system

Abstract

Provide a system. A visitor detection means; a means for recording the visitor's voice; A means for converting the recorded voice into text data; A means for analyzing text data and extracting reasons for visits; A means for determining a visitor based on the reason for the visit; means for generating and reproducing a response message according to the determination result; A system including:

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 recent years, there has been an increase in fraud and unwanted door-to-door sales targeting elderly people and single-person households. While there is a need for technology to temporarily block such visitors, current technology does not adequately address this issue. Furthermore, the resulting stress and decreased safety have become serious social problems. Therefore, this invention aims to automate the identification and response of visitors, thereby providing a safer and more secure life. [Means for solving the problem]

[0005] The system of the present invention provides a system including a means for detecting visitors, a means for recording the visitor's voice, a means for converting the recorded voice into text data, a means for analyzing the text data and extracting the reason for the visit, a means for determining the visitor based on the reason for the visit, and a means for generating and playing a response message in accordance with the determination result (Claim 1).

[0006] Furthermore, this system includes a means for determining visitors that compares them with a list of suspicious people or unwanted sales people and selects the necessary messages (Claim 2). This makes it possible to distinguish between suspicious visitors and unwanted sales people and notify the user of only safe visitors.

[0007] It also includes a means for sending a notification to the user's mobile device when the judgment result is that the visitor is safe (claim 3). This allows the user to remotely confirm and respond to the visitor if they are safe, improving convenience and peace of mind.

[0008] A "visitor detection means" is part of a system that detects the presence of visitors using sensors, cameras, microphones, etc.

[0009] "Audio recording means" refers to a device or system module for recording what a visitor says.

[0010] "Speech-to-text conversion means" refers to software or algorithms that analyze recorded voice data and convert it into text data.

[0011] The "text analysis means" is a system module for analyzing the text data generated by the speech-to-text conversion means and extracting the reason for the visit and related information from the content.

[0012] The "visitor determination means" is a system module that evaluates and determines whether a visitor is safe or suspicious, or whether they are an unwanted sales call, based on information extracted by the text analysis means.

[0013] The "response message generating means" is software or a system module for generating an appropriate response message to a visitor based on the determination result obtained by the visitor determining means.

[0014] A "suspicious person list" is a database that contains information on individuals and companies that have been determined to be engaging in suspicious activities.

[0015] The "Unwanted Sales List" is a database that compiles information on unwanted door-to-door sales calls.

[0016] The "mobile terminal notification means" is a communication module and software for notifying the user's mobile terminal of visitor information and the judgment results. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

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

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

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

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0032] 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.

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

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and finally notifying the user. Detailed embodiments of the system are described below.

[0039] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[0040] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[0041] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[0042] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[0043] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[0044] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[0045] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[0046] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[0047] By having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with its built-in camera and record audio with its microphone.

[0051] Step 2:

[0052] Terminal: Sends visitor detection information to the server, including visitor images and other detection data.

[0053] Step 3:

[0054] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates the first response message, "Who is this?", and sends it to the device.

[0055] Step 4:

[0056] Terminal: Records responses from visitors. Responses are recorded in real time and the audio data is sent to the server.

[0057] Step 5:

[0058] Server: The received voice data is processed by a voice recognition module and converted into text data. The converted text data is analyzed to extract the reason for the visit.

[0059] Step 6:

[0060] Server: The reason for the visit is extracted using the text analysis module and compared with lists of suspicious people and unwanted sales. Based on the comparison results, the safety of the visitor is determined.

[0061] Step 7:

[0062] Server: Generates a response message based on the result of the judgment. In the case of a suspicious person or unwanted sales, a message such as "You do not need that product" or "The person in question is not present" is generated.

[0063] Step 8:

[0064] Terminal: The response message sent from the server is played back to the visitor. If the visitor is suspicious or trying to make unwanted sales, the message is used to respond to the visitor.

[0065] Step 9:

[0066] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[0067] Step 10:

[0068] User: Checks visitor information on a mobile device. If necessary, the user can remotely unlock the door via the intercom terminal. If the visitor is deemed unwanted, the user can have a "No entry" message played on the mobile device.

[0069] Example 1

[0070] 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."

[0071] In recent years, there has been a demand for stronger security within homes, but dealing with suspicious individuals and unwanted visitors is a burden for many people. Furthermore, dealing with visitors poses a particularly high risk for elderly people and those living alone. In these circumstances, there is a need for a system that reduces the burden by automating the entire process, from visitor detection to voice response, judgment, and user notification.

[0072] 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.

[0073] In this invention, the server includes means for detecting visitor movement, means for notifying the user of the presence of a visitor, means for generating a voice response message, means for recording the visitor's voice, means for converting the recorded voice into text data, means for analyzing the text data and extracting the reason for the visit, means for identifying the visitor based on the reason for the visit, means for generating and playing a response message in accordance with the identification result, means for displaying a video of the visitor, means for notifying the user, and means for the user to respond remotely. This automates the entire process from detecting the visitor to responding, identifying, and notifying the user, reducing the burden on the user and enabling improved home security.

[0074] A "means for detecting visitor movement" is a device or method that uses a camera or sensor to detect the movement or presence of a visitor.

[0075] The "means for notifying the presence of a visitor" refers to a communication method or device for transmitting visitor detection information to the server.

[0076] "Means for generating voice response messages" refers to devices or methods that use AI or programs to generate response messages for visitors.

[0077] The "means for recording the visitor's voice" refers to a device or method for recording the visitor's speech using a voice input device such as a microphone.

[0078] A "means for converting recorded voice into text data" is a device or method that uses voice recognition technology to convert recorded voice data into text form.

[0079] The "means for analyzing text data and extracting the reason for visit" is a device or method for extracting the purpose or reason for visit from text data converted using text analysis technology.

[0080] The "means for determining visitors based on the reason for visit" refers to a device or method for determining whether a visitor is safe or suspicious, or whether they are an unwanted sales call, based on the extracted reason for visit.

[0081] The "means for generating and playing back a response message in accordance with the judgment result" refers to a device or method for creating an appropriate response message based on the judgment result of the visitor and playing back the message.

[0082] The "means for displaying visitor images" refers to a display device or method for showing the visitor images captured by the camera to the user.

[0083] The "means for notifying the user" refers to a communication device or method for transmitting visitor information and the determination results to the user's mobile terminal or the like.

[0084] The "means for a user to respond remotely" refers to a device or method that allows a user to remotely respond to or give instructions to a visitor from a remote location.

[0085] The present invention is a system that automatically performs a series of processes from detecting a visitor, generating a response message, determining the reason for the visit, and finally notifying the user. Detailed embodiments of the system are described below.

[0086] First, the device is equipped with a camera and microphone. Specifically, the camera uses motion detection software (e.g., OpenCV) to detect visitor movement. When this motion is detected, the visitor's presence is confirmed via the intercom's microcontroller (e.g., Arduino).

[0087] Next, when the device detects the presence of a visitor, it immediately notifies the server of that information, using the REST API to send data in JSON format.

[0088] When the server receives the notification, it launches an AI response module (e.g., IBM Watson (registered trademark), Google (registered trademark) Dialogflow). This AI response module generates the first response message, "Who is this?", and sends it to the device. The device then plays the received message to the visitor through the speaker.

[0089] When the visitor responds, the device records the voice with a microphone and transmits it in real time to the server, which then converts the recorded voice into text data using a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft® Azure® Speech Service).

[0090] Next, the text data is analyzed using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. Based on the extracted reason for the visit, the server compares the visitor with a list of suspicious people or unwanted sales people to determine the visitor's identity.

[0091] Based on the result of the judgment, the server generates an appropriate response message and sends it back to the terminal, which then plays the response message over the speaker and conveys it to the visitor.

[0092] In particular, if the visitor is safe, the server notifies the user's mobile device (e.g., smartphone app) of the visitor's video and the reason for their visit. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door. This operation is performed by controlling the intercom relay from the mobile app via API.

[0093] As a concrete example, consider the case where the user is an elderly person living alone. Suppose a salesperson from a telephone company visits and the camera detects their presence. A voice message, "Who is this?", is played through the speaker, and the visitor responds, "This is ____ from the telephone company." The voice is recorded on the device and sent to the server in real time. The server converts the voice into text and analyzes it as "telephone company salesperson." It then compares it with a list of unwanted sales, generates a message saying "You don't need that product," and plays it through the device. This allows the elderly person to avoid unnecessary visits.

[0094] Example prompts to input to a generative AI model:

[0095] When a visitor speaks into the intercom and says "This is ____ from the telephone company," convert it into text and match it with your unwanted sales list to generate an appropriate response message.

[0096] This system significantly reduces the security risks associated with visits by having the terminal, server, and user cooperate to execute a series of processes, providing a safe and comfortable home environment.

[0097] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0098] Step 1:

[0099] The device uses a camera and motion detection software (e.g., OpenCV) to detect visitor movement. The input is video data from the camera, and the output is a signal indicating "motion detected." When this signal is detected, a microcontroller (e.g., Arduino) is triggered to confirm the visitor's presence. Specifically, the device detects the visitor's movement from the video captured by the camera, and the moment the movement is detected, a button on the intercom is pressed.

[0100] Step 2:

[0101] After the device confirms the visitor's presence, it immediately notifies the server of this information. The input is a signal indicating the visitor's presence, and the output is data sent to the server. Specifically, the visitor's presence information is sent to the server in JSON format using a REST API.

[0102] Step 3:

[0103] When the server receives a visitor presence notification, it launches an AI response module (e.g., IBM Watson, Google Dialogflow). The input is the presence notification data from the device, and the output is the generated initial response message. The AI ​​response module generates a response message such as "Who is this?" and sends it to the device. Specifically, the AI ​​automatically generates a response message for the visitor based on the notification it receives.

[0104] Step 4:

[0105] The terminal receives a message from the server and plays it to the visitor through the speaker. The input is the message data sent from the server, and the output is the audio message played on the speaker. Specifically, the message "Who is this?" is played to the visitor.

[0106] Step 5:

[0107] When the visitor responds, the device records the voice with a microphone and transmits it to the server in real time. The input is the visitor's voice, and the output is the recorded voice data. Specifically, the visitor's response voice is recorded and streamed to the server as voice data.

[0108] Step 6:

[0109] The server uses a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft Azure Speech Service) to convert the recorded audio into text data. The input is the visitor's voice data, and the output is the text data. Specifically, the audio data is sent to the speech recognition engine in real time and converted into text.

[0110] Step 7:

[0111] The server analyzes the text data using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. The input is the text data, and the output is the extracted reason for the visit. Specifically, the text data is input into a natural language analysis module to identify the reason for the visit.

[0112] Step 8:

[0113] The server compares the reason for the visit with a list of suspicious people and unwanted salespeople to determine the visitor. The input is the analyzed reason for the visit and existing list data, and the output is the visitor's judgment result. Specifically, the reason for the visit is compared with the list data to determine whether the visitor is suspicious or an unwanted salesperson.

[0114] Step 9:

[0115] Based on the judgment result, the server generates an appropriate response message and sends it back to the terminal. The input is the judgment result data, and the output is the generated response message. Specifically, depending on the judgment result, a message such as "You do not need that product" is generated and sent to the terminal.

[0116] Step 10:

[0117] The terminal receives a response message from the server and plays it back to the visitor through the speaker. The input is the response message data sent from the server, and the output is the voice message played back through the speaker. Specifically, a message such as "You do not need that product" is played back.

[0118] Step 11:

[0119] If the visitor is determined to be safe, the server notifies the user's mobile device of the visitor's video and the reason for their visit. The input is information about the visitor who was determined to be safe, and the output is the notification sent to the mobile device. Specifically, the server sends the visitor's video and the reason for their visit to the user's smartphone and notifies them.

[0120] Step 12:

[0121] The user checks the visitor's information on a mobile device and remotely unlocks or denies the visitor as necessary. The input is the visitor's information and the judgment result, and the output is a signal to remotely unlock or deny the visitor. Specifically, the user uses a smartphone app to control the intercom relay to remotely control the lock.

[0122] (Application example 1)

[0123] 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."

[0124] While there is a demand for more efficient response to visitors and improved security at home, elderly people and those living alone often have insufficient measures in place to protect against suspicious individuals and unwanted sales calls. There is also a need for a way to quickly check visitor information and respond appropriately, even when the user is out. In such an environment, the challenge is to provide a system that automatically detects and responds to visitors, notifying the user and enabling remote control.

[0125] 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.

[0126] In this invention, the server includes a means for determining the visitor by comparing the visitor with a list of suspicious persons or unwanted sales people and selecting the necessary message, a means for sending a notification to the user's mobile terminal when the determination result is safe, and a means for the user to unlock the door using a remote terminal. This makes it possible to consistently automate the process from visitor detection to response, notification to the user, and even remote door unlocking.

[0127] "Visitor detection" is the act of automatically detecting the presence of visitors using devices such as cameras and sensors.

[0128] "Audio recording" refers to the act of using a microphone to record a visitor's speech as electronic data.

[0129] "Conversion to text data" is the process of converting recorded voice data into written information using voice recognition technology.

[0130] "Text data analysis" is the process of using artificial intelligence and natural language processing technology to interpret the meaning of voice-to-text data and extract the reason for the visit.

[0131] "Visitor assessment" is the act of determining whether a visitor is safe, suspicious, or an unwanted sales call based on the extracted reason for the visit.

[0132] "Generating and playing a response message" refers to the act of generating an appropriate response message based on the visitor's assessment result and playing it back as audio.

[0133] "Generating and playing a response message in the case of a suspicious person or unwanted sales" refers to the act of generating and playing a message indicating the intention to reject a visitor if the visitor is determined to be a suspicious person or unwanted sales person.

[0134] "Remote terminal" refers to a mobile device, such as a mobile phone or smartphone, that a user can use away from home.

[0135] "Notification to the user's remote terminal" refers to the act of sending visitor information and judgment results to the user's mobile terminal in real time and notifying them.

[0136] "Unlocking the door" refers to an action in which a user uses a remote terminal to unlock the door of their home.

[0137] This invention is a security system that automates a series of processes from visitor detection to playback of a response message and final user notification. This system is mainly composed of a terminal that detects visitors, a server that analyzes data and generates responses, and a user's mobile terminal.

[0138] First, the device is equipped with a camera and microphone. When a visitor presses the intercom button or the camera detects movement, the device detects the visitor's presence and immediately notifies the server. The server receives the notification and activates the AI ​​response module. This module generates the initial response message, "Who is this?", and sends it to the device. Once a conversation with the visitor begins, the visitor's voice response is recorded.

[0139] The device then records the visitor's response and sends the audio data to the server. The server receives the audio data and converts it into text data using a speech recognition module (e.g., Google speech recognition API). This text data is then analyzed by a text analysis module to extract the reason for the visit. The server then compares the reason for the visit with a list of suspicious people and unwanted sales people to determine whether the visitor is suspicious, a safe visitor, or an unwanted sales person. Based on this determination, the server generates an appropriate response message in the next step.

[0140] For example, if the visitor is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here," which is sent to the terminal and played. On the other hand, if the visitor is determined to be safe, the server generates a message to notify the user's remote terminal of the reason for the visit and video footage. The user can check the visitor's information on the remote terminal and unlock the door via the intercom terminal if necessary. Notifications are made in real time, allowing the user to respond quickly.

[0141] As a concrete example of this system, consider the case where an elderly person is alone at home and receives a visit from a sales representative from a telecommunications company. The camera and microphone detect the visitor's presence and play a voice message asking, "Who is this?" If the visitor responds, "I'm a representative from the telecommunications company," the voice is converted into text and analyzed as a "telecommunications company salesperson." The server compares this with a list of unwanted salespeople and determines that the visit is unwanted. The server then generates a message saying, "You don't need that product," and plays it to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[0142] By using a generative AI model, the accuracy of analyzing the reason for visit can be improved, enabling faster and more accurate responses. An example of a specific prompt is as follows: "Please recognize the visitor's voice and convert it into text. We will use an AI model to analyze the reason for visit based on the visitor's response to 'Who is this?'"

[0143] As described above, by having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[0144] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0145] Step 1:

[0146] The device detects visitors. Specifically, it detects the presence of a visitor by the device's camera and motion detection sensor, or by pressing the intercom button. The input at this time is the camera image and the intercom button press signal. By receiving this data, it determines whether a visitor is present. The output is visitor detection information.

[0147] Step 2:

[0148] The terminal sends the detected information to the server. The input is the detected visitor information, which is then sent to the server. Specifically, data is sent over the network in the form of an HTTP request, etc. The output is that the server receives the detected information.

[0149] Step 3:

[0150] The server starts the AI ​​response module and generates the initial response message "Who is this?". The input is the visitor detection information, and the AI ​​response module is executed. As data processing, the AI ​​generates an appropriate response message. The output is the generated response message.

[0151] Step 4:

[0152] The terminal plays the generated response message. The input is the response message sent from the server. The terminal uses a speaker to ask the visitor, "Who is this?". The output is the played audio response.

[0153] Step 5:

[0154] The terminal records the visitor's response voice. The input is the visitor's voice, which is recorded using a microphone. Voice data is generated as data processing. The output is the recorded voice data.

[0155] Step 6:

[0156] The terminal sends the recorded voice data to the server. The input is the recorded voice data, which is sent to the server via the network. The output is the server receiving the voice data.

[0157] Step 7:

[0158] The server uses a speech recognition module to convert voice data into text data. The input is voice data, which is converted into text information using speech recognition technology (for example, Google speech recognition API). The output is text data.

[0159] Step 8:

[0160] The server uses a text analysis module to analyze the text data and extract the reason for the visit. The input is the text data, and the generative AI model is used to analyze the meaning. The output is the analyzed reason for the visit.

[0161] Step 9:

[0162] The server identifies visitors based on the reason for their visit. The input is the reason for the visit, and data manipulation is performed to match it with lists of suspicious people and unwanted sales. The output is the visitor's identification result.

[0163] Step 10:

[0164] The server generates a response message according to the judgment result and sends it to the terminal. The input is the visitor's judgment result, and an appropriate response message (e.g., "You don't need that product" in the case of an unwanted sale) is generated. The output is the generated response message.

[0165] Step 11:

[0166] The terminal plays the generated response message. The input is the response message sent from the server, and it responds to the visitor again using the speaker. The output is the played voice response.

[0167] Step 12:

[0168] If the server determines that the visitor is safe, it notifies the user's remote device of the reason for the visit and the video. The input is the safe visitor determination result and necessary data (video, reason for visit), which are sent to the remote device. The output is the notification sent to the user's remote device.

[0169] Step 13:

[0170] The user checks the visitor information on the remote terminal and unlocks the door if necessary. The input is the visitor information acquired on the remote terminal and the door unlock operation is performed. The output is that the door is unlocked.

[0171] 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.

[0172] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and recognizing the emotional state of the user. Detailed embodiments of the system are described below.

[0173] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[0174] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[0175] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[0176] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[0177] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[0178] The present invention also incorporates an emotion engine, which allows for optimal response to visitors by taking into account the user's emotional state.

[0179] The device or the user's mobile device captures the user's voice and facial expressions and sends them to the emotion engine, which then analyzes the user's emotional state (e.g., relief, vigilance, anxiety, fear, etc.) based on this data.

[0180] The server determines the final response message by taking into account not only the visitor's judgment result but also the user's emotional state from the emotion engine. For example, if the user is feeling anxious or scared, the server can generate an emergency message and execute measures to notify emergency contacts or the police.

[0181] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[0182] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. During this time, the emotion engine analyzes the user's voice and facial expressions, and if it determines that the user is feeling anxious, it will automatically notify emergency contacts.

[0183] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[0184] In this way, the terminal, server, user, and emotion engine work together to execute a series of processes, and this system significantly reduces the security risks associated with visits, providing a safe and comfortable home environment.

[0185] The processing flow will be explained below.

[0186] Step 1:

[0187] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with the camera and record audio with the microphone.

[0188] Step 2:

[0189] Terminal: Notifies the server of the visitor's detection information. This notification includes the visitor's image and detection data.

[0190] Step 3:

[0191] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates a response message saying "Who is this?" and sends it to the device.

[0192] Step 4:

[0193] Terminal: Records responses from visitors and sends the recorded audio data to the server in real time.

[0194] Step 5:

[0195] Server: The received voice data is processed by a voice recognition module, and the voice is converted into text data. The converted text data is analyzed to extract the reason for the visit.

[0196] Step 6:

[0197] Server: The reason for the visit extracted using the text analysis module is compared with the suspicious person list and unwanted sales list. Based on the comparison results, the safety of the visitor is determined.

[0198] Step 7:

[0199] Server: Generates a response message based on the result of the judgment. If the person is judged to be suspicious or to be making an unwanted sales pitch, a message such as "You do not need that product" or "The person in question is not present" is generated and sent to the terminal.

[0200] Step 8:

[0201] Terminal: Plays the response message to the visitor. If necessary, you can also request to see the certificate.

[0202] Step 9:

[0203] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[0204] Step 10:

[0205] User: Checks visitor information on a mobile device. If necessary, the door can be unlocked remotely via the intercom terminal. If the user wants to reject the visitor, a "No" message can be played.

[0206] Step 11:

[0207] Terminal: Captures the user's voice and facial expressions and sends them to the emotion engine.

[0208] Step 12:

[0209] Server: The emotion engine analyzes the captured voice and facial expressions to determine the user's emotional state (e.g., relief, alertness, anxiety, fear, etc.).

[0210] Step 13:

[0211] Server: Determines the appropriate response based on the user's emotional state and the visitor's assessment. If the server determines that the user is feeling anxious or scared, it will send a notification to emergency contacts and the police.

[0212] Step 14:

[0213] Server: Determines the final response and takes appropriate action, such as notifying emergency contacts or sending an alert to the user.

[0214] This series of processes enables efficient detection and response of visitors and recognition of the user's emotional state, providing a safe and secure living environment.

[0215] Example 2

[0216] 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."

[0217] In today's home environment, identifying and responding to visitors is often time-consuming and poses security risks. Elderly people living alone and busy households in particular require a fast and appropriate response to visitors. It is also necessary to accurately understand the visitor's intentions and effectively eliminate suspicious individuals and unwanted sales attempts. Furthermore, responding in a way that takes the user's emotional state into account can provide a greater sense of security.

[0218] 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 a means for detecting visitors, a means for recording the visitor's voice, a means for converting the recorded voice into text data, a means for analyzing the text data and extracting the reason for the visit, a means for determining the visitor based on the reason for the visit, a means for analyzing the user's emotional state, and a means for generating and playing a response message based on the determination result and the user's emotional state. This makes it possible to accurately understand the visitor's intentions, effectively eliminate suspicious individuals and unwanted sales tactics, and provide an optimal response that takes the user's emotional state into consideration.

[0219] "Means for detecting visitors" refers to devices or systems that use cameras or microphones to detect the presence of visitors.

[0220] "Means for recording visitor audio" refers to devices or systems that digitally record visitor speech and audio dialogue.

[0221] "Means for converting recorded speech into text data" refers to a device or system that uses speech recognition technology to automatically convert recorded speech into text form.

[0222] "Means for analyzing text data and extracting reasons for visit" refers to devices or systems that analyze text data and identify the visitor's intentions and reasons from its content.

[0223] "Means for determining visitors based on the reason for visit" refers to devices or systems that determine whether a visitor is suspicious, an unwanted visitor, or a safe visitor based on the extracted reason for visit.

[0224] "Means for analyzing the user's emotional state" refers to a device or system that analyzes the user's voice and facial expression data to identify the user's emotional state at that time.

[0225] "Means for generating and playing a response message based on the judgment result and the user's emotional state" refers to a device or system that automatically creates an appropriate response message and plays it to the visitor, taking into account the visitor's judgment result and the user's emotional state.

[0226] This invention is a system that automatically and centrally performs everything from detecting visitors to generating and playing response messages, recognizing the user's emotional state, and responding based on that. Specifically, the system is configured with a camera and microphone on the terminal, and various modules on the server.

[0227] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device immediately notifies the server. A standard surveillance camera and a high-sensitivity microphone are used.

[0228] When the server receives a notification from the terminal, it launches the AI ​​response module. The AI ​​response module generates an initial response message asking the visitor, "Who is this?" and sends it to the terminal. The terminal then plays this message aloud to the visitor. The AI ​​response module used here incorporates a generative AI model.

[0229] The device records the visitor's response and sends the audio data to the server. The server then uses a speech recognition module to convert the audio data into text data. For example, the Google Cloud Speech-to-Text API is used as the speech recognition module. The converted text data is then analyzed by a text analysis module to extract the reason for the visit.

[0230] The server determines the visitor based on the reason for the visit and compares them with a pre-prepared list of suspicious people or unwanted sales people. If the visitor is determined to be suspicious or an unwanted visitor, it generates a response message such as "You do not need that product" or "The visitor is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be safe, it notifies the user's mobile terminal of the reason for the visit and video. This notification uses real-time communication technology.

[0231] Furthermore, the emotion engine captures the user's voice and facial expressions and sends them to the emotion analysis module, which analyzes them to identify the user's emotional state. The emotion analysis module uses the Microsoft Azure Emotion API, among other tools. The server determines the final response message by taking into account not only the visitor's judgment but also the user's emotional state. For example, if the user is feeling anxious or scared, it can generate an emergency message and send a notification to emergency contacts or the police.

[0232] As a concrete example, consider the case where the user is an elderly person living alone. When the visitor responds, "I'm a salesperson from the telephone company," the server analyzes the voice and checks it against a list of unwanted sales. If it is determined that the product is unwanted, it generates a response message saying, "You don't need that product," and plays it to the visitor via their device. If the emotion engine detects anxiety in the user during this time, it automatically notifies emergency contacts. Furthermore, if the visitor is determined to be safe, the system connects to the user's mobile device in real time and notifies them of the visitor's information. The user can also unlock the door from their mobile device.

[0233] An example prompt based on a generative AI model is:

[0234] "Who is this?"

[0235] "There's no need for such products."

[0236] "The person in question is not here."

[0237] "We're making sure you're safe."

[0238] This system integrates everything from detecting visitors to generating and executing response messages based on the user's emotional state into a single flow, significantly reducing the security risks posed by visitors and providing a safe and comfortable home environment.

[0239] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0240] Step 1:

[0241] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device senses the visitor's presence. As a specific example, the device saves a frame at the moment the camera detects a moving object. The input is visitor presence information, and the output is visitor presence notification data.

[0242] Step 2:

[0243] The server receives the notification from the terminal and starts the AI ​​response module. The AI ​​response module generates the first response message, "Who is this?", and sends it to the terminal. The terminal then plays this message aloud to the visitor. The input is the notification data from the terminal, and the output is the response message, "Who is this?"

[0244] Step 3:

[0245] The terminal records the visitor's response and sends the voice data to the server. For example, a response such as "This is ____ from the telephone company" is recorded. The input is the visitor's voice, and the output is the recorded voice data.

[0246] Step 4:

[0247] The server processes the voice data received from the device using a voice recognition module. This module automatically converts the recorded voice into text format. The voice recognition module used includes the Google Cloud Speech-to-Text API. The converted text data is output. The input is the recorded voice data, and the output is text data.

[0248] Step 5:

[0249] The server analyzes the text data converted by the text analysis module and extracts the reason for the visit. The text analysis module uses natural language processing technology to identify the reason for the visit. For example, it may be analyzed as "telephone company sales." The input is text data, and the output is the reason for the visit.

[0250] Step 6:

[0251] The server then compares the analyzed reason for the visit with a list of suspicious individuals and unwanted salespeople prepared in advance to determine the visitor's identity. Based on the results of the determination, it generates an appropriate response message. For example, it generates a message such as "You do not need that product." The input is the reason for the visit, and the output is the determination result and the response message.

[0252] Step 7:

[0253] The terminal receives the response message from the server and plays it back to the visitor by voice. For example, it plays back a message saying, "You don't need that product." The input is the response message from the server, and the output is the voice message played back to the visitor.

[0254] Step 8:

[0255] The terminal or the user's mobile device captures the user's voice and facial expression. These data are sent to the emotion analysis module. The input is the user's voice and facial expression data, and the output is emotional state data.

[0256] Step 9:

[0257] The server receives the user's emotional state data from the emotion analysis module and determines the optimal response along with the visitor's assessment result. For example, if the user feels anxious or scared, it generates an emergency message and sends a notification to emergency contacts and the police. The input is the emotional state data and the visitor's assessment result, and the output is the final response message and emergency notification.

[0258] (Application example 2)

[0259] 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."

[0260] For elderly people and people living alone to live their daily lives with peace of mind, it is necessary to respond appropriately to visitors and reduce security risks. However, conventional intercom systems do not identify visitors or analyze user emotions, and further improvements in safety are required. Furthermore, since it is difficult to respond in real time when the user is in a remote location, prompt notification of visitor information is also important. Therefore, there is a need for a system that can detect visitors, identify them, generate response messages, and respond according to the user's emotional state in an integrated manner.

[0261] 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.

[0262] In this invention, the server includes means for detecting visitors, means for recording the visitor's voice and converting it into text data, means for analyzing the voice and extracting the reason for the visit, means for generating and playing a response message taking into account the judgment result and the user's emotional state, and means for analyzing the user's emotions and selecting a message according to that state. This enables the integrated process from visitor detection to judgment, generation of a response message, and response according to the user's emotional state to be performed automatically, thereby improving the safety and security of users.

[0263] "Means for detecting visitors" refers to means for recognizing and detecting the presence of visitors using devices such as cameras and sensors.

[0264] The "means for recording the visitor's voice" refers to a means for recording the contents of the visitor's speech using a voice collecting device such as a microphone.

[0265] "Means for converting recorded audio into text data" refers to means for converting recorded audio data into text information using voice recognition software or an API.

[0266] "Means for analyzing text data and extracting reasons for visit" refers to means for identifying and extracting reasons for visit from data that has been converted from voice to text using a natural language processing algorithm.

[0267] "Means for determining visitors based on the reason for their visit" refers to a means for confirming and determining whether a visitor has a purpose for visiting based on the results of text analysis.

[0268] "Means for generating and playing a response message taking into consideration the judgment result and the emotional state of the user" refers to means for creating an appropriate response message that reflects both the visitor's judgment result and the user's emotional state at the time, and conveying it to the visitor.

[0269] A "suspicious person list" is a list of people who are considered suspicious based on past data and information provided by the police.

[0270] An "unwanted sales list" is a list of people or companies whose specific sales purposes or sales activities are considered nuisances.

[0271] "Means for performing emotion analysis" refers to means for analyzing the user's facial expressions and voice patterns to identify the emotion (e.g., relief, vigilance, anxiety, fear, etc.) that the person is currently feeling.

[0272] A "means for sending notifications" is a means for sending information or alerts in real time to a user's mobile device, such as a smartphone or tablet.

[0273] "Smart glasses" are glasses-type wearable devices that have built-in cameras, microphones, displays, etc. and have advanced functions such as internet connectivity.

[0274] This invention is a system that detects visitors and automatically responds appropriately. Specifically, it detects the presence of a visitor, analyzes their voice data to extract the reason for their visit, and generates and plays a response message based on that information. It also analyzes the user's emotional state and provides an optimal response accordingly. The entire system functions in cooperation with a server, a terminal, and smart glasses.

[0275] Hardware and Software Configuration

[0276] 1. Smart Glasses

[0277] The device has a built-in camera and microphone, collects video and audio of visitors, and is worn by the user to interact with visitors and display emergency notifications.

[0278] 2. Server

[0279] Equipped with a high-performance CPU and GPU, it is responsible for data processing and running AI models, including speech recognition, text analysis, sentiment analysis, and response message generation.

[0280] 3. Speech Recognition Module

[0281] Use the Google Speech-to-Text API to convert audio data into text data.

[0282] 4. Text Analysis Module

[0283] A natural language processing model using TENSORFLOW (registered trademark) is used to extract reasons for visits from text data.

[0284] 5. Emotion Engine

[0285] The algorithm combines OpenCV and TensorFlow to analyze the user's facial expressions and vocal emotions.

[0286] 6. Message Generation Module

[0287] Generative AI models such as GPT-3® are used to generate response messages for visitors.

[0288] System Operation

[0289] The server receives the video and audio data sent from the smart glasses. It then converts the audio into text using a voice recognition module, and analyzes the text data using a text analysis module to extract the reason for the visit. The extracted reason for the visit is compared with a list of suspicious people and unwanted sales people to determine the visitor.

[0290] At the same time, the user's facial expression data captured by the smart glasses' camera is analyzed by the emotion engine to evaluate the user's emotional state. Based on the judgment result and the user's emotional state, the server uses a generative AI model to generate the most appropriate response message and sends it to the smart glasses.

[0291] For example, if the user is feeling anxious, the generated message will be short and safety-oriented.

[0292] Examples:

[0293] Consider a scenario in which an elderly person is wearing smart glasses. When a visitor arrives at the front door and rings the doorbell, the camera and microphone in the smart glasses detect the movement and send audio and video to the server. The server analyzes the audio data and automatically extracts the reason for the visit. If the visitor is determined to be an unwanted sales tactic, or if the emotion engine determines that the elderly person is feeling anxious, a safety-focused message is generated.

[0294] Example prompt sentence:

[0295] Convert visitor speech to text and identify the reason for their visit. Then, use your emotion engine to determine the user's emotional state and generate a reassuring message.

[0296] Caller says: "Hello, this is a professional company. Do you have time?"

[0297] User's emotional state: "Anxious"

[0298] Generates the message: "Thank you for visiting, but we're currently unavailable."

[0299] In this way, the present invention realizes a system that performs a consistent process from detecting visitors to generating a response message and responding based on the user's emotional state.

[0300] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0301] Step 1:

[0302] Smart glasses detect visitors.

[0303] Input: Camera video, audio data

[0304] How it works: The smart glasses' built-in camera captures video and a built-in microphone records the visitor's audio. The visual data is used to detect the visitor's presence.

[0305] Step 2:

[0306] The smart glasses send the collected data to a server.

[0307] Input: Camera video, audio data

[0308] Output: Audio and video data are sent to the server.

[0309] How it works: The smart glasses transmit the captured data to a server in real time, where it is transferred via an internet connection.

[0310] Step 3:

[0311] The server converts the voice data into text data.

[0312] Input: Audio data

[0313] Output: Text data

[0314] Specific operation: The server uses the Google Speech-to-Text API to convert the transmitted voice data into text. The voice waveform data is converted into character string data.

[0315] Step 4:

[0316] The server analyzes the text data and extracts the reason for the visit.

[0317] Input: Text data

[0318] Output: Reason for visit

[0319] Specific operation: The server uses TensorFlow to analyze the text data with the text analysis module and extract the reason for the visit. A natural language processing model is used.

[0320] Step 5:

[0321] The server determines who the visitor is.

[0322] Input: Reason for visit

[0323] Output: Judgment result (safe, suspicious person, unwanted sales)

[0324] Specific operation: The server checks the extracted reason for the visit against the suspicious person list and unwanted sales list to determine which category the visitor belongs to. A database search is performed.

[0325] Step 6:

[0326] The smart glasses capture the user's emotional state and send it to the emotion engine.

[0327] Input: User video data

[0328] Output: User's emotional state (e.g., relief, alertness, anxiety, fear)

[0329] How it works: The camera in the smart glasses captures the user's facial expressions and sends the data to the emotion engine, which uses OpenCV and TensorFlow to analyze the user's emotional state.

[0330] Step 7:

[0331] The server generates a response message based on the judgment result and the user's emotional state.

[0332] Input: Judgment result, user's emotional state

[0333] Output: Response message

[0334] Specific operation: Based on the judgment result and emotional state, the server generates an appropriate response message using a generative AI model such as GPT-3. The message to be generated is determined using the prompt sentence.

[0335] Step 8:

[0336] The reply message is sent to the smart glasses and played.

[0337] Input: Response message

[0338] Output: Message playback through smart glasses

[0339] Specific behavior: The generated response message is sent to the smart glasses and played as audio, allowing the user to listen to the message.

[0340] 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.

[0341] 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.

[0342] 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.

[0343] [Second embodiment]

[0344] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0345] 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.

[0346] 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).

[0347] 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.

[0348] 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.

[0349] 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).

[0350] 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.

[0351] 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.

[0352] 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.

[0353] 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.

[0354] 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.

[0355] 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."

[0356] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and finally notifying the user. Detailed embodiments of the system are described below.

[0357] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[0358] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[0359] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[0360] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[0361] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[0362] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[0363] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[0364] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[0365] By having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[0366] The processing flow will be explained below.

[0367] Step 1:

[0368] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with its built-in camera and record audio with its microphone.

[0369] Step 2:

[0370] Terminal: Sends visitor detection information to the server, including visitor images and other detection data.

[0371] Step 3:

[0372] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates the first response message, "Who is this?", and sends it to the device.

[0373] Step 4:

[0374] Terminal: Records responses from visitors. Responses are recorded in real time and the audio data is sent to the server.

[0375] Step 5:

[0376] Server: The received voice data is processed by a voice recognition module and converted into text data. The converted text data is analyzed to extract the reason for the visit.

[0377] Step 6:

[0378] Server: The reason for the visit is extracted using the text analysis module and compared with lists of suspicious people and unwanted sales. Based on the comparison results, the safety of the visitor is determined.

[0379] Step 7:

[0380] Server: Generates a response message based on the result of the judgment. In the case of a suspicious person or unwanted sales, a message such as "You do not need that product" or "The person in question is not present" is generated.

[0381] Step 8:

[0382] Terminal: The response message sent from the server is played back to the visitor. If the visitor is suspicious or trying to make unwanted sales, the message is used to respond to the visitor.

[0383] Step 9:

[0384] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[0385] Step 10:

[0386] User: Checks visitor information on a mobile device. If necessary, the user can remotely unlock the door via the intercom terminal. If the visitor is deemed unwanted, the user can have a "No entry" message played on the mobile device.

[0387] Example 1

[0388] 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."

[0389] In recent years, there has been a demand for stronger security within homes, but dealing with suspicious individuals and unwanted visitors is a burden for many people. Furthermore, dealing with visitors poses a particularly high risk for elderly people and those living alone. In these circumstances, there is a need for a system that reduces the burden by automating the entire process, from visitor detection to voice response, judgment, and user notification.

[0390] 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.

[0391] In this invention, the server includes means for detecting visitor movement, means for notifying the user of the presence of a visitor, means for generating a voice response message, means for recording the visitor's voice, means for converting the recorded voice into text data, means for analyzing the text data and extracting the reason for the visit, means for identifying the visitor based on the reason for the visit, means for generating and playing a response message in accordance with the identification result, means for displaying a video of the visitor, means for notifying the user, and means for the user to respond remotely. This automates the entire process from detecting the visitor to responding, identifying, and notifying the user, reducing the burden on the user and enabling improved home security.

[0392] A "means for detecting visitor movement" is a device or method that uses a camera or sensor to detect the movement or presence of a visitor.

[0393] The "means for notifying the presence of a visitor" refers to a communication method or device for transmitting visitor detection information to the server.

[0394] "Means for generating voice response messages" refers to devices or methods that use AI or programs to generate response messages for visitors.

[0395] The "means for recording the visitor's voice" refers to a device or method for recording the visitor's speech using a voice input device such as a microphone.

[0396] A "means for converting recorded voice into text data" is a device or method that uses voice recognition technology to convert recorded voice data into text form.

[0397] The "means for analyzing text data and extracting the reason for visit" is a device or method for extracting the purpose or reason for visit from text data converted using text analysis technology.

[0398] The "means for determining visitors based on the reason for visit" refers to a device or method for determining whether a visitor is safe or suspicious, or whether they are an unwanted sales call, based on the extracted reason for visit.

[0399] The "means for generating and playing back a response message in accordance with the judgment result" refers to a device or method for creating an appropriate response message based on the judgment result of the visitor and playing back the message.

[0400] The "means for displaying visitor images" refers to a display device or method for showing the visitor images captured by the camera to the user.

[0401] The "means for notifying the user" refers to a communication device or method for transmitting visitor information and the determination results to the user's mobile terminal or the like.

[0402] The "means for a user to respond remotely" refers to a device or method that allows a user to remotely respond to or give instructions to a visitor from a remote location.

[0403] The present invention is a system that automatically performs a series of processes from detecting a visitor, generating a response message, determining the reason for the visit, and finally notifying the user. Detailed embodiments of the system are described below.

[0404] First, the device is equipped with a camera and microphone. Specifically, the camera uses motion detection software (e.g., OpenCV) to detect visitor movement. When this motion is detected, the visitor's presence is confirmed via the intercom's microcontroller (e.g., Arduino).

[0405] Next, when the device detects the presence of a visitor, it immediately notifies the server of that information, using the REST API to send data in JSON format.

[0406] When the server receives the notification, it launches an AI response module (e.g., IBM Watson, Google Dialogflow). This AI response module generates the first response message, "Who is this?", and sends it to the device. The device then plays the received message to the visitor through the speaker.

[0407] When the visitor responds, the device records the audio with a microphone and transmits it in real time to the server, which then converts the recorded audio into text data using a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft Azure Speech Service).

[0408] Next, the text data is analyzed using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. Based on the extracted reason for the visit, the server compares the visitor with a list of suspicious people or unwanted sales people to determine the visitor's identity.

[0409] Based on the result of the judgment, the server generates an appropriate response message and sends it back to the terminal, which then plays the response message over the speaker and conveys it to the visitor.

[0410] In particular, if the visitor is safe, the server notifies the user's mobile device (e.g., smartphone app) of the visitor's video and the reason for their visit. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door. This operation is performed by controlling the intercom relay from the mobile app via API.

[0411] As a concrete example, consider the case where the user is an elderly person living alone. Suppose a salesperson from a telephone company visits and the camera detects their presence. A voice message, "Who is this?", is played through the speaker, and the visitor responds, "This is ____ from the telephone company." The voice is recorded on the device and sent to the server in real time. The server converts the voice into text and analyzes it as "telephone company salesperson." It then compares it with a list of unwanted sales, generates a message saying "You don't need that product," and plays it through the device. This allows the elderly person to avoid unnecessary visits.

[0412] Example prompts to input to a generative AI model:

[0413] When a visitor speaks into the intercom and says "This is ____ from the telephone company," convert it into text and match it with your unwanted sales list to generate an appropriate response message.

[0414] This system significantly reduces the security risks associated with visits by having the terminal, server, and user cooperate to execute a series of processes, providing a safe and comfortable home environment.

[0415] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0416] Step 1:

[0417] The device uses a camera and motion detection software (e.g., OpenCV) to detect visitor movement. The input is video data from the camera, and the output is a signal indicating "motion detected." When this signal is detected, a microcontroller (e.g., Arduino) is triggered to confirm the visitor's presence. Specifically, the device detects the visitor's movement from the video captured by the camera, and the moment the movement is detected, a button on the intercom is pressed.

[0418] Step 2:

[0419] After the device confirms the visitor's presence, it immediately notifies the server of this information. The input is a signal indicating the visitor's presence, and the output is data sent to the server. Specifically, the visitor's presence information is sent to the server in JSON format using a REST API.

[0420] Step 3:

[0421] When the server receives a visitor presence notification, it launches an AI response module (e.g., IBM Watson, Google Dialogflow). The input is the presence notification data from the device, and the output is the generated initial response message. The AI ​​response module generates a response message such as "Who is this?" and sends it to the device. Specifically, the AI ​​automatically generates a response message for the visitor based on the notification it receives.

[0422] Step 4:

[0423] The terminal receives a message from the server and plays it to the visitor through the speaker. The input is the message data sent from the server, and the output is the audio message played on the speaker. Specifically, the message "Who is this?" is played to the visitor.

[0424] Step 5:

[0425] When the visitor responds, the device records the voice with a microphone and transmits it to the server in real time. The input is the visitor's voice, and the output is the recorded voice data. Specifically, the visitor's response voice is recorded and streamed to the server as voice data.

[0426] Step 6:

[0427] The server uses a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft Azure Speech Service) to convert the recorded audio into text data. The input is the visitor's voice data, and the output is the text data. Specifically, the audio data is sent to the speech recognition engine in real time and converted into text.

[0428] Step 7:

[0429] The server analyzes the text data using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. The input is the text data, and the output is the extracted reason for the visit. Specifically, the text data is input into a natural language analysis module to identify the reason for the visit.

[0430] Step 8:

[0431] The server compares the reason for the visit with a list of suspicious people and unwanted salespeople to determine the visitor. The input is the analyzed reason for the visit and existing list data, and the output is the visitor's judgment result. Specifically, the reason for the visit is compared with the list data to determine whether the visitor is suspicious or an unwanted salesperson.

[0432] Step 9:

[0433] Based on the judgment result, the server generates an appropriate response message and sends it back to the terminal. The input is the judgment result data, and the output is the generated response message. Specifically, depending on the judgment result, a message such as "You do not need that product" is generated and sent to the terminal.

[0434] Step 10:

[0435] The terminal receives a response message from the server and plays it back to the visitor through the speaker. The input is the response message data sent from the server, and the output is the voice message played back through the speaker. Specifically, a message such as "You do not need that product" is played back.

[0436] Step 11:

[0437] If the visitor is determined to be safe, the server notifies the user's mobile device of the visitor's video and the reason for their visit. The input is information about the visitor who was determined to be safe, and the output is the notification sent to the mobile device. Specifically, the server sends the visitor's video and the reason for their visit to the user's smartphone and notifies them.

[0438] Step 12:

[0439] The user checks the visitor's information on a mobile device and remotely unlocks or denies the visitor as necessary. The input is the visitor's information and the judgment result, and the output is a signal to remotely unlock or deny the visitor. Specifically, the user uses a smartphone app to control the intercom relay to remotely control the lock.

[0440] (Application example 1)

[0441] 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."

[0442] While there is a demand for more efficient response to visitors and improved security at home, elderly people and those living alone often have insufficient measures in place to protect against suspicious individuals and unwanted sales calls. There is also a need for a way to quickly check visitor information and respond appropriately, even when the user is out. In such an environment, the challenge is to provide a system that automatically detects and responds to visitors, notifying the user and enabling remote control.

[0443] 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.

[0444] In this invention, the server includes a means for determining the visitor by comparing the visitor with a list of suspicious persons or unwanted sales people and selecting the necessary message, a means for sending a notification to the user's mobile terminal when the determination result is safe, and a means for the user to unlock the door using a remote terminal. This makes it possible to consistently automate the process from visitor detection to response, notification to the user, and even remote door unlocking.

[0445] "Visitor detection" is the act of automatically detecting the presence of visitors using devices such as cameras and sensors.

[0446] "Audio recording" refers to the act of using a microphone to record a visitor's speech as electronic data.

[0447] "Conversion to text data" is the process of converting recorded voice data into written information using voice recognition technology.

[0448] "Text data analysis" is the process of using artificial intelligence and natural language processing technology to interpret the meaning of voice-to-text data and extract the reason for the visit.

[0449] "Visitor assessment" is the act of determining whether a visitor is safe, suspicious, or an unwanted sales call based on the extracted reason for the visit.

[0450] "Generating and playing a response message" refers to the act of generating an appropriate response message based on the visitor's assessment result and playing it back as audio.

[0451] "Generating and playing a response message in the case of a suspicious person or unwanted sales" refers to the act of generating and playing a message indicating the intention to reject a visitor if the visitor is determined to be a suspicious person or unwanted sales person.

[0452] "Remote terminal" refers to a mobile device, such as a mobile phone or smartphone, that a user can use away from home.

[0453] "Notification to the user's remote terminal" refers to the act of sending visitor information and judgment results to the user's mobile terminal in real time and notifying them.

[0454] "Unlocking the door" refers to an action in which a user uses a remote terminal to unlock the door of their home.

[0455] This invention is a security system that automates a series of processes from visitor detection to playback of a response message and final user notification. This system is mainly composed of a terminal that detects visitors, a server that analyzes data and generates responses, and a user's mobile terminal.

[0456] First, the device is equipped with a camera and microphone. When a visitor presses the intercom button or the camera detects movement, the device detects the visitor's presence and immediately notifies the server. The server receives the notification and activates the AI ​​response module. This module generates the initial response message, "Who is this?", and sends it to the device. Once a conversation with the visitor begins, the visitor's voice response is recorded.

[0457] The device then records the visitor's response and sends the audio data to the server. The server receives the audio data and converts it into text data using a speech recognition module (e.g., Google speech recognition API). This text data is then analyzed by a text analysis module to extract the reason for the visit. The server then compares the reason for the visit with a list of suspicious people and unwanted sales people to determine whether the visitor is suspicious, a safe visitor, or an unwanted sales person. Based on this determination, the server generates an appropriate response message in the next step.

[0458] For example, if the visitor is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here," which is sent to the terminal and played. On the other hand, if the visitor is determined to be safe, the server generates a message to notify the user's remote terminal of the reason for the visit and video footage. The user can check the visitor's information on the remote terminal and unlock the door via the intercom terminal if necessary. Notifications are made in real time, allowing the user to respond quickly.

[0459] As a concrete example of this system, consider the case where an elderly person is alone at home and receives a visit from a sales representative from a telecommunications company. The camera and microphone detect the visitor's presence and play a voice message asking, "Who is this?" If the visitor responds, "I'm a representative from the telecommunications company," the voice is converted into text and analyzed as a "telecommunications company salesperson." The server compares this with a list of unwanted salespeople and determines that the visit is unwanted. The server then generates a message saying, "You don't need that product," and plays it to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[0460] By using a generative AI model, the accuracy of analyzing the reason for visit can be improved, enabling faster and more accurate responses. An example of a specific prompt is as follows: "Please recognize the visitor's voice and convert it into text. We will use an AI model to analyze the reason for visit based on the visitor's response to 'Who is this?'"

[0461] As described above, by having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[0462] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0463] Step 1:

[0464] The device detects visitors. Specifically, it detects the presence of a visitor by the device's camera and motion detection sensor, or by pressing the intercom button. The input at this time is the camera image and the intercom button press signal. By receiving this data, it determines whether a visitor is present. The output is visitor detection information.

[0465] Step 2:

[0466] The terminal sends the detected information to the server. The input is the detected visitor information, which is then sent to the server. Specifically, data is sent over the network in the form of an HTTP request, etc. The output is that the server receives the detected information.

[0467] Step 3:

[0468] The server starts the AI ​​response module and generates the initial response message "Who is this?". The input is the visitor detection information, and the AI ​​response module is executed. As data processing, the AI ​​generates an appropriate response message. The output is the generated response message.

[0469] Step 4:

[0470] The terminal plays the generated response message. The input is the response message sent from the server. The terminal uses a speaker to ask the visitor, "Who is this?". The output is the played audio response.

[0471] Step 5:

[0472] The terminal records the visitor's response voice. The input is the visitor's voice, which is recorded using a microphone. Voice data is generated as data processing. The output is the recorded voice data.

[0473] Step 6:

[0474] The terminal sends the recorded voice data to the server. The input is the recorded voice data, which is sent to the server via the network. The output is the server receiving the voice data.

[0475] Step 7:

[0476] The server uses a speech recognition module to convert voice data into text data. The input is voice data, which is converted into text information using speech recognition technology (for example, Google speech recognition API). The output is text data.

[0477] Step 8:

[0478] The server uses a text analysis module to analyze the text data and extract the reason for the visit. The input is the text data, and the generative AI model is used to analyze the meaning. The output is the analyzed reason for the visit.

[0479] Step 9:

[0480] The server identifies visitors based on the reason for their visit. The input is the reason for the visit, and data manipulation is performed to match it with lists of suspicious people and unwanted sales. The output is the visitor's identification result.

[0481] Step 10:

[0482] The server generates a response message according to the judgment result and sends it to the terminal. The input is the visitor's judgment result, and an appropriate response message (e.g., "You don't need that product" in the case of an unwanted sale) is generated. The output is the generated response message.

[0483] Step 11:

[0484] The terminal plays the generated response message. The input is the response message sent from the server, and it responds to the visitor again using the speaker. The output is the played voice response.

[0485] Step 12:

[0486] If the server determines that the visitor is safe, it notifies the user's remote device of the reason for the visit and the video. The input is the safe visitor determination result and necessary data (video, reason for visit), which are sent to the remote device. The output is the notification sent to the user's remote device.

[0487] Step 13:

[0488] The user checks the visitor information on the remote terminal and unlocks the door if necessary. The input is the visitor information acquired on the remote terminal and the door unlock operation is performed. The output is that the door is unlocked.

[0489] 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.

[0490] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and recognizing the emotional state of the user. Detailed embodiments of the system are described below.

[0491] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[0492] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[0493] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[0494] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[0495] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[0496] The present invention also incorporates an emotion engine, which allows for optimal response to visitors by taking into account the user's emotional state.

[0497] The device or the user's mobile device captures the user's voice and facial expressions and sends them to the emotion engine, which then analyzes the user's emotional state (e.g., relief, vigilance, anxiety, fear, etc.) based on this data.

[0498] The server determines the final response message by taking into account not only the visitor's judgment result but also the user's emotional state from the emotion engine. For example, if the user is feeling anxious or scared, the server can generate an emergency message and execute measures to notify emergency contacts or the police.

[0499] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[0500] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. During this time, the emotion engine analyzes the user's voice and facial expressions, and if it determines that the user is feeling anxious, it will automatically notify emergency contacts.

[0501] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[0502] In this way, the terminal, server, user, and emotion engine work together to execute a series of processes, and this system significantly reduces the security risks associated with visits, providing a safe and comfortable home environment.

[0503] The processing flow will be explained below.

[0504] Step 1:

[0505] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with the camera and record audio with the microphone.

[0506] Step 2:

[0507] Terminal: Notifies the server of the visitor's detection information. This notification includes the visitor's image and detection data.

[0508] Step 3:

[0509] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates a response message saying "Who is this?" and sends it to the device.

[0510] Step 4:

[0511] Terminal: Records responses from visitors and sends the recorded audio data to the server in real time.

[0512] Step 5:

[0513] Server: The received voice data is processed by a voice recognition module, and the voice is converted into text data. The converted text data is analyzed to extract the reason for the visit.

[0514] Step 6:

[0515] Server: The reason for the visit extracted using the text analysis module is compared with the suspicious person list and unwanted sales list. Based on the comparison results, the safety of the visitor is determined.

[0516] Step 7:

[0517] Server: Generates a response message based on the result of the judgment. If the person is judged to be suspicious or to be making an unwanted sales pitch, a message such as "You do not need that product" or "The person in question is not present" is generated and sent to the terminal.

[0518] Step 8:

[0519] Terminal: Plays the response message to the visitor. If necessary, you can also request to see the certificate.

[0520] Step 9:

[0521] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[0522] Step 10:

[0523] User: Checks visitor information on a mobile device. If necessary, the door can be unlocked remotely via the intercom terminal. If the user wants to reject the visitor, a "No" message can be played.

[0524] Step 11:

[0525] Terminal: Captures the user's voice and facial expressions and sends them to the emotion engine.

[0526] Step 12:

[0527] Server: The emotion engine analyzes the captured voice and facial expressions to determine the user's emotional state (e.g., relief, alertness, anxiety, fear, etc.).

[0528] Step 13:

[0529] Server: Determines the appropriate response based on the user's emotional state and the visitor's assessment. If the server determines that the user is feeling anxious or scared, it will send a notification to emergency contacts and the police.

[0530] Step 14:

[0531] Server: Determines the final response and takes appropriate action, such as notifying emergency contacts or sending an alert to the user.

[0532] This series of processes enables efficient detection and response of visitors and recognition of the user's emotional state, providing a safe and secure living environment.

[0533] Example 2

[0534] 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."

[0535] In today's home environment, identifying and responding to visitors is often time-consuming and poses security risks. Elderly people living alone and busy households in particular require a fast and appropriate response to visitors. It is also necessary to accurately understand the visitor's intentions and effectively eliminate suspicious individuals and unwanted sales attempts. Furthermore, responding in a way that takes the user's emotional state into account can provide a greater sense of security.

[0536] 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 a means for detecting visitors, a means for recording the visitor's voice, a means for converting the recorded voice into text data, a means for analyzing the text data and extracting the reason for the visit, a means for determining the visitor based on the reason for the visit, a means for analyzing the user's emotional state, and a means for generating and playing a response message based on the determination result and the user's emotional state. This makes it possible to accurately understand the visitor's intentions, effectively eliminate suspicious individuals and unwanted sales tactics, and provide an optimal response that takes the user's emotional state into consideration.

[0537] "Means for detecting visitors" refers to devices or systems that use cameras or microphones to detect the presence of visitors.

[0538] "Means for recording visitor audio" refers to devices or systems that digitally record visitor speech and audio dialogue.

[0539] "Means for converting recorded speech into text data" refers to a device or system that uses speech recognition technology to automatically convert recorded speech into text form.

[0540] "Means for analyzing text data and extracting reasons for visit" refers to devices or systems that analyze text data and identify the visitor's intentions and reasons from its content.

[0541] "Means for determining visitors based on the reason for visit" refers to devices or systems that determine whether a visitor is suspicious, an unwanted visitor, or a safe visitor based on the extracted reason for visit.

[0542] "Means for analyzing the user's emotional state" refers to a device or system that analyzes the user's voice and facial expression data to identify the user's emotional state at that time.

[0543] "Means for generating and playing a response message based on the judgment result and the user's emotional state" refers to a device or system that automatically creates an appropriate response message and plays it to the visitor, taking into account the visitor's judgment result and the user's emotional state.

[0544] This invention is a system that automatically and centrally performs everything from detecting visitors to generating and playing response messages, recognizing the user's emotional state, and responding based on that. Specifically, the system is configured with a camera and microphone on the terminal, and various modules on the server.

[0545] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device immediately notifies the server. A standard surveillance camera and a high-sensitivity microphone are used.

[0546] When the server receives a notification from the terminal, it launches the AI ​​response module. The AI ​​response module generates an initial response message asking the visitor, "Who is this?" and sends it to the terminal. The terminal then plays this message aloud to the visitor. The AI ​​response module used here incorporates a generative AI model.

[0547] The device records the visitor's response and sends the audio data to the server. The server then uses a speech recognition module to convert the audio data into text data. For example, the Google Cloud Speech-to-Text API is used as the speech recognition module. The converted text data is then analyzed by a text analysis module to extract the reason for the visit.

[0548] The server determines the visitor based on the reason for the visit and compares them with a pre-prepared list of suspicious people or unwanted sales people. If the visitor is determined to be suspicious or an unwanted visitor, it generates a response message such as "You do not need that product" or "The visitor is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be safe, it notifies the user's mobile terminal of the reason for the visit and video. This notification uses real-time communication technology.

[0549] Furthermore, the emotion engine captures the user's voice and facial expressions and sends them to the emotion analysis module, which analyzes them to identify the user's emotional state. The emotion analysis module uses the Microsoft Azure Emotion API, among other tools. The server determines the final response message by taking into account not only the visitor's judgment but also the user's emotional state. For example, if the user is feeling anxious or scared, it can generate an emergency message and send a notification to emergency contacts or the police.

[0550] As a concrete example, consider the case where the user is an elderly person living alone. When the visitor responds, "I'm a salesperson from the telephone company," the server analyzes the voice and checks it against a list of unwanted sales. If it is determined that the product is unwanted, it generates a response message saying, "You don't need that product," and plays it to the visitor via their device. If the emotion engine detects anxiety in the user during this time, it automatically notifies emergency contacts. Furthermore, if the visitor is determined to be safe, the system connects to the user's mobile device in real time and notifies them of the visitor's information. The user can also unlock the door from their mobile device.

[0551] An example prompt based on a generative AI model is:

[0552] "Who is this?"

[0553] "There's no need for such products."

[0554] "The person in question is not here."

[0555] "We're making sure you're safe."

[0556] This system integrates everything from detecting visitors to generating and executing response messages based on the user's emotional state into a single flow, significantly reducing the security risks posed by visitors and providing a safe and comfortable home environment.

[0557] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0558] Step 1:

[0559] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device senses the visitor's presence. As a specific example, the device saves a frame at the moment the camera detects a moving object. The input is visitor presence information, and the output is visitor presence notification data.

[0560] Step 2:

[0561] The server receives the notification from the terminal and starts the AI ​​response module. The AI ​​response module generates the first response message, "Who is this?", and sends it to the terminal. The terminal then plays this message aloud to the visitor. The input is the notification data from the terminal, and the output is the response message, "Who is this?"

[0562] Step 3:

[0563] The terminal records the visitor's response and sends the voice data to the server. For example, a response such as "This is ____ from the telephone company" is recorded. The input is the visitor's voice, and the output is the recorded voice data.

[0564] Step 4:

[0565] The server processes the voice data received from the device using a voice recognition module. This module automatically converts the recorded voice into text format. The voice recognition module used includes the Google Cloud Speech-to-Text API. The converted text data is output. The input is the recorded voice data, and the output is text data.

[0566] Step 5:

[0567] The server analyzes the text data converted by the text analysis module and extracts the reason for the visit. The text analysis module uses natural language processing technology to identify the reason for the visit. For example, it may be analyzed as "telephone company sales." The input is text data, and the output is the reason for the visit.

[0568] Step 6:

[0569] The server then compares the analyzed reason for the visit with a list of suspicious individuals and unwanted salespeople prepared in advance to determine the visitor's identity. Based on the results of the determination, it generates an appropriate response message. For example, it generates a message such as "You do not need that product." The input is the reason for the visit, and the output is the determination result and the response message.

[0570] Step 7:

[0571] The terminal receives the response message from the server and plays it back to the visitor by voice. For example, it plays back a message saying, "You don't need that product." The input is the response message from the server, and the output is the voice message played back to the visitor.

[0572] Step 8:

[0573] The terminal or the user's mobile device captures the user's voice and facial expression. These data are sent to the emotion analysis module. The input is the user's voice and facial expression data, and the output is emotional state data.

[0574] Step 9:

[0575] The server receives the user's emotional state data from the emotion analysis module and determines the optimal response along with the visitor's assessment result. For example, if the user feels anxious or scared, it generates an emergency message and sends a notification to emergency contacts and the police. The input is the emotional state data and the visitor's assessment result, and the output is the final response message and emergency notification.

[0576] (Application example 2)

[0577] 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."

[0578] For elderly people and people living alone to live their daily lives with peace of mind, it is necessary to respond appropriately to visitors and reduce security risks. However, conventional intercom systems do not identify visitors or analyze user emotions, and further improvements in safety are required. Furthermore, since it is difficult to respond in real time when the user is in a remote location, prompt notification of visitor information is also important. Therefore, there is a need for a system that can detect visitors, identify them, generate response messages, and respond according to the user's emotional state in an integrated manner.

[0579] 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.

[0580] In this invention, the server includes means for detecting visitors, means for recording the visitor's voice and converting it into text data, means for analyzing the voice and extracting the reason for the visit, means for generating and playing a response message taking into account the judgment result and the user's emotional state, and means for analyzing the user's emotions and selecting a message according to that state. This enables the integrated process from visitor detection to judgment, generation of a response message, and response according to the user's emotional state to be performed automatically, thereby improving the safety and security of users.

[0581] "Means for detecting visitors" refers to means for recognizing and detecting the presence of visitors using devices such as cameras and sensors.

[0582] The "means for recording the visitor's voice" refers to a means for recording the contents of the visitor's speech using a voice collecting device such as a microphone.

[0583] "Means for converting recorded audio into text data" refers to means for converting recorded audio data into text information using voice recognition software or an API.

[0584] "Means for analyzing text data and extracting reasons for visit" refers to means for identifying and extracting reasons for visit from data that has been converted from voice to text using a natural language processing algorithm.

[0585] "Means for determining visitors based on the reason for their visit" refers to a means for confirming and determining whether a visitor has a purpose for visiting based on the results of text analysis.

[0586] "Means for generating and playing a response message taking into consideration the judgment result and the emotional state of the user" refers to means for creating an appropriate response message that reflects both the visitor's judgment result and the user's emotional state at the time, and conveying it to the visitor.

[0587] A "suspicious person list" is a list of people who are considered suspicious based on past data and information provided by the police.

[0588] An "unwanted sales list" is a list of people or companies whose specific sales purposes or sales activities are considered nuisances.

[0589] "Means for performing emotion analysis" refers to means for analyzing the user's facial expressions and voice patterns to identify the emotion (e.g., relief, vigilance, anxiety, fear, etc.) that the person is currently feeling.

[0590] A "means for sending notifications" is a means for sending information or alerts in real time to a user's mobile device, such as a smartphone or tablet.

[0591] "Smart glasses" are glasses-type wearable devices that have built-in cameras, microphones, displays, etc. and have advanced functions such as internet connectivity.

[0592] This invention is a system that detects visitors and automatically responds appropriately. Specifically, it detects the presence of a visitor, analyzes their voice data to extract the reason for their visit, and generates and plays a response message based on that information. It also analyzes the user's emotional state and provides an optimal response accordingly. The entire system functions in cooperation with a server, a terminal, and smart glasses.

[0593] Hardware and Software Configuration

[0594] 1. Smart Glasses

[0595] The device has a built-in camera and microphone, collects video and audio of visitors, and is worn by the user to interact with visitors and display emergency notifications.

[0596] 2. Server

[0597] Equipped with a high-performance CPU and GPU, it is responsible for data processing and running AI models, including speech recognition, text analysis, sentiment analysis, and response message generation.

[0598] 3. Speech Recognition Module

[0599] Use the Google Speech-to-Text API to convert audio data into text data.

[0600] 4. Text Analysis Module

[0601] A natural language processing model using TensorFlow extracts reasons for visits from text data.

[0602] 5. Emotion Engine

[0603] The algorithm combines OpenCV and TensorFlow to analyze the user's facial expressions and vocal emotions.

[0604] 6. Message Generation Module

[0605] Use generative AI models such as GPT-3 to generate response messages for visitors.

[0606] System Operation

[0607] The server receives the video and audio data sent from the smart glasses. It then converts the audio into text using a voice recognition module, and analyzes the text data using a text analysis module to extract the reason for the visit. The extracted reason for the visit is compared with a list of suspicious people and unwanted sales people to determine the visitor.

[0608] At the same time, the user's facial expression data captured by the smart glasses' camera is analyzed by the emotion engine to evaluate the user's emotional state. Based on the judgment result and the user's emotional state, the server uses a generative AI model to generate the most appropriate response message and sends it to the smart glasses.

[0609] For example, if the user is feeling anxious, the generated message will be short and safety-oriented.

[0610] Examples:

[0611] Consider a scenario in which an elderly person is wearing smart glasses. When a visitor arrives at the front door and rings the doorbell, the camera and microphone in the smart glasses detect the movement and send audio and video to the server. The server analyzes the audio data and automatically extracts the reason for the visit. If the visitor is determined to be an unwanted sales tactic, or if the emotion engine determines that the elderly person is feeling anxious, a safety-focused message is generated.

[0612] Example prompt sentence:

[0613] Convert visitor speech to text and identify the reason for their visit. Then, use your emotion engine to determine the user's emotional state and generate a reassuring message.

[0614] Caller says: "Hello, this is a professional company. Do you have time?"

[0615] User's emotional state: "Anxious"

[0616] Generates the message: "Thank you for visiting, but we're currently unavailable."

[0617] In this way, the present invention realizes a system that performs a consistent process from detecting visitors to generating a response message and responding based on the user's emotional state.

[0618] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0619] Step 1:

[0620] Smart glasses detect visitors.

[0621] Input: Camera video, audio data

[0622] How it works: The smart glasses' built-in camera captures video and a built-in microphone records the visitor's audio. The visual data is used to detect the visitor's presence.

[0623] Step 2:

[0624] The smart glasses send the collected data to a server.

[0625] Input: Camera video, audio data

[0626] Output: Audio and video data are sent to the server.

[0627] How it works: The smart glasses transmit the captured data to a server in real time, where it is transferred via an internet connection.

[0628] Step 3:

[0629] The server converts the voice data into text data.

[0630] Input: Audio data

[0631] Output: Text data

[0632] Specific operation: The server uses the Google Speech-to-Text API to convert the transmitted voice data into text. The voice waveform data is converted into character string data.

[0633] Step 4:

[0634] The server analyzes the text data and extracts the reason for the visit.

[0635] Input: Text data

[0636] Output: Reason for visit

[0637] Specific operation: The server uses TensorFlow to analyze the text data with the text analysis module and extract the reason for the visit. A natural language processing model is used.

[0638] Step 5:

[0639] The server determines who the visitor is.

[0640] Input: Reason for visit

[0641] Output: Judgment result (safe, suspicious person, unwanted sales)

[0642] Specific operation: The server checks the extracted reason for the visit against the suspicious person list and unwanted sales list to determine which category the visitor belongs to. A database search is performed.

[0643] Step 6:

[0644] The smart glasses capture the user's emotional state and send it to the emotion engine.

[0645] Input: User video data

[0646] Output: User's emotional state (e.g., relief, alertness, anxiety, fear)

[0647] How it works: The camera in the smart glasses captures the user's facial expressions and sends the data to the emotion engine, which uses OpenCV and TensorFlow to analyze the user's emotional state.

[0648] Step 7:

[0649] The server generates a response message based on the judgment result and the user's emotional state.

[0650] Input: Judgment result, user's emotional state

[0651] Output: Response message

[0652] Specific operation: Based on the judgment result and emotional state, the server generates an appropriate response message using a generative AI model such as GPT-3. The message to be generated is determined using the prompt sentence.

[0653] Step 8:

[0654] The reply message is sent to the smart glasses and played.

[0655] Input: Response message

[0656] Output: Message playback through smart glasses

[0657] Specific behavior: The generated response message is sent to the smart glasses and played as audio, allowing the user to listen to the message.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] [Third embodiment]

[0662] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0663] 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.

[0664] 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).

[0665] 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.

[0666] 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.

[0667] 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).

[0668] 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.

[0669] 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.

[0670] 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.

[0671] 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.

[0672] 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.

[0673] 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."

[0674] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and finally notifying the user. Detailed embodiments of the system are described below.

[0675] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[0676] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[0677] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[0678] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[0679] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[0680] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[0681] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[0682] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[0683] By having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[0684] The processing flow will be explained below.

[0685] Step 1:

[0686] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with its built-in camera and record audio with its microphone.

[0687] Step 2:

[0688] Terminal: Sends visitor detection information to the server, including visitor images and other detection data.

[0689] Step 3:

[0690] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates the first response message, "Who is this?", and sends it to the device.

[0691] Step 4:

[0692] Terminal: Records responses from visitors. Responses are recorded in real time and the audio data is sent to the server.

[0693] Step 5:

[0694] Server: The received voice data is processed by a voice recognition module and converted into text data. The converted text data is analyzed to extract the reason for the visit.

[0695] Step 6:

[0696] Server: The reason for the visit is extracted using the text analysis module and compared with lists of suspicious people and unwanted sales. Based on the comparison results, the safety of the visitor is determined.

[0697] Step 7:

[0698] Server: Generates a response message based on the result of the judgment. In the case of a suspicious person or unwanted sales, a message such as "You do not need that product" or "The person in question is not present" is generated.

[0699] Step 8:

[0700] Terminal: The response message sent from the server is played back to the visitor. If the visitor is suspicious or trying to make unwanted sales, the message is used to respond to the visitor.

[0701] Step 9:

[0702] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[0703] Step 10:

[0704] User: Checks visitor information on a mobile device. If necessary, the user can remotely unlock the door via the intercom terminal. If the visitor is deemed unwanted, the user can have a "No entry" message played on the mobile device.

[0705] Example 1

[0706] 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."

[0707] In recent years, there has been a demand for stronger security within homes, but dealing with suspicious individuals and unwanted visitors is a burden for many people. Furthermore, dealing with visitors poses a particularly high risk for elderly people and those living alone. In these circumstances, there is a need for a system that reduces the burden by automating the entire process, from visitor detection to voice response, judgment, and user notification.

[0708] 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.

[0709] In this invention, the server includes means for detecting visitor movement, means for notifying the user of the presence of a visitor, means for generating a voice response message, means for recording the visitor's voice, means for converting the recorded voice into text data, means for analyzing the text data and extracting the reason for the visit, means for identifying the visitor based on the reason for the visit, means for generating and playing a response message in accordance with the identification result, means for displaying a video of the visitor, means for notifying the user, and means for the user to respond remotely. This automates the entire process from detecting the visitor to responding, identifying, and notifying the user, reducing the burden on the user and enabling improved home security.

[0710] A "means for detecting visitor movement" is a device or method that uses a camera or sensor to detect the movement or presence of a visitor.

[0711] The "means for notifying the presence of a visitor" refers to a communication method or device for transmitting visitor detection information to the server.

[0712] "Means for generating voice response messages" refers to devices or methods that use AI or programs to generate response messages for visitors.

[0713] The "means for recording the visitor's voice" refers to a device or method for recording the visitor's speech using a voice input device such as a microphone.

[0714] A "means for converting recorded voice into text data" is a device or method that uses voice recognition technology to convert recorded voice data into text form.

[0715] The "means for analyzing text data and extracting the reason for visit" is a device or method for extracting the purpose or reason for visit from text data converted using text analysis technology.

[0716] The "means for determining visitors based on the reason for visit" refers to a device or method for determining whether a visitor is safe or suspicious, or whether they are an unwanted sales call, based on the extracted reason for visit.

[0717] The "means for generating and playing back a response message in accordance with the judgment result" refers to a device or method for creating an appropriate response message based on the judgment result of the visitor and playing back the message.

[0718] The "means for displaying visitor images" refers to a display device or method for showing the visitor images captured by the camera to the user.

[0719] The "means for notifying the user" refers to a communication device or method for transmitting visitor information and the determination results to the user's mobile terminal or the like.

[0720] The "means for a user to respond remotely" refers to a device or method that allows a user to remotely respond to or give instructions to a visitor from a remote location.

[0721] The present invention is a system that automatically performs a series of processes from detecting a visitor, generating a response message, determining the reason for the visit, and finally notifying the user. Detailed embodiments of the system are described below.

[0722] First, the device is equipped with a camera and microphone. Specifically, the camera uses motion detection software (e.g., OpenCV) to detect visitor movement. When this motion is detected, the visitor's presence is confirmed via the intercom's microcontroller (e.g., Arduino).

[0723] Next, when the device detects the presence of a visitor, it immediately notifies the server of that information, using the REST API to send data in JSON format.

[0724] When the server receives the notification, it launches an AI response module (e.g., IBM Watson, Google Dialogflow). This AI response module generates the first response message, "Who is this?", and sends it to the device. The device then plays the received message to the visitor through the speaker.

[0725] When the visitor responds, the device records the audio with a microphone and transmits it in real time to the server, which then converts the recorded audio into text data using a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft Azure Speech Service).

[0726] Next, the text data is analyzed using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. Based on the extracted reason for the visit, the server compares the visitor with a list of suspicious people or unwanted sales people to determine the visitor's identity.

[0727] Based on the result of the judgment, the server generates an appropriate response message and sends it back to the terminal, which then plays the response message over the speaker and conveys it to the visitor.

[0728] In particular, if the visitor is safe, the server notifies the user's mobile device (e.g., smartphone app) of the visitor's video and the reason for their visit. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door. This operation is performed by controlling the intercom relay from the mobile app via API.

[0729] As a concrete example, consider the case where the user is an elderly person living alone. Suppose a salesperson from a telephone company visits and the camera detects their presence. A voice message, "Who is this?", is played through the speaker, and the visitor responds, "This is ____ from the telephone company." The voice is recorded on the device and sent to the server in real time. The server converts the voice into text and analyzes it as "telephone company salesperson." It then compares it with a list of unwanted sales, generates a message saying "You don't need that product," and plays it through the device. This allows the elderly person to avoid unnecessary visits.

[0730] Example prompts to input to a generative AI model:

[0731] When a visitor speaks into the intercom and says "This is ____ from the telephone company," convert it into text and match it with your unwanted sales list to generate an appropriate response message.

[0732] This system significantly reduces the security risks associated with visits by having the terminal, server, and user cooperate to execute a series of processes, providing a safe and comfortable home environment.

[0733] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0734] Step 1:

[0735] The device uses a camera and motion detection software (e.g., OpenCV) to detect visitor movement. The input is video data from the camera, and the output is a signal indicating "motion detected." When this signal is detected, a microcontroller (e.g., Arduino) is triggered to confirm the visitor's presence. Specifically, the device detects the visitor's movement from the video captured by the camera, and the moment the movement is detected, a button on the intercom is pressed.

[0736] Step 2:

[0737] After the device confirms the visitor's presence, it immediately notifies the server of this information. The input is a signal indicating the visitor's presence, and the output is data sent to the server. Specifically, the visitor's presence information is sent to the server in JSON format using a REST API.

[0738] Step 3:

[0739] When the server receives a visitor presence notification, it launches an AI response module (e.g., IBM Watson, Google Dialogflow). The input is the presence notification data from the device, and the output is the generated initial response message. The AI ​​response module generates a response message such as "Who is this?" and sends it to the device. Specifically, the AI ​​automatically generates a response message for the visitor based on the notification it receives.

[0740] Step 4:

[0741] The terminal receives a message from the server and plays it to the visitor through the speaker. The input is the message data sent from the server, and the output is the audio message played on the speaker. Specifically, the message "Who is this?" is played to the visitor.

[0742] Step 5:

[0743] When the visitor responds, the device records the voice with a microphone and transmits it to the server in real time. The input is the visitor's voice, and the output is the recorded voice data. Specifically, the visitor's response voice is recorded and streamed to the server as voice data.

[0744] Step 6:

[0745] The server uses a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft Azure Speech Service) to convert the recorded audio into text data. The input is the visitor's voice data, and the output is the text data. Specifically, the audio data is sent to the speech recognition engine in real time and converted into text.

[0746] Step 7:

[0747] The server analyzes the text data using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. The input is the text data, and the output is the extracted reason for the visit. Specifically, the text data is input into a natural language analysis module to identify the reason for the visit.

[0748] Step 8:

[0749] The server compares the reason for the visit with a list of suspicious people and unwanted salespeople to determine the visitor. The input is the analyzed reason for the visit and existing list data, and the output is the visitor's judgment result. Specifically, the reason for the visit is compared with the list data to determine whether the visitor is suspicious or an unwanted salesperson.

[0750] Step 9:

[0751] Based on the judgment result, the server generates an appropriate response message and sends it back to the terminal. The input is the judgment result data, and the output is the generated response message. Specifically, depending on the judgment result, a message such as "You do not need that product" is generated and sent to the terminal.

[0752] Step 10:

[0753] The terminal receives a response message from the server and plays it back to the visitor through the speaker. The input is the response message data sent from the server, and the output is the voice message played back through the speaker. Specifically, a message such as "You do not need that product" is played back.

[0754] Step 11:

[0755] If the visitor is determined to be safe, the server notifies the user's mobile device of the visitor's video and the reason for their visit. The input is information about the visitor who was determined to be safe, and the output is the notification sent to the mobile device. Specifically, the server sends the visitor's video and the reason for their visit to the user's smartphone and notifies them.

[0756] Step 12:

[0757] The user checks the visitor's information on a mobile device and remotely unlocks or denies the visitor as necessary. The input is the visitor's information and the judgment result, and the output is a signal to remotely unlock or deny the visitor. Specifically, the user uses a smartphone app to control the intercom relay to remotely control the lock.

[0758] (Application example 1)

[0759] 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."

[0760] While there is a demand for more efficient response to visitors and improved security at home, elderly people and those living alone often have insufficient measures in place to protect against suspicious individuals and unwanted sales calls. There is also a need for a way to quickly check visitor information and respond appropriately, even when the user is out. In such an environment, the challenge is to provide a system that automatically detects and responds to visitors, notifying the user and enabling remote control.

[0761] 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.

[0762] In this invention, the server includes a means for determining the visitor by comparing the visitor with a list of suspicious persons or unwanted sales people and selecting the necessary message, a means for sending a notification to the user's mobile terminal when the determination result is safe, and a means for the user to unlock the door using a remote terminal. This makes it possible to consistently automate the process from visitor detection to response, notification to the user, and even remote door unlocking.

[0763] "Visitor detection" is the act of automatically detecting the presence of visitors using devices such as cameras and sensors.

[0764] "Audio recording" refers to the act of using a microphone to record a visitor's speech as electronic data.

[0765] "Conversion to text data" is the process of converting recorded voice data into written information using voice recognition technology.

[0766] "Text data analysis" is the process of using artificial intelligence and natural language processing technology to interpret the meaning of voice-to-text data and extract the reason for the visit.

[0767] "Visitor assessment" is the act of determining whether a visitor is safe, suspicious, or an unwanted sales call based on the extracted reason for the visit.

[0768] "Generating and playing a response message" refers to the act of generating an appropriate response message based on the visitor's assessment result and playing it back as audio.

[0769] "Generating and playing a response message in the case of a suspicious person or unwanted sales" refers to the act of generating and playing a message indicating the intention to reject a visitor if the visitor is determined to be a suspicious person or unwanted sales person.

[0770] "Remote terminal" refers to a mobile device, such as a mobile phone or smartphone, that a user can use away from home.

[0771] "Notification to the user's remote terminal" refers to the act of sending visitor information and judgment results to the user's mobile terminal in real time and notifying them.

[0772] "Unlocking the door" refers to an action in which a user uses a remote terminal to unlock the door of their home.

[0773] This invention is a security system that automates a series of processes from visitor detection to playback of a response message and final user notification. This system is mainly composed of a terminal that detects visitors, a server that analyzes data and generates responses, and a user's mobile terminal.

[0774] First, the device is equipped with a camera and microphone. When a visitor presses the intercom button or the camera detects movement, the device detects the visitor's presence and immediately notifies the server. The server receives the notification and activates the AI ​​response module. This module generates the initial response message, "Who is this?", and sends it to the device. Once a conversation with the visitor begins, the visitor's voice response is recorded.

[0775] The device then records the visitor's response and sends the audio data to the server. The server receives the audio data and converts it into text data using a speech recognition module (e.g., Google speech recognition API). This text data is then analyzed by a text analysis module to extract the reason for the visit. The server then compares the reason for the visit with a list of suspicious people and unwanted sales people to determine whether the visitor is suspicious, a safe visitor, or an unwanted sales person. Based on this determination, the server generates an appropriate response message in the next step.

[0776] For example, if the visitor is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here," which is sent to the terminal and played. On the other hand, if the visitor is determined to be safe, the server generates a message to notify the user's remote terminal of the reason for the visit and video footage. The user can check the visitor's information on the remote terminal and unlock the door via the intercom terminal if necessary. Notifications are made in real time, allowing the user to respond quickly.

[0777] As a concrete example of this system, consider the case where an elderly person is alone at home and receives a visit from a sales representative from a telecommunications company. The camera and microphone detect the visitor's presence and play a voice message asking, "Who is this?" If the visitor responds, "I'm a representative from the telecommunications company," the voice is converted into text and analyzed as a "telecommunications company salesperson." The server compares this with a list of unwanted salespeople and determines that the visit is unwanted. The server then generates a message saying, "You don't need that product," and plays it to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[0778] By using a generative AI model, the accuracy of analyzing the reason for visit can be improved, enabling faster and more accurate responses. An example of a specific prompt is as follows: "Please recognize the visitor's voice and convert it into text. We will use an AI model to analyze the reason for visit based on the visitor's response to 'Who is this?'"

[0779] As described above, by having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[0780] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0781] Step 1:

[0782] The device detects visitors. Specifically, it detects the presence of a visitor by the device's camera and motion detection sensor, or by pressing the intercom button. The input at this time is the camera image and the intercom button press signal. By receiving this data, it determines whether a visitor is present. The output is visitor detection information.

[0783] Step 2:

[0784] The terminal sends the detected information to the server. The input is the detected visitor information, which is then sent to the server. Specifically, data is sent over the network in the form of an HTTP request, etc. The output is that the server receives the detected information.

[0785] Step 3:

[0786] The server starts the AI ​​response module and generates the initial response message "Who is this?". The input is the visitor detection information, and the AI ​​response module is executed. As data processing, the AI ​​generates an appropriate response message. The output is the generated response message.

[0787] Step 4:

[0788] The terminal plays the generated response message. The input is the response message sent from the server. The terminal uses a speaker to ask the visitor, "Who is this?". The output is the played audio response.

[0789] Step 5:

[0790] The terminal records the visitor's response voice. The input is the visitor's voice, which is recorded using a microphone. Voice data is generated as data processing. The output is the recorded voice data.

[0791] Step 6:

[0792] The terminal sends the recorded voice data to the server. The input is the recorded voice data, which is sent to the server via the network. The output is the server receiving the voice data.

[0793] Step 7:

[0794] The server uses a speech recognition module to convert voice data into text data. The input is voice data, which is converted into text information using speech recognition technology (for example, Google speech recognition API). The output is text data.

[0795] Step 8:

[0796] The server uses a text analysis module to analyze the text data and extract the reason for the visit. The input is the text data, and the generative AI model is used to analyze the meaning. The output is the analyzed reason for the visit.

[0797] Step 9:

[0798] The server identifies visitors based on the reason for their visit. The input is the reason for the visit, and data manipulation is performed to match it with lists of suspicious people and unwanted sales. The output is the visitor's identification result.

[0799] Step 10:

[0800] The server generates a response message according to the judgment result and sends it to the terminal. The input is the visitor's judgment result, and an appropriate response message (e.g., "You don't need that product" in the case of an unwanted sale) is generated. The output is the generated response message.

[0801] Step 11:

[0802] The terminal plays the generated response message. The input is the response message sent from the server, and it responds to the visitor again using the speaker. The output is the played voice response.

[0803] Step 12:

[0804] If the server determines that the visitor is safe, it notifies the user's remote device of the reason for the visit and the video. The input is the safe visitor determination result and necessary data (video, reason for visit), which are sent to the remote device. The output is the notification sent to the user's remote device.

[0805] Step 13:

[0806] The user checks the visitor information on the remote terminal and unlocks the door if necessary. The input is the visitor information acquired on the remote terminal and the door unlock operation is performed. The output is that the door is unlocked.

[0807] 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.

[0808] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and recognizing the emotional state of the user. Detailed embodiments of the system are described below.

[0809] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[0810] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[0811] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[0812] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[0813] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[0814] The present invention also incorporates an emotion engine, which allows for optimal response to visitors by taking into account the user's emotional state.

[0815] The device or the user's mobile device captures the user's voice and facial expressions and sends them to the emotion engine, which then analyzes the user's emotional state (e.g., relief, vigilance, anxiety, fear, etc.) based on this data.

[0816] The server determines the final response message by taking into account not only the visitor's judgment result but also the user's emotional state from the emotion engine. For example, if the user is feeling anxious or scared, the server can generate an emergency message and execute measures to notify emergency contacts or the police.

[0817] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[0818] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. During this time, the emotion engine analyzes the user's voice and facial expressions, and if it determines that the user is feeling anxious, it will automatically notify emergency contacts.

[0819] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[0820] In this way, the terminal, server, user, and emotion engine work together to execute a series of processes, and this system significantly reduces the security risks associated with visits, providing a safe and comfortable home environment.

[0821] The processing flow will be explained below.

[0822] Step 1:

[0823] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with the camera and record audio with the microphone.

[0824] Step 2:

[0825] Terminal: Notifies the server of the visitor's detection information. This notification includes the visitor's image and detection data.

[0826] Step 3:

[0827] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates a response message saying "Who is this?" and sends it to the device.

[0828] Step 4:

[0829] Terminal: Records responses from visitors and sends the recorded audio data to the server in real time.

[0830] Step 5:

[0831] Server: The received voice data is processed by a voice recognition module, and the voice is converted into text data. The converted text data is analyzed to extract the reason for the visit.

[0832] Step 6:

[0833] Server: The reason for the visit extracted using the text analysis module is compared with the suspicious person list and unwanted sales list. Based on the comparison results, the safety of the visitor is determined.

[0834] Step 7:

[0835] Server: Generates a response message based on the result of the judgment. If the person is judged to be suspicious or to be making an unwanted sales pitch, a message such as "You do not need that product" or "The person in question is not present" is generated and sent to the terminal.

[0836] Step 8:

[0837] Terminal: Plays the response message to the visitor. If necessary, you can also request to see the certificate.

[0838] Step 9:

[0839] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[0840] Step 10:

[0841] User: Checks visitor information on a mobile device. If necessary, the door can be unlocked remotely via the intercom terminal. If the user wants to reject the visitor, a "No" message can be played.

[0842] Step 11:

[0843] Terminal: Captures the user's voice and facial expressions and sends them to the emotion engine.

[0844] Step 12:

[0845] Server: The emotion engine analyzes the captured voice and facial expressions to determine the user's emotional state (e.g., relief, alertness, anxiety, fear, etc.).

[0846] Step 13:

[0847] Server: Determines the appropriate response based on the user's emotional state and the visitor's assessment. If the server determines that the user is feeling anxious or scared, it will send a notification to emergency contacts and the police.

[0848] Step 14:

[0849] Server: Determines the final response and takes appropriate action, such as notifying emergency contacts or sending an alert to the user.

[0850] This series of processes enables efficient detection and response of visitors and recognition of the user's emotional state, providing a safe and secure living environment.

[0851] Example 2

[0852] 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."

[0853] In today's home environment, identifying and responding to visitors is often time-consuming and poses security risks. Elderly people living alone and busy households in particular require a fast and appropriate response to visitors. It is also necessary to accurately understand the visitor's intentions and effectively eliminate suspicious individuals and unwanted sales attempts. Furthermore, responding in a way that takes the user's emotional state into account can provide a greater sense of security.

[0854] 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 a means for detecting visitors, a means for recording the visitor's voice, a means for converting the recorded voice into text data, a means for analyzing the text data and extracting the reason for the visit, a means for determining the visitor based on the reason for the visit, a means for analyzing the user's emotional state, and a means for generating and playing a response message based on the determination result and the user's emotional state. This makes it possible to accurately understand the visitor's intentions, effectively eliminate suspicious individuals and unwanted sales tactics, and provide an optimal response that takes the user's emotional state into consideration.

[0855] "Means for detecting visitors" refers to devices or systems that use cameras or microphones to detect the presence of visitors.

[0856] "Means for recording visitor audio" refers to devices or systems that digitally record visitor speech and audio dialogue.

[0857] "Means for converting recorded speech into text data" refers to a device or system that uses speech recognition technology to automatically convert recorded speech into text form.

[0858] "Means for analyzing text data and extracting reasons for visit" refers to devices or systems that analyze text data and identify the visitor's intentions and reasons from its content.

[0859] "Means for determining visitors based on the reason for visit" refers to devices or systems that determine whether a visitor is suspicious, an unwanted visitor, or a safe visitor based on the extracted reason for visit.

[0860] "Means for analyzing the user's emotional state" refers to a device or system that analyzes the user's voice and facial expression data to identify the user's emotional state at that time.

[0861] "Means for generating and playing a response message based on the judgment result and the user's emotional state" refers to a device or system that automatically creates an appropriate response message and plays it to the visitor, taking into account the visitor's judgment result and the user's emotional state.

[0862] This invention is a system that automatically and centrally performs everything from detecting visitors to generating and playing response messages, recognizing the user's emotional state, and responding based on that. Specifically, the system is configured with a camera and microphone on the terminal, and various modules on the server.

[0863] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device immediately notifies the server. A standard surveillance camera and a high-sensitivity microphone are used.

[0864] When the server receives a notification from the terminal, it launches the AI ​​response module. The AI ​​response module generates an initial response message asking the visitor, "Who is this?" and sends it to the terminal. The terminal then plays this message aloud to the visitor. The AI ​​response module used here incorporates a generative AI model.

[0865] The device records the visitor's response and sends the audio data to the server. The server then uses a speech recognition module to convert the audio data into text data. For example, the Google Cloud Speech-to-Text API is used as the speech recognition module. The converted text data is then analyzed by a text analysis module to extract the reason for the visit.

[0866] The server determines the visitor based on the reason for the visit and compares them with a pre-prepared list of suspicious people or unwanted sales people. If the visitor is determined to be suspicious or an unwanted visitor, it generates a response message such as "You do not need that product" or "The visitor is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be safe, it notifies the user's mobile terminal of the reason for the visit and video. This notification uses real-time communication technology.

[0867] Furthermore, the emotion engine captures the user's voice and facial expressions and sends them to the emotion analysis module, which analyzes them to identify the user's emotional state. The emotion analysis module uses the Microsoft Azure Emotion API, among other tools. The server determines the final response message by taking into account not only the visitor's judgment but also the user's emotional state. For example, if the user is feeling anxious or scared, it can generate an emergency message and send a notification to emergency contacts or the police.

[0868] As a concrete example, consider the case where the user is an elderly person living alone. When the visitor responds, "I'm a salesperson from the telephone company," the server analyzes the voice and checks it against a list of unwanted sales. If it is determined that the product is unwanted, it generates a response message saying, "You don't need that product," and plays it to the visitor via their device. If the emotion engine detects anxiety in the user during this time, it automatically notifies emergency contacts. Furthermore, if the visitor is determined to be safe, the system connects to the user's mobile device in real time and notifies them of the visitor's information. The user can also unlock the door from their mobile device.

[0869] An example prompt based on a generative AI model is:

[0870] "Who is this?"

[0871] "There's no need for such products."

[0872] "The person in question is not here."

[0873] "We're making sure you're safe."

[0874] This system integrates everything from detecting visitors to generating and executing response messages based on the user's emotional state into a single flow, significantly reducing the security risks posed by visitors and providing a safe and comfortable home environment.

[0875] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0876] Step 1:

[0877] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device senses the visitor's presence. As a specific example, the device saves a frame at the moment the camera detects a moving object. The input is visitor presence information, and the output is visitor presence notification data.

[0878] Step 2:

[0879] The server receives the notification from the terminal and starts the AI ​​response module. The AI ​​response module generates the first response message, "Who is this?", and sends it to the terminal. The terminal then plays this message aloud to the visitor. The input is the notification data from the terminal, and the output is the response message, "Who is this?"

[0880] Step 3:

[0881] The terminal records the visitor's response and sends the voice data to the server. For example, a response such as "This is ____ from the telephone company" is recorded. The input is the visitor's voice, and the output is the recorded voice data.

[0882] Step 4:

[0883] The server processes the voice data received from the device using a voice recognition module. This module automatically converts the recorded voice into text format. The voice recognition module used includes the Google Cloud Speech-to-Text API. The converted text data is output. The input is the recorded voice data, and the output is text data.

[0884] Step 5:

[0885] The server analyzes the text data converted by the text analysis module and extracts the reason for the visit. The text analysis module uses natural language processing technology to identify the reason for the visit. For example, it may be analyzed as "telephone company sales." The input is text data, and the output is the reason for the visit.

[0886] Step 6:

[0887] The server then compares the analyzed reason for the visit with a list of suspicious individuals and unwanted salespeople prepared in advance to determine the visitor's identity. Based on the results of the determination, it generates an appropriate response message. For example, it generates a message such as "You do not need that product." The input is the reason for the visit, and the output is the determination result and the response message.

[0888] Step 7:

[0889] The terminal receives the response message from the server and plays it back to the visitor by voice. For example, it plays back a message saying, "You don't need that product." The input is the response message from the server, and the output is the voice message played back to the visitor.

[0890] Step 8:

[0891] The terminal or the user's mobile device captures the user's voice and facial expression. These data are sent to the emotion analysis module. The input is the user's voice and facial expression data, and the output is emotional state data.

[0892] Step 9:

[0893] The server receives the user's emotional state data from the emotion analysis module and determines the optimal response along with the visitor's assessment result. For example, if the user feels anxious or scared, it generates an emergency message and sends a notification to emergency contacts and the police. The input is the emotional state data and the visitor's assessment result, and the output is the final response message and emergency notification.

[0894] (Application example 2)

[0895] 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."

[0896] For elderly people and people living alone to live their daily lives with peace of mind, it is necessary to respond appropriately to visitors and reduce security risks. However, conventional intercom systems do not identify visitors or analyze user emotions, and further improvements in safety are required. Furthermore, since it is difficult to respond in real time when the user is in a remote location, prompt notification of visitor information is also important. Therefore, there is a need for a system that can detect visitors, identify them, generate response messages, and respond according to the user's emotional state in an integrated manner.

[0897] 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.

[0898] In this invention, the server includes means for detecting visitors, means for recording the visitor's voice and converting it into text data, means for analyzing the voice and extracting the reason for the visit, means for generating and playing a response message taking into account the judgment result and the user's emotional state, and means for analyzing the user's emotions and selecting a message according to that state. This enables the integrated process from visitor detection to judgment, generation of a response message, and response according to the user's emotional state to be performed automatically, thereby improving the safety and security of users.

[0899] "Means for detecting visitors" refers to means for recognizing and detecting the presence of visitors using devices such as cameras and sensors.

[0900] The "means for recording the visitor's voice" refers to a means for recording the contents of the visitor's speech using a voice collecting device such as a microphone.

[0901] "Means for converting recorded audio into text data" refers to means for converting recorded audio data into text information using voice recognition software or an API.

[0902] "Means for analyzing text data and extracting reasons for visit" refers to means for identifying and extracting reasons for visit from data that has been converted from voice to text using a natural language processing algorithm.

[0903] "Means for determining visitors based on the reason for their visit" refers to a means for confirming and determining whether a visitor has a purpose for visiting based on the results of text analysis.

[0904] "Means for generating and playing a response message taking into consideration the judgment result and the emotional state of the user" refers to means for creating an appropriate response message that reflects both the visitor's judgment result and the user's emotional state at the time, and conveying it to the visitor.

[0905] A "suspicious person list" is a list of people who are considered suspicious based on past data and information provided by the police.

[0906] An "unwanted sales list" is a list of people or companies whose specific sales purposes or sales activities are considered nuisances.

[0907] "Means for performing emotion analysis" refers to means for analyzing the user's facial expressions and voice patterns to identify the emotion (e.g., relief, vigilance, anxiety, fear, etc.) that the person is currently feeling.

[0908] A "means for sending notifications" is a means for sending information or alerts in real time to a user's mobile device, such as a smartphone or tablet.

[0909] "Smart glasses" are glasses-type wearable devices that have built-in cameras, microphones, displays, etc. and have advanced functions such as internet connectivity.

[0910] This invention is a system that detects visitors and automatically responds appropriately. Specifically, it detects the presence of a visitor, analyzes their voice data to extract the reason for their visit, and generates and plays a response message based on that information. It also analyzes the user's emotional state and provides an optimal response accordingly. The entire system functions in cooperation with a server, a terminal, and smart glasses.

[0911] Hardware and Software Configuration

[0912] 1. Smart Glasses

[0913] The device has a built-in camera and microphone, collects video and audio of visitors, and is worn by the user to interact with visitors and display emergency notifications.

[0914] 2. Server

[0915] Equipped with a high-performance CPU and GPU, it is responsible for data processing and running AI models, including speech recognition, text analysis, sentiment analysis, and response message generation.

[0916] 3. Speech Recognition Module

[0917] Use the Google Speech-to-Text API to convert audio data into text data.

[0918] 4. Text Analysis Module

[0919] A natural language processing model using TensorFlow extracts reasons for visits from text data.

[0920] 5. Emotion Engine

[0921] The algorithm combines OpenCV and TensorFlow to analyze the user's facial expressions and vocal emotions.

[0922] 6. Message Generation Module

[0923] Use generative AI models such as GPT-3 to generate response messages for visitors.

[0924] System Operation

[0925] The server receives the video and audio data sent from the smart glasses. It then converts the audio into text using a voice recognition module, and analyzes the text data using a text analysis module to extract the reason for the visit. The extracted reason for the visit is compared with a list of suspicious people and unwanted sales people to determine the visitor.

[0926] At the same time, the user's facial expression data captured by the smart glasses' camera is analyzed by the emotion engine to evaluate the user's emotional state. Based on the judgment result and the user's emotional state, the server uses a generative AI model to generate the most appropriate response message and sends it to the smart glasses.

[0927] For example, if the user is feeling anxious, the generated message will be short and safety-oriented.

[0928] Examples:

[0929] Consider a scenario in which an elderly person is wearing smart glasses. When a visitor arrives at the front door and rings the doorbell, the camera and microphone in the smart glasses detect the movement and send audio and video to the server. The server analyzes the audio data and automatically extracts the reason for the visit. If the visitor is determined to be an unwanted sales tactic, or if the emotion engine determines that the elderly person is feeling anxious, a safety-focused message is generated.

[0930] Example prompt sentence:

[0931] Convert visitor speech to text and identify the reason for their visit. Then, use your emotion engine to determine the user's emotional state and generate a reassuring message.

[0932] Caller says: "Hello, this is a professional company. Do you have time?"

[0933] User's emotional state: "Anxious"

[0934] Generates the message: "Thank you for visiting, but we're currently unavailable."

[0935] In this way, the present invention realizes a system that performs a consistent process from detecting visitors to generating a response message and responding based on the user's emotional state.

[0936] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0937] Step 1:

[0938] Smart glasses detect visitors.

[0939] Input: Camera video, audio data

[0940] How it works: The smart glasses' built-in camera captures video and a built-in microphone records the visitor's audio. The visual data is used to detect the visitor's presence.

[0941] Step 2:

[0942] The smart glasses send the collected data to a server.

[0943] Input: Camera video, audio data

[0944] Output: Audio and video data are sent to the server.

[0945] How it works: The smart glasses transmit the captured data to a server in real time, where it is transferred via an internet connection.

[0946] Step 3:

[0947] The server converts the voice data into text data.

[0948] Input: Audio data

[0949] Output: Text data

[0950] Specific operation: The server uses the Google Speech-to-Text API to convert the transmitted voice data into text. The voice waveform data is converted into character string data.

[0951] Step 4:

[0952] The server analyzes the text data and extracts the reason for the visit.

[0953] Input: Text data

[0954] Output: Reason for visit

[0955] Specific operation: The server uses TensorFlow to analyze the text data with the text analysis module and extract the reason for the visit. A natural language processing model is used.

[0956] Step 5:

[0957] The server determines who the visitor is.

[0958] Input: Reason for visit

[0959] Output: Judgment result (safe, suspicious person, unwanted sales)

[0960] Specific operation: The server checks the extracted reason for the visit against the suspicious person list and unwanted sales list to determine which category the visitor belongs to. A database search is performed.

[0961] Step 6:

[0962] The smart glasses capture the user's emotional state and send it to the emotion engine.

[0963] Input: User video data

[0964] Output: User's emotional state (e.g., relief, alertness, anxiety, fear)

[0965] How it works: The camera in the smart glasses captures the user's facial expressions and sends the data to the emotion engine, which uses OpenCV and TensorFlow to analyze the user's emotional state.

[0966] Step 7:

[0967] The server generates a response message based on the judgment result and the user's emotional state.

[0968] Input: Judgment result, user's emotional state

[0969] Output: Response message

[0970] Specific operation: Based on the judgment result and emotional state, the server generates an appropriate response message using a generative AI model such as GPT-3. The message to be generated is determined using the prompt sentence.

[0971] Step 8:

[0972] The reply message is sent to the smart glasses and played.

[0973] Input: Response message

[0974] Output: Message playback through smart glasses

[0975] Specific behavior: The generated response message is sent to the smart glasses and played as audio, allowing the user to listen to the message.

[0976] 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.

[0977] 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.

[0978] 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.

[0979] [Fourth embodiment]

[0980] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0981] 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.

[0982] 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).

[0983] 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.

[0984] 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.

[0985] 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).

[0986] 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.

[0987] 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.

[0988] 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.

[0989] 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.

[0990] 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.

[0991] 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.

[0992] 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."

[0993] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and finally notifying the user. Detailed embodiments of the system are described below.

[0994] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[0995] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[0996] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[0997] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[0998] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[0999] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[1000] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[1001] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[1002] By having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[1003] The processing flow will be explained below.

[1004] Step 1:

[1005] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with its built-in camera and record audio with its microphone.

[1006] Step 2:

[1007] Terminal: Sends visitor detection information to the server, including visitor images and other detection data.

[1008] Step 3:

[1009] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates the first response message, "Who is this?", and sends it to the device.

[1010] Step 4:

[1011] Terminal: Records responses from visitors. Responses are recorded in real time and the audio data is sent to the server.

[1012] Step 5:

[1013] Server: The received voice data is processed by a voice recognition module and converted into text data. The converted text data is analyzed to extract the reason for the visit.

[1014] Step 6:

[1015] Server: The reason for the visit is extracted using the text analysis module and compared with lists of suspicious people and unwanted sales. Based on the comparison results, the safety of the visitor is determined.

[1016] Step 7:

[1017] Server: Generates a response message based on the result of the judgment. In the case of a suspicious person or unwanted sales, a message such as "You do not need that product" or "The person in question is not present" is generated.

[1018] Step 8:

[1019] Terminal: The response message sent from the server is played back to the visitor. If the visitor is suspicious or trying to make unwanted sales, the message is used to respond to the visitor.

[1020] Step 9:

[1021] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[1022] Step 10:

[1023] User: Checks visitor information on a mobile device. If necessary, the user can remotely unlock the door via the intercom terminal. If the visitor is deemed unwanted, the user can have a "No entry" message played on the mobile device.

[1024] Example 1

[1025] 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."

[1026] In recent years, there has been a demand for stronger security within homes, but dealing with suspicious individuals and unwanted visitors is a burden for many people. Furthermore, dealing with visitors poses a particularly high risk for elderly people and those living alone. In these circumstances, there is a need for a system that reduces the burden by automating the entire process, from visitor detection to voice response, judgment, and user notification.

[1027] 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.

[1028] In this invention, the server includes means for detecting visitor movement, means for notifying the user of the presence of a visitor, means for generating a voice response message, means for recording the visitor's voice, means for converting the recorded voice into text data, means for analyzing the text data and extracting the reason for the visit, means for identifying the visitor based on the reason for the visit, means for generating and playing a response message in accordance with the identification result, means for displaying a video of the visitor, means for notifying the user, and means for the user to respond remotely. This automates the entire process from detecting the visitor to responding, identifying, and notifying the user, reducing the burden on the user and enabling improved home security.

[1029] A "means for detecting visitor movement" is a device or method that uses a camera or sensor to detect the movement or presence of a visitor.

[1030] The "means for notifying the presence of a visitor" refers to a communication method or device for transmitting visitor detection information to the server.

[1031] "Means for generating voice response messages" refers to devices or methods that use AI or programs to generate response messages for visitors.

[1032] The "means for recording the visitor's voice" refers to a device or method for recording the visitor's speech using a voice input device such as a microphone.

[1033] A "means for converting recorded voice into text data" is a device or method that uses voice recognition technology to convert recorded voice data into text form.

[1034] The "means for analyzing text data and extracting the reason for visit" is a device or method for extracting the purpose or reason for visit from text data converted using text analysis technology.

[1035] The "means for determining visitors based on the reason for visit" refers to a device or method for determining whether a visitor is safe or suspicious, or whether they are an unwanted sales call, based on the extracted reason for visit.

[1036] The "means for generating and playing back a response message in accordance with the judgment result" refers to a device or method for creating an appropriate response message based on the judgment result of the visitor and playing back the message.

[1037] The "means for displaying visitor images" refers to a display device or method for showing the visitor images captured by the camera to the user.

[1038] The "means for notifying the user" refers to a communication device or method for transmitting visitor information and the determination results to the user's mobile terminal or the like.

[1039] The "means for a user to respond remotely" refers to a device or method that allows a user to remotely respond to or give instructions to a visitor from a remote location.

[1040] The present invention is a system that automatically performs a series of processes from detecting a visitor, generating a response message, determining the reason for the visit, and finally notifying the user. Detailed embodiments of the system are described below.

[1041] First, the device is equipped with a camera and microphone. Specifically, the camera uses motion detection software (e.g., OpenCV) to detect visitor movement. When this motion is detected, the visitor's presence is confirmed via the intercom's microcontroller (e.g., Arduino).

[1042] Next, when the device detects the presence of a visitor, it immediately notifies the server of that information, using the REST API to send data in JSON format.

[1043] When the server receives the notification, it launches an AI response module (e.g., IBM Watson, Google Dialogflow). This AI response module generates the first response message, "Who is this?", and sends it to the device. The device then plays the received message to the visitor through the speaker.

[1044] When the visitor responds, the device records the audio with a microphone and transmits it in real time to the server, which then converts the recorded audio into text data using a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft Azure Speech Service).

[1045] Next, the text data is analyzed using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. Based on the extracted reason for the visit, the server compares the visitor with a list of suspicious people or unwanted sales people to determine the visitor's identity.

[1046] Based on the result of the judgment, the server generates an appropriate response message and sends it back to the terminal, which then plays the response message over the speaker and conveys it to the visitor.

[1047] In particular, if the visitor is safe, the server notifies the user's mobile device (e.g., smartphone app) of the visitor's video and the reason for their visit. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door. This operation is performed by controlling the intercom relay from the mobile app via API.

[1048] As a concrete example, consider the case where the user is an elderly person living alone. Suppose a salesperson from a telephone company visits and the camera detects their presence. A voice message, "Who is this?", is played through the speaker, and the visitor responds, "This is ____ from the telephone company." The voice is recorded on the device and sent to the server in real time. The server converts the voice into text and analyzes it as "telephone company salesperson." It then compares it with a list of unwanted sales, generates a message saying "You don't need that product," and plays it through the device. This allows the elderly person to avoid unnecessary visits.

[1049] Example prompts to input to a generative AI model:

[1050] When a visitor speaks into the intercom and says "This is ____ from the telephone company," convert it into text and match it with your unwanted sales list to generate an appropriate response message.

[1051] This system significantly reduces the security risks associated with visits by having the terminal, server, and user cooperate to execute a series of processes, providing a safe and comfortable home environment.

[1052] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1053] Step 1:

[1054] The device uses a camera and motion detection software (e.g., OpenCV) to detect visitor movement. The input is video data from the camera, and the output is a signal indicating "motion detected." When this signal is detected, a microcontroller (e.g., Arduino) is triggered to confirm the visitor's presence. Specifically, the device detects the visitor's movement from the video captured by the camera, and the moment the movement is detected, a button on the intercom is pressed.

[1055] Step 2:

[1056] After the device confirms the visitor's presence, it immediately notifies the server of this information. The input is a signal indicating the visitor's presence, and the output is data sent to the server. Specifically, the visitor's presence information is sent to the server in JSON format using a REST API.

[1057] Step 3:

[1058] When the server receives a visitor presence notification, it launches an AI response module (e.g., IBM Watson, Google Dialogflow). The input is the presence notification data from the device, and the output is the generated initial response message. The AI ​​response module generates a response message such as "Who is this?" and sends it to the device. Specifically, the AI ​​automatically generates a response message for the visitor based on the notification it receives.

[1059] Step 4:

[1060] The terminal receives a message from the server and plays it to the visitor through the speaker. The input is the message data sent from the server, and the output is the audio message played on the speaker. Specifically, the message "Who is this?" is played to the visitor.

[1061] Step 5:

[1062] When the visitor responds, the device records the voice with a microphone and transmits it to the server in real time. The input is the visitor's voice, and the output is the recorded voice data. Specifically, the visitor's response voice is recorded and streamed to the server as voice data.

[1063] Step 6:

[1064] The server uses a speech recognition module (e.g., Google Cloud Speech-to-Text, Microsoft Azure Speech Service) to convert the recorded audio into text data. The input is the visitor's voice data, and the output is the text data. Specifically, the audio data is sent to the speech recognition engine in real time and converted into text.

[1065] Step 7:

[1066] The server analyzes the text data using a text analysis module (e.g., Amazon Comprehend, SpaCy) to extract the reason for the visit. The input is the text data, and the output is the extracted reason for the visit. Specifically, the text data is input into a natural language analysis module to identify the reason for the visit.

[1067] Step 8:

[1068] The server compares the reason for the visit with a list of suspicious people and unwanted salespeople to determine the visitor. The input is the analyzed reason for the visit and existing list data, and the output is the visitor's judgment result. Specifically, the reason for the visit is compared with the list data to determine whether the visitor is suspicious or an unwanted salesperson.

[1069] Step 9:

[1070] Based on the judgment result, the server generates an appropriate response message and sends it back to the terminal. The input is the judgment result data, and the output is the generated response message. Specifically, depending on the judgment result, a message such as "You do not need that product" is generated and sent to the terminal.

[1071] Step 10:

[1072] The terminal receives a response message from the server and plays it back to the visitor through the speaker. The input is the response message data sent from the server, and the output is the voice message played back through the speaker. Specifically, a message such as "You do not need that product" is played back.

[1073] Step 11:

[1074] If the visitor is determined to be safe, the server notifies the user's mobile device of the visitor's video and the reason for their visit. The input is information about the visitor who was determined to be safe, and the output is the notification sent to the mobile device. Specifically, the server sends the visitor's video and the reason for their visit to the user's smartphone and notifies them.

[1075] Step 12:

[1076] The user checks the visitor's information on a mobile device and remotely unlocks or denies the visitor as necessary. The input is the visitor's information and the judgment result, and the output is a signal to remotely unlock or deny the visitor. Specifically, the user uses a smartphone app to control the intercom relay to remotely control the lock.

[1077] (Application example 1)

[1078] 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."

[1079] While there is a demand for more efficient response to visitors and improved security at home, elderly people and those living alone often have insufficient measures in place to protect against suspicious individuals and unwanted sales calls. There is also a need for a way to quickly check visitor information and respond appropriately, even when the user is out. In such an environment, the challenge is to provide a system that automatically detects and responds to visitors, notifying the user and enabling remote control.

[1080] 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.

[1081] In this invention, the server includes a means for determining the visitor by comparing the visitor with a list of suspicious persons or unwanted sales people and selecting the necessary message, a means for sending a notification to the user's mobile terminal when the determination result is safe, and a means for the user to unlock the door using a remote terminal. This makes it possible to consistently automate the process from visitor detection to response, notification to the user, and even remote door unlocking.

[1082] "Visitor detection" is the act of automatically detecting the presence of visitors using devices such as cameras and sensors.

[1083] "Audio recording" refers to the act of using a microphone to record a visitor's speech as electronic data.

[1084] "Conversion to text data" is the process of converting recorded voice data into written information using voice recognition technology.

[1085] "Text data analysis" is the process of using artificial intelligence and natural language processing technology to interpret the meaning of voice-to-text data and extract the reason for the visit.

[1086] "Visitor assessment" is the act of determining whether a visitor is safe, suspicious, or an unwanted sales call based on the extracted reason for the visit.

[1087] "Generating and playing a response message" refers to the act of generating an appropriate response message based on the visitor's assessment result and playing it back as audio.

[1088] "Generating and playing a response message in the case of a suspicious person or unwanted sales" refers to the act of generating and playing a message indicating the intention to reject a visitor if the visitor is determined to be a suspicious person or unwanted sales person.

[1089] "Remote terminal" refers to a mobile device, such as a mobile phone or smartphone, that a user can use away from home.

[1090] "Notification to the user's remote terminal" refers to the act of sending visitor information and judgment results to the user's mobile terminal in real time and notifying them.

[1091] "Unlocking the door" refers to an action in which a user uses a remote terminal to unlock the door of their home.

[1092] This invention is a security system that automates a series of processes from visitor detection to playback of a response message and final user notification. This system is mainly composed of a terminal that detects visitors, a server that analyzes data and generates responses, and a user's mobile terminal.

[1093] First, the device is equipped with a camera and microphone. When a visitor presses the intercom button or the camera detects movement, the device detects the visitor's presence and immediately notifies the server. The server receives the notification and activates the AI ​​response module. This module generates the initial response message, "Who is this?", and sends it to the device. Once a conversation with the visitor begins, the visitor's voice response is recorded.

[1094] The device then records the visitor's response and sends the audio data to the server. The server receives the audio data and converts it into text data using a speech recognition module (e.g., Google speech recognition API). This text data is then analyzed by a text analysis module to extract the reason for the visit. The server then compares the reason for the visit with a list of suspicious people and unwanted sales people to determine whether the visitor is suspicious, a safe visitor, or an unwanted sales person. Based on this determination, the server generates an appropriate response message in the next step.

[1095] For example, if the visitor is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here," which is sent to the terminal and played. On the other hand, if the visitor is determined to be safe, the server generates a message to notify the user's remote terminal of the reason for the visit and video footage. The user can check the visitor's information on the remote terminal and unlock the door via the intercom terminal if necessary. Notifications are made in real time, allowing the user to respond quickly.

[1096] As a concrete example of this system, consider the case where an elderly person is alone at home and receives a visit from a sales representative from a telecommunications company. The camera and microphone detect the visitor's presence and play a voice message asking, "Who is this?" If the visitor responds, "I'm a representative from the telecommunications company," the voice is converted into text and analyzed as a "telecommunications company salesperson." The server compares this with a list of unwanted salespeople and determines that the visit is unwanted. The server then generates a message saying, "You don't need that product," and plays it to the visitor via their device. This allows the elderly person to avoid unwanted visits without having to deal with them directly.

[1097] By using a generative AI model, the accuracy of analyzing the reason for visit can be improved, enabling faster and more accurate responses. An example of a specific prompt is as follows: "Please recognize the visitor's voice and convert it into text. We will use an AI model to analyze the reason for visit based on the visitor's response to 'Who is this?'"

[1098] As described above, by having the terminal, server, and user cooperate to execute a series of processes, this system significantly reduces the security risks associated with visits and provides a safe and comfortable home environment.

[1099] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1100] Step 1:

[1101] The device detects visitors. Specifically, it detects the presence of a visitor by the device's camera and motion detection sensor, or by pressing the intercom button. The input at this time is the camera image and the intercom button press signal. By receiving this data, it determines whether a visitor is present. The output is visitor detection information.

[1102] Step 2:

[1103] The terminal sends the detected information to the server. The input is the detected visitor information, which is then sent to the server. Specifically, data is sent over the network in the form of an HTTP request, etc. The output is that the server receives the detected information.

[1104] Step 3:

[1105] The server starts the AI ​​response module and generates the initial response message "Who is this?". The input is the visitor detection information, and the AI ​​response module is executed. As data processing, the AI ​​generates an appropriate response message. The output is the generated response message.

[1106] Step 4:

[1107] The terminal plays the generated response message. The input is the response message sent from the server. The terminal uses a speaker to ask the visitor, "Who is this?". The output is the played audio response.

[1108] Step 5:

[1109] The terminal records the visitor's response voice. The input is the visitor's voice, which is recorded using a microphone. Voice data is generated as data processing. The output is the recorded voice data.

[1110] Step 6:

[1111] The terminal sends the recorded voice data to the server. The input is the recorded voice data, which is sent to the server via the network. The output is the server receiving the voice data.

[1112] Step 7:

[1113] The server uses a speech recognition module to convert voice data into text data. The input is voice data, which is converted into text information using speech recognition technology (for example, Google speech recognition API). The output is text data.

[1114] Step 8:

[1115] The server uses a text analysis module to analyze the text data and extract the reason for the visit. The input is the text data, and the generative AI model is used to analyze the meaning. The output is the analyzed reason for the visit.

[1116] Step 9:

[1117] The server identifies visitors based on the reason for their visit. The input is the reason for the visit, and data manipulation is performed to match it with lists of suspicious people and unwanted sales. The output is the visitor's identification result.

[1118] Step 10:

[1119] The server generates a response message according to the judgment result and sends it to the terminal. The input is the visitor's judgment result, and an appropriate response message (e.g., "You don't need that product" in the case of an unwanted sale) is generated. The output is the generated response message.

[1120] Step 11:

[1121] The terminal plays the generated response message. The input is the response message sent from the server, and it responds to the visitor again using the speaker. The output is the played voice response.

[1122] Step 12:

[1123] If the server determines that the visitor is safe, it notifies the user's remote device of the reason for the visit and the video. The input is the safe visitor determination result and necessary data (video, reason for visit), which are sent to the remote device. The output is the notification sent to the user's remote device.

[1124] Step 13:

[1125] The user checks the visitor information on the remote terminal and unlocks the door if necessary. The input is the visitor information acquired on the remote terminal and the door unlock operation is performed. The output is that the door is unlocked.

[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] The present invention is a system that automatically performs a series of processes from detecting a visitor to playing a response message and recognizing the emotional state of the user. Detailed embodiments of the system are described below.

[1128] First, the device is equipped with a camera and microphone, and when a visitor presses the intercom button or the camera detects movement, it detects the visitor's presence. The device immediately notifies the server of this information.

[1129] The server receives the notification and starts the AI ​​response module, which generates the first response message, "Who is this?", and sends it to the terminal. The AI ​​then starts a dialogue with the visitor, and in the next step, it records the visitor's voice.

[1130] The device records the visitor's response and sends the audio data to the server, which then uses a speech recognition module to convert the audio into text data, which is then analyzed to extract the reason for the visit.

[1131] The server determines whether the visitor is a suspicious person, a safe visitor, or an unwanted sales person based on the reason for the visit analyzed by the text analysis module. Based on the result of the determination, the server generates an appropriate response message.

[1132] For example, if the person is determined to be suspicious or an unwanted salesperson, the server generates a message such as "You do not need that product" or "The person is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be a safe person, the server generates a message to notify the user of the reason for the visit and video footage to the user's mobile terminal.

[1133] The present invention also incorporates an emotion engine, which allows for optimal response to visitors by taking into account the user's emotional state.

[1134] The device or the user's mobile device captures the user's voice and facial expressions and sends them to the emotion engine, which then analyzes the user's emotional state (e.g., relief, vigilance, anxiety, fear, etc.) based on this data.

[1135] The server determines the final response message by taking into account not only the visitor's judgment result but also the user's emotional state from the emotion engine. For example, if the user is feeling anxious or scared, the server can generate an emergency message and execute measures to notify emergency contacts or the police.

[1136] As a concrete example, consider the case where the user is an elderly person living alone. When a sales representative from a telephone company visits, the camera and microphone detect their presence and play a voice message saying, "Who is this?" If the visitor responds with, "This is ____ from the telephone company," the voice is converted into text, and the text data is analyzed as "telephone company sales representative."

[1137] The server compares this with an unwanted sales list and determines it to be an unwanted visit. A message saying "You don't need that product" is then generated and played to the visitor via their device. During this time, the emotion engine analyzes the user's voice and facial expressions, and if it determines that the user is feeling anxious, it will automatically notify emergency contacts.

[1138] This system works in conjunction with the user's mobile device to notify them if the visitor is genuine. The user can check the visitor's information on their mobile device and, if necessary, remotely unlock the door via the intercom terminal. In addition, since the notification is sent in real time, the user can respond quickly.

[1139] In this way, the terminal, server, user, and emotion engine work together to execute a series of processes, and this system significantly reduces the security risks associated with visits, providing a safe and comfortable home environment.

[1140] The processing flow will be explained below.

[1141] Step 1:

[1142] Device: A visitor presses the intercom button or the camera detects motion. To confirm the visitor's presence, the device prepares to capture an image with the camera and record audio with the microphone.

[1143] Step 2:

[1144] Terminal: Notifies the server of the visitor's detection information. This notification includes the visitor's image and detection data.

[1145] Step 3:

[1146] Server: Upon receiving the notification, the server launches the AI ​​response module. The server generates a response message saying "Who is this?" and sends it to the device.

[1147] Step 4:

[1148] Terminal: Records responses from visitors and sends the recorded audio data to the server in real time.

[1149] Step 5:

[1150] Server: The received voice data is processed by a voice recognition module, and the voice is converted into text data. The converted text data is analyzed to extract the reason for the visit.

[1151] Step 6:

[1152] Server: The reason for the visit extracted using the text analysis module is compared with the suspicious person list and unwanted sales list. Based on the comparison results, the safety of the visitor is determined.

[1153] Step 7:

[1154] Server: Generates a response message based on the result of the judgment. If the person is judged to be suspicious or to be making an unwanted sales pitch, a message such as "You do not need that product" or "The person in question is not present" is generated and sent to the terminal.

[1155] Step 8:

[1156] Terminal: Plays the response message to the visitor. If necessary, you can also request to see the certificate.

[1157] Step 9:

[1158] Server: If the visitor is deemed safe, a notification is sent to the user's mobile device, including the reason for the visit and a video of the visitor.

[1159] Step 10:

[1160] User: Checks visitor information on a mobile device. If necessary, the door can be unlocked remotely via the intercom terminal. If the user wants to reject the visitor, a "No" message can be played.

[1161] Step 11:

[1162] Terminal: Captures the user's voice and facial expressions and sends them to the emotion engine.

[1163] Step 12:

[1164] Server: The emotion engine analyzes the captured voice and facial expressions to determine the user's emotional state (e.g., relief, alertness, anxiety, fear, etc.).

[1165] Step 13:

[1166] Server: Determines the appropriate response based on the user's emotional state and the visitor's assessment. If the server determines that the user is feeling anxious or scared, it will send a notification to emergency contacts and the police.

[1167] Step 14:

[1168] Server: Determines the final response and takes appropriate action, such as notifying emergency contacts or sending an alert to the user.

[1169] This series of processes enables efficient detection and response of visitors and recognition of the user's emotional state, providing a safe and secure living environment.

[1170] Example 2

[1171] 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."

[1172] In today's home environment, identifying and responding to visitors is often time-consuming and poses security risks. Elderly people living alone and busy households in particular require a fast and appropriate response to visitors. It is also necessary to accurately understand the visitor's intentions and effectively eliminate suspicious individuals and unwanted sales attempts. Furthermore, responding in a way that takes the user's emotional state into account can provide a greater sense of security.

[1173] 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 a means for detecting visitors, a means for recording the visitor's voice, a means for converting the recorded voice into text data, a means for analyzing the text data and extracting the reason for the visit, a means for determining the visitor based on the reason for the visit, a means for analyzing the user's emotional state, and a means for generating and playing a response message based on the determination result and the user's emotional state. This makes it possible to accurately understand the visitor's intentions, effectively eliminate suspicious individuals and unwanted sales tactics, and provide an optimal response that takes the user's emotional state into consideration.

[1174] "Means for detecting visitors" refers to devices or systems that use cameras or microphones to detect the presence of visitors.

[1175] "Means for recording visitor audio" refers to devices or systems that digitally record visitor speech and audio dialogue.

[1176] "Means for converting recorded speech into text data" refers to a device or system that uses speech recognition technology to automatically convert recorded speech into text form.

[1177] "Means for analyzing text data and extracting reasons for visit" refers to devices or systems that analyze text data and identify the visitor's intentions and reasons from its content.

[1178] "Means for determining visitors based on the reason for visit" refers to devices or systems that determine whether a visitor is suspicious, an unwanted visitor, or a safe visitor based on the extracted reason for visit.

[1179] "Means for analyzing the user's emotional state" refers to a device or system that analyzes the user's voice and facial expression data to identify the user's emotional state at that time.

[1180] "Means for generating and playing a response message based on the judgment result and the user's emotional state" refers to a device or system that automatically creates an appropriate response message and plays it to the visitor, taking into account the visitor's judgment result and the user's emotional state.

[1181] This invention is a system that automatically and centrally performs everything from detecting visitors to generating and playing response messages, recognizing the user's emotional state, and responding based on that. Specifically, the system is configured with a camera and microphone on the terminal, and various modules on the server.

[1182] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device immediately notifies the server. A standard surveillance camera and a high-sensitivity microphone are used.

[1183] When the server receives a notification from the terminal, it launches the AI ​​response module. The AI ​​response module generates an initial response message asking the visitor, "Who is this?" and sends it to the terminal. The terminal then plays this message aloud to the visitor. The AI ​​response module used here incorporates a generative AI model.

[1184] The device records the visitor's response and sends the audio data to the server. The server then uses a speech recognition module to convert the audio data into text data. For example, the Google Cloud Speech-to-Text API is used as the speech recognition module. The converted text data is then analyzed by a text analysis module to extract the reason for the visit.

[1185] The server determines the visitor based on the reason for the visit and compares them with a pre-prepared list of suspicious people or unwanted sales people. If the visitor is determined to be suspicious or an unwanted visitor, it generates a response message such as "You do not need that product" or "The visitor is not here" and sends it to the terminal. On the other hand, if the visitor is determined to be safe, it notifies the user's mobile terminal of the reason for the visit and video. This notification uses real-time communication technology.

[1186] Furthermore, the emotion engine captures the user's voice and facial expressions and sends them to the emotion analysis module, which analyzes them to identify the user's emotional state. The emotion analysis module uses the Microsoft Azure Emotion API, among other tools. The server determines the final response message by taking into account not only the visitor's judgment but also the user's emotional state. For example, if the user is feeling anxious or scared, it can generate an emergency message and send a notification to emergency contacts or the police.

[1187] As a concrete example, consider the case where the user is an elderly person living alone. When the visitor responds, "I'm a salesperson from the telephone company," the server analyzes the voice and checks it against a list of unwanted sales. If it is determined that the product is unwanted, it generates a response message saying, "You don't need that product," and plays it to the visitor via their device. If the emotion engine detects anxiety in the user during this time, it automatically notifies emergency contacts. Furthermore, if the visitor is determined to be safe, the system connects to the user's mobile device in real time and notifies them of the visitor's information. The user can also unlock the door from their mobile device.

[1188] An example prompt based on a generative AI model is:

[1189] "Who is this?"

[1190] "There's no need for such products."

[1191] "The person in question is not here."

[1192] "We're making sure you're safe."

[1193] This system integrates everything from detecting visitors to generating and executing response messages based on the user's emotional state into a single flow, significantly reducing the security risks posed by visitors and providing a safe and comfortable home environment.

[1194] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1195] Step 1:

[1196] The device uses a camera and microphone to detect visitors. When a visitor presses the intercom button or the camera detects movement, the device senses the visitor's presence. As a specific example, the device saves a frame at the moment the camera detects a moving object. The input is visitor presence information, and the output is visitor presence notification data.

[1197] Step 2:

[1198] The server receives the notification from the terminal and starts the AI ​​response module. The AI ​​response module generates the first response message, "Who is this?", and sends it to the terminal. The terminal then plays this message aloud to the visitor. The input is the notification data from the terminal, and the output is the response message, "Who is this?"

[1199] Step 3:

[1200] The terminal records the visitor's response and sends the voice data to the server. For example, a response such as "This is ____ from the telephone company" is recorded. The input is the visitor's voice, and the output is the recorded voice data.

[1201] Step 4:

[1202] The server processes the voice data received from the device using a voice recognition module. This module automatically converts the recorded voice into text format. The voice recognition module used includes the Google Cloud Speech-to-Text API. The converted text data is output. The input is the recorded voice data, and the output is text data.

[1203] Step 5:

[1204] The server analyzes the text data converted by the text analysis module and extracts the reason for the visit. The text analysis module uses natural language processing technology to identify the reason for the visit. For example, it may be analyzed as "telephone company sales." The input is text data, and the output is the reason for the visit.

[1205] Step 6:

[1206] The server then compares the analyzed reason for the visit with a list of suspicious individuals and unwanted salespeople prepared in advance to determine the visitor's identity. Based on the results of the determination, it generates an appropriate response message. For example, it generates a message such as "You do not need that product." The input is the reason for the visit, and the output is the determination result and the response message.

[1207] Step 7:

[1208] The terminal receives the response message from the server and plays it back to the visitor by voice. For example, it plays back a message saying, "You don't need that product." The input is the response message from the server, and the output is the voice message played back to the visitor.

[1209] Step 8:

[1210] The terminal or the user's mobile device captures the user's voice and facial expression. These data are sent to the emotion analysis module. The input is the user's voice and facial expression data, and the output is emotional state data.

[1211] Step 9:

[1212] The server receives the user's emotional state data from the emotion analysis module and determines the optimal response along with the visitor's assessment result. For example, if the user feels anxious or scared, it generates an emergency message and sends a notification to emergency contacts and the police. The input is the emotional state data and the visitor's assessment result, and the output is the final response message and emergency notification.

[1213] (Application example 2)

[1214] 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."

[1215] For elderly people and people living alone to live their daily lives with peace of mind, it is necessary to respond appropriately to visitors and reduce security risks. However, conventional intercom systems do not identify visitors or analyze user emotions, and further improvements in safety are required. Furthermore, since it is difficult to respond in real time when the user is in a remote location, prompt notification of visitor information is also important. Therefore, there is a need for a system that can detect visitors, identify them, generate response messages, and respond according to the user's emotional state in an integrated manner.

[1216] 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.

[1217] In this invention, the server includes means for detecting visitors, means for recording the visitor's voice and converting it into text data, means for analyzing the voice and extracting the reason for the visit, means for generating and playing a response message taking into account the judgment result and the user's emotional state, and means for analyzing the user's emotions and selecting a message according to that state. This enables the integrated process from visitor detection to judgment, generation of a response message, and response according to the user's emotional state to be performed automatically, thereby improving the safety and security of users.

[1218] "Means for detecting visitors" refers to means for recognizing and detecting the presence of visitors using devices such as cameras and sensors.

[1219] The "means for recording the visitor's voice" refers to a means for recording the contents of the visitor's speech using a voice collecting device such as a microphone.

[1220] "Means for converting recorded audio into text data" refers to means for converting recorded audio data into text information using voice recognition software or an API.

[1221] "Means for analyzing text data and extracting reasons for visit" refers to means for identifying and extracting reasons for visit from data that has been converted from voice to text using a natural language processing algorithm.

[1222] "Means for determining visitors based on the reason for their visit" refers to a means for confirming and determining whether a visitor has a purpose for visiting based on the results of text analysis.

[1223] "Means for generating and playing a response message taking into consideration the judgment result and the emotional state of the user" refers to means for creating an appropriate response message that reflects both the visitor's judgment result and the user's emotional state at the time, and conveying it to the visitor.

[1224] A "suspicious person list" is a list of people who are considered suspicious based on past data and information provided by the police.

[1225] An "unwanted sales list" is a list of people or companies whose specific sales purposes or sales activities are considered nuisances.

[1226] "Means for performing emotion analysis" refers to means for analyzing the user's facial expressions and voice patterns to identify the emotion (e.g., relief, vigilance, anxiety, fear, etc.) that the person is currently feeling.

[1227] A "means for sending notifications" is a means for sending information or alerts in real time to a user's mobile device, such as a smartphone or tablet.

[1228] "Smart glasses" are glasses-type wearable devices that have built-in cameras, microphones, displays, etc. and have advanced functions such as internet connectivity.

[1229] This invention is a system that detects visitors and automatically responds appropriately. Specifically, it detects the presence of a visitor, analyzes their voice data to extract the reason for their visit, and generates and plays a response message based on that information. It also analyzes the user's emotional state and provides an optimal response accordingly. The entire system functions in cooperation with a server, a terminal, and smart glasses.

[1230] Hardware and Software Configuration

[1231] 1. Smart Glasses

[1232] The device has a built-in camera and microphone, collects video and audio of visitors, and is worn by the user to interact with visitors and display emergency notifications.

[1233] 2. Server

[1234] Equipped with a high-performance CPU and GPU, it is responsible for data processing and running AI models, including speech recognition, text analysis, sentiment analysis, and response message generation.

[1235] 3. Speech Recognition Module

[1236] Use the Google Speech-to-Text API to convert audio data into text data.

[1237] 4. Text Analysis Module

[1238] A natural language processing model using TensorFlow extracts reasons for visits from text data.

[1239] 5. Emotion Engine

[1240] The algorithm combines OpenCV and TensorFlow to analyze the user's facial expressions and vocal emotions.

[1241] 6. Message Generation Module

[1242] Use generative AI models such as GPT-3 to generate response messages for visitors.

[1243] System Operation

[1244] The server receives the video and audio data sent from the smart glasses. It then converts the audio into text using a voice recognition module, and analyzes the text data using a text analysis module to extract the reason for the visit. The extracted reason for the visit is compared with a list of suspicious people and unwanted sales people to determine the visitor.

[1245] At the same time, the user's facial expression data captured by the smart glasses' camera is analyzed by the emotion engine to evaluate the user's emotional state. Based on the judgment result and the user's emotional state, the server uses a generative AI model to generate the most appropriate response message and sends it to the smart glasses.

[1246] For example, if the user is feeling anxious, the generated message will be short and safety-oriented.

[1247] Examples:

[1248] Consider a scenario in which an elderly person is wearing smart glasses. When a visitor arrives at the front door and rings the doorbell, the camera and microphone in the smart glasses detect the movement and send audio and video to the server. The server analyzes the audio data and automatically extracts the reason for the visit. If the visitor is determined to be an unwanted sales tactic, or if the emotion engine determines that the elderly person is feeling anxious, a safety-focused message is generated.

[1249] Example prompt sentence:

[1250] Convert visitor speech to text and identify the reason for their visit. Then, use your emotion engine to determine the user's emotional state and generate a reassuring message.

[1251] Caller says: "Hello, this is a professional company. Do you have time?"

[1252] User's emotional state: "Anxious"

[1253] Generates the message: "Thank you for visiting, but we're currently unavailable."

[1254] In this way, the present invention realizes a system that performs a consistent process from detecting visitors to generating a response message and responding based on the user's emotional state.

[1255] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1256] Step 1:

[1257] Smart glasses detect visitors.

[1258] Input: Camera video, audio data

[1259] How it works: The smart glasses' built-in camera captures video and a built-in microphone records the visitor's audio. The visual data is used to detect the visitor's presence.

[1260] Step 2:

[1261] The smart glasses send the collected data to a server.

[1262] Input: Camera video, audio data

[1263] Output: Audio and video data are sent to the server.

[1264] How it works: The smart glasses transmit the captured data to a server in real time, where it is transferred via an internet connection.

[1265] Step 3:

[1266] The server converts the voice data into text data.

[1267] Input: Audio data

[1268] Output: Text data

[1269] Specific operation: The server uses the Google Speech-to-Text API to convert the transmitted voice data into text. The voice waveform data is converted into character string data.

[1270] Step 4:

[1271] The server analyzes the text data and extracts the reason for the visit.

[1272] Input: Text data

[1273] Output: Reason for visit

[1274] Specific operation: The server uses TensorFlow to analyze the text data with the text analysis module and extract the reason for the visit. A natural language processing model is used.

[1275] Step 5:

[1276] The server determines who the visitor is.

[1277] Input: Reason for visit

[1278] Output: Judgment result (safe, suspicious person, unwanted sales)

[1279] Specific operation: The server checks the extracted reason for the visit against the suspicious person list and unwanted sales list to determine which category the visitor belongs to. A database search is performed.

[1280] Step 6:

[1281] The smart glasses capture the user's emotional state and send it to the emotion engine.

[1282] Input: User video data

[1283] Output: User's emotional state (e.g., relief, alertness, anxiety, fear)

[1284] How it works: The camera in the smart glasses captures the user's facial expressions and sends the data to the emotion engine, which uses OpenCV and TensorFlow to analyze the user's emotional state.

[1285] Step 7:

[1286] The server generates a response message based on the judgment result and the user's emotional state.

[1287] Input: Judgment result, user's emotional state

[1288] Output: Response message

[1289] Specific operation: Based on the judgment result and emotional state, the server generates an appropriate response message using a generative AI model such as GPT-3. The message to be generated is determined using the prompt sentence.

[1290] Step 8:

[1291] The reply message is sent to the smart glasses and played.

[1292] Input: Response message

[1293] Output: Message playback through smart glasses

[1294] Specific behavior: The generated response message is sent to the smart glasses and played as audio, allowing the user to listen to the message.

[1295] 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.

[1296] 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.

[1297] 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 robot 414.

[1298] 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.

[1299] 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.

[1300] 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.

[1301] 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).

[1302] 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.

[1303] 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."

[1304] 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.

[1305] 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).

[1306] 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.

[1307] 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.

[1308] 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.

[1309] 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.

[1310] 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.

[1311] 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.

[1312] 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.

[1313] 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.

[1314] 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.

[1315] 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.

[1316] The following is further disclosed regarding the above embodiment.

[1317] (Claim 1)

[1318] a means for detecting visitors;

[1319] a means for recording the visitor's voice;

[1320] A means for converting the recorded voice into text data;

[1321] A means for analyzing text data and extracting reasons for visits;

[1322] A means for determining a visitor based on the reason for the visit;

[1323] means for generating and reproducing a response message according to the determination result;

[1324] A system including:

[1325] (Claim 2)

[1326] 2. The system according to claim 1, wherein the visitor determining means includes means for comparing the visitor with a list of suspicious persons and a list of unwanted sales people and selecting necessary messages.

[1327] (Claim 3)

[1328] 2. The system according to claim 1, further comprising means for sending a notification to the user's mobile terminal when the determination result indicates safety.

[1329] "Example 1"

[1330] (Claim 1)

[1331] a means for detecting visitor movement;

[1332] a means of notifying the presence of a visitor;

[1333] means for generating a voice greeting;

[1334] a means for recording the visitor's voice;

[1335] A means for converting the recorded voice into text data;

[1336] A means for analyzing text data and extracting reasons for visits;

[1337] A means for determining a visitor based on the reason for the visit;

[1338] means for generating and reproducing a response message according to the determination result;

[1339] means for displaying an image of the visitor;

[1340] a means for notifying a user;

[1341] a means for the user to respond remotely;

[1342] A system including:

[1343] (Claim 2)

[1344] 2. The system according to claim 1, wherein the visitor determining means includes means for checking against a registered list and selecting a required message.

[1345] (Claim 3)

[1346] 2. The system according to claim 1, further comprising means for sending a notification to the user's mobile terminal when the determination result indicates safety.

[1347] "Application Example 1"

[1348] (Claim 1)

[1349] a means for detecting visitors;

[1350] a means for recording the visitor's voice;

[1351] A means for converting the recorded voice into text data;

[1352] A means for analyzing text data and extracting reasons for visits;

[1353] A means for determining a visitor based on the reason for the visit;

[1354] means for generating and reproducing a response message according to the determination result;

[1355] In the case of suspicious people or unwanted sales calls, a means to generate and play a response message,

[1356] means for sending a notification to the user's remote terminal when the visitor is determined to be safe, allowing the user to confirm the information;

[1357] means for a user to unlock the door using a remote terminal;

[1358] A system including:

[1359] (Claim 2)

[1360] 2. The system according to claim 1, wherein the visitor determining means includes means for comparing the visitor with a list of suspicious persons and a list of unwanted sales people and selecting necessary messages.

[1361] (Claim 3)

[1362] 2. The system according to claim 1, further comprising means for sending a notification to the user's mobile terminal when the determination result indicates safety.

[1363] "Example 2: Combining Emotion Engines"

[1364] (Claim 1)

[1365] a means for detecting visitors;

[1366] a means for recording the visitor's voice;

[1367] A means for converting the recorded voice into text data;

[1368] A means for analyzing text data and extracting reasons for visits;

[1369] A means for determining a visitor based on the reason for the visit;

[1370] means for analyzing the emotional state of a user;

[1371] means for generating and playing a response message based on the determination result and the user's emotional state;

[1372] A system including:

[1373] (Claim 2)

[1374] 2. The system according to claim 1, wherein the visitor determining means includes means for comparing the visitor with a list of suspicious persons and a list of unwanted sales and selecting a necessary message.

[1375] (Claim 3)

[1376] 2. The system according to claim 1, further comprising means for sending a notification to the user's mobile terminal when the determination result indicates safety.

[1377] "Application example 2 when combining emotion engines"

[1378] (Claim 1)

[1379] a means for detecting visitors;

[1380] a means for recording the visitor's voice;

[1381] A means for converting the recorded voice into text data;

[1382] A means for analyzing text data and extracting reasons for visits;

[1383] A means for determining a visitor based on the extracted reason for visit;

[1384] means for generating and playing a response message taking into account the determination result and the user's emotional state;

[1385] A system including:

[1386] (Claim 2)

[1387] 2. The system according to claim 1, wherein the visitor determining means includes means for comparing the visitor with a list of suspicious persons and a list of unwanted sales people and selecting necessary messages.

[1388] (Claim 3)

[1389] The system of claim 1 further comprising: means for sending a notification to the user's mobile device if the judgment result is that the device is safe; and means for analyzing the user's emotions and generating a response message according to the user's emotional state. [Explanation of symbols]

[1390] 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 detecting visitors; a means for recording the visitor's voice; A means for converting the recorded voice into text data; A means for analyzing text data and extracting reasons for visits; A means for determining a visitor based on the reason for the visit; means for generating and reproducing a response message according to the determination result; A system including:

2. 2. The system according to claim 1, wherein the visitor determining means includes means for comparing the visitor with a list of suspicious persons and a list of unwanted sales people and selecting a necessary message.

3. 2. The system according to claim 1, further comprising means for sending a notification to the user's mobile terminal when the determination result indicates safety.

Images