[0955] The system according to claim 1, which uses facial recognition technology and voice analysis technology in the analysis of the aforementioned environmental data.

[0956] "Example 2 of combining an emotion engine"

[0957] (Claim 1)

[0958] A means for acquiring photographic data to detect the user's surrounding conditions,

[0959] Means for acquiring audio data,

[0960] Means for obtaining location information,

[0961] A means for analyzing the aforementioned shooting data, audio data, and location information to determine whether other people are present in the vicinity,

[0962] It is equipped with an emotion analysis function for analyzing emotional states, and a means for determining the user's emotional state,

[0963] Means for adjusting the method of providing sensitive information based on the aforementioned judgment and sentiment analysis results,

[0964] A system that includes this.

[0965] (Claim 2)

[0966] The system according to claim 1, which provides the sensitive information by voice or visual means.

[0967] (Claim 3)

[0968] The system according to claim 1, wherein a face recognition algorithm and an acoustic analysis algorithm are used in the analysis of the aforementioned condition data.

[0969] "Application example 2 when combining with an emotional engine"

[0970] (Claim 1)

[0971] A means for acquiring image information to detect the user's surrounding environment,

[0972] Means for acquiring acoustic information,

[0973] Means for obtaining location information,

[0974] A means for analyzing the aforementioned image information, acoustic information, and location information to determine whether other people are present in the vicinity,

[0975] Means for changing the method of providing sensitive information based on the aforementioned determination,

[0976] Before providing the aforementioned sensitive information, a means of requesting confirmation from the user,

[0977] A means of analyzing the user's emotional state and providing emergency notifications in an appropriate manner,

[0978] A means of automatically issuing a warning when the user is in a dangerous situation,

[0979] A system that includes this.

[0980] (Claim 2)

[0981] The system according to claim 1, which provides the sensitive information audibly or visually and provides vibration notification according to the user's state.

[0982] (Claim 3)

[0983] The system according to claim 1, wherein in the analysis of the environmental information, a face recognition algorithm, an acoustic analysis algorithm, and an emotion analysis engine are used. [Explanation of symbols]

[0984] 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 means of acquiring data to detect the user's surrounding environment, Means for acquiring ambient sounds, Means for obtaining location information, A means for analyzing the aforementioned data, ambient sounds, and location information to determine whether other people are present in the vicinity, Means for changing the method of providing sensitive information based on the aforementioned determination, Before providing the aforementioned sensitive information, a means of requesting confirmation from the user, A means of encrypting and providing message content, A system that includes this.

2. The system according to claim 1, which securely provides the aforementioned sensitive information.

3. The system according to claim 1, wherein facial recognition technology and voice analysis technology are used in the analysis of the aforementioned environmental data.

Images