System

Abstract

A system is provided.SOLUTION: The system includes a means for acquiring peripheral information, a means for analyzing the acquired peripheral information, a means for generating appropriate action information based on an analysis result, a means for transmitting the generated action information, and a means for notifying a user of the received action information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, situations requiring a quick response are on the rise. However, taking appropriate action in our busy daily lives is often difficult. In particular, in cases of lost children and emergencies, immediate information acquisition and appropriate action are required. Furthermore, because compensation for providing information is unclear, there is a lack of incentive for information providers to actively participate. This invention aims to solve these problems and provide a system that enables immediate response regardless of time or place. [Means for solving the problem]

[0005] This invention is a system including the following means. The system enables immediate response by combining means for acquiring peripheral information, means for analyzing the acquired peripheral information, means for generating appropriate behavioral information based on the analysis results, means for transmitting the generated behavioral information, and means for notifying the user of the received behavioral information. Furthermore, by further including means for acquiring location information and sensor information as peripheral information, evaluating the trustworthiness of information providers, and providing rewards based on the evaluation, the system can increase incentives for providing information. This allows necessary information to be provided promptly and appropriately, enabling users to take prompt action.

[0006] "Peripheral information" refers to the location information of the terminal and data obtained from surrounding sensors.

[0007] "Means of acquisition" refers to the functions and modules that allow a terminal to collect peripheral information, such as location information and sensor information.

[0008] "Means of analysis" refers to the function of analyzing collected peripheral information using a common language or specific parameters and converting it into meaningful data.

[0009] The "means for generating behavioral information" refers to a function for creating information or notifications that instruct the user on appropriate behavior to be taken based on the analysis results.

[0010] The "transmitting means" refers to a function for transmitting the generated behavioral information to another terminal or server via a network.

[0011] The "notification means" refers to a function for notifying the user of the received behavioral information using the display screen of the terminal or other notification methods.

[0012] An "information provider" refers to a user who provides information about a lost child or other surrounding information.

[0013] "Reliability" refers to an index used to evaluate the accuracy and usefulness of information provided by an information provider.

[0014] "Rewards" refers to tokens or other incentives given to information providers for useful information they provide. [Brief explanation of the drawings]

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

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

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

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

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

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

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a 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 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

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

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0033] The storage 32 stores a data generation model 58 and an 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 process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0036] To implement the present invention, the following system and program are used: The system is mainly composed of a server, a terminal, and a user.

[0037] Acquisition and analysis of surrounding information

[0038] Device:

[0039] The device acquires its current location using a built-in GPS module, and also uses sensors such as a camera, microphone, and thermometer to collect data on the surrounding environment.

[0040] The device filters and analyzes the collected data based on the common language "Feel!!" For example, if the device detects an abnormal sound, image, or temperature fluctuation, it will recognize this as a specific event, such as a "lost child."

[0041] Generation and transmission of behavioral information

[0042] server:

[0043] The server receives location and sensor information sent from the device, analyzes this information, and determines whether specific action is required.

[0044] For example, if the server receives location information of a child who appears to be lost in a park, it generates action information such as "notify a nearby parent."

[0045] The generated behavioral information is distributed from the server to the relevant devices, enabling a rapid response.

[0046] Receiving and notifying behavioral information

[0047] Device:

[0048] When the terminal receives the behavioral information sent from the server, it notifies the user by, for example, displaying a pop-up message on the screen to alert the user.

[0049] The user is notified and can take appropriate action.

[0050] Information provision and evaluation

[0051] User:

[0052] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[0053] Other users can rate the information they receive, for example, saying "this information was accurate" or "this information was helpful."

[0054] server:

[0055] The server receives information posted by users, analyzes the content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[0056] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[0057] Specific examples

[0058] Scenario: You find a lost child in the park

[0059] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[0060] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[0061] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[0062] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[0063] In this way, the present invention provides a system that allows all parties involved to respond quickly and appropriately.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] The device obtains current location information and surrounding sensor information (e.g., camera and microphone data) from the GPS module and sensors.

[0067] Step 2:

[0068] The device filters and analyzes the acquired location and sensor information based on the common language "Feel!!" If an abnormal sound or image of a person is detected, the information is identified as an event.

[0069] Step 3:

[0070] The device compiles the analysis results into a data packet and sends it to the server. The transmitted data includes location information, sensor information, and the analysis results.

[0071] Step 4:

[0072] The server analyzes the data packets received from the device and determines whether a specific action is required. For example, if it determines that the device may be lost, it proceeds to the next step.

[0073] Step 5:

[0074] The server generates behavioral information as needed, which includes specific actions the user should take (e.g., "notify a nearby parent / guardian").

[0075] Step 6:

[0076] The server transmits the generated behavioral information to multiple related devices, with the transmission range limited to the vicinity of the location where the lost child was found.

[0077] Step 7:

[0078] The device notifies the user of the behavioral information received from the server, for example, by a pop-up message on the screen or an audio alert.

[0079] Step 8:

[0080] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying a nearby parent.

[0081] Step 9:

[0082] Users submit information about their lost children through the application, which can include photos and text descriptions.

[0083] Step 10:

[0084] The server receives information posted by users, determines whether it is necessary to notify other users, evaluates the reliability of the posted information, and awards tokens to highly rated information providers.

[0085] Step 11:

[0086] The server updates the reliability score of the information provider and grants rewards (e.g., tokens) based on the rating. Highly rated information providers are awarded more tokens, which act as an incentive for them to provide information next time.

[0087] Through this procedure, the present invention provides a system that can respond quickly and appropriately, and can promote active participation by information providers.

[0088] Example 1

[0089] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0090] Conventional systems have had problems in that it is difficult to quickly grasp the surrounding situation and take appropriate action. In addition, the reliability of information provided by users is not evaluated sufficiently, and incentives are not provided, resulting in insufficient information provision.

[0091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0092] In this invention, the server includes means for acquiring peripheral information, means for filtering and analyzing the acquired peripheral information based on a common language, and means for recognizing a specific event based on the analysis results, thereby enabling the server to quickly grasp the surrounding situation and respond quickly to the specific event.

[0093] "Peripheral information" is a general term for data related to the surrounding environment, such as location information and sensor information acquired by a terminal.

[0094] A "common language" refers to a unified protocol or format used when exchanging data between multiple devices or software, and in this system it refers to "Feel!!".

[0095] "Filtering" refers to the process of selecting necessary data from the acquired peripheral information and removing unnecessary data.

[0096] "Analysis" refers to the process of detecting specific patterns or anomalies based on the data selected by the filters.

[0097] An "event" refers to a specific occurrence or situation that is recognized as a result of analysis, such as a "child getting lost."

[0098] "Behavioral information" refers to specific instructions or notifications generated in response to a recognized event.

[0099] "Transmission" refers to sending the generated behavioral information from the server to the corresponding terminal.

[0100] "Notification" refers to the act of the terminal conveying the transmitted behavioral information to the user.

[0101] "Reliability" is an index for evaluating the accuracy and usefulness of information provided by a user.

[0102] "Rewards" refer to incentives or tokens given to information providers based on their trustworthiness.

[0103] To implement this invention, a system consisting of a server, a terminal, and a user is used. The following hardware and software are required for the system to operate.

[0104] Acquisition and analysis of surrounding information

[0105] Device:

[0106] The device uses a built-in GPS module to obtain its current location, and is equipped with multiple sensors, including a camera, microphone, and thermometer, to collect data on the surrounding environment.

[0107] The device filters and analyzes the collected data based on the common language "Feel!!," which detects abnormal sounds, images, and temperature fluctuations and recognizes them as specific events such as a lost child.

[0108] Generation and transmission of behavioral information

[0109] server:

[0110] The server receives and analyzes location and sensor information sent from the device, using a high-speed analysis algorithm to analyze the received data and determine whether specific action is required.

[0111] The server generates behavioral information based on the analysis results and distributes it to the relevant devices. For example, if the server receives information about a lost child, it generates behavioral information such as "notify nearby parents."

[0112] Receiving and notifying behavioral information

[0113] Device:

[0114] The device receives the behavioral information sent from the server and notifies the user by displaying a pop-up message on the screen, allowing the user to take appropriate action.

[0115] Information provision and evaluation

[0116] User:

[0117] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[0118] Other users can rate the information they receive and provide feedback such as "This information was accurate" or "This information was helpful."

[0119] server:

[0120] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[0121] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[0122] Specific examples

[0123] Scenario: You find a lost child in the park

[0124] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[0125] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[0126] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[0127] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[0128] Example prompts to input to the generative AI model

[0129] Here is an example prompt to describe this system to a generative AI model:

[0130] Please explain in detail the response system when a lost child is found in a park. The system consists of a device, a server, and a user. The device uses GPS and a camera to collect location information and images and detect abnormalities. The server analyzes the received information and notifies a nearby parent. When the device receives the notification, it displays a message to the user. The user then takes appropriate action.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1: Obtaining and filtering surrounding information

[0133] The device uses a built-in GPS module to obtain its current location, and also uses sensors such as a camera, microphone, and thermometer to collect data about the surrounding environment.

[0134] Input: Location information from the GPS module, image data from the camera, audio data from the microphone, and temperature data from the thermometer.

[0135] Data processing: Data collected from sensors is filtered based on the common language "Feel!!" to remove unnecessary data.

[0136] Output: filtered location, image data, audio data, temperature data.

[0137] Specific operations: The device periodically reads the GPS module, the camera captures images at regular intervals, the microphone continuously records audio, and the thermometer measures the temperature in real time.

[0138] Step 2: Data analysis and event recognition

[0139] The device analyzes the filtered data and recognizes specific events (e.g., a child getting lost).

[0140] Input: filtered location information, image data, audio data, temperature data.

[0141] Data processing: Image analysis algorithms are used to detect anomalies, audio analysis algorithms to detect abnormal sounds (e.g. screaming or crying), and temperature data is analyzed to detect abnormal temperature fluctuations.

[0142] Output: Data recognized as a specific event (e.g., "Lost child found").

[0143] Specific operation: The device's internal software analyzes captured images and recorded audio, and if the captured images or audio exceed a set threshold, it tags the device as "lost."

[0144] Step 3: Generate and send behavioral information

[0145] The server receives the event data sent from the terminal, analyzes it, and generates specific behavioral information.

[0146] Input: Event data sent from the device (e.g., "Lost child").

[0147] Data processing: The server analyzes the received event data and determines whether specific actions are required. Based on the analysis results, it generates behavioral information.

[0148] Output: Generated action information (e.g., "Notify nearby parents about the lost child").

[0149] Specific operation: Based on the analysis results, the server generates a message stating, "A child has been lost in the northeast area of ​​the park. We are requesting the assistance of nearby parents." and creates a distribution list.

[0150] Step 4: Receiving and notifying behavioral information

[0151] The terminal receives the behavior information sent from the server and notifies the user.

[0152] Input: Behavioral information sent from the server (e.g., "A lost child has been found").

[0153] Data processing: The received behavioral information is stored in an internal queue and converted into a format for notifying the user.

[0154] Output: A notification message that will be displayed to the user (e.g., "A lost child has been found. Please help.").

[0155] Specific operation: A pop-up message will be displayed on the device display and an audio alert will be issued at the same time.

[0156] Step 5: Information and evaluation

[0157] Users use their devices to post information about lost children and other important information to the server, which analyzes and evaluates the information received and calculates the trustworthiness of the information provider.

[0158] Input: User-provided information (e.g., "I found a lost child in the northeast area").

[0159] Data processing: The server analyzes the posted information, determines its usefulness, and aggregates feedback from other users to calculate the rating of the information provider.

[0160] Output: Post information with usefulness rating and confidence points.

[0161] Specific operation: The server determines the usefulness based on the analysis results, aggregates feedback such as "This information was accurate" or "It was useful," and updates the reliability.

[0162] Step 6: Rewarding

[0163] The server rewards information providers who receive high ratings (e.g., tokens).

[0164] Input: Confidence points.

[0165] Data processing: Calculate and issue rewards to users who exceed a certain level of trust points.

[0166] Output: The token that is granted to the user.

[0167] Specific operation: The server automatically issues tokens that can be used on the system to users whose trust points exceed a threshold.

[0168] (Application example 1)

[0169] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0170] Conventional systems that acquire and analyze surrounding information lack the means to evaluate the reliability and usefulness of the information. Furthermore, security services such as detecting suspicious individuals and responding quickly to accidents require the ability to detect abnormal situations in real time and prompt appropriate responses. Furthermore, a mechanism is needed to appropriately evaluate the reliability of information providers and provide incentives for promptly providing useful information to users.

[0171] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0172] In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information, means for generating appropriate behavioral information based on the analysis results, means for transmitting the generated behavioral information, means for notifying the user of the received behavioral information, means for the user to evaluate the information received, and means for calculating the reliability of the information provider and generating a reward based on the evaluation. This allows the user to notice abnormal situations in real time and respond quickly, and makes it possible to encourage the provision of useful information through the reliability evaluation of the information provider.

[0173] "Around-the-world information" is data about the environment collected using various sensors such as a GPS module, a camera module, an audio sensor, and a temperature sensor.

[0174] "Analysis results" are information obtained as a result of data analysis performed on a server or terminal based on collected peripheral information.

[0175] "Behavioral information" is information that is generated by the server based on the analysis results and that instructs specific responses and actions.

[0176] "Reliability" is a numerical value calculated based on the accuracy and usefulness of the information provided by the user, based on the evaluations of other users and the server's analysis.

[0177] A "reward" is an incentive given to an information provider based on a reliability evaluation, and may take the form of points or tokens, for example.

[0178] "Security event" means an abnormal situation such as a suspicious person, fire, or accident detected by the system.

[0179] A "notification" is a message or alert sent from a server to a user terminal, and is information that prompts the user to take necessary action or take caution.

[0180] A "generative AI model" is an artificial intelligence that learns patterns and trends from large amounts of data and generates appropriate action information or notifications for specific inputs.

[0181] A "prompt" is text that is input as an instruction or question to a generative AI model and is used to control the AI's behavior.

[0182] To implement this invention, the following system and program are used: The system mainly comprises a server, a terminal, and a user.

[0183] Acquisition and analysis of surrounding information

[0184] The device acquires its current location using a built-in GPS module. It also has various sensors, such as a camera, microphone, and thermometer, which it uses to collect data on the surrounding situation. The device filters and analyzes the collected data. Specifically, it recognizes sound, video, and temperature fluctuations as specific security events, such as the presence of a suspicious person.

[0185] Generation and transmission of behavioral information

[0186] The server receives location information and sensor information sent from the device. It analyzes this information and determines whether specific action is necessary. Based on the analysis results, such as the location information of suspicious individuals and abnormal temperature fluctuations, the server generates behavioral information such as "notify security guards" or "warn the user." This generated behavioral information is distributed from the server to multiple relevant devices, enabling a prompt response.

[0187] Receiving and notifying behavioral information

[0188] When the device receives the behavioral information sent from the server, it notifies the user. For example, a pop-up message saying "A suspicious person has been detected. Please be careful" can be displayed on the screen of a smartphone or smart glasses. The user can receive this notification and take appropriate action.

[0189] Information provision and evaluation

[0190] Users can use their own devices to post nearby security information. This information is sent to the server and shared with other users. Other users can rate the information they receive, for example, rating it as "this information was accurate" or "helpful." The server receives the information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings from other users. Information providers who receive high ratings are awarded tokens as a reward. This gives users an incentive to provide more information proactively.

[0191] Hardware and software used

[0192] The system is implemented using the following hardware and software:

[0193] Hardware: Smartphone, smart glasses (camera, microphone, GPS sensor, thermometer)

[0194] software:

[0195] GPS module (location information acquisition)

[0196] Camera module (image acquisition)

[0197] Microphone module (voice acquisition)

[0198] Thermometer module (temperature acquisition)

[0199] Server-side software:

[0200] Data reception and analysis system (Python, Flask, or other web frameworks)

[0201] Notification sending system (Push notification API)

[0202] Generative AI models:

[0203] AI models that learn patterns and trends from large amounts of data and generate appropriate actionable information or notifications for specific inputs

[0204] Specific examples

[0205] For example, consider a suspicious person detection application in a park. If a device detects a unique sound (scream, glass breaking), an abnormal temperature change, or significant camera movement in the park, it sends that data to a server. The server analyzes this information and immediately generates behavioral information such as "A suspicious person has been detected in the park. Please be careful," and notifies nearby parents, security guards, etc.

[0206] Example prompts for generative AI models

[0207] "How can I implement an application that collects sensor information needed to detect suspicious activity in busy areas of a park, analyzes it, and generates appropriate notifications?"

[0208] Collect data from various sensors (camera, microphone, thermometer, GPS).

[0209] The data is sent to the server and analyzed on the server side.

[0210] Receives notifications from the server and notifies the user.

[0211] In this way, the present invention provides a security service system that allows all parties involved to respond quickly and appropriately.

[0212] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0213] Step 1:

[0214] The device uses its built-in GPS module, camera, microphone, and thermometer to collect current location information and surrounding situation data.

[0215] Specific operations: The GPS module obtains the current location, the camera captures surrounding images, the microphone records audio, and the thermometer measures the surrounding temperature.

[0216] Input: Location information from GPS, video data from camera, audio data from microphone, temperature data from temperature sensor.

[0217] Output: A set of acquired location information, video data, audio data, and temperature data.

[0218] Step 2:

[0219] The device filters and analyzes the collected data, specifically analyzing audio, video, and temperature fluctuations to identify specific security events.

[0220] How it works: It uses analytical algorithms to detect abnormal sounds, images, and temperature fluctuations, and tags them as "suspicious person" or "abnormal temperature."

[0221] Input: A set of location information, video data, audio data, and temperature data.

[0222] Output: Abnormal event information as the analysis result (e.g., "suspicious person" or "abnormal temperature").

[0223] Step 3:

[0224] The terminal transmits the analysis results to the server.

[0225] Specific operation: The analysis results are packaged in JSON format and sent to the server using an HTTP POST request.

[0226] Input: Abnormal event information.

[0227] Output: JSON formatted data sent to the server.

[0228] Step 4:

[0229] The server receives and analyzes the location and sensor information sent from the device, and generates specific behavioral information based on this information.

[0230] Specific operation: Recorded in a database on the server side, and an analysis algorithm is applied to generate action information such as "notify security guard" or "warn user."

[0231] Input: Location information, video data, audio data, and temperature data sent from the device.

[0232] Output: Action information (e.g., "Notify security" or "Alert user").

[0233] Step 5:

[0234] The server distributes the generated behavioral information to the corresponding terminals.

[0235] Specific behavior: Send a message containing behavioral information using the push notification system.

[0236] Input: Behavioral information.

[0237] Output: Notifications delivered to the device.

[0238] Step 6:

[0239] The terminal receives the behavioral information sent from the server and notifies the user.

[0240] Specific behavior: A pop-up message will be displayed on the device screen and sound or vibration will be emitted to alert the user.

[0241] Input: Behavioral information sent from the server.

[0242] Output: Notifications via popup message, sound and vibration.

[0243] Step 7:

[0244] The user checks the notification and takes appropriate action.

[0245] Specific actions: The user checks the notification on the screen and, if necessary, takes specific action, such as spotting and reporting a suspicious person in the park.

[0246] Input: Notifications displayed on the device.

[0247] Output: The user's specific response action (e.g., finding and reporting a suspicious person).

[0248] Step 8:

[0249] The user evaluates the received information and sends feedback to the server via his / her terminal.

[0250] Specific operations: Press the rating button, enter a comment, etc., and send the rating information to the server.

[0251] Input: User rating information and feedback.

[0252] Output: Rating information and feedback sent to the server.

[0253] Step 9:

[0254] The server receives the rating information from the user, calculates the reliability of the information provider, and generates a reward based on the rating.

[0255] Specific operation: The received evaluation information is recorded in a database, an analysis algorithm is applied to calculate the trustworthiness of the information provider, and a token is generated according to the evaluation.

[0256] Input: Rating information from users.

[0257] Output: Calculated informant confidence and generated reward tokens.

[0258] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0259] To implement this invention, a program that combines a system including a server, a terminal, and a user with an emotion engine is used. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, as well as the emotion engine that recognizes the user's emotions.

[0260] Acquisition and analysis of surrounding information

[0261] Device:

[0262] The device acquires surrounding information using a built-in GPS module and various sensors (camera, microphone, thermometer, etc.).

[0263] The acquired information is filtered and analyzed using the common language "Feel!!" For example, if an abnormal sound or image is detected, this information is identified as a specific event such as a "lost child."

[0264] Implementing the Emotion Engine

[0265] Device:

[0266] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes camera images, voice input, and text input to determine the user's emotional state.

[0267] The emotion engine generates emotion data by analyzing the user's facial expressions, tone of voice, and choice of words, and this data reflects the user's changing emotions in real time.

[0268] Generation and transmission of behavioral information

[0269] server:

[0270] The server receives surrounding information and emotion data sent from the device, analyzes this information, and determines whether specific action is required.

[0271] When generating behavioral information, emotional data may also be taken into consideration as necessary. For example, if the user is in a panic, behavioral information including advice on how to deal with the situation calmly may be generated.

[0272] The generated behavioral information is distributed from the server to a plurality of related terminals.

[0273] Receiving and notifying behavioral information

[0274] Device:

[0275] Receive notifications about behavioral information and emotions sent from the server, such as a message saying "Please stay calm."

[0276] After receiving the behavioral information, the user takes appropriate action based on the information.

[0277] Information provision and evaluation

[0278] User:

[0279] Users can post surrounding information and emotional data using their own devices, which is then sent to a server and shared with other users.

[0280] Other users can rate the information and the results of the ratings are sent to the server.

[0281] server:

[0282] The server analyzes the received posted information and emotional data and calculates the reliability score of the information provider.

[0283] Highly rated informants are awarded tokens, which are also adjusted based on data from the sentiment engine.

[0284] Specific examples

[0285] Scenario: You find a lost child in the park

[0286] 1. When the device finds a lost child in a park, it acquires GPS location information and camera footage, and identifies the child as "lost" using the common language "Feel!!" The emotion engine also detects anxiety or tension from the user's facial expressions and voice.

[0287] 2. The server receives this data and generates action information such as "notifying nearby parents of the lost child and encouraging the user to act calmly."

[0288] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian."

[0289] 4. The user receives a notification, protects the lost child, and notifies nearby parents. If the user's emotions change during this process, they are also monitored by the emotion engine and appropriate feedback is provided.

[0290] In addition to sharing information in real time and encouraging appropriate behavior, this system takes into account the user's emotional state, enabling even more accurate responses.

[0291] The processing flow will be explained below.

[0292] Step 1:

[0293] The device uses the GPS module and various sensors (camera, microphone, thermometer, etc.) to obtain current location information and surrounding sensor information.

[0294] Step 2:

[0295] The location and sensor information acquired by the device is filtered and analyzed based on the common language "Feel!!" For example, if an abnormal sound or image is detected, it will be identified as a "lost child" or "an abnormal situation."

[0296] Step 3:

[0297] The device uses an emotion engine to analyze the user's emotions and determine the user's current emotional state (e.g., anxiety, fear, panic) based on camera footage, microphone audio, and text input.

[0298] Step 4:

[0299] The device transmits the analyzed surrounding information and emotion data to the server. The transmitted data includes location information, sensor information, analysis results, and emotion data.

[0300] Step 5:

[0301] The server analyzes the data received from the device and determines whether a specific action is required. For example, if a child is lost in a specific location, it may determine that immediate action is required.

[0302] Step 6:

[0303] The server generates behavioral information based on the analysis results. The behavioral information includes specific actions the user should take (e.g., "stay calm and notify a nearby parent or guardian"). This information also takes into account emotional data, and may include a message to alleviate anxiety.

[0304] Step 7:

[0305] The server then transmits the generated behavioral information to related devices in the vicinity. The behavioral information is distributed only within the vicinity of the lost child's location.

[0306] Step 8:

[0307] The device notifies the user of the behavioral information and emotion notifications received from the server. For example, a message such as "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian" is displayed on the screen.

[0308] Step 9:

[0309] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying nearby parents.

[0310] Step 10:

[0311] Users submit information about their lost child through the application, including location, photos, a text description, and the user's emotional state.

[0312] Step 11:

[0313] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the reliability score of the information provider based on the ratings of other users.

[0314] Step 12:

[0315] The server will award tokens to highly rated information providers, which will provide users with an incentive to provide information.

[0316] Step 13:

[0317] The server updates the reliability scores of the information providers and distributes behavioral information to highly rated information providers with higher priority.

[0318] Through this series of processes, the present invention enables a quick and appropriate response and promotes behavior that takes into consideration the user's feelings.

[0319] Example 2

[0320] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0321] Although conventional systems were able to acquire and analyze peripheral information, they were unable to generate appropriate behavioral information that took the user's emotional state into account. Furthermore, they lacked a mechanism for evaluating highly reliable information providers and providing rewards based on that evaluation. This resulted in problems such as insufficient assurance of the reliability of information and the appropriateness of responses.

[0322] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information using a common language, emotion recognition means for recognizing the user's emotion, means for generating appropriate behavioral information based on the analysis result and the emotion recognition result, means for transmitting the generated behavioral information, and means for notifying the user of the received behavioral information. This enables highly accurate analysis of the peripheral information and appropriate responses that take into account the user's emotional state. In addition, the reliability of the information can be improved by providing rewards to highly reliable information providers.

[0323] "Around-the-world information" is data that indicates the user and their surroundings, such as location information, sensor information, and camera images and audio.

[0324] "Means for acquiring" refers to a device or function for capturing surrounding information using hardware devices such as a GPS module, camera, microphone, thermometer, etc.

[0325] "Means for analysis using a common language" refers to algorithms or software that filter and analyze surrounding information based on a common language such as "Feel!!" to identify specific events.

[0326] "Emotion recognition means for recognizing user emotions" refers to software or algorithms that analyze camera images, voice input, and text input to determine the user's emotional state from their facial expressions, tone of voice, and choice of words.

[0327] The "means for generating behavioral information" refers to a device or software for creating information to encourage the user to take specific and appropriate behavior based on the analysis results and emotion recognition results.

[0328] The "means for transmitting behavioral information" is a device or function for transmitting the generated behavioral information to the associated terminal via a network.

[0329] The "means for notifying the user of the behavioral information" refers to a device or function for visually or audibly conveying the received behavioral information to the user.

[0330] The "trustworthiness of information provider" is an index for evaluating the degree of contribution and trustworthiness of a user who posted peripheral information and emotion data.

[0331] The "rewarding means" is a device or function for providing rewards such as tokens or points to users based on their trustworthiness.

[0332] MODE FOR CARRYING OUT THE INVENTION

[0333] This invention can be implemented in a system including a server, a terminal, and a user. It also uses a program that combines an emotion engine. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, and is characterized by an emotion engine that recognizes the user's emotions.

[0334] Hardware and software used

[0335] Device:

[0336] GPS module (acquisition of location information)

[0337] Camera (image and video capture)

[0338] Microphone (audio capture)

[0339] Thermometer (acquiring temperature information)

[0340] Emotion engine (analysis of user's emotional state)

[0341] server:

[0342] Data analysis engine (analysis of peripheral information and emotional data)

[0343] Behavioral information generation module (generating behavioral information based on analysis results)

[0344] Communication module (sending and receiving behavioral information)

[0345] Trustworthiness evaluation engine (calculating the trustworthiness of information providers)

[0346] User:

[0347] Data submission via terminal operation

[0348] Reviewing received behavioral information and taking appropriate action

[0349] Examples of data processing and data calculation

[0350] Obtaining surrounding information:

[0351] The device uses its built-in GPS module, camera, microphone, and thermometer to collect information about its surroundings. For example, if the device is in a park, it can collect location information (GPS), camera footage and photos taken on the spot, surrounding audio (microphone), and temperature information (thermometer).

[0352] Surrounding area analysis:

[0353] The device uses the common language "Feel!!" to filter and analyze the surrounding information it acquires. For example, it can detect a crying child from camera footage and recognize the child's crying from audio data. This allows it to identify the event as a "lost child."

[0354] Emotion engine implementation:

[0355] The device is equipped with an emotion engine that analyzes camera images, voice input, and text input to determine the user's emotional state. For example, if the user has an anxious expression, it can detect this and determine from the tone of the user's voice that they are in a tense state.

[0356] Behavioral information generation:

[0357] The server receives and analyzes the surrounding information and emotional data sent from the device. For example, the server receives "information about a lost child" and the user's "anxiety" and generates behavioral information according to the situation. Specifically, it generates behavioral information such as "notify a nearby parent to calmly deal with the situation."

[0358] Sending behavioral information and notifications:

[0359] The server distributes the generated behavioral information to multiple related devices. For example, the server may send a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[0360] Information provision and reliability assessment:

[0361] Users can post surrounding information and emotional data using their devices, and that information is sent to the server and shared with other users. For example, a user can post a message saying, "I found a lost child," along with a photo or video. The server analyzes this information, evaluates the trustworthiness of the information provider, and then awards a token based on that evaluation.

[0362] Examples of prompt statements

[0363] "Please explain how a user who finds a lost child in a park should respond by generating behavioral information based on data from the emotion engine and notifying nearby parents."

[0364] The above is a specific embodiment for carrying out the invention. This system enables real-time information sharing and appropriate behavior promotion, and in particular, enables quick and appropriate responses that take into account the user's emotional state.

[0365] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0366] Step 1: Obtaining surrounding information

[0367] The device acquires surrounding information using a GPS module, camera, microphone, and thermometer. The inputs include the current geographical location (GPS), camera footage, video, audio (microphone), and temperature data. By collecting these data, the user's surroundings can be understood. The output is a dataset of acquired surrounding information.

[0368] Example: The device takes photos of the surroundings with a camera, obtains location information from GPS, records surrounding audio with a microphone, and measures the ambient temperature with a thermometer.

[0369] Step 2: Analyze surrounding information

[0370] The device analyzes the acquired surrounding information using the common language "Feel!!". The input is the surrounding information dataset acquired in step 1. This is analyzed to identify specific events (e.g., abnormal sound or video detection). The output is filtered and analyzed event data.

[0371] Example: The device analyzes camera footage to detect a child's crying face, and analyzes audio data acquired from the microphone to identify the "child's crying sound."

[0372] Step 3: Recognize emotions

[0373] The device uses an emotion recognition engine to recognize the user's emotional state. Inputs include the user's facial image (camera), tone of voice (microphone), and text input. These are analyzed to generate the user's emotional data. The output is the analyzed emotional data.

[0374] Example: The device camera captures the user's face, and the emotion recognition engine detects an "anxious expression." The microphone analyzes the tone of the voice and determines that the user is in a tense state.

[0375] Step 4: Generate behavioral information

[0376] The server receives and analyzes the surrounding information and emotional data sent from the device. The inputs are the surrounding information and emotional data. Based on this, it determines the necessary response and generates specific behavioral information. The output is behavioral information that requires a response.

[0377] Example: The server receives "information about the lost child" and "user anxiety data" and generates action information such as "notify a nearby parent so that the situation can be dealt with calmly."

[0378] Step 5: Sending behavioral information and notifications

[0379] The server sends the generated behavioral information to the related terminals. The input is the generated behavioral information. This is notified to the terminals via the network. The output is the behavioral information sent to each terminal.

[0380] Example: The server sends a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[0381] Step 6: Provide information

[0382] Users can post surrounding information and emotional data from their own devices. The inputs include surrounding information (GPS, camera footage, etc.) and emotional data. These are sent to a server. The output is the posted information aggregated on the server.

[0383] Example: A user posts a message saying "I found my lost child" and a photo. This is sent to the server.

[0384] Step 7: Evaluate and reward your information

[0385] The server analyzes the received posted information and emotion data to evaluate the trustworthiness of the information provider. The inputs are the posted information and evaluation data. Based on this, a trustworthiness score is calculated and a reward is awarded. The output is a trustworthiness score and a reward (e.g., tokens).

[0386] Example: The server recognizes the posted information as highly rated and gives a token to the information provider.

[0387] (Application example 2)

[0388] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0389] In conventional brick-and-mortar stores, it was difficult to grasp the emotional state of customers in real time and provide services that corresponded to that state. Furthermore, improving the customer experience and managing in-store safety required a great deal of effort, making it difficult to provide efficient customer support. As a result, there were concerns about a decline in customer satisfaction and the occurrence of problems. In response, there was a need for a system that could improve customer satisfaction by utilizing customer emotional data and providing appropriate support.

[0390] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0391] In this invention, the server is configured with a means for acquiring peripheral information, a means for analyzing the acquired peripheral information and emotional data, a means for generating appropriate behavioral information based on the analysis results and emotional data, a means for transmitting the generated behavioral information, and a means for notifying the user and store staff of the received behavioral information. This makes it possible to grasp the emotional state of the customer in real time and provide prompt and appropriate support according to that state.

[0392] A "means for acquiring surrounding information" is a device that uses sensors such as a camera, microphone, or thermometer to collect various data about a specific location or environment.

[0393] The "means for analyzing peripheral information and emotional data" refers to algorithms or software for analyzing the collected peripheral information and the user's emotional data and determining their contents.

[0394] "Emotion data" is data that indicates the user's emotional state and is generated by analyzing the user's facial expressions, tone of voice, choice of words, etc.

[0395] "Means for generating appropriate behavioral information" refers to algorithms or software that determine specific actions that users and store staff should take based on analysis results and emotional data.

[0396] A "generative AI model" is a trained model that uses artificial intelligence to generate behavioral information and provides appropriate output in response to specific prompts.

[0397] A "prompt" is an instruction to be input into a generative AI model, and is text that contains specific instructions for generating behavioral information appropriate to a specific situation.

[0398] The "means for transmitting behavioral information" is a communication system for transmitting the generated behavioral information to other devices or users.

[0399] The "means for notifying the user and store staff of the behavioral information" refers to a device or software for visually or audibly notifying the user and store staff of the received behavioral information.

[0400] To put this invention into practice, it is necessary to build a system that collects and analyzes peripheral information and emotional data, and generates and distributes appropriate behavioral information. This system is mainly composed of three components: a server, a terminal, and a user.

[0401] Acquisition and analysis of surrounding information

[0402] Device:

[0403] The device is equipped with built-in sensors such as a camera, microphone, and thermometer. These sensors are used to acquire surrounding information. For example, the camera captures the customer's facial expressions, and the microphone collects the customer's tone of voice and words. The device also has a communication function to send this data to a server.

[0404] Examples:

[0405] In a physical store in a shopping mall, staff wearing smart glasses capture customers' facial expressions and tone of voice in real time.

[0406] Implementing the Emotion Engine

[0407] Device:

[0408] The device is equipped with an emotion engine that analyzes collected data and determines the user's emotional state. This engine generates emotion data by analyzing camera images, voice input, and text input. For example, if a customer is confused, the system will capture their facial expression and tone of voice and generate appropriate emotion data.

[0409] Examples:

[0410] In the same shopping mall scenario, the emotion engine detects signs of confusion in customers' facial expressions and picks up signs of stress from tone analysis.

[0411] Generation and transmission of behavioral information

[0412] server:

[0413] The server receives and analyzes the surrounding information and emotional data sent from the device. Using a generative AI model, it generates appropriate behavioral information based on the collected data. For example, a message might be generated saying, "The customer appears to be in trouble. Please contact a staff member for assistance." The generated behavioral information is then sent to each device using a prompt.

[0414] Examples:

[0415] The server receives the emotion data and generates behavioral information such as, "The customer is lost. Please instruct the customer to ask a staff member for help."

[0416] Receiving and notifying behavioral information

[0417] Device:

[0418] The device receives the behavioral information sent from the server and notifies the user of the information. The notification method is either visual (display display) or audio (voice alert). For example, a message such as "The customer is lost. Please provide support" may appear on the smart glasses display.

[0419] Examples:

[0420] The staff's smart glasses will display a message saying, "A customer is confused. Please assist," prompting a quick response.

[0421] Information provision and evaluation

[0422] User:

[0423] Users can post surrounding information and emotional data using their own devices. This information is sent to the server and shared with other users. Ratings from other users are also collected and calculated as a reliability score. Rewards are awarded to highly reliable information providers.

[0424] Examples:

[0425] The system rewards staff who consistently provide accurate information with tokens, providing an incentive.

[0426] Generative AI model prompt

[0427] The following prompt sentences are examples of behavioral information generated based on emotion data:

[0428] The customer seems confused. Please message a staff member for immediate assistance.

[0429]

[0430] Your customers are having fun. Send them a thank you message: "Thank you for visiting us. We hope you continue to enjoy your time."

[0431] In this way, by accurately analyzing emotional data and generating and distributing appropriate behavioral information, we can expect to improve customer experience and safety management in physical stores.

[0432] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0433] Step 1:

[0434] Obtaining surrounding information

[0435] The device collects surrounding information using sensors such as a built-in camera, microphone, and thermometer. Specifically, the camera captures the customer's facial expression, and the microphone records the customer's tone of voice and words. This allows the device to obtain facial image, voice data, and temperature data of the customer as input.

[0436] Step 2:

[0437] Generating emotion data

[0438] The device analyzes the acquired peripheral information using an emotion engine. The collected facial expression images are subjected to facial recognition using OpenCV, and the resulting data is used to determine emotions. Meanwhile, the voice data is converted to text using the SpeechRecognition library, and the text is then analyzed using an NLP model to generate emotion data. This outputs emotion data that indicates the customer's emotional state.

[0439] Step 3:

[0440] Sending data

[0441] The device sends the generated emotion data and peripheral information to the server. At this time, the data is encrypted and sent using a secure communication protocol (e.g., HTTPS). The emotion data and peripheral information are treated as input and sent to the server.

[0442] Step 4:

[0443] Generation of behavioral information

[0444] The server receives the emotion data and peripheral information sent from the device. Using a generative AI model, it generates appropriate behavioral information based on this data. For example, if the emotion data indicates "confusion," the server generates a prompt statement such as, "The customer is in trouble. Please instruct the customer to ask a staff member for help." The input is the emotion data and peripheral information, and the output is the generated behavioral information.

[0445] Step 5:

[0446] Sending behavioral information

[0447] The server transmits the generated behavioral information to the user's and store staff's terminals. This transmission is also performed using a secure communication protocol. The input is the generated behavioral information, and the output is a behavioral guidance message sent to the store staff's terminal.

[0448] Step 6:

[0449] Notification of behavioral information

[0450] The terminal notifies the user and store staff of the behavioral information received from the server. Specifically, a message saying "A customer is in trouble. Please provide support" is displayed on the display of the smart glasses or smartphone. The input is the behavioral information sent from the server, and the output is a notification transmitted to the user and store staff.

[0451] Step 7:

[0452] Behavioral evaluation and feedback

[0453] The user responds based on the provided behavioral information and reports the results to the system. The response is then evaluated by other users and by automatic analysis. The evaluation results are sent to the server and accumulated as the information provider's credibility score. The input is the results of the behavioral information implementation and user feedback, and the output is the evaluation results and credibility score.

[0454] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0455] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0456] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0457] [Second embodiment]

[0458] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0459] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0460] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0461] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0462] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0463] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0464] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0465] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0466] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0467] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0468] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0469] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0470] To implement the present invention, the following system and program are used: The system is mainly composed of a server, a terminal, and a user.

[0471] Acquisition and analysis of surrounding information

[0472] Device:

[0473] The device acquires its current location using a built-in GPS module, and also uses sensors such as a camera, microphone, and thermometer to collect data on the surrounding environment.

[0474] The device filters and analyzes the collected data based on the common language "Feel!!" For example, if the device detects an abnormal sound, image, or temperature fluctuation, it will recognize this as a specific event, such as a "lost child."

[0475] Generation and transmission of behavioral information

[0476] server:

[0477] The server receives location and sensor information sent from the device, analyzes this information, and determines whether specific action is required.

[0478] For example, if the server receives location information of a child who appears to be lost in a park, it generates action information such as "notify a nearby parent."

[0479] The generated behavioral information is distributed from the server to the relevant devices, enabling a rapid response.

[0480] Receiving and notifying behavioral information

[0481] Device:

[0482] When the terminal receives the behavioral information sent from the server, it notifies the user by, for example, displaying a pop-up message on the screen to alert the user.

[0483] The user is notified and can take appropriate action.

[0484] Information provision and evaluation

[0485] User:

[0486] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[0487] Other users can rate the information they receive, for example, saying "this information was accurate" or "this information was helpful."

[0488] server:

[0489] The server receives information posted by users, analyzes the content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[0490] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[0491] Specific examples

[0492] Scenario: You find a lost child in the park

[0493] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[0494] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[0495] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[0496] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[0497] In this way, the present invention provides a system that allows all parties involved to respond quickly and appropriately.

[0498] The processing flow will be explained below.

[0499] Step 1:

[0500] The device obtains current location information and surrounding sensor information (e.g., camera and microphone data) from the GPS module and sensors.

[0501] Step 2:

[0502] The device filters and analyzes the acquired location and sensor information based on the common language "Feel!!" If an abnormal sound or image of a person is detected, the information is identified as an event.

[0503] Step 3:

[0504] The device compiles the analysis results into a data packet and sends it to the server. The transmitted data includes location information, sensor information, and the analysis results.

[0505] Step 4:

[0506] The server analyzes the data packets received from the device and determines whether a specific action is required. For example, if it determines that the device may be lost, it proceeds to the next step.

[0507] Step 5:

[0508] The server generates behavioral information as needed, which includes specific actions the user should take (e.g., "notify a nearby parent / guardian").

[0509] Step 6:

[0510] The server transmits the generated behavioral information to multiple related devices, with the transmission range limited to the vicinity of the location where the lost child was found.

[0511] Step 7:

[0512] The device notifies the user of the behavioral information received from the server, for example, by a pop-up message on the screen or an audio alert.

[0513] Step 8:

[0514] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying a nearby parent.

[0515] Step 9:

[0516] Users submit information about their lost children through the application, which can include photos and text descriptions.

[0517] Step 10:

[0518] The server receives information posted by users, determines whether it is necessary to notify other users, evaluates the reliability of the posted information, and awards tokens to highly rated information providers.

[0519] Step 11:

[0520] The server updates the reliability score of the information provider and grants rewards (e.g., tokens) based on the rating. Highly rated information providers are awarded more tokens, which act as an incentive for them to provide information next time.

[0521] Through this procedure, the present invention provides a system that can respond quickly and appropriately, and can promote active participation by information providers.

[0522] Example 1

[0523] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0524] Conventional systems have had problems in that it is difficult to quickly grasp the surrounding situation and take appropriate action. In addition, the reliability of information provided by users is not evaluated sufficiently, and incentives are not provided, resulting in insufficient information provision.

[0525] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0526] In this invention, the server includes means for acquiring peripheral information, means for filtering and analyzing the acquired peripheral information based on a common language, and means for recognizing a specific event based on the analysis results, thereby enabling the server to quickly grasp the surrounding situation and respond quickly to the specific event.

[0527] "Peripheral information" is a general term for data related to the surrounding environment, such as location information and sensor information acquired by a terminal.

[0528] A "common language" refers to a unified protocol or format used when exchanging data between multiple devices or software, and in this system it refers to "Feel!!".

[0529] "Filtering" refers to the process of selecting necessary data from the acquired peripheral information and removing unnecessary data.

[0530] "Analysis" refers to the process of detecting specific patterns or anomalies based on the data selected by the filters.

[0531] An "event" refers to a specific occurrence or situation that is recognized as a result of analysis, such as a "child getting lost."

[0532] "Behavioral information" refers to specific instructions or notifications generated in response to a recognized event.

[0533] "Transmission" refers to sending the generated behavioral information from the server to the corresponding terminal.

[0534] "Notification" refers to the act of the terminal conveying the transmitted behavioral information to the user.

[0535] "Reliability" is an index for evaluating the accuracy and usefulness of information provided by a user.

[0536] "Rewards" refer to incentives or tokens given to information providers based on their trustworthiness.

[0537] To implement this invention, a system consisting of a server, a terminal, and a user is used. The following hardware and software are required for the system to operate.

[0538] Acquisition and analysis of surrounding information

[0539] Device:

[0540] The device uses a built-in GPS module to obtain its current location, and is equipped with multiple sensors, including a camera, microphone, and thermometer, to collect data on the surrounding environment.

[0541] The device filters and analyzes the collected data based on the common language "Feel!!," which detects abnormal sounds, images, and temperature fluctuations and recognizes them as specific events such as a lost child.

[0542] Generation and transmission of behavioral information

[0543] server:

[0544] The server receives and analyzes location and sensor information sent from the device, using a high-speed analysis algorithm to analyze the received data and determine whether specific action is required.

[0545] The server generates behavioral information based on the analysis results and distributes it to the relevant devices. For example, if the server receives information about a lost child, it generates behavioral information such as "notify nearby parents."

[0546] Receiving and notifying behavioral information

[0547] Device:

[0548] The device receives the behavioral information sent from the server and notifies the user by displaying a pop-up message on the screen, allowing the user to take appropriate action.

[0549] Information provision and evaluation

[0550] User:

[0551] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[0552] Other users can rate the information they receive and provide feedback such as "This information was accurate" or "This information was helpful."

[0553] server:

[0554] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[0555] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[0556] Specific examples

[0557] Scenario: You find a lost child in the park

[0558] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[0559] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[0560] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[0561] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[0562] Example prompts to input to the generative AI model

[0563] Here is an example prompt to describe this system to a generative AI model:

[0564] Please explain in detail the response system when a lost child is found in a park. The system consists of a device, a server, and a user. The device uses GPS and a camera to collect location information and images and detect abnormalities. The server analyzes the received information and notifies a nearby parent. When the device receives the notification, it displays a message to the user. The user then takes appropriate action.

[0565] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0566] Step 1: Obtaining and filtering surrounding information

[0567] The device uses a built-in GPS module to obtain its current location, and also uses sensors such as a camera, microphone, and thermometer to collect data about the surrounding environment.

[0568] Input: Location information from the GPS module, image data from the camera, audio data from the microphone, and temperature data from the thermometer.

[0569] Data processing: Data collected from sensors is filtered based on the common language "Feel!!" to remove unnecessary data.

[0570] Output: filtered location, image data, audio data, temperature data.

[0571] Specific operations: The device periodically reads the GPS module, the camera captures images at regular intervals, the microphone continuously records audio, and the thermometer measures the temperature in real time.

[0572] Step 2: Data analysis and event recognition

[0573] The device analyzes the filtered data and recognizes specific events (e.g., a child getting lost).

[0574] Input: filtered location information, image data, audio data, temperature data.

[0575] Data processing: Image analysis algorithms are used to detect anomalies, audio analysis algorithms to detect abnormal sounds (e.g. screaming or crying), and temperature data is analyzed to detect abnormal temperature fluctuations.

[0576] Output: Data recognized as a specific event (e.g., "Lost child found").

[0577] Specific operation: The device's internal software analyzes captured images and recorded audio, and if the captured images or audio exceed a set threshold, it tags the device as "lost."

[0578] Step 3: Generate and send behavioral information

[0579] The server receives the event data sent from the terminal, analyzes it, and generates specific behavioral information.

[0580] Input: Event data sent from the device (e.g., "Lost child").

[0581] Data processing: The server analyzes the received event data and determines whether specific actions are required. Based on the analysis results, it generates behavioral information.

[0582] Output: Generated action information (e.g., "Notify nearby parents about the lost child").

[0583] Specific operation: Based on the analysis results, the server generates a message stating, "A child has been lost in the northeast area of ​​the park. We are requesting the assistance of nearby parents." and creates a distribution list.

[0584] Step 4: Receiving and notifying behavioral information

[0585] The terminal receives the behavior information sent from the server and notifies the user.

[0586] Input: Behavioral information sent from the server (e.g., "A lost child has been found").

[0587] Data processing: The received behavioral information is stored in an internal queue and converted into a format for notifying the user.

[0588] Output: A notification message that will be displayed to the user (e.g., "A lost child has been found. Please help.").

[0589] Specific operation: A pop-up message will be displayed on the device display and an audio alert will be issued at the same time.

[0590] Step 5: Information and evaluation

[0591] Users use their devices to post information about lost children and other important information to the server, which analyzes and evaluates the information received and calculates the trustworthiness of the information provider.

[0592] Input: User-provided information (e.g., "I found a lost child in the northeast area").

[0593] Data processing: The server analyzes the posted information, determines its usefulness, and aggregates feedback from other users to calculate the rating of the information provider.

[0594] Output: Post information with usefulness rating and confidence points.

[0595] Specific operation: The server determines the usefulness based on the analysis results, aggregates feedback such as "This information was accurate" or "It was useful," and updates the reliability.

[0596] Step 6: Rewarding

[0597] The server rewards information providers who receive high ratings (e.g., tokens).

[0598] Input: Confidence points.

[0599] Data processing: Calculate and issue rewards to users who exceed a certain level of trust points.

[0600] Output: The token that is granted to the user.

[0601] Specific operation: The server automatically issues tokens that can be used on the system to users whose trust points exceed a threshold.

[0602] (Application example 1)

[0603] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0604] Conventional systems that acquire and analyze surrounding information lack the means to evaluate the reliability and usefulness of the information. Furthermore, security services such as detecting suspicious individuals and responding quickly to accidents require the ability to detect abnormal situations in real time and prompt appropriate responses. Furthermore, a mechanism is needed to appropriately evaluate the reliability of information providers and provide incentives for promptly providing useful information to users.

[0605] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0606] In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information, means for generating appropriate behavioral information based on the analysis results, means for transmitting the generated behavioral information, means for notifying the user of the received behavioral information, means for the user to evaluate the information received, and means for calculating the reliability of the information provider and generating a reward based on the evaluation. This allows the user to notice abnormal situations in real time and respond quickly, and makes it possible to encourage the provision of useful information through the reliability evaluation of the information provider.

[0607] "Around-the-world information" is data about the environment collected using various sensors such as a GPS module, a camera module, an audio sensor, and a temperature sensor.

[0608] "Analysis results" are information obtained as a result of data analysis performed on a server or terminal based on collected peripheral information.

[0609] "Behavioral information" is information that is generated by the server based on the analysis results and that instructs specific responses and actions.

[0610] "Reliability" is a numerical value calculated based on the accuracy and usefulness of the information provided by the user, based on the evaluations of other users and the server's analysis.

[0611] A "reward" is an incentive given to an information provider based on a reliability evaluation, and may take the form of points or tokens, for example.

[0612] "Security event" means an abnormal situation such as a suspicious person, fire, or accident detected by the system.

[0613] A "notification" is a message or alert sent from a server to a user terminal, and is information that prompts the user to take necessary action or take caution.

[0614] A "generative AI model" is an artificial intelligence that learns patterns and trends from large amounts of data and generates appropriate action information or notifications for specific inputs.

[0615] A "prompt" is text that is input as an instruction or question to a generative AI model and is used to control the AI's behavior.

[0616] To implement this invention, the following system and program are used: The system mainly comprises a server, a terminal, and a user.

[0617] Acquisition and analysis of surrounding information

[0618] The device acquires its current location using a built-in GPS module. It also has various sensors, such as a camera, microphone, and thermometer, which it uses to collect data on the surrounding situation. The device filters and analyzes the collected data. Specifically, it recognizes sound, video, and temperature fluctuations as specific security events, such as the presence of a suspicious person.

[0619] Generation and transmission of behavioral information

[0620] The server receives location information and sensor information sent from the device. It analyzes this information and determines whether specific action is necessary. Based on the analysis results, such as the location information of suspicious individuals and abnormal temperature fluctuations, the server generates behavioral information such as "notify security guards" or "warn the user." This generated behavioral information is distributed from the server to multiple relevant devices, enabling a prompt response.

[0621] Receiving and notifying behavioral information

[0622] When the device receives the behavioral information sent from the server, it notifies the user. For example, a pop-up message saying "A suspicious person has been detected. Please be careful" can be displayed on the screen of a smartphone or smart glasses. The user can receive this notification and take appropriate action.

[0623] Information provision and evaluation

[0624] Users can use their own devices to post nearby security information. This information is sent to the server and shared with other users. Other users can rate the information they receive, for example, rating it as "this information was accurate" or "helpful." The server receives the information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings from other users. Information providers who receive high ratings are awarded tokens as a reward. This gives users an incentive to provide more information proactively.

[0625] Hardware and software used

[0626] The system is implemented using the following hardware and software:

[0627] Hardware: Smartphone, smart glasses (camera, microphone, GPS sensor, thermometer)

[0628] software:

[0629] GPS module (location information acquisition)

[0630] Camera module (image acquisition)

[0631] Microphone module (voice acquisition)

[0632] Thermometer module (temperature acquisition)

[0633] Server-side software:

[0634] Data reception and analysis system (Python, Flask, or other web frameworks)

[0635] Notification sending system (Push notification API)

[0636] Generative AI models:

[0637] AI models that learn patterns and trends from large amounts of data and generate appropriate actionable information or notifications for specific inputs

[0638] Specific examples

[0639] For example, consider a suspicious person detection application in a park. If a device detects a unique sound (scream, glass breaking), an abnormal temperature change, or significant camera movement in the park, it sends that data to a server. The server analyzes this information and immediately generates behavioral information such as "A suspicious person has been detected in the park. Please be careful," and notifies nearby parents, security guards, etc.

[0640] Example prompts for generative AI models

[0641] "How can I implement an application that collects sensor information needed to detect suspicious activity in busy areas of a park, analyzes it, and generates appropriate notifications?"

[0642] Collect data from various sensors (camera, microphone, thermometer, GPS).

[0643] The data is sent to the server and analyzed on the server side.

[0644] Receives notifications from the server and notifies the user.

[0645] In this way, the present invention provides a security service system that allows all parties involved to respond quickly and appropriately.

[0646] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0647] Step 1:

[0648] The device uses its built-in GPS module, camera, microphone, and thermometer to collect current location information and surrounding situation data.

[0649] Specific operations: The GPS module obtains the current location, the camera captures surrounding images, the microphone records audio, and the thermometer measures the surrounding temperature.

[0650] Input: Location information from GPS, video data from camera, audio data from microphone, temperature data from temperature sensor.

[0651] Output: A set of acquired location information, video data, audio data, and temperature data.

[0652] Step 2:

[0653] The device filters and analyzes the collected data, specifically analyzing audio, video, and temperature fluctuations to identify specific security events.

[0654] How it works: It uses analytical algorithms to detect abnormal sounds, images, and temperature fluctuations, and tags them as "suspicious person" or "abnormal temperature."

[0655] Input: A set of location information, video data, audio data, and temperature data.

[0656] Output: Abnormal event information as the analysis result (e.g., "suspicious person" or "abnormal temperature").

[0657] Step 3:

[0658] The terminal transmits the analysis results to the server.

[0659] Specific operation: The analysis results are packaged in JSON format and sent to the server using an HTTP POST request.

[0660] Input: Abnormal event information.

[0661] Output: JSON formatted data sent to the server.

[0662] Step 4:

[0663] The server receives and analyzes the location and sensor information sent from the device, and generates specific behavioral information based on this information.

[0664] Specific operation: Recorded in a database on the server side, and an analysis algorithm is applied to generate action information such as "notify security guard" or "warn user."

[0665] Input: Location information, video data, audio data, and temperature data sent from the device.

[0666] Output: Action information (e.g., "Notify security" or "Alert user").

[0667] Step 5:

[0668] The server distributes the generated behavioral information to the corresponding terminals.

[0669] Specific behavior: Send a message containing behavioral information using the push notification system.

[0670] Input: Behavioral information.

[0671] Output: Notifications delivered to the device.

[0672] Step 6:

[0673] The terminal receives the behavioral information sent from the server and notifies the user.

[0674] Specific behavior: A pop-up message will be displayed on the device screen and sound or vibration will be emitted to alert the user.

[0675] Input: Behavioral information sent from the server.

[0676] Output: Notifications via popup message, sound and vibration.

[0677] Step 7:

[0678] The user checks the notification and takes appropriate action.

[0679] Specific actions: The user checks the notification on the screen and, if necessary, takes specific action, such as spotting and reporting a suspicious person in the park.

[0680] Input: Notifications displayed on the device.

[0681] Output: The user's specific response action (e.g., finding and reporting a suspicious person).

[0682] Step 8:

[0683] The user evaluates the received information and sends feedback to the server via his / her terminal.

[0684] Specific operations: Press the rating button, enter a comment, etc., and send the rating information to the server.

[0685] Input: User rating information and feedback.

[0686] Output: Rating information and feedback sent to the server.

[0687] Step 9:

[0688] The server receives the rating information from the user, calculates the reliability of the information provider, and generates a reward based on the rating.

[0689] Specific operation: The received evaluation information is recorded in a database, an analysis algorithm is applied to calculate the trustworthiness of the information provider, and a token is generated according to the evaluation.

[0690] Input: Rating information from users.

[0691] Output: Calculated informant confidence and generated reward tokens.

[0692] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0693] To implement this invention, a program that combines a system including a server, a terminal, and a user with an emotion engine is used. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, as well as the emotion engine that recognizes the user's emotions.

[0694] Acquisition and analysis of surrounding information

[0695] Device:

[0696] The device acquires surrounding information using a built-in GPS module and various sensors (camera, microphone, thermometer, etc.).

[0697] The acquired information is filtered and analyzed using the common language "Feel!!" For example, if an abnormal sound or image is detected, this information is identified as a specific event such as a "lost child."

[0698] Implementing the Emotion Engine

[0699] Device:

[0700] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes camera images, voice input, and text input to determine the user's emotional state.

[0701] The emotion engine generates emotion data by analyzing the user's facial expressions, tone of voice, and choice of words, and this data reflects the user's changing emotions in real time.

[0702] Generation and transmission of behavioral information

[0703] server:

[0704] The server receives surrounding information and emotion data sent from the device, analyzes this information, and determines whether specific action is required.

[0705] When generating behavioral information, emotional data may also be taken into consideration as necessary. For example, if the user is in a panic, behavioral information including advice on how to deal with the situation calmly may be generated.

[0706] The generated behavioral information is distributed from the server to a plurality of related terminals.

[0707] Receiving and notifying behavioral information

[0708] Device:

[0709] Receive notifications about behavioral information and emotions sent from the server, such as a message saying "Please stay calm."

[0710] After receiving the behavioral information, the user takes appropriate action based on the information.

[0711] Information provision and evaluation

[0712] User:

[0713] Users can post surrounding information and emotional data using their own devices, which is then sent to a server and shared with other users.

[0714] Other users can rate the information and the results of the ratings are sent to the server.

[0715] server:

[0716] The server analyzes the received posted information and emotional data and calculates the reliability score of the information provider.

[0717] Highly rated informants are awarded tokens, which are also adjusted based on data from the sentiment engine.

[0718] Specific examples

[0719] Scenario: You find a lost child in the park

[0720] 1. When the device finds a lost child in a park, it acquires GPS location information and camera footage, and identifies the child as "lost" using the common language "Feel!!" The emotion engine also detects anxiety or tension from the user's facial expressions and voice.

[0721] 2. The server receives this data and generates action information such as "notifying nearby parents of the lost child and encouraging the user to act calmly."

[0722] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian."

[0723] 4. The user receives a notification, protects the lost child, and notifies nearby parents. If the user's emotions change during this process, they are also monitored by the emotion engine and appropriate feedback is provided.

[0724] In addition to sharing information in real time and encouraging appropriate behavior, this system takes into account the user's emotional state, enabling even more accurate responses.

[0725] The processing flow will be explained below.

[0726] Step 1:

[0727] The device uses the GPS module and various sensors (camera, microphone, thermometer, etc.) to obtain current location information and surrounding sensor information.

[0728] Step 2:

[0729] The location and sensor information acquired by the device is filtered and analyzed based on the common language "Feel!!" For example, if an abnormal sound or image is detected, it will be identified as a "lost child" or "an abnormal situation."

[0730] Step 3:

[0731] The device uses an emotion engine to analyze the user's emotions and determine the user's current emotional state (e.g., anxiety, fear, panic) based on camera footage, microphone audio, and text input.

[0732] Step 4:

[0733] The device transmits the analyzed surrounding information and emotion data to the server. The transmitted data includes location information, sensor information, analysis results, and emotion data.

[0734] Step 5:

[0735] The server analyzes the data received from the device and determines whether a specific action is required. For example, if a child is lost in a specific location, it may determine that immediate action is required.

[0736] Step 6:

[0737] The server generates behavioral information based on the analysis results. The behavioral information includes specific actions the user should take (e.g., "stay calm and notify a nearby parent or guardian"). This information also takes into account emotional data, and may include a message to alleviate anxiety.

[0738] Step 7:

[0739] The server then transmits the generated behavioral information to related devices in the vicinity. The behavioral information is distributed only within the vicinity of the lost child's location.

[0740] Step 8:

[0741] The device notifies the user of the behavioral information and emotion notifications received from the server. For example, a message such as "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian" is displayed on the screen.

[0742] Step 9:

[0743] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying nearby parents.

[0744] Step 10:

[0745] Users submit information about their lost child through the application, including location, photos, a text description, and the user's emotional state.

[0746] Step 11:

[0747] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the reliability score of the information provider based on the ratings of other users.

[0748] Step 12:

[0749] The server will award tokens to highly rated information providers, which will provide users with an incentive to provide information.

[0750] Step 13:

[0751] The server updates the reliability scores of the information providers and distributes behavioral information to highly rated information providers with higher priority.

[0752] Through this series of processes, the present invention enables a quick and appropriate response and promotes behavior that takes into consideration the user's feelings.

[0753] Example 2

[0754] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0755] Although conventional systems were able to acquire and analyze peripheral information, they were unable to generate appropriate behavioral information that took the user's emotional state into account. Furthermore, they lacked a mechanism for evaluating highly reliable information providers and providing rewards based on that evaluation. This resulted in problems such as insufficient assurance of the reliability of information and the appropriateness of responses.

[0756] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information using a common language, emotion recognition means for recognizing the user's emotion, means for generating appropriate behavioral information based on the analysis result and the emotion recognition result, means for transmitting the generated behavioral information, and means for notifying the user of the received behavioral information. This enables highly accurate analysis of the peripheral information and appropriate responses that take into account the user's emotional state. In addition, the reliability of the information can be improved by providing rewards to highly reliable information providers.

[0757] "Around-the-world information" is data that indicates the user and their surroundings, such as location information, sensor information, and camera images and audio.

[0758] "Means for acquiring" refers to a device or function for capturing surrounding information using hardware devices such as a GPS module, camera, microphone, thermometer, etc.

[0759] "Means for analysis using a common language" refers to algorithms or software that filter and analyze surrounding information based on a common language such as "Feel!!" to identify specific events.

[0760] "Emotion recognition means for recognizing user emotions" refers to software or algorithms that analyze camera images, voice input, and text input to determine the user's emotional state from their facial expressions, tone of voice, and choice of words.

[0761] The "means for generating behavioral information" refers to a device or software for creating information to encourage the user to take specific and appropriate behavior based on the analysis results and emotion recognition results.

[0762] The "means for transmitting behavioral information" is a device or function for transmitting the generated behavioral information to the associated terminal via a network.

[0763] The "means for notifying the user of the behavioral information" refers to a device or function for visually or audibly conveying the received behavioral information to the user.

[0764] The "trustworthiness of information provider" is an index for evaluating the degree of contribution and trustworthiness of a user who posted peripheral information and emotion data.

[0765] The "rewarding means" is a device or function for providing rewards such as tokens or points to users based on their trustworthiness.

[0766] MODE FOR CARRYING OUT THE INVENTION

[0767] This invention can be implemented in a system including a server, a terminal, and a user. It also uses a program that combines an emotion engine. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, and is characterized by an emotion engine that recognizes the user's emotions.

[0768] Hardware and software used

[0769] Device:

[0770] GPS module (acquisition of location information)

[0771] Camera (image and video capture)

[0772] Microphone (audio capture)

[0773] Thermometer (acquiring temperature information)

[0774] Emotion engine (analysis of user's emotional state)

[0775] server:

[0776] Data analysis engine (analysis of peripheral information and emotional data)

[0777] Behavioral information generation module (generating behavioral information based on analysis results)

[0778] Communication module (sending and receiving behavioral information)

[0779] Trustworthiness evaluation engine (calculating the trustworthiness of information providers)

[0780] User:

[0781] Data submission via terminal operation

[0782] Reviewing received behavioral information and taking appropriate action

[0783] Examples of data processing and data calculation

[0784] Obtaining surrounding information:

[0785] The device uses its built-in GPS module, camera, microphone, and thermometer to collect information about its surroundings. For example, if the device is in a park, it can collect location information (GPS), camera footage and photos taken on the spot, surrounding audio (microphone), and temperature information (thermometer).

[0786] Surrounding area analysis:

[0787] The device uses the common language "Feel!!" to filter and analyze the surrounding information it acquires. For example, it can detect a crying child from camera footage and recognize the child's crying from audio data. This allows it to identify the event as a "lost child."

[0788] Emotion engine implementation:

[0789] The device is equipped with an emotion engine that analyzes camera images, voice input, and text input to determine the user's emotional state. For example, if the user has an anxious expression, it can detect this and determine from the tone of the user's voice that they are in a tense state.

[0790] Behavioral information generation:

[0791] The server receives and analyzes the surrounding information and emotional data sent from the device. For example, the server receives "information about a lost child" and the user's "anxiety" and generates behavioral information according to the situation. Specifically, it generates behavioral information such as "notify a nearby parent to calmly deal with the situation."

[0792] Sending behavioral information and notifications:

[0793] The server distributes the generated behavioral information to multiple related devices. For example, the server may send a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[0794] Information provision and reliability assessment:

[0795] Users can post surrounding information and emotional data using their devices, and that information is sent to the server and shared with other users. For example, a user can post a message saying, "I found a lost child," along with a photo or video. The server analyzes this information, evaluates the trustworthiness of the information provider, and then awards a token based on that evaluation.

[0796] Examples of prompt statements

[0797] "Please explain how a user who finds a lost child in a park should respond by generating behavioral information based on data from the emotion engine and notifying nearby parents."

[0798] The above is a specific embodiment for carrying out the invention. This system enables real-time information sharing and appropriate behavior promotion, and in particular, enables quick and appropriate responses that take into account the user's emotional state.

[0799] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0800] Step 1: Obtaining surrounding information

[0801] The device acquires surrounding information using a GPS module, camera, microphone, and thermometer. The inputs include the current geographical location (GPS), camera footage, video, audio (microphone), and temperature data. By collecting these data, the user's surroundings can be understood. The output is a dataset of acquired surrounding information.

[0802] Example: The device takes photos of the surroundings with a camera, obtains location information from GPS, records surrounding audio with a microphone, and measures the ambient temperature with a thermometer.

[0803] Step 2: Analyze surrounding information

[0804] The device analyzes the acquired surrounding information using the common language "Feel!!". The input is the surrounding information dataset acquired in step 1. This is analyzed to identify specific events (e.g., abnormal sound or video detection). The output is filtered and analyzed event data.

[0805] Example: The device analyzes camera footage to detect a child's crying face, and analyzes audio data acquired from the microphone to identify the "child's crying sound."

[0806] Step 3: Recognize emotions

[0807] The device uses an emotion recognition engine to recognize the user's emotional state. Inputs include the user's facial image (camera), tone of voice (microphone), and text input. These are analyzed to generate the user's emotional data. The output is the analyzed emotional data.

[0808] Example: The device camera captures the user's face, and the emotion recognition engine detects an "anxious expression." The microphone analyzes the tone of the voice and determines that the user is in a tense state.

[0809] Step 4: Generate behavioral information

[0810] The server receives and analyzes the surrounding information and emotional data sent from the device. The inputs are the surrounding information and emotional data. Based on this, it determines the necessary response and generates specific behavioral information. The output is behavioral information that requires a response.

[0811] Example: The server receives "information about the lost child" and "user anxiety data" and generates action information such as "notify a nearby parent so that the situation can be dealt with calmly."

[0812] Step 5: Sending behavioral information and notifications

[0813] The server sends the generated behavioral information to the related terminals. The input is the generated behavioral information. This is notified to the terminals via the network. The output is the behavioral information sent to each terminal.

[0814] Example: The server sends a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[0815] Step 6: Provide information

[0816] Users can post surrounding information and emotional data from their own devices. The inputs include surrounding information (GPS, camera footage, etc.) and emotional data. These are sent to a server. The output is the posted information aggregated on the server.

[0817] Example: A user posts a message saying "I found my lost child" and a photo. This is sent to the server.

[0818] Step 7: Evaluate and reward your information

[0819] The server analyzes the received posted information and emotion data to evaluate the trustworthiness of the information provider. The inputs are the posted information and evaluation data. Based on this, a trustworthiness score is calculated and a reward is awarded. The output is a trustworthiness score and a reward (e.g., tokens).

[0820] Example: The server recognizes the posted information as highly rated and gives a token to the information provider.

[0821] (Application example 2)

[0822] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0823] In conventional brick-and-mortar stores, it was difficult to grasp the emotional state of customers in real time and provide services that corresponded to that state. Furthermore, improving the customer experience and managing in-store safety required a great deal of effort, making it difficult to provide efficient customer support. As a result, there were concerns about a decline in customer satisfaction and the occurrence of problems. In response, there was a need for a system that could improve customer satisfaction by utilizing customer emotional data and providing appropriate support.

[0824] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0825] In this invention, the server is configured with a means for acquiring peripheral information, a means for analyzing the acquired peripheral information and emotional data, a means for generating appropriate behavioral information based on the analysis results and emotional data, a means for transmitting the generated behavioral information, and a means for notifying the user and store staff of the received behavioral information. This makes it possible to grasp the emotional state of the customer in real time and provide prompt and appropriate support according to that state.

[0826] A "means for acquiring surrounding information" is a device that uses sensors such as a camera, microphone, or thermometer to collect various data about a specific location or environment.

[0827] The "means for analyzing peripheral information and emotional data" refers to algorithms or software for analyzing the collected peripheral information and the user's emotional data and determining their contents.

[0828] "Emotion data" is data that indicates the user's emotional state and is generated by analyzing the user's facial expressions, tone of voice, choice of words, etc.

[0829] "Means for generating appropriate behavioral information" refers to algorithms or software that determine specific actions that users and store staff should take based on analysis results and emotional data.

[0830] A "generative AI model" is a trained model that uses artificial intelligence to generate behavioral information and provides appropriate output in response to specific prompts.

[0831] A "prompt" is an instruction to be input into a generative AI model, and is text that contains specific instructions for generating behavioral information appropriate to a specific situation.

[0832] The "means for transmitting behavioral information" is a communication system for transmitting the generated behavioral information to other devices or users.

[0833] The "means for notifying the user and store staff of the behavioral information" refers to a device or software for visually or audibly notifying the user and store staff of the received behavioral information.

[0834] To put this invention into practice, it is necessary to build a system that collects and analyzes peripheral information and emotional data, and generates and distributes appropriate behavioral information. This system is mainly composed of three components: a server, a terminal, and a user.

[0835] Acquisition and analysis of surrounding information

[0836] Device:

[0837] The device is equipped with built-in sensors such as a camera, microphone, and thermometer. These sensors are used to acquire surrounding information. For example, the camera captures the customer's facial expressions, and the microphone collects the customer's tone of voice and words. The device also has a communication function to send this data to a server.

[0838] Examples:

[0839] In a physical store in a shopping mall, staff wearing smart glasses capture customers' facial expressions and tone of voice in real time.

[0840] Implementing the Emotion Engine

[0841] Device:

[0842] The device is equipped with an emotion engine that analyzes collected data and determines the user's emotional state. This engine generates emotion data by analyzing camera images, voice input, and text input. For example, if a customer is confused, the system will capture their facial expression and tone of voice and generate appropriate emotion data.

[0843] Examples:

[0844] In the same shopping mall scenario, the emotion engine detects signs of confusion in customers' facial expressions and picks up signs of stress from tone analysis.

[0845] Generation and transmission of behavioral information

[0846] server:

[0847] The server receives and analyzes the surrounding information and emotional data sent from the device. Using a generative AI model, it generates appropriate behavioral information based on the collected data. For example, a message might be generated saying, "The customer appears to be in trouble. Please contact a staff member for assistance." The generated behavioral information is then sent to each device using a prompt.

[0848] Examples:

[0849] The server receives the emotion data and generates behavioral information such as, "The customer is lost. Please instruct the customer to ask a staff member for help."

[0850] Receiving and notifying behavioral information

[0851] Device:

[0852] The device receives the behavioral information sent from the server and notifies the user of the information. The notification method is either visual (display display) or audio (voice alert). For example, a message such as "The customer is lost. Please provide support" may appear on the smart glasses display.

[0853] Examples:

[0854] The staff's smart glasses will display a message saying, "A customer is confused. Please assist," prompting a quick response.

[0855] Information provision and evaluation

[0856] User:

[0857] Users can post surrounding information and emotional data using their own devices. This information is sent to the server and shared with other users. Ratings from other users are also collected and calculated as a reliability score. Rewards are awarded to highly reliable information providers.

[0858] Examples:

[0859] The system rewards staff who consistently provide accurate information with tokens, providing an incentive.

[0860] Generative AI model prompt

[0861] The following prompt sentences are examples of behavioral information generated based on emotion data:

[0862] The customer seems confused. Please message a staff member for immediate assistance.

[0863]

[0864] Your customers are having fun. Send them a thank you message: "Thank you for visiting us. We hope you continue to enjoy your time."

[0865] In this way, by accurately analyzing emotional data and generating and distributing appropriate behavioral information, we can expect to improve customer experience and safety management in physical stores.

[0866] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0867] Step 1:

[0868] Obtaining surrounding information

[0869] The device collects surrounding information using sensors such as a built-in camera, microphone, and thermometer. Specifically, the camera captures the customer's facial expression, and the microphone records the customer's tone of voice and words. This allows the device to obtain facial image, voice data, and temperature data of the customer as input.

[0870] Step 2:

[0871] Generating emotion data

[0872] The device analyzes the acquired peripheral information using an emotion engine. The collected facial expression images are subjected to facial recognition using OpenCV, and the resulting data is used to determine emotions. Meanwhile, the voice data is converted to text using the SpeechRecognition library, and the text is then analyzed using an NLP model to generate emotion data. This outputs emotion data that indicates the customer's emotional state.

[0873] Step 3:

[0874] Sending data

[0875] The device sends the generated emotion data and peripheral information to the server. At this time, the data is encrypted and sent using a secure communication protocol (e.g., HTTPS). The emotion data and peripheral information are treated as input and sent to the server.

[0876] Step 4:

[0877] Generation of behavioral information

[0878] The server receives the emotion data and peripheral information sent from the device. Using a generative AI model, it generates appropriate behavioral information based on this data. For example, if the emotion data indicates "confusion," the server generates a prompt statement such as, "The customer is in trouble. Please instruct the customer to ask a staff member for help." The input is the emotion data and peripheral information, and the output is the generated behavioral information.

[0879] Step 5:

[0880] Sending behavioral information

[0881] The server transmits the generated behavioral information to the user's and store staff's terminals. This transmission is also performed using a secure communication protocol. The input is the generated behavioral information, and the output is a behavioral guidance message sent to the store staff's terminal.

[0882] Step 6:

[0883] Notification of behavioral information

[0884] The terminal notifies the user and store staff of the behavioral information received from the server. Specifically, a message saying "A customer is in trouble. Please provide support" is displayed on the display of the smart glasses or smartphone. The input is the behavioral information sent from the server, and the output is a notification transmitted to the user and store staff.

[0885] Step 7:

[0886] Behavioral evaluation and feedback

[0887] The user responds based on the provided behavioral information and reports the results to the system. The response is then evaluated by other users and by automatic analysis. The evaluation results are sent to the server and accumulated as the information provider's credibility score. The input is the results of the behavioral information implementation and user feedback, and the output is the evaluation results and credibility score.

[0888] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0889] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0890] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0891] [Third embodiment]

[0892] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0893] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0894] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0895] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0896] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0897] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0898] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0899] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0900] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0901] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0902] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0903] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0904] To implement the present invention, the following system and program are used: The system is mainly composed of a server, a terminal, and a user.

[0905] Acquisition and analysis of surrounding information

[0906] Device:

[0907] The device acquires its current location using a built-in GPS module, and also uses sensors such as a camera, microphone, and thermometer to collect data on the surrounding environment.

[0908] The device filters and analyzes the collected data based on the common language "Feel!!" For example, if the device detects an abnormal sound, image, or temperature fluctuation, it will recognize this as a specific event, such as a "lost child."

[0909] Generation and transmission of behavioral information

[0910] server:

[0911] The server receives location and sensor information sent from the device, analyzes this information, and determines whether specific action is required.

[0912] For example, if the server receives location information of a child who appears to be lost in a park, it generates action information such as "notify a nearby parent."

[0913] The generated behavioral information is distributed from the server to the relevant devices, enabling a rapid response.

[0914] Receiving and notifying behavioral information

[0915] Device:

[0916] When the terminal receives the behavioral information sent from the server, it notifies the user by, for example, displaying a pop-up message on the screen to alert the user.

[0917] The user is notified and can take appropriate action.

[0918] Information provision and evaluation

[0919] User:

[0920] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[0921] Other users can rate the information they receive, for example, saying "this information was accurate" or "this information was helpful."

[0922] server:

[0923] The server receives information posted by users, analyzes the content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[0924] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[0925] Specific examples

[0926] Scenario: You find a lost child in the park

[0927] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[0928] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[0929] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[0930] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[0931] In this way, the present invention provides a system that allows all parties involved to respond quickly and appropriately.

[0932] The processing flow will be explained below.

[0933] Step 1:

[0934] The device obtains current location information and surrounding sensor information (e.g., camera and microphone data) from the GPS module and sensors.

[0935] Step 2:

[0936] The device filters and analyzes the acquired location and sensor information based on the common language "Feel!!" If an abnormal sound or image of a person is detected, the information is identified as an event.

[0937] Step 3:

[0938] The device compiles the analysis results into a data packet and sends it to the server. The transmitted data includes location information, sensor information, and the analysis results.

[0939] Step 4:

[0940] The server analyzes the data packets received from the device and determines whether a specific action is required. For example, if it determines that the device may be lost, it proceeds to the next step.

[0941] Step 5:

[0942] The server generates behavioral information as needed, which includes specific actions the user should take (e.g., "notify a nearby parent / guardian").

[0943] Step 6:

[0944] The server transmits the generated behavioral information to multiple related devices, with the transmission range limited to the vicinity of the location where the lost child was found.

[0945] Step 7:

[0946] The device notifies the user of the behavioral information received from the server, for example, by a pop-up message on the screen or an audio alert.

[0947] Step 8:

[0948] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying a nearby parent.

[0949] Step 9:

[0950] Users submit information about their lost children through the application, which can include photos and text descriptions.

[0951] Step 10:

[0952] The server receives information posted by users, determines whether it is necessary to notify other users, evaluates the reliability of the posted information, and awards tokens to highly rated information providers.

[0953] Step 11:

[0954] The server updates the reliability score of the information provider and grants rewards (e.g., tokens) based on the rating. Highly rated information providers are awarded more tokens, which act as an incentive for them to provide information next time.

[0955] Through this procedure, the present invention provides a system that can respond quickly and appropriately, and can promote active participation by information providers.

[0956] Example 1

[0957] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0958] Conventional systems have had problems in that it is difficult to quickly grasp the surrounding situation and take appropriate action. In addition, the reliability of information provided by users is not evaluated sufficiently, and incentives are not provided, resulting in insufficient information provision.

[0959] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0960] In this invention, the server includes means for acquiring peripheral information, means for filtering and analyzing the acquired peripheral information based on a common language, and means for recognizing a specific event based on the analysis results, thereby enabling the server to quickly grasp the surrounding situation and respond quickly to the specific event.

[0961] "Peripheral information" is a general term for data related to the surrounding environment, such as location information and sensor information acquired by a terminal.

[0962] A "common language" refers to a unified protocol or format used when exchanging data between multiple devices or software, and in this system it refers to "Feel!!".

[0963] "Filtering" refers to the process of selecting necessary data from the acquired peripheral information and removing unnecessary data.

[0964] "Analysis" refers to the process of detecting specific patterns or anomalies based on the data selected by the filters.

[0965] An "event" refers to a specific occurrence or situation that is recognized as a result of analysis, such as a "child getting lost."

[0966] "Behavioral information" refers to specific instructions or notifications generated in response to a recognized event.

[0967] "Transmission" refers to sending the generated behavioral information from the server to the corresponding terminal.

[0968] "Notification" refers to the act of the terminal conveying the transmitted behavioral information to the user.

[0969] "Reliability" is an index for evaluating the accuracy and usefulness of information provided by a user.

[0970] "Rewards" refer to incentives or tokens given to information providers based on their trustworthiness.

[0971] To implement this invention, a system consisting of a server, a terminal, and a user is used. The following hardware and software are required for the system to operate.

[0972] Acquisition and analysis of surrounding information

[0973] Device:

[0974] The device uses a built-in GPS module to obtain its current location, and is equipped with multiple sensors, including a camera, microphone, and thermometer, to collect data on the surrounding environment.

[0975] The device filters and analyzes the collected data based on the common language "Feel!!," which detects abnormal sounds, images, and temperature fluctuations and recognizes them as specific events such as a lost child.

[0976] Generation and transmission of behavioral information

[0977] server:

[0978] The server receives and analyzes location and sensor information sent from the device, using a high-speed analysis algorithm to analyze the received data and determine whether specific action is required.

[0979] The server generates behavioral information based on the analysis results and distributes it to the relevant devices. For example, if the server receives information about a lost child, it generates behavioral information such as "notify nearby parents."

[0980] Receiving and notifying behavioral information

[0981] Device:

[0982] The device receives the behavioral information sent from the server and notifies the user by displaying a pop-up message on the screen, allowing the user to take appropriate action.

[0983] Information provision and evaluation

[0984] User:

[0985] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[0986] Other users can rate the information they receive and provide feedback such as "This information was accurate" or "This information was helpful."

[0987] server:

[0988] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[0989] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[0990] Specific examples

[0991] Scenario: You find a lost child in the park

[0992] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[0993] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[0994] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[0995] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[0996] Example prompts to input to the generative AI model

[0997] Here is an example prompt to describe this system to a generative AI model:

[0998] Please explain in detail the response system when a lost child is found in a park. The system consists of a device, a server, and a user. The device uses GPS and a camera to collect location information and images and detect abnormalities. The server analyzes the received information and notifies a nearby parent. When the device receives the notification, it displays a message to the user. The user then takes appropriate action.

[0999] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1000] Step 1: Obtaining and filtering surrounding information

[1001] The device uses a built-in GPS module to obtain its current location, and also uses sensors such as a camera, microphone, and thermometer to collect data about the surrounding environment.

[1002] Input: Location information from the GPS module, image data from the camera, audio data from the microphone, and temperature data from the thermometer.

[1003] Data processing: Data collected from sensors is filtered based on the common language "Feel!!" to remove unnecessary data.

[1004] Output: filtered location, image data, audio data, temperature data.

[1005] Specific operations: The device periodically reads the GPS module, the camera captures images at regular intervals, the microphone continuously records audio, and the thermometer measures the temperature in real time.

[1006] Step 2: Data analysis and event recognition

[1007] The device analyzes the filtered data and recognizes specific events (e.g., a child getting lost).

[1008] Input: filtered location information, image data, audio data, temperature data.

[1009] Data processing: Image analysis algorithms are used to detect anomalies, audio analysis algorithms to detect abnormal sounds (e.g. screaming or crying), and temperature data is analyzed to detect abnormal temperature fluctuations.

[1010] Output: Data recognized as a specific event (e.g., "Lost child found").

[1011] Specific operation: The device's internal software analyzes captured images and recorded audio, and if the captured images or audio exceed a set threshold, it tags the device as "lost."

[1012] Step 3: Generate and send behavioral information

[1013] The server receives the event data sent from the terminal, analyzes it, and generates specific behavioral information.

[1014] Input: Event data sent from the device (e.g., "Lost child").

[1015] Data processing: The server analyzes the received event data and determines whether specific actions are required. Based on the analysis results, it generates behavioral information.

[1016] Output: Generated action information (e.g., "Notify nearby parents about the lost child").

[1017] Specific operation: Based on the analysis results, the server generates a message stating, "A child has been lost in the northeast area of ​​the park. We are requesting the assistance of nearby parents." and creates a distribution list.

[1018] Step 4: Receiving and notifying behavioral information

[1019] The terminal receives the behavior information sent from the server and notifies the user.

[1020] Input: Behavioral information sent from the server (e.g., "A lost child has been found").

[1021] Data processing: The received behavioral information is stored in an internal queue and converted into a format for notifying the user.

[1022] Output: A notification message that will be displayed to the user (e.g., "A lost child has been found. Please help.").

[1023] Specific operation: A pop-up message will be displayed on the device display and an audio alert will be issued at the same time.

[1024] Step 5: Information and evaluation

[1025] Users use their devices to post information about lost children and other important information to the server, which analyzes and evaluates the information received and calculates the trustworthiness of the information provider.

[1026] Input: User-provided information (e.g., "I found a lost child in the northeast area").

[1027] Data processing: The server analyzes the posted information, determines its usefulness, and aggregates feedback from other users to calculate the rating of the information provider.

[1028] Output: Post information with usefulness rating and confidence points.

[1029] Specific operation: The server determines the usefulness based on the analysis results, aggregates feedback such as "This information was accurate" or "It was useful," and updates the reliability.

[1030] Step 6: Rewarding

[1031] The server rewards information providers who receive high ratings (e.g., tokens).

[1032] Input: Confidence points.

[1033] Data processing: Calculate and issue rewards to users who exceed a certain level of trust points.

[1034] Output: The token that is granted to the user.

[1035] Specific operation: The server automatically issues tokens that can be used on the system to users whose trust points exceed a threshold.

[1036] (Application example 1)

[1037] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1038] Conventional systems that acquire and analyze surrounding information lack the means to evaluate the reliability and usefulness of the information. Furthermore, security services such as detecting suspicious individuals and responding quickly to accidents require the ability to detect abnormal situations in real time and prompt appropriate responses. Furthermore, a mechanism is needed to appropriately evaluate the reliability of information providers and provide incentives for promptly providing useful information to users.

[1039] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1040] In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information, means for generating appropriate behavioral information based on the analysis results, means for transmitting the generated behavioral information, means for notifying the user of the received behavioral information, means for the user to evaluate the information received, and means for calculating the reliability of the information provider and generating a reward based on the evaluation. This allows the user to notice abnormal situations in real time and respond quickly, and makes it possible to encourage the provision of useful information through the reliability evaluation of the information provider.

[1041] "Around-the-world information" is data about the environment collected using various sensors such as a GPS module, a camera module, an audio sensor, and a temperature sensor.

[1042] "Analysis results" are information obtained as a result of data analysis performed on a server or terminal based on collected peripheral information.

[1043] "Behavioral information" is information that is generated by the server based on the analysis results and that instructs specific responses and actions.

[1044] "Reliability" is a numerical value calculated based on the accuracy and usefulness of the information provided by the user, based on the evaluations of other users and the server's analysis.

[1045] A "reward" is an incentive given to an information provider based on a reliability evaluation, and may take the form of points or tokens, for example.

[1046] "Security event" means an abnormal situation such as a suspicious person, fire, or accident detected by the system.

[1047] A "notification" is a message or alert sent from a server to a user terminal, and is information that prompts the user to take necessary action or take caution.

[1048] A "generative AI model" is an artificial intelligence that learns patterns and trends from large amounts of data and generates appropriate action information or notifications for specific inputs.

[1049] A "prompt" is text that is input as an instruction or question to a generative AI model and is used to control the AI's behavior.

[1050] To implement this invention, the following system and program are used: The system mainly comprises a server, a terminal, and a user.

[1051] Acquisition and analysis of surrounding information

[1052] The device acquires its current location using a built-in GPS module. It also has various sensors, such as a camera, microphone, and thermometer, which it uses to collect data on the surrounding situation. The device filters and analyzes the collected data. Specifically, it recognizes sound, video, and temperature fluctuations as specific security events, such as the presence of a suspicious person.

[1053] Generation and transmission of behavioral information

[1054] The server receives location information and sensor information sent from the device. It analyzes this information and determines whether specific action is necessary. Based on the analysis results, such as the location information of suspicious individuals and abnormal temperature fluctuations, the server generates behavioral information such as "notify security guards" or "warn the user." This generated behavioral information is distributed from the server to multiple relevant devices, enabling a prompt response.

[1055] Receiving and notifying behavioral information

[1056] When the device receives the behavioral information sent from the server, it notifies the user. For example, a pop-up message saying "A suspicious person has been detected. Please be careful" can be displayed on the screen of a smartphone or smart glasses. The user can receive this notification and take appropriate action.

[1057] Information provision and evaluation

[1058] Users can use their own devices to post nearby security information. This information is sent to the server and shared with other users. Other users can rate the information they receive, for example, rating it as "this information was accurate" or "helpful." The server receives the information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings from other users. Information providers who receive high ratings are awarded tokens as a reward. This gives users an incentive to provide more information proactively.

[1059] Hardware and software used

[1060] The system is implemented using the following hardware and software:

[1061] Hardware: Smartphone, smart glasses (camera, microphone, GPS sensor, thermometer)

[1062] software:

[1063] GPS module (location information acquisition)

[1064] Camera module (image acquisition)

[1065] Microphone module (voice acquisition)

[1066] Thermometer module (temperature acquisition)

[1067] Server-side software:

[1068] Data reception and analysis system (Python, Flask, or other web frameworks)

[1069] Notification sending system (Push notification API)

[1070] Generative AI models:

[1071] AI models that learn patterns and trends from large amounts of data and generate appropriate actionable information or notifications for specific inputs

[1072] Specific examples

[1073] For example, consider a suspicious person detection application in a park. If a device detects a unique sound (scream, glass breaking), an abnormal temperature change, or significant camera movement in the park, it sends that data to a server. The server analyzes this information and immediately generates behavioral information such as "A suspicious person has been detected in the park. Please be careful," and notifies nearby parents, security guards, etc.

[1074] Example prompts for generative AI models

[1075] "How can I implement an application that collects sensor information needed to detect suspicious activity in busy areas of a park, analyzes it, and generates appropriate notifications?"

[1076] Collect data from various sensors (camera, microphone, thermometer, GPS).

[1077] The data is sent to the server and analyzed on the server side.

[1078] Receives notifications from the server and notifies the user.

[1079] In this way, the present invention provides a security service system that allows all parties involved to respond quickly and appropriately.

[1080] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1081] Step 1:

[1082] The device uses its built-in GPS module, camera, microphone, and thermometer to collect current location information and surrounding situation data.

[1083] Specific operations: The GPS module obtains the current location, the camera captures surrounding images, the microphone records audio, and the thermometer measures the surrounding temperature.

[1084] Input: Location information from GPS, video data from camera, audio data from microphone, temperature data from temperature sensor.

[1085] Output: A set of acquired location information, video data, audio data, and temperature data.

[1086] Step 2:

[1087] The device filters and analyzes the collected data, specifically analyzing audio, video, and temperature fluctuations to identify specific security events.

[1088] How it works: It uses analytical algorithms to detect abnormal sounds, images, and temperature fluctuations, and tags them as "suspicious person" or "abnormal temperature."

[1089] Input: A set of location information, video data, audio data, and temperature data.

[1090] Output: Abnormal event information as the analysis result (e.g., "suspicious person" or "abnormal temperature").

[1091] Step 3:

[1092] The terminal transmits the analysis results to the server.

[1093] Specific operation: The analysis results are packaged in JSON format and sent to the server using an HTTP POST request.

[1094] Input: Abnormal event information.

[1095] Output: JSON formatted data sent to the server.

[1096] Step 4:

[1097] The server receives and analyzes the location and sensor information sent from the device, and generates specific behavioral information based on this information.

[1098] Specific operation: Recorded in a database on the server side, and an analysis algorithm is applied to generate action information such as "notify security guard" or "warn user."

[1099] Input: Location information, video data, audio data, and temperature data sent from the device.

[1100] Output: Action information (e.g., "Notify security" or "Alert user").

[1101] Step 5:

[1102] The server distributes the generated behavioral information to the corresponding terminals.

[1103] Specific behavior: Send a message containing behavioral information using the push notification system.

[1104] Input: Behavioral information.

[1105] Output: Notifications delivered to the device.

[1106] Step 6:

[1107] The terminal receives the behavioral information sent from the server and notifies the user.

[1108] Specific behavior: A pop-up message will be displayed on the device screen and sound or vibration will be emitted to alert the user.

[1109] Input: Behavioral information sent from the server.

[1110] Output: Notifications via popup message, sound and vibration.

[1111] Step 7:

[1112] The user checks the notification and takes appropriate action.

[1113] Specific actions: The user checks the notification on the screen and, if necessary, takes specific action, such as spotting and reporting a suspicious person in the park.

[1114] Input: Notifications displayed on the device.

[1115] Output: The user's specific response action (e.g., finding and reporting a suspicious person).

[1116] Step 8:

[1117] The user evaluates the received information and sends feedback to the server via his / her terminal.

[1118] Specific operations: Press the rating button, enter a comment, etc., and send the rating information to the server.

[1119] Input: User rating information and feedback.

[1120] Output: Rating information and feedback sent to the server.

[1121] Step 9:

[1122] The server receives the rating information from the user, calculates the reliability of the information provider, and generates a reward based on the rating.

[1123] Specific operation: The received evaluation information is recorded in a database, an analysis algorithm is applied to calculate the trustworthiness of the information provider, and a token is generated according to the evaluation.

[1124] Input: Rating information from users.

[1125] Output: Calculated informant confidence and generated reward tokens.

[1126] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1127] To implement this invention, a program that combines a system including a server, a terminal, and a user with an emotion engine is used. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, as well as the emotion engine that recognizes the user's emotions.

[1128] Acquisition and analysis of surrounding information

[1129] Device:

[1130] The device acquires surrounding information using a built-in GPS module and various sensors (camera, microphone, thermometer, etc.).

[1131] The acquired information is filtered and analyzed using the common language "Feel!!" For example, if an abnormal sound or image is detected, this information is identified as a specific event such as a "lost child."

[1132] Implementing the Emotion Engine

[1133] Device:

[1134] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes camera images, voice input, and text input to determine the user's emotional state.

[1135] The emotion engine generates emotion data by analyzing the user's facial expressions, tone of voice, and choice of words, and this data reflects the user's changing emotions in real time.

[1136] Generation and transmission of behavioral information

[1137] server:

[1138] The server receives surrounding information and emotion data sent from the device, analyzes this information, and determines whether specific action is required.

[1139] When generating behavioral information, emotional data may also be taken into consideration as necessary. For example, if the user is in a panic, behavioral information including advice on how to deal with the situation calmly may be generated.

[1140] The generated behavioral information is distributed from the server to a plurality of related terminals.

[1141] Receiving and notifying behavioral information

[1142] Device:

[1143] Receive notifications about behavioral information and emotions sent from the server, such as a message saying "Please stay calm."

[1144] After receiving the behavioral information, the user takes appropriate action based on the information.

[1145] Information provision and evaluation

[1146] User:

[1147] Users can post surrounding information and emotional data using their own devices, which is then sent to a server and shared with other users.

[1148] Other users can rate the information and the results of the ratings are sent to the server.

[1149] server:

[1150] The server analyzes the received posted information and emotional data and calculates the reliability score of the information provider.

[1151] Highly rated informants are awarded tokens, which are also adjusted based on data from the sentiment engine.

[1152] Specific examples

[1153] Scenario: You find a lost child in the park

[1154] 1. When the device finds a lost child in a park, it acquires GPS location information and camera footage, and identifies the child as "lost" using the common language "Feel!!" The emotion engine also detects anxiety or tension from the user's facial expressions and voice.

[1155] 2. The server receives this data and generates action information such as "notifying nearby parents of the lost child and encouraging the user to act calmly."

[1156] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian."

[1157] 4. The user receives a notification, protects the lost child, and notifies nearby parents. If the user's emotions change during this process, they are also monitored by the emotion engine and appropriate feedback is provided.

[1158] In addition to sharing information in real time and encouraging appropriate behavior, this system takes into account the user's emotional state, enabling even more accurate responses.

[1159] The processing flow will be explained below.

[1160] Step 1:

[1161] The device uses the GPS module and various sensors (camera, microphone, thermometer, etc.) to obtain current location information and surrounding sensor information.

[1162] Step 2:

[1163] The location and sensor information acquired by the device is filtered and analyzed based on the common language "Feel!!" For example, if an abnormal sound or image is detected, it will be identified as a "lost child" or "an abnormal situation."

[1164] Step 3:

[1165] The device uses an emotion engine to analyze the user's emotions and determine the user's current emotional state (e.g., anxiety, fear, panic) based on camera footage, microphone audio, and text input.

[1166] Step 4:

[1167] The device transmits the analyzed surrounding information and emotion data to the server. The transmitted data includes location information, sensor information, analysis results, and emotion data.

[1168] Step 5:

[1169] The server analyzes the data received from the device and determines whether a specific action is required. For example, if a child is lost in a specific location, it may determine that immediate action is required.

[1170] Step 6:

[1171] The server generates behavioral information based on the analysis results. The behavioral information includes specific actions the user should take (e.g., "stay calm and notify a nearby parent or guardian"). This information also takes into account emotional data, and may include a message to alleviate anxiety.

[1172] Step 7:

[1173] The server then transmits the generated behavioral information to related devices in the vicinity. The behavioral information is distributed only within the vicinity of the lost child's location.

[1174] Step 8:

[1175] The device notifies the user of the behavioral information and emotion notifications received from the server. For example, a message such as "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian" is displayed on the screen.

[1176] Step 9:

[1177] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying nearby parents.

[1178] Step 10:

[1179] Users submit information about their lost child through the application, including location, photos, a text description, and the user's emotional state.

[1180] Step 11:

[1181] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the reliability score of the information provider based on the ratings of other users.

[1182] Step 12:

[1183] The server will award tokens to highly rated information providers, which will provide users with an incentive to provide information.

[1184] Step 13:

[1185] The server updates the reliability scores of the information providers and distributes behavioral information to highly rated information providers with higher priority.

[1186] Through this series of processes, the present invention enables a quick and appropriate response and promotes behavior that takes into consideration the user's feelings.

[1187] Example 2

[1188] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1189] Although conventional systems were able to acquire and analyze peripheral information, they were unable to generate appropriate behavioral information that took the user's emotional state into account. Furthermore, they lacked a mechanism for evaluating highly reliable information providers and providing rewards based on that evaluation. This resulted in problems such as insufficient assurance of the reliability of information and the appropriateness of responses.

[1190] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information using a common language, emotion recognition means for recognizing the user's emotion, means for generating appropriate behavioral information based on the analysis result and the emotion recognition result, means for transmitting the generated behavioral information, and means for notifying the user of the received behavioral information. This enables highly accurate analysis of the peripheral information and appropriate responses that take into account the user's emotional state. In addition, the reliability of the information can be improved by providing rewards to highly reliable information providers.

[1191] "Around-the-world information" is data that indicates the user and their surroundings, such as location information, sensor information, and camera images and audio.

[1192] "Means for acquiring" refers to a device or function for capturing surrounding information using hardware devices such as a GPS module, camera, microphone, thermometer, etc.

[1193] "Means for analysis using a common language" refers to algorithms or software that filter and analyze surrounding information based on a common language such as "Feel!!" to identify specific events.

[1194] "Emotion recognition means for recognizing user emotions" refers to software or algorithms that analyze camera images, voice input, and text input to determine the user's emotional state from their facial expressions, tone of voice, and choice of words.

[1195] The "means for generating behavioral information" refers to a device or software for creating information to encourage the user to take specific and appropriate behavior based on the analysis results and emotion recognition results.

[1196] The "means for transmitting behavioral information" is a device or function for transmitting the generated behavioral information to the associated terminal via a network.

[1197] The "means for notifying the user of the behavioral information" refers to a device or function for visually or audibly conveying the received behavioral information to the user.

[1198] The "trustworthiness of information provider" is an index for evaluating the degree of contribution and trustworthiness of a user who posted peripheral information and emotion data.

[1199] The "rewarding means" is a device or function for providing rewards such as tokens or points to users based on their trustworthiness.

[1200] MODE FOR CARRYING OUT THE INVENTION

[1201] This invention can be implemented in a system including a server, a terminal, and a user. It also uses a program that combines an emotion engine. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, and is characterized by an emotion engine that recognizes the user's emotions.

[1202] Hardware and software used

[1203] Device:

[1204] GPS module (acquisition of location information)

[1205] Camera (image and video capture)

[1206] Microphone (audio capture)

[1207] Thermometer (acquiring temperature information)

[1208] Emotion engine (analysis of user's emotional state)

[1209] server:

[1210] Data analysis engine (analysis of peripheral information and emotional data)

[1211] Behavioral information generation module (generating behavioral information based on analysis results)

[1212] Communication module (sending and receiving behavioral information)

[1213] Trustworthiness evaluation engine (calculating the trustworthiness of information providers)

[1214] User:

[1215] Data submission via terminal operation

[1216] Reviewing received behavioral information and taking appropriate action

[1217] Examples of data processing and data calculation

[1218] Obtaining surrounding information:

[1219] The device uses its built-in GPS module, camera, microphone, and thermometer to collect information about its surroundings. For example, if the device is in a park, it can collect location information (GPS), camera footage and photos taken on the spot, surrounding audio (microphone), and temperature information (thermometer).

[1220] Surrounding area analysis:

[1221] The device uses the common language "Feel!!" to filter and analyze the surrounding information it acquires. For example, it can detect a crying child from camera footage and recognize the child's crying from audio data. This allows it to identify the event as a "lost child."

[1222] Emotion engine implementation:

[1223] The device is equipped with an emotion engine that analyzes camera images, voice input, and text input to determine the user's emotional state. For example, if the user has an anxious expression, it can detect this and determine from the tone of the user's voice that they are in a tense state.

[1224] Behavioral information generation:

[1225] The server receives and analyzes the surrounding information and emotional data sent from the device. For example, the server receives "information about a lost child" and the user's "anxiety" and generates behavioral information according to the situation. Specifically, it generates behavioral information such as "notify a nearby parent to calmly deal with the situation."

[1226] Sending behavioral information and notifications:

[1227] The server distributes the generated behavioral information to multiple related devices. For example, the server may send a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[1228] Information provision and reliability assessment:

[1229] Users can post surrounding information and emotional data using their devices, and that information is sent to the server and shared with other users. For example, a user can post a message saying, "I found a lost child," along with a photo or video. The server analyzes this information, evaluates the trustworthiness of the information provider, and then awards a token based on that evaluation.

[1230] Examples of prompt statements

[1231] "Please explain how a user who finds a lost child in a park should respond by generating behavioral information based on data from the emotion engine and notifying nearby parents."

[1232] The above is a specific embodiment for carrying out the invention. This system enables real-time information sharing and appropriate behavior promotion, and in particular, enables quick and appropriate responses that take into account the user's emotional state.

[1233] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1234] Step 1: Obtaining surrounding information

[1235] The device acquires surrounding information using a GPS module, camera, microphone, and thermometer. The inputs include the current geographical location (GPS), camera footage, video, audio (microphone), and temperature data. By collecting these data, the user's surroundings can be understood. The output is a dataset of acquired surrounding information.

[1236] Example: The device takes photos of the surroundings with a camera, obtains location information from GPS, records surrounding audio with a microphone, and measures the ambient temperature with a thermometer.

[1237] Step 2: Analyze surrounding information

[1238] The device analyzes the acquired surrounding information using the common language "Feel!!". The input is the surrounding information dataset acquired in step 1. This is analyzed to identify specific events (e.g., abnormal sound or video detection). The output is filtered and analyzed event data.

[1239] Example: The device analyzes camera footage to detect a child's crying face, and analyzes audio data acquired from the microphone to identify the "child's crying sound."

[1240] Step 3: Recognize emotions

[1241] The device uses an emotion recognition engine to recognize the user's emotional state. Inputs include the user's facial image (camera), tone of voice (microphone), and text input. These are analyzed to generate the user's emotional data. The output is the analyzed emotional data.

[1242] Example: The device camera captures the user's face, and the emotion recognition engine detects an "anxious expression." The microphone analyzes the tone of the voice and determines that the user is in a tense state.

[1243] Step 4: Generate behavioral information

[1244] The server receives and analyzes the surrounding information and emotional data sent from the device. The inputs are the surrounding information and emotional data. Based on this, it determines the necessary response and generates specific behavioral information. The output is behavioral information that requires a response.

[1245] Example: The server receives "information about the lost child" and "user anxiety data" and generates action information such as "notify a nearby parent so that the situation can be dealt with calmly."

[1246] Step 5: Sending behavioral information and notifications

[1247] The server sends the generated behavioral information to the related terminals. The input is the generated behavioral information. This is notified to the terminals via the network. The output is the behavioral information sent to each terminal.

[1248] Example: The server sends a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[1249] Step 6: Provide information

[1250] Users can post surrounding information and emotional data from their own devices. The inputs include surrounding information (GPS, camera footage, etc.) and emotional data. These are sent to a server. The output is the posted information aggregated on the server.

[1251] Example: A user posts a message saying "I found my lost child" and a photo. This is sent to the server.

[1252] Step 7: Evaluate and reward your information

[1253] The server analyzes the received posted information and emotion data to evaluate the trustworthiness of the information provider. The inputs are the posted information and evaluation data. Based on this, a trustworthiness score is calculated and a reward is awarded. The output is a trustworthiness score and a reward (e.g., tokens).

[1254] Example: The server recognizes the posted information as highly rated and gives a token to the information provider.

[1255] (Application example 2)

[1256] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1257] In conventional brick-and-mortar stores, it was difficult to grasp the emotional state of customers in real time and provide services that corresponded to that state. Furthermore, improving the customer experience and managing in-store safety required a great deal of effort, making it difficult to provide efficient customer support. As a result, there were concerns about a decline in customer satisfaction and the occurrence of problems. In response, there was a need for a system that could improve customer satisfaction by utilizing customer emotional data and providing appropriate support.

[1258] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1259] In this invention, the server is configured with a means for acquiring peripheral information, a means for analyzing the acquired peripheral information and emotional data, a means for generating appropriate behavioral information based on the analysis results and emotional data, a means for transmitting the generated behavioral information, and a means for notifying the user and store staff of the received behavioral information. This makes it possible to grasp the emotional state of the customer in real time and provide prompt and appropriate support according to that state.

[1260] A "means for acquiring surrounding information" is a device that uses sensors such as a camera, microphone, or thermometer to collect various data about a specific location or environment.

[1261] The "means for analyzing peripheral information and emotional data" refers to algorithms or software for analyzing the collected peripheral information and the user's emotional data and determining their contents.

[1262] "Emotion data" is data that indicates the user's emotional state and is generated by analyzing the user's facial expressions, tone of voice, choice of words, etc.

[1263] "Means for generating appropriate behavioral information" refers to algorithms or software that determine specific actions that users and store staff should take based on analysis results and emotional data.

[1264] A "generative AI model" is a trained model that uses artificial intelligence to generate behavioral information and provides appropriate output in response to specific prompts.

[1265] A "prompt" is an instruction to be input into a generative AI model, and is text that contains specific instructions for generating behavioral information appropriate to a specific situation.

[1266] The "means for transmitting behavioral information" is a communication system for transmitting the generated behavioral information to other devices or users.

[1267] The "means for notifying the user and store staff of the behavioral information" refers to a device or software for visually or audibly notifying the user and store staff of the received behavioral information.

[1268] To put this invention into practice, it is necessary to build a system that collects and analyzes peripheral information and emotional data, and generates and distributes appropriate behavioral information. This system is mainly composed of three components: a server, a terminal, and a user.

[1269] Acquisition and analysis of surrounding information

[1270] Device:

[1271] The device is equipped with built-in sensors such as a camera, microphone, and thermometer. These sensors are used to acquire surrounding information. For example, the camera captures the customer's facial expressions, and the microphone collects the customer's tone of voice and words. The device also has a communication function to send this data to a server.

[1272] Examples:

[1273] In a physical store in a shopping mall, staff wearing smart glasses capture customers' facial expressions and tone of voice in real time.

[1274] Implementing the Emotion Engine

[1275] Device:

[1276] The device is equipped with an emotion engine that analyzes collected data and determines the user's emotional state. This engine generates emotion data by analyzing camera images, voice input, and text input. For example, if a customer is confused, the system will capture their facial expression and tone of voice and generate appropriate emotion data.

[1277] Examples:

[1278] In the same shopping mall scenario, the emotion engine detects signs of confusion in customers' facial expressions and picks up signs of stress from tone analysis.

[1279] Generation and transmission of behavioral information

[1280] server:

[1281] The server receives and analyzes the surrounding information and emotional data sent from the device. Using a generative AI model, it generates appropriate behavioral information based on the collected data. For example, a message might be generated saying, "The customer appears to be in trouble. Please contact a staff member for assistance." The generated behavioral information is then sent to each device using a prompt.

[1282] Examples:

[1283] The server receives the emotion data and generates behavioral information such as, "The customer is lost. Please instruct the customer to ask a staff member for help."

[1284] Receiving and notifying behavioral information

[1285] Device:

[1286] The device receives the behavioral information sent from the server and notifies the user of the information. The notification method is either visual (display display) or audio (voice alert). For example, a message such as "The customer is lost. Please provide support" may appear on the smart glasses display.

[1287] Examples:

[1288] The staff's smart glasses will display a message saying, "A customer is confused. Please assist," prompting a quick response.

[1289] Information provision and evaluation

[1290] User:

[1291] Users can post surrounding information and emotional data using their own devices. This information is sent to the server and shared with other users. Ratings from other users are also collected and calculated as a reliability score. Rewards are awarded to highly reliable information providers.

[1292] Examples:

[1293] The system rewards staff who consistently provide accurate information with tokens, providing an incentive.

[1294] Generative AI model prompt

[1295] The following prompt sentences are examples of behavioral information generated based on emotion data:

[1296] The customer seems confused. Please message a staff member for immediate assistance.

[1297]

[1298] Your customers are having fun. Send them a thank you message: "Thank you for visiting us. We hope you continue to enjoy your time."

[1299] In this way, by accurately analyzing emotional data and generating and distributing appropriate behavioral information, we can expect to improve customer experience and safety management in physical stores.

[1300] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1301] Step 1:

[1302] Obtaining surrounding information

[1303] The device collects surrounding information using sensors such as a built-in camera, microphone, and thermometer. Specifically, the camera captures the customer's facial expression, and the microphone records the customer's tone of voice and words. This allows the device to obtain facial image, voice data, and temperature data of the customer as input.

[1304] Step 2:

[1305] Generating emotion data

[1306] The device analyzes the acquired peripheral information using an emotion engine. The collected facial expression images are subjected to facial recognition using OpenCV, and the resulting data is used to determine emotions. Meanwhile, the voice data is converted to text using the SpeechRecognition library, and the text is then analyzed using an NLP model to generate emotion data. This outputs emotion data that indicates the customer's emotional state.

[1307] Step 3:

[1308] Sending data

[1309] The device sends the generated emotion data and peripheral information to the server. At this time, the data is encrypted and sent using a secure communication protocol (e.g., HTTPS). The emotion data and peripheral information are treated as input and sent to the server.

[1310] Step 4:

[1311] Generation of behavioral information

[1312] The server receives the emotion data and peripheral information sent from the device. Using a generative AI model, it generates appropriate behavioral information based on this data. For example, if the emotion data indicates "confusion," the server generates a prompt statement such as, "The customer is in trouble. Please instruct the customer to ask a staff member for help." The input is the emotion data and peripheral information, and the output is the generated behavioral information.

[1313] Step 5:

[1314] Sending behavioral information

[1315] The server transmits the generated behavioral information to the user's and store staff's terminals. This transmission is also performed using a secure communication protocol. The input is the generated behavioral information, and the output is a behavioral guidance message sent to the store staff's terminal.

[1316] Step 6:

[1317] Notification of behavioral information

[1318] The terminal notifies the user and store staff of the behavioral information received from the server. Specifically, a message saying "A customer is in trouble. Please provide support" is displayed on the display of the smart glasses or smartphone. The input is the behavioral information sent from the server, and the output is a notification transmitted to the user and store staff.

[1319] Step 7:

[1320] Behavioral evaluation and feedback

[1321] The user responds based on the provided behavioral information and reports the results to the system. The response is then evaluated by other users and by automatic analysis. The evaluation results are sent to the server and accumulated as the information provider's credibility score. The input is the results of the behavioral information implementation and user feedback, and the output is the evaluation results and credibility score.

[1322] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1323] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1324] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1325] [Fourth embodiment]

[1326] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1327] 7, a 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.

[1328] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1329] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1330] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1331] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1332] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1333] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1334] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1335] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1336] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1337] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1338] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1339] To implement the present invention, the following system and program are used: The system is mainly composed of a server, a terminal, and a user.

[1340] Acquisition and analysis of surrounding information

[1341] Device:

[1342] The device acquires its current location using a built-in GPS module, and also uses sensors such as a camera, microphone, and thermometer to collect data on the surrounding environment.

[1343] The device filters and analyzes the collected data based on the common language "Feel!!" For example, if the device detects an abnormal sound, image, or temperature fluctuation, it will recognize this as a specific event, such as a "lost child."

[1344] Generation and transmission of behavioral information

[1345] server:

[1346] The server receives location and sensor information sent from the device, analyzes this information, and determines whether specific action is required.

[1347] For example, if the server receives location information of a child who appears to be lost in a park, it generates action information such as "notify a nearby parent."

[1348] The generated behavioral information is distributed from the server to the relevant devices, enabling a rapid response.

[1349] Receiving and notifying behavioral information

[1350] Device:

[1351] When the terminal receives the behavioral information sent from the server, it notifies the user by, for example, displaying a pop-up message on the screen to alert the user.

[1352] The user is notified and can take appropriate action.

[1353] Information provision and evaluation

[1354] User:

[1355] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[1356] Other users can rate the information they receive, for example, saying "this information was accurate" or "this information was helpful."

[1357] server:

[1358] The server receives information posted by users, analyzes the content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[1359] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[1360] Specific examples

[1361] Scenario: You find a lost child in the park

[1362] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[1363] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[1364] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[1365] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[1366] In this way, the present invention provides a system that allows all parties involved to respond quickly and appropriately.

[1367] The processing flow will be explained below.

[1368] Step 1:

[1369] The device obtains current location information and surrounding sensor information (e.g., camera and microphone data) from the GPS module and sensors.

[1370] Step 2:

[1371] The device filters and analyzes the acquired location and sensor information based on the common language "Feel!!" If an abnormal sound or image of a person is detected, the information is identified as an event.

[1372] Step 3:

[1373] The device compiles the analysis results into a data packet and sends it to the server. The transmitted data includes location information, sensor information, and the analysis results.

[1374] Step 4:

[1375] The server analyzes the data packets received from the device and determines whether a specific action is required. For example, if it determines that the device may be lost, it proceeds to the next step.

[1376] Step 5:

[1377] The server generates behavioral information as needed, which includes specific actions the user should take (e.g., "notify a nearby parent / guardian").

[1378] Step 6:

[1379] The server transmits the generated behavioral information to multiple related devices, with the transmission range limited to the vicinity of the location where the lost child was found.

[1380] Step 7:

[1381] The device notifies the user of the behavioral information received from the server, for example, by a pop-up message on the screen or an audio alert.

[1382] Step 8:

[1383] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying a nearby parent.

[1384] Step 9:

[1385] Users submit information about their lost children through the application, which can include photos and text descriptions.

[1386] Step 10:

[1387] The server receives information posted by users, determines whether it is necessary to notify other users, evaluates the reliability of the posted information, and awards tokens to highly rated information providers.

[1388] Step 11:

[1389] The server updates the reliability score of the information provider and grants rewards (e.g., tokens) based on the rating. Highly rated information providers are awarded more tokens, which act as an incentive for them to provide information next time.

[1390] Through this procedure, the present invention provides a system that can respond quickly and appropriately, and can promote active participation by information providers.

[1391] Example 1

[1392] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1393] Conventional systems have had problems in that it is difficult to quickly grasp the surrounding situation and take appropriate action. In addition, the reliability of information provided by users is not evaluated sufficiently, and incentives are not provided, resulting in insufficient information provision.

[1394] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1395] In this invention, the server includes means for acquiring peripheral information, means for filtering and analyzing the acquired peripheral information based on a common language, and means for recognizing a specific event based on the analysis results, thereby enabling the server to quickly grasp the surrounding situation and respond quickly to the specific event.

[1396] "Peripheral information" is a general term for data related to the surrounding environment, such as location information and sensor information acquired by a terminal.

[1397] A "common language" refers to a unified protocol or format used when exchanging data between multiple devices or software, and in this system it refers to "Feel!!".

[1398] "Filtering" refers to the process of selecting necessary data from the acquired peripheral information and removing unnecessary data.

[1399] "Analysis" refers to the process of detecting specific patterns or anomalies based on the data selected by the filters.

[1400] An "event" refers to a specific occurrence or situation that is recognized as a result of analysis, such as a "child getting lost."

[1401] "Behavioral information" refers to specific instructions or notifications generated in response to a recognized event.

[1402] "Transmission" refers to sending the generated behavioral information from the server to the corresponding terminal.

[1403] "Notification" refers to the act of the terminal conveying the transmitted behavioral information to the user.

[1404] "Reliability" is an index for evaluating the accuracy and usefulness of information provided by a user.

[1405] "Rewards" refer to incentives or tokens given to information providers based on their trustworthiness.

[1406] To implement this invention, a system consisting of a server, a terminal, and a user is used. The following hardware and software are required for the system to operate.

[1407] Acquisition and analysis of surrounding information

[1408] Device:

[1409] The device uses a built-in GPS module to obtain its current location, and is equipped with multiple sensors, including a camera, microphone, and thermometer, to collect data on the surrounding environment.

[1410] The device filters and analyzes the collected data based on the common language "Feel!!," which detects abnormal sounds, images, and temperature fluctuations and recognizes them as specific events such as a lost child.

[1411] Generation and transmission of behavioral information

[1412] server:

[1413] The server receives and analyzes location and sensor information sent from the device, using a high-speed analysis algorithm to analyze the received data and determine whether specific action is required.

[1414] The server generates behavioral information based on the analysis results and distributes it to the relevant devices. For example, if the server receives information about a lost child, it generates behavioral information such as "notify nearby parents."

[1415] Receiving and notifying behavioral information

[1416] Device:

[1417] The device receives the behavioral information sent from the server and notifies the user by displaying a pop-up message on the screen, allowing the user to take appropriate action.

[1418] Information provision and evaluation

[1419] User:

[1420] Users can use their devices to post information about lost children and other important information, which is then sent to a server and shared with other users.

[1421] Other users can rate the information they receive and provide feedback such as "This information was accurate" or "This information was helpful."

[1422] server:

[1423] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings of other users.

[1424] Tokens are awarded to information providers who receive high ratings, which gives users an incentive to provide more information proactively.

[1425] Specific examples

[1426] Scenario: You find a lost child in the park

[1427] 1. When the device finds a lost child in a park, it uses GPS and a camera to collect location information and an image, and identifies the child as "lost" using the common language "Feel!!".

[1428] 2. The server receives this information, analyzes it, and generates action information such as "notify nearby parents of the lost child."

[1429] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please help." on the screen.

[1430] 4. The user sees the notification and takes specific action, such as protecting a lost child in the park.

[1431] Example prompts to input to the generative AI model

[1432] Here is an example prompt to describe this system to a generative AI model:

[1433] Please explain in detail the response system when a lost child is found in a park. The system consists of a device, a server, and a user. The device uses GPS and a camera to collect location information and images and detect abnormalities. The server analyzes the received information and notifies a nearby parent. When the device receives the notification, it displays a message to the user. The user then takes appropriate action.

[1434] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1435] Step 1: Obtaining and filtering surrounding information

[1436] The device uses a built-in GPS module to obtain its current location, and also uses sensors such as a camera, microphone, and thermometer to collect data about the surrounding environment.

[1437] Input: Location information from the GPS module, image data from the camera, audio data from the microphone, and temperature data from the thermometer.

[1438] Data processing: Data collected from sensors is filtered based on the common language "Feel!!" to remove unnecessary data.

[1439] Output: filtered location, image data, audio data, temperature data.

[1440] Specific operations: The device periodically reads the GPS module, the camera captures images at regular intervals, the microphone continuously records audio, and the thermometer measures the temperature in real time.

[1441] Step 2: Data analysis and event recognition

[1442] The device analyzes the filtered data and recognizes specific events (e.g., a child getting lost).

[1443] Input: filtered location information, image data, audio data, temperature data.

[1444] Data processing: Image analysis algorithms are used to detect anomalies, audio analysis algorithms to detect abnormal sounds (e.g. screaming or crying), and temperature data is analyzed to detect abnormal temperature fluctuations.

[1445] Output: Data recognized as a specific event (e.g., "Lost child found").

[1446] Specific operation: The device's internal software analyzes captured images and recorded audio, and if the captured images or audio exceed a set threshold, it tags the device as "lost."

[1447] Step 3: Generate and send behavioral information

[1448] The server receives the event data sent from the terminal, analyzes it, and generates specific behavioral information.

[1449] Input: Event data sent from the device (e.g., "Lost child").

[1450] Data processing: The server analyzes the received event data and determines whether specific actions are required. Based on the analysis results, it generates behavioral information.

[1451] Output: Generated action information (e.g., "Notify nearby parents about the lost child").

[1452] Specific operation: Based on the analysis results, the server generates a message stating, "A child has been lost in the northeast area of ​​the park. We are requesting the assistance of nearby parents." and creates a distribution list.

[1453] Step 4: Receiving and notifying behavioral information

[1454] The terminal receives the behavior information sent from the server and notifies the user.

[1455] Input: Behavioral information sent from the server (e.g., "A lost child has been found").

[1456] Data processing: The received behavioral information is stored in an internal queue and converted into a format for notifying the user.

[1457] Output: A notification message that will be displayed to the user (e.g., "A lost child has been found. Please help.").

[1458] Specific operation: A pop-up message will be displayed on the device display and an audio alert will be issued at the same time.

[1459] Step 5: Information and evaluation

[1460] Users use their devices to post information about lost children and other important information to the server, which analyzes and evaluates the information received and calculates the trustworthiness of the information provider.

[1461] Input: User-provided information (e.g., "I found a lost child in the northeast area").

[1462] Data processing: The server analyzes the posted information, determines its usefulness, and aggregates feedback from other users to calculate the rating of the information provider.

[1463] Output: Post information with usefulness rating and confidence points.

[1464] Specific operation: The server determines the usefulness based on the analysis results, aggregates feedback such as "This information was accurate" or "It was useful," and updates the reliability.

[1465] Step 6: Rewarding

[1466] The server rewards information providers who receive high ratings (e.g., tokens).

[1467] Input: Confidence points.

[1468] Data processing: Calculate and issue rewards to users who exceed a certain level of trust points.

[1469] Output: The token that is granted to the user.

[1470] Specific operation: The server automatically issues tokens that can be used on the system to users whose trust points exceed a threshold.

[1471] (Application example 1)

[1472] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1473] Conventional systems that acquire and analyze surrounding information lack the means to evaluate the reliability and usefulness of the information. Furthermore, security services such as detecting suspicious individuals and responding quickly to accidents require the ability to detect abnormal situations in real time and prompt appropriate responses. Furthermore, a mechanism is needed to appropriately evaluate the reliability of information providers and provide incentives for promptly providing useful information to users.

[1474] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1475] In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information, means for generating appropriate behavioral information based on the analysis results, means for transmitting the generated behavioral information, means for notifying the user of the received behavioral information, means for the user to evaluate the information received, and means for calculating the reliability of the information provider and generating a reward based on the evaluation. This allows the user to notice abnormal situations in real time and respond quickly, and makes it possible to encourage the provision of useful information through the reliability evaluation of the information provider.

[1476] "Around-the-world information" is data about the environment collected using various sensors such as a GPS module, a camera module, an audio sensor, and a temperature sensor.

[1477] "Analysis results" are information obtained as a result of data analysis performed on a server or terminal based on collected peripheral information.

[1478] "Behavioral information" is information that is generated by the server based on the analysis results and that instructs specific responses and actions.

[1479] "Reliability" is a numerical value calculated based on the accuracy and usefulness of the information provided by the user, based on the evaluations of other users and the server's analysis.

[1480] A "reward" is an incentive given to an information provider based on a reliability evaluation, and may take the form of points or tokens, for example.

[1481] "Security event" means an abnormal situation such as a suspicious person, fire, or accident detected by the system.

[1482] A "notification" is a message or alert sent from a server to a user terminal, and is information that prompts the user to take necessary action or take caution.

[1483] A "generative AI model" is an artificial intelligence that learns patterns and trends from large amounts of data and generates appropriate action information or notifications for specific inputs.

[1484] A "prompt" is text that is input as an instruction or question to a generative AI model and is used to control the AI's behavior.

[1485] To implement this invention, the following system and program are used: The system mainly comprises a server, a terminal, and a user.

[1486] Acquisition and analysis of surrounding information

[1487] The device acquires its current location using a built-in GPS module. It also has various sensors, such as a camera, microphone, and thermometer, which it uses to collect data on the surrounding situation. The device filters and analyzes the collected data. Specifically, it recognizes sound, video, and temperature fluctuations as specific security events, such as the presence of a suspicious person.

[1488] Generation and transmission of behavioral information

[1489] The server receives location information and sensor information sent from the device. It analyzes this information and determines whether specific action is necessary. Based on the analysis results, such as the location information of suspicious individuals and abnormal temperature fluctuations, the server generates behavioral information such as "notify security guards" or "warn the user." This generated behavioral information is distributed from the server to multiple relevant devices, enabling a prompt response.

[1490] Receiving and notifying behavioral information

[1491] When the device receives the behavioral information sent from the server, it notifies the user. For example, a pop-up message saying "A suspicious person has been detected. Please be careful" can be displayed on the screen of a smartphone or smart glasses. The user can receive this notification and take appropriate action.

[1492] Information provision and evaluation

[1493] Users can use their own devices to post nearby security information. This information is sent to the server and shared with other users. Other users can rate the information they receive, for example, rating it as "this information was accurate" or "helpful." The server receives the information posted by users, analyzes its content, and determines its usefulness. It also calculates the trustworthiness of the information provider based on the ratings from other users. Information providers who receive high ratings are awarded tokens as a reward. This gives users an incentive to provide more information proactively.

[1494] Hardware and software used

[1495] The system is implemented using the following hardware and software:

[1496] Hardware: Smartphone, smart glasses (camera, microphone, GPS sensor, thermometer)

[1497] software:

[1498] GPS module (location information acquisition)

[1499] Camera module (image acquisition)

[1500] Microphone module (voice acquisition)

[1501] Thermometer module (temperature acquisition)

[1502] Server-side software:

[1503] Data reception and analysis system (Python, Flask, or other web frameworks)

[1504] Notification sending system (Push notification API)

[1505] Generative AI models:

[1506] AI models that learn patterns and trends from large amounts of data and generate appropriate actionable information or notifications for specific inputs

[1507] Specific examples

[1508] For example, consider a suspicious person detection application in a park. If a device detects a unique sound (scream, glass breaking), an abnormal temperature change, or significant camera movement in the park, it sends that data to a server. The server analyzes this information and immediately generates behavioral information such as "A suspicious person has been detected in the park. Please be careful," and notifies nearby parents, security guards, etc.

[1509] Example prompts for generative AI models

[1510] "How can I implement an application that collects sensor information needed to detect suspicious activity in busy areas of a park, analyzes it, and generates appropriate notifications?"

[1511] Collect data from various sensors (camera, microphone, thermometer, GPS).

[1512] The data is sent to the server and analyzed on the server side.

[1513] Receives notifications from the server and notifies the user.

[1514] In this way, the present invention provides a security service system that allows all parties involved to respond quickly and appropriately.

[1515] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1516] Step 1:

[1517] The device uses its built-in GPS module, camera, microphone, and thermometer to collect current location information and surrounding situation data.

[1518] Specific operations: The GPS module obtains the current location, the camera captures surrounding images, the microphone records audio, and the thermometer measures the surrounding temperature.

[1519] Input: Location information from GPS, video data from camera, audio data from microphone, temperature data from temperature sensor.

[1520] Output: A set of acquired location information, video data, audio data, and temperature data.

[1521] Step 2:

[1522] The device filters and analyzes the collected data, specifically analyzing audio, video, and temperature fluctuations to identify specific security events.

[1523] How it works: It uses analytical algorithms to detect abnormal sounds, images, and temperature fluctuations, and tags them as "suspicious person" or "abnormal temperature."

[1524] Input: A set of location information, video data, audio data, and temperature data.

[1525] Output: Abnormal event information as the analysis result (e.g., "suspicious person" or "abnormal temperature").

[1526] Step 3:

[1527] The terminal transmits the analysis results to the server.

[1528] Specific operation: The analysis results are packaged in JSON format and sent to the server using an HTTP POST request.

[1529] Input: Abnormal event information.

[1530] Output: JSON formatted data sent to the server.

[1531] Step 4:

[1532] The server receives and analyzes the location and sensor information sent from the device, and generates specific behavioral information based on this information.

[1533] Specific operation: Recorded in a database on the server side, and an analysis algorithm is applied to generate action information such as "notify security guard" or "warn user."

[1534] Input: Location information, video data, audio data, and temperature data sent from the device.

[1535] Output: Action information (e.g., "Notify security" or "Alert user").

[1536] Step 5:

[1537] The server distributes the generated behavioral information to the corresponding terminals.

[1538] Specific behavior: Send a message containing behavioral information using the push notification system.

[1539] Input: Behavioral information.

[1540] Output: Notifications delivered to the device.

[1541] Step 6:

[1542] The terminal receives the behavioral information sent from the server and notifies the user.

[1543] Specific behavior: A pop-up message will be displayed on the device screen and sound or vibration will be emitted to alert the user.

[1544] Input: Behavioral information sent from the server.

[1545] Output: Notifications via popup message, sound and vibration.

[1546] Step 7:

[1547] The user checks the notification and takes appropriate action.

[1548] Specific actions: The user checks the notification on the screen and, if necessary, takes specific action, such as spotting and reporting a suspicious person in the park.

[1549] Input: Notifications displayed on the device.

[1550] Output: The user's specific response action (e.g., finding and reporting a suspicious person).

[1551] Step 8:

[1552] The user evaluates the received information and sends feedback to the server via his / her terminal.

[1553] Specific operations: Press the rating button, enter a comment, etc., and send the rating information to the server.

[1554] Input: User rating information and feedback.

[1555] Output: Rating information and feedback sent to the server.

[1556] Step 9:

[1557] The server receives the rating information from the user, calculates the reliability of the information provider, and generates a reward based on the rating.

[1558] Specific operation: The received evaluation information is recorded in a database, an analysis algorithm is applied to calculate the trustworthiness of the information provider, and a token is generated according to the evaluation.

[1559] Input: Rating information from users.

[1560] Output: Calculated informant confidence and generated reward tokens.

[1561] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1562] To implement this invention, a program that combines a system including a server, a terminal, and a user with an emotion engine is used. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, as well as the emotion engine that recognizes the user's emotions.

[1563] Acquisition and analysis of surrounding information

[1564] Device:

[1565] The device acquires surrounding information using a built-in GPS module and various sensors (camera, microphone, thermometer, etc.).

[1566] The acquired information is filtered and analyzed using the common language "Feel!!" For example, if an abnormal sound or image is detected, this information is identified as a specific event such as a "lost child."

[1567] Implementing the Emotion Engine

[1568] Device:

[1569] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes camera images, voice input, and text input to determine the user's emotional state.

[1570] The emotion engine generates emotion data by analyzing the user's facial expressions, tone of voice, and choice of words, and this data reflects the user's changing emotions in real time.

[1571] Generation and transmission of behavioral information

[1572] server:

[1573] The server receives surrounding information and emotion data sent from the device, analyzes this information, and determines whether specific action is required.

[1574] When generating behavioral information, emotional data may also be taken into consideration as necessary. For example, if the user is in a panic, behavioral information including advice on how to deal with the situation calmly may be generated.

[1575] The generated behavioral information is distributed from the server to a plurality of related terminals.

[1576] Receiving and notifying behavioral information

[1577] Device:

[1578] Receive notifications about behavioral information and emotions sent from the server, such as a message saying "Please stay calm."

[1579] After receiving the behavioral information, the user takes appropriate action based on the information.

[1580] Information provision and evaluation

[1581] User:

[1582] Users can post surrounding information and emotional data using their own devices, which is then sent to a server and shared with other users.

[1583] Other users can rate the information and the results of the ratings are sent to the server.

[1584] server:

[1585] The server analyzes the received posted information and emotional data and calculates the reliability score of the information provider.

[1586] Highly rated informants are awarded tokens, which are also adjusted based on data from the sentiment engine.

[1587] Specific examples

[1588] Scenario: You find a lost child in the park

[1589] 1. When the device finds a lost child in a park, it acquires GPS location information and camera footage, and identifies the child as "lost" using the common language "Feel!!" The emotion engine also detects anxiety or tension from the user's facial expressions and voice.

[1590] 2. The server receives this data and generates action information such as "notifying nearby parents of the lost child and encouraging the user to act calmly."

[1591] 3. The device receives a notification from the server and displays the message "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian."

[1592] 4. The user receives a notification, protects the lost child, and notifies nearby parents. If the user's emotions change during this process, they are also monitored by the emotion engine and appropriate feedback is provided.

[1593] In addition to sharing information in real time and encouraging appropriate behavior, this system takes into account the user's emotional state, enabling even more accurate responses.

[1594] The processing flow will be explained below.

[1595] Step 1:

[1596] The device uses the GPS module and various sensors (camera, microphone, thermometer, etc.) to obtain current location information and surrounding sensor information.

[1597] Step 2:

[1598] The location and sensor information acquired by the device is filtered and analyzed based on the common language "Feel!!" For example, if an abnormal sound or image is detected, it will be identified as a "lost child" or "an abnormal situation."

[1599] Step 3:

[1600] The device uses an emotion engine to analyze the user's emotions and determine the user's current emotional state (e.g., anxiety, fear, panic) based on camera footage, microphone audio, and text input.

[1601] Step 4:

[1602] The device transmits the analyzed surrounding information and emotion data to the server. The transmitted data includes location information, sensor information, analysis results, and emotion data.

[1603] Step 5:

[1604] The server analyzes the data received from the device and determines whether a specific action is required. For example, if a child is lost in a specific location, it may determine that immediate action is required.

[1605] Step 6:

[1606] The server generates behavioral information based on the analysis results. The behavioral information includes specific actions the user should take (e.g., "stay calm and notify a nearby parent or guardian"). This information also takes into account emotional data, and may include a message to alleviate anxiety.

[1607] Step 7:

[1608] The server then transmits the generated behavioral information to related devices in the vicinity. The behavioral information is distributed only within the vicinity of the lost child's location.

[1609] Step 8:

[1610] The device notifies the user of the behavioral information and emotion notifications received from the server. For example, a message such as "A lost child has been found. Please remain calm, check your surroundings, and notify a nearby parent or guardian" is displayed on the screen.

[1611] Step 9:

[1612] The user checks the notification from the device and takes the instructed action, for example, protecting a lost child and notifying nearby parents.

[1613] Step 10:

[1614] Users submit information about their lost child through the application, including location, photos, a text description, and the user's emotional state.

[1615] Step 11:

[1616] The server receives information posted by users, analyzes its content, and determines its usefulness. It also calculates the reliability score of the information provider based on the ratings of other users.

[1617] Step 12:

[1618] The server will award tokens to highly rated information providers, which will provide users with an incentive to provide information.

[1619] Step 13:

[1620] The server updates the reliability scores of the information providers and distributes behavioral information to highly rated information providers with higher priority.

[1621] Through this series of processes, the present invention enables a quick and appropriate response and promotes behavior that takes into consideration the user's feelings.

[1622] Example 2

[1623] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1624] Although conventional systems were able to acquire and analyze peripheral information, they were unable to generate appropriate behavioral information that took the user's emotional state into account. Furthermore, they lacked a mechanism for evaluating highly reliable information providers and providing rewards based on that evaluation. This resulted in problems such as insufficient assurance of the reliability of information and the appropriateness of responses.

[1625] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring peripheral information, means for analyzing the acquired peripheral information using a common language, emotion recognition means for recognizing the user's emotion, means for generating appropriate behavioral information based on the analysis result and the emotion recognition result, means for transmitting the generated behavioral information, and means for notifying the user of the received behavioral information. This enables highly accurate analysis of the peripheral information and appropriate responses that take into account the user's emotional state. In addition, the reliability of the information can be improved by providing rewards to highly reliable information providers.

[1626] "Around-the-world information" is data that indicates the user and their surroundings, such as location information, sensor information, and camera images and audio.

[1627] "Means for acquiring" refers to a device or function for capturing surrounding information using hardware devices such as a GPS module, camera, microphone, thermometer, etc.

[1628] "Means for analysis using a common language" refers to algorithms or software that filter and analyze surrounding information based on a common language such as "Feel!!" to identify specific events.

[1629] "Emotion recognition means for recognizing user emotions" refers to software or algorithms that analyze camera images, voice input, and text input to determine the user's emotional state from their facial expressions, tone of voice, and choice of words.

[1630] The "means for generating behavioral information" refers to a device or software for creating information to encourage the user to take specific and appropriate behavior based on the analysis results and emotion recognition results.

[1631] The "means for transmitting behavioral information" is a device or function for transmitting the generated behavioral information to the associated terminal via a network.

[1632] The "means for notifying the user of the behavioral information" refers to a device or function for visually or audibly conveying the received behavioral information to the user.

[1633] The "trustworthiness of information provider" is an index for evaluating the degree of contribution and trustworthiness of a user who posted peripheral information and emotion data.

[1634] The "rewarding means" is a device or function for providing rewards such as tokens or points to users based on their trustworthiness.

[1635] MODE FOR CARRYING OUT THE INVENTION

[1636] This invention can be implemented in a system including a server, a terminal, and a user. It also uses a program that combines an emotion engine. This system has the functions of acquiring and analyzing peripheral information, generating, transmitting, and notifying behavioral information, and is characterized by an emotion engine that recognizes the user's emotions.

[1637] Hardware and software used

[1638] Device:

[1639] GPS module (acquisition of location information)

[1640] Camera (image and video capture)

[1641] Microphone (audio capture)

[1642] Thermometer (acquiring temperature information)

[1643] Emotion engine (analysis of user's emotional state)

[1644] server:

[1645] Data analysis engine (analysis of peripheral information and emotional data)

[1646] Behavioral information generation module (generating behavioral information based on analysis results)

[1647] Communication module (sending and receiving behavioral information)

[1648] Trustworthiness evaluation engine (calculating the trustworthiness of information providers)

[1649] User:

[1650] Data submission via terminal operation

[1651] Reviewing received behavioral information and taking appropriate action

[1652] Examples of data processing and data calculation

[1653] Obtaining surrounding information:

[1654] The device uses its built-in GPS module, camera, microphone, and thermometer to collect information about its surroundings. For example, if the device is in a park, it can collect location information (GPS), camera footage and photos taken on the spot, surrounding audio (microphone), and temperature information (thermometer).

[1655] Surrounding area analysis:

[1656] The device uses the common language "Feel!!" to filter and analyze the surrounding information it acquires. For example, it can detect a crying child from camera footage and recognize the child's crying from audio data. This allows it to identify the event as a "lost child."

[1657] Emotion engine implementation:

[1658] The device is equipped with an emotion engine that analyzes camera images, voice input, and text input to determine the user's emotional state. For example, if the user has an anxious expression, it can detect this and determine from the tone of the user's voice that they are in a tense state.

[1659] Behavioral information generation:

[1660] The server receives and analyzes the surrounding information and emotional data sent from the device. For example, the server receives "information about a lost child" and the user's "anxiety" and generates behavioral information according to the situation. Specifically, it generates behavioral information such as "notify a nearby parent to calmly deal with the situation."

[1661] Sending behavioral information and notifications:

[1662] The server distributes the generated behavioral information to multiple related devices. For example, the server may send a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[1663] Information provision and reliability assessment:

[1664] Users can post surrounding information and emotional data using their devices, and that information is sent to the server and shared with other users. For example, a user can post a message saying, "I found a lost child," along with a photo or video. The server analyzes this information, evaluates the trustworthiness of the information provider, and then awards a token based on that evaluation.

[1665] Examples of prompt statements

[1666] "Please explain how a user who finds a lost child in a park should respond by generating behavioral information based on data from the emotion engine and notifying nearby parents."

[1667] The above is a specific embodiment for carrying out the invention. This system enables real-time information sharing and appropriate behavior promotion, and in particular, enables quick and appropriate responses that take into account the user's emotional state.

[1668] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1669] Step 1: Obtaining surrounding information

[1670] The device acquires surrounding information using a GPS module, camera, microphone, and thermometer. The inputs include the current geographical location (GPS), camera footage, video, audio (microphone), and temperature data. By collecting these data, the user's surroundings can be understood. The output is a dataset of acquired surrounding information.

[1671] Example: The device takes photos of the surroundings with a camera, obtains location information from GPS, records surrounding audio with a microphone, and measures the ambient temperature with a thermometer.

[1672] Step 2: Analyze surrounding information

[1673] The device analyzes the acquired surrounding information using the common language "Feel!!". The input is the surrounding information dataset acquired in step 1. This is analyzed to identify specific events (e.g., abnormal sound or video detection). The output is filtered and analyzed event data.

[1674] Example: The device analyzes camera footage to detect a child's crying face, and analyzes audio data acquired from the microphone to identify the "child's crying sound."

[1675] Step 3: Recognize emotions

[1676] The device uses an emotion recognition engine to recognize the user's emotional state. Inputs include the user's facial image (camera), tone of voice (microphone), and text input. These are analyzed to generate the user's emotional data. The output is the analyzed emotional data.

[1677] Example: The device camera captures the user's face, and the emotion recognition engine detects an "anxious expression." The microphone analyzes the tone of the voice and determines that the user is in a tense state.

[1678] Step 4: Generate behavioral information

[1679] The server receives and analyzes the surrounding information and emotional data sent from the device. The inputs are the surrounding information and emotional data. Based on this, it determines the necessary response and generates specific behavioral information. The output is behavioral information that requires a response.

[1680] Example: The server receives "information about the lost child" and "user anxiety data" and generates action information such as "notify a nearby parent so that the situation can be dealt with calmly."

[1681] Step 5: Sending behavioral information and notifications

[1682] The server sends the generated behavioral information to the related terminals. The input is the generated behavioral information. This is notified to the terminals via the network. The output is the behavioral information sent to each terminal.

[1683] Example: The server sends a message to the device saying, "A lost child has been found. Please stay calm, check your surroundings, and notify a nearby parent."

[1684] Step 6: Provide information

[1685] Users can post surrounding information and emotional data from their own devices. The inputs include surrounding information (GPS, camera footage, etc.) and emotional data. These are sent to a server. The output is the posted information aggregated on the server.

[1686] Example: A user posts a message saying "I found my lost child" and a photo. This is sent to the server.

[1687] Step 7: Evaluate and reward your information

[1688] The server analyzes the received posted information and emotion data to evaluate the trustworthiness of the information provider. The inputs are the posted information and evaluation data. Based on this, a trustworthiness score is calculated and a reward is awarded. The output is a trustworthiness score and a reward (e.g., tokens).

[1689] Example: The server recognizes the posted information as highly rated and gives a token to the information provider.

[1690] (Application example 2)

[1691] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1692] In conventional brick-and-mortar stores, it was difficult to grasp the emotional state of customers in real time and provide services that corresponded to that state. Furthermore, improving the customer experience and managing in-store safety required a great deal of effort, making it difficult to provide efficient customer support. As a result, there were concerns about a decline in customer satisfaction and the occurrence of problems. In response, there was a need for a system that could improve customer satisfaction by utilizing customer emotional data and providing appropriate support.

[1693] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1694] In this invention, the server is configured with a means for acquiring peripheral information, a means for analyzing the acquired peripheral information and emotional data, a means for generating appropriate behavioral information based on the analysis results and emotional data, a means for transmitting the generated behavioral information, and a means for notifying the user and store staff of the received behavioral information. This makes it possible to grasp the emotional state of the customer in real time and provide prompt and appropriate support according to that state.

[1695] A "means for acquiring surrounding information" is a device that uses sensors such as a camera, microphone, or thermometer to collect various data about a specific location or environment.

[1696] The "means for analyzing peripheral information and emotional data" refers to algorithms or software for analyzing the collected peripheral information and the user's emotional data and determining their contents.

[1697] "Emotion data" is data that indicates the user's emotional state and is generated by analyzing the user's facial expressions, tone of voice, choice of words, etc.

[1698] "Means for generating appropriate behavioral information" refers to algorithms or software that determine specific actions that users and store staff should take based on analysis results and emotional data.

[1699] A "generative AI model" is a trained model that uses artificial intelligence to generate behavioral information and provides appropriate output in response to specific prompts.

[1700] A "prompt" is an instruction to be input into a generative AI model, and is text that contains specific instructions for generating behavioral information appropriate to a specific situation.

[1701] The "means for transmitting behavioral information" is a communication system for transmitting the generated behavioral information to other devices or users.

[1702] The "means for notifying the user and store staff of the behavioral information" refers to a device or software for visually or audibly notifying the user and store staff of the received behavioral information.

[1703] To put this invention into practice, it is necessary to build a system that collects and analyzes peripheral information and emotional data, and generates and distributes appropriate behavioral information. This system is mainly composed of three components: a server, a terminal, and a user.

[1704] Acquisition and analysis of surrounding information

[1705] Device:

[1706] The device is equipped with built-in sensors such as a camera, microphone, and thermometer. These sensors are used to acquire surrounding information. For example, the camera captures the customer's facial expressions, and the microphone collects the customer's tone of voice and words. The device also has a communication function to send this data to a server.

[1707] Examples:

[1708] In a physical store in a shopping mall, staff wearing smart glasses capture customers' facial expressions and tone of voice in real time.

[1709] Implementing the Emotion Engine

[1710] Device:

[1711] The device is equipped with an emotion engine that analyzes collected data and determines the user's emotional state. This engine generates emotion data by analyzing camera images, voice input, and text input. For example, if a customer is confused, the system will capture their facial expression and tone of voice and generate appropriate emotion data.

[1712] Examples:

[1713] In the same shopping mall scenario, the emotion engine detects signs of confusion in customers' facial expressions and picks up signs of stress from tone analysis.

[1714] Generation and transmission of behavioral information

[1715] server:

[1716] The server receives and analyzes the surrounding information and emotional data sent from the device. Using a generative AI model, it generates appropriate behavioral information based on the collected data. For example, a message might be generated saying, "The customer appears to be in trouble. Please contact a staff member for assistance." The generated behavioral information is then sent to each device using a prompt.

[1717] Examples:

[1718] The server receives the emotion data and generates behavioral information such as, "The customer is lost. Please instruct the customer to ask a staff member for help."

[1719] Receiving and notifying behavioral information

[1720] Device:

[1721] The device receives the behavioral information sent from the server and notifies the user of the information. The notification method is either visual (display display) or audio (voice alert). For example, a message such as "The customer is lost. Please provide support" may appear on the smart glasses display.

[1722] Examples:

[1723] The staff's smart glasses will display a message saying, "A customer is confused. Please assist," prompting a quick response.

[1724] Information provision and evaluation

[1725] User:

[1726] Users can post surrounding information and emotional data using their own devices. This information is sent to the server and shared with other users. Ratings from other users are also collected and calculated as a reliability score. Rewards are awarded to highly reliable information providers.

[1727] Examples:

[1728] The system rewards staff who consistently provide accurate information with tokens, providing an incentive.

[1729] Generative AI model prompt

[1730] The following prompt sentences are examples of behavioral information generated based on emotion data:

[1731] The customer seems confused. Please message a staff member for immediate assistance.

[1732]

[1733] Your customers are having fun. Send them a thank you message: "Thank you for visiting us. We hope you continue to enjoy your time."

[1734] In this way, by accurately analyzing emotional data and generating and distributing appropriate behavioral information, we can expect to improve customer experience and safety management in physical stores.

[1735] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1736] Step 1:

[1737] Obtaining surrounding information

[1738] The device collects surrounding information using sensors such as a built-in camera, microphone, and thermometer. Specifically, the camera captures the customer's facial expression, and the microphone records the customer's tone of voice and words. This allows the device to obtain facial image, voice data, and temperature data of the customer as input.

[1739] Step 2:

[1740] Generating emotion data

[1741] The device analyzes the acquired peripheral information using an emotion engine. The collected facial expression images are subjected to facial recognition using OpenCV, and the resulting data is used to determine emotions. Meanwhile, the voice data is converted to text using the SpeechRecognition library, and the text is then analyzed using an NLP model to generate emotion data. This outputs emotion data that indicates the customer's emotional state.

[1742] Step 3:

[1743] Sending data

[1744] The device sends the generated emotion data and peripheral information to the server. At this time, the data is encrypted and sent using a secure communication protocol (e.g., HTTPS). The emotion data and peripheral information are treated as input and sent to the server.

[1745] Step 4:

[1746] Generation of behavioral information

[1747] The server receives the emotion data and peripheral information sent from the device. Using a generative AI model, it generates appropriate behavioral information based on this data. For example, if the emotion data indicates "confusion," the server generates a prompt statement such as, "The customer is in trouble. Please instruct the customer to ask a staff member for help." The input is the emotion data and peripheral information, and the output is the generated behavioral information.

[1748] Step 5:

[1749] Sending behavioral information

[1750] The server transmits the generated behavioral information to the user's and store staff's terminals. This transmission is also performed using a secure communication protocol. The input is the generated behavioral information, and the output is a behavioral guidance message sent to the store staff's terminal.

[1751] Step 6:

[1752] Notification of behavioral information

[1753] The terminal notifies the user and store staff of the behavioral information received from the server. Specifically, a message saying "A customer is in trouble. Please provide support" is displayed on the display of the smart glasses or smartphone. The input is the behavioral information sent from the server, and the output is a notification transmitted to the user and store staff.

[1754] Step 7:

[1755] Behavioral evaluation and feedback

[1756] The user responds based on the provided behavioral information and reports the results to the system. The response is then evaluated by other users and by automatic analysis. The evaluation results are sent to the server and accumulated as the information provider's credibility score. The input is the results of the behavioral information implementation and user feedback, and the output is the evaluation results and credibility score.

[1757] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1758] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1759] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1760] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1761] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1762] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1763] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1764] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1765] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1766] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1767] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1768] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1769] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1770] 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.

[1771] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1772] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1773] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1774] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1775] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1776] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1777] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1778] The following is further disclosed regarding the above embodiment.

[1779] (Claim 1)

[1780] A means for acquiring peripheral information;

[1781] A means for analyzing the acquired peripheral information;

[1782] means for generating appropriate behavioral information based on the analysis results;

[1783] means for transmitting the generated behavioral information;

[1784] means for notifying a user of the received behavioral information;

[1785] A system including:

[1786] (Claim 2)

[1787] The system according to claim 1, wherein the peripheral information is obtained as location information and sensor information.

[1788] (Claim 3)

[1789] 10. The system of claim 1, further comprising means for evaluating the trustworthiness of the information provider and awarding a reward based on the evaluation.

[1790] "Example 1"

[1791] (Claim 1)

[1792] A means for acquiring peripheral information;

[1793] means for filtering and analyzing the acquired peripheral information based on a common language;

[1794] a means for recognizing a particular event based on the analysis results;

[1795] means for generating appropriate behavioral information based on the recognized events;

[1796] means for transmitting the generated behavioral information;

[1797] means for notifying a user of the received behavioral information;

[1798] means for evaluating information from users and calculating the reliability of information providers based on the evaluation;

[1799] a means for awarding a reward based on the reliability;

[1800] A system including:

[1801] (Claim 2)

[1802] The system according to claim 1, wherein location information and sensor information are acquired and analyzed as peripheral information.

[1803] (Claim 3)

[1804] 10. The system of claim 1, wherein appropriate behavioral information is generated and distributed to a plurality of terminals.

[1805] "Application Example 1"

[1806] (Claim 1)

[1807] A means for acquiring peripheral information;

[1808] A means for analyzing the acquired peripheral information;

[1809] means for generating appropriate behavioral information based on the analysis results;

[1810] means for transmitting the generated behavioral information;

[1811] means for notifying a user of the received behavioral information;

[1812] means for a user to evaluate the received information;

[1813] a means for calculating the trustworthiness of the information provider and generating a reward based on the evaluation;

[1814] A system including:

[1815] (Claim 2)

[1816] The system according to claim 1, wherein the peripheral information is obtained as location information and sensor information.

[1817] (Claim 3)

[1818] 10. The system of claim 1, further comprising means for evaluating the trustworthiness of the information provider and awarding a reward based on the evaluation.

[1819] (Claim 4)

[1820] The means for acquiring surrounding information includes a GPS module, a camera module, an audio sensor, and a temperature sensor,

[1821] 10. The system of claim 1, further comprising means for communicating with the server to notify the server of the detection of a particular security event.

[1822] (Claim 5)

[1823] The system according to claim 4, wherein the server analyzes data and generates behavioral information using prompt sentences based on instructions from the generative AI model.

[1824] "Example 2: Combining Emotion Engines"

[1825] (Claim 1)

[1826] A means for acquiring peripheral information;

[1827] A means of analyzing the acquired peripheral information using a common language;

[1828] emotion recognition means for recognizing an emotion of a user;

[1829] a means for generating appropriate behavioral information based on the analysis result and the emotion recognition result;

[1830] means for transmitting the generated behavioral information;

[1831] means for notifying a user of the received behavioral information;

[1832] A system including:

[1833] (Claim 2)

[1834] 2. The system according to claim 1, wherein the system acquires location information and sensor information as peripheral information, and recognizes the user's emotional state based on the user's facial expression, voice, and choice of words.

[1835] (Claim 3)

[1836] 10. The system of claim 1, further comprising means for evaluating the trustworthiness of the information provider and awarding a reward based on the evaluation.

[1837] "Application example 2 when combining emotion engines"

[1838] (Claim 1)

[1839] A means for acquiring peripheral information;

[1840] means for analyzing the acquired peripheral information and emotion data;

[1841] means for generating appropriate behavioral information based on the analysis results and emotion data;

[1842] means for transmitting the generated behavioral information;

[1843] means for notifying the user and store staff of the received behavioral information;

[1844] A system including:

[1845] (Claim 2)

[1846] 2. The system of claim 1, wherein the location information and sensor information are obtained from camera images, audio data, and text data.

[1847] (Claim 3)

[1848] The system of claim 1, further comprising: means for generating the behavioral information using a generative AI model and a prompt sentence in generating the behavioral information. [Explanation of symbols]

[1849] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for acquiring peripheral information; A means for analyzing the acquired peripheral information; means for generating appropriate behavioral information based on the analysis results; means for transmitting the generated behavioral information; means for notifying a user of the received behavioral information; A system including:

2. The system according to claim 1 , wherein the peripheral information is location information and sensor information.

3. 10. The system of claim 1, further comprising means for evaluating the trustworthiness of the information provider and providing a reward based on the evaluation.

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