system

Abstract

We provide the system. [Solution] An image acquisition means for detecting conditions in the environment, Image analysis means for analyzing acquired image data to identify suspicious persons, A notification system that generates and notifies alerts when an anomaly is detected, A recording means for storing the detected information, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, crime prevention measures for ensuring personal safety and security are very important. However, in many households and facilities, the thorough implementation of crime prevention measures is hindered by costs and complex management. In particular, there is a lack of systems with the ability to respond immediately to prevent the intrusion of suspicious persons, and situations where single women, the elderly, and families with children are worried. Therefore, it is required to eliminate such worries and provide an environment in which people can live with peace of mind.

Means for Solving the Problems

[0005] This invention provides an image analysis means that acquires environmental conditions using a camera and analyzes the image data in real time using AI technology. Based on the analysis results, if a suspicious person or abnormal situation is identified, it immediately generates an alert and has a notification means to notify a remote monitoring management system. Furthermore, the system has a recording means to record and store the detected information, which can be reviewed later and used as evidence if necessary. In addition, by using a mobile means that autonomously patrols the facility and its surroundings, wide-area and efficient monitoring is achieved. As a result, users can easily implement advanced security measures and live their daily lives with peace of mind.

[0006] "Environmental conditions" refers to physical or human activity information that the system acquires from the surrounding area.

[0007] "Image acquisition means" refers to a function that uses devices such as cameras to collect visual data of the environment in real time.

[0008] "Image data" refers to digital data that represents visual information collected by image acquisition methods.

[0009] "Image analysis means" refers to AI technology used to analyze collected image data and identify suspicious individuals or unusual events.

[0010] A "suspicious person" refers to an individual who deviates from normal behavior patterns or enters unauthorized areas.

[0011] "When an anomaly is detected" refers to the point in time when the system identifies activity or behavior that differs from normal conditions.

[0012] An "alert" refers to a warning or notification generated by a system to alert users to a detected anomaly.

[0013] "Notification means" refers to a function that sends alerts to relevant parties and devices to quickly inform them of the situation.

[0014] "The recording means for storage" refers to storage technologies that hold data on detected situations or events and enable later reference.

[0015] "The mobile means that autonomously patrols" refers to a function that performs monitoring activities while automatically moving along a set route.

Brief Description of the Drawings

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

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

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

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

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

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] As one embodiment of the present invention, the security robot system consists of an autonomous mobile terminal equipped with various sensors and cameras, and a server that analyzes and manages the data. The terminal autonomously patrols a designated area, acquiring images of its surroundings using its cameras, and can also detect surrounding sounds and movements using its sensors. This allows for the collection of data on the environment in real time.

[0038] The collected data is sent from the terminal to the server. The server uses advanced AI technology to analyze the data and identify suspicious individuals or unusual situations. For example, the server uses image recognition technology to identify people's actions and faces in the video and compare them to pre-set behavioral patterns. This makes it possible to detect unusual behavior or intrusion into unauthorized areas with high accuracy.

[0039] If an anomaly is detected, the server immediately generates an alert and notifies the management company and the resident user via a notification system. The notification is sent in real time through a smartphone app, and the user can view the video feed at that time through the app. This allows the user to obtain information in real time to take prompt action.

[0040] Furthermore, the system has the capability to save all records, with the server using recording devices to save detected situations and video footage. This allows residents and management companies to review events that occurred later and use them as evidence if necessary. Through this series of functions, the system significantly enhances security in the living environment and supports a safer living environment.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The device autonomously begins moving along a pre-configured patrol route. It uses its built-in sensors and GPS to determine its current location and move precisely.

[0044] Step 2:

[0045] While the device is patrolling, it uses its camera to acquire image data of its surroundings. At the same time, sound sensors and motion sensors are activated to collect data on sounds and movements in the environment.

[0046] Step 3:

[0047] The device transmits collected image data and sensor data to the server. The data is transmitted in real time using wireless communication technology.

[0048] Step 4:

[0049] The server uses AI technology to analyze transmitted image data and detect suspicious individuals or unusual situations. This analysis includes facial recognition and motion analysis.

[0050] Step 5:

[0051] If an anomaly is detected, the server generates an alert based on that information. The alert includes details of the detected situation.

[0052] Step 6:

[0053] The server sends alerts to the management company and resident users via a notification system. Notifications are delivered in real time through a smartphone app.

[0054] Step 7:

[0055] Users receive notifications via a smartphone app and can check the situation. If necessary, users can take action such as contacting the police or administrators.

[0056] Step 8:

[0057] Anomalies are recorded and saved on the server. The saved data can be used later for verification or as evidence.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] Ensuring safety in modern society is a crucial issue, and it is especially important to quickly detect and respond to intruders and abnormal situations. However, existing surveillance systems are insufficient in acquiring visual information and detecting anomalies, and they have limitations in real-time notification and record keeping. In this situation, there is a need to build a system that can effectively monitor the environment and quickly notify of anomalies.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes a visual sensor means for acquiring image information, a sensing means for detecting sound and movement, and an information processing means for analyzing the acquired data and identifying the characteristics of a person. This enables more accurate and rapid anomaly detection and notification.

[0063] A "visual sensor means" is a device for acquiring video information of a target, which allows for the visual detection of surrounding conditions and abnormalities.

[0064] A "sensing means" is a device that detects sound or the movement of objects, and has the function of detecting changes in the environment.

[0065] "Information processing means" refers to technologies that analyze acquired data and identify specific characteristics, and are means of extracting useful information from data using AI algorithms.

[0066] A "communication means" is a system that transmits information to a remote location when an anomaly is detected, and is a device that enables rapid information transmission via a network.

[0067] A "storage system" is a system that records and securely stores detected data, serving as a foundation for later verification and analysis of that data.

[0068] A "means of transport" is a device that autonomously moves within a designated area to collect information, enabling efficient patrol and surveillance.

[0069] "Networking means" refers to technologies that transmit and receive information via communication networks, and is a system that enables remote monitoring and operation.

[0070] This invention is designed as a security and surveillance system and consists of a terminal equipped with various sensors and cameras, a server that analyzes and manages information, and users that receive and utilize the information.

[0071] The server processes data using advanced AI technology to detect anomalies. Specifically, the server analyzes image data acquired by visual sensors using image recognition software to identify specific behaviors and characteristics. It also analyzes data sent from sound and motion detection devices to identify abnormal sounds and movements. To achieve this processing, the server uses a computer equipped with high-performance CPUs and GPUs.

[0072] The terminal is equipped with a means of mobility to collect environmental data while autonomously moving around the area. The terminal transmits data to a server via Wi-Fi or 5G communication, providing environmental information in real time. In this way, the terminal efficiently monitors a specific area and automatically looks for any suspicious activity.

[0073] When an anomaly is detected, the user receives a notification from the server via the network. The notification is sent through a smartphone app, allowing the user to view real-time video and detection information on the app. This enables the user to take swift action and ensure safety.

[0074] As a concrete example, in nighttime surveillance of a commercial facility, a terminal detects an intruder during patrol, and a server analyzes the details. After confirming the anomaly, the server sends an alert to the facility manager, prompting a quick response. In such a situation, the user can view detailed video footage through the app and take measures such as reporting to the police.

[0075] An example of a prompt using a generative AI model is, "Please tell me more about the security robot system for commercial facilities. What are the system's main functions and the technologies used?" This prompt allows the generative AI to obtain specific details and technical information about the invention.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The terminal autonomously patrols a designated area and acquires image information using visual sensors. The input to the terminal is ambient environmental data, and the output is the acquired image data. It also activates sound and motion detection sensors to collect ambient audio and motion data. The terminal temporarily stores this data in its internal storage.

[0079] Step 2:

[0080] The device transmits collected image and audio data to the server. The input consists of various data stored within the device, while the output is the data transferred to the server. Transmission utilizes Wi-Fi or 5G communication, and the data is compressed in real time and transmitted via protocols designed to minimize network latency.

[0081] Step 3:

[0082] The server analyzes the received image data using AI technology. The input data is raw data sent from the terminal, and the AI ​​model operates, producing output that identifies suspicious individuals and abnormal behavioral patterns. Specifically, an image recognition algorithm is used to analyze the characteristics of a person and compare them with pre-set behavioral patterns.

[0083] Step 4:

[0084] The server analyzes audio data and identifies abnormal sounds. The input data is audio sent from the terminal, and the output is information on whether or not an abnormal sound was detected. The server uses audio analysis software to process sounds that have patterns different from the norm.

[0085] Step 5:

[0086] Based on the analysis results, the server activates a communication system that sends an alert to the user if an anomaly is detected. The input is the analysis results, and the output is a real-time notification to the user. The user can receive the notification, understand the situation, and view the video feed via a smartphone app.

[0087] Step 6:

[0088] The server records all detection information and analysis results using storage mechanisms. The input is comprehensive detection data, and the output is securely stored data records. The stored data can be reviewed later and used for further analysis to enhance security.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] Conventional security systems have the capability to detect anomalies, but they lack sufficient means to provide the detected information to the user's external devices in real time. Furthermore, there are challenges in enabling users to respond quickly to environmental monitoring while on the move or to immediate notifications.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify a suspicious person, a notification means for generating an alert when an anomaly is detected and notifying an external device via a communication device, a recording means for storing the detected information, and a means for transmitting video in real time via communication with an external device. This enables the user to check abnormal events in real time and respond quickly.

[0094] "Image acquisition means for detecting environmental conditions" refers to a device that has the function of acquiring still images or videos to visualize the surrounding conditions.

[0095] An "image analysis device" is a device that uses a data processing algorithm to identify specific objects or abnormal movements based on acquired image data.

[0096] A "notification means that generates alerts and notifies external devices via a communication device" is a system that compiles warnings when an anomaly is detected and provides that information to remote users.

[0097] "Recording means for storing detected information" refers to a device or platform for storing collected data and analysis results in digital format for a long period of time.

[0098] "Means of transmitting video in real time through communication with external devices" refers to communication devices and software functions for immediately providing acquired video data to external parties via the internet or network.

[0099] In this security system, the terminal is a multi-functional mobile device that autonomously patrols the environment, acquiring detailed image and audio data. Specifically, the camera and sensors mounted on the terminal simultaneously collect visual information and ambient sounds. This makes it possible to understand the environment's situation in real time.

[0100] The server receives the collected data and analyzes it using advanced image analysis technology. The analysis utilizes an AI framework such as TENSORFLOW®, and a generative AI model identifies abnormal behavior within the images, detecting suspicious individuals. Furthermore, if an anomaly is detected, a notification message is immediately generated and sent to the user's smartphone or smart glasses.

[0101] Users can receive this notification in real time and view the video stream at that moment through a dedicated app. The app utilizes a mobile application platform built with ANDROID® Studio and iOS Xcode. This allows users to take quick and accurate action.

[0102] As a concrete example, suppose one afternoon the device detects unusual activity in an outdoor parking lot. In this case, an alert notification is immediately sent to the user's smartphone, and the user can view the video footage of the scene in real time via the app and quickly contact the security company.

[0103] Furthermore, an example of a prompt message to be input to the generating AI model is, "Please utilize an advanced image analysis algorithm that identifies suspicious behavior in this image and immediately reports any anomalies." Based on this prompt message, the AI ​​model operates to achieve highly accurate anomaly detection.

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

[0105] Step 1:

[0106] The device patrols the environment, acquiring images and sounds of its surroundings using its camera and sensors. The input is information about the surrounding environment, which is output as digital data. Specifically, it captures video with the camera and detects sound waves and vibrations with the sensors.

[0107] Step 2:

[0108] The terminal transmits the acquired digital data to the server. The input is the digital data generated in step 1, and the output is obtained by sending it to the server via network communication. Specifically, data transmission is performed using communication methods such as Wi-Fi or LTE.

[0109] Step 3:

[0110] The server analyzes the data it receives. The input is the digital data sent in step 2, which is then subjected to image analysis processing using an AI model to obtain output. Specifically, it utilizes generative AI models such as TensorFlow to perform image analysis to identify suspicious individuals and abnormal behavior. Instructions for the analysis algorithm are also given simultaneously using prompt messages.

[0111] Step 4:

[0112] The server generates an alert based on the analysis results. The input is the analysis results obtained in step 3. Based on these analysis results, it determines if an anomaly has occurred, generates an alert message, and sends it to the user device in real time. Specifically, it uses a notification system to send a push notification to an external device such as a smartphone.

[0113] Step 5:

[0114] Based on the alert notification received by the user, a dedicated app is launched to view real-time video. The input is the alert notification from the server, and the output is the display of the corresponding video stream in the app based on this. Specifically, live video is streamed on the interface to provide the user with visual information.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] As a specific embodiment of the present invention, the security robot system is equipped with a means of movement, an image acquisition means, an image analysis means, a notification means, a recording means, and a sensor means, in addition to an emotion engine. This allows the system to provide a function that recognizes and responds to the user's emotions, in addition to normal security functions.

[0117] The device autonomously moves along a pre-configured patrol route, using its camera to acquire visual data from the environment and collecting data from sound and motion sensors. This data is then transmitted from the device to a server.

[0118] The server analyzes image data and sensor data in real time. The image analysis system uses AI technology to identify and record suspicious individuals and unusual situations. If an anomaly is detected, the server also sends alerts to the management company and residents via notification systems.

[0119] The emotion engine acquires facial and voice data through the user's smartphone app camera and analyzes the user's emotional state. For example, if the emotion engine detects anxiety or fear in the user, the server prioritizes the alert and provides a prompt notification. In addition, the user's emotional data is recorded, allowing the user to analyze their own emotional tendencies based on their system usage.

[0120] For example, if a user at home at night detects the approach of a suspicious person, the device identifies this using image data and sensor data and reports it to the server. Simultaneously, an emotion engine analyzes the user's facial expressions and voice to detect emotions such as anxiety and tension. Based on this information, the server can send enhanced alerts to residents and management companies, prompting a quick response. This system provides a comprehensive security environment that considers the user's psychological well-being in addition to standard security functions.

[0121] The following describes the processing flow.

[0122] Step 1:

[0123] The device moves along a predetermined patrol route, using its camera to acquire images of its surroundings. Simultaneously, it collects data from the environment using sound and motion sensors.

[0124] Step 2:

[0125] The device transmits collected image data and sensor data to the server. The data is transmitted in real time using wireless communication.

[0126] Step 3:

[0127] The server uses AI technology to analyze the received image data and identify suspicious individuals or unusual situations. The detected anomaly information is stored by recording devices.

[0128] Step 4:

[0129] The server uses an emotion engine to acquire the user's facial expressions and voice data through the smartphone app, and then analyzes the user's emotional state.

[0130] Step 5:

[0131] The emotion engine analyzes the user's emotions, and if it detects anxiety or fear, the server adjusts the alert priority. Based on the priority, it sends appropriate alerts to the management company and the user using notification methods.

[0132] Step 6:

[0133] Users receive alerts via a smartphone app and check the situation. If necessary, users can take action, such as contacting the police or administrators.

[0134] Step 7:

[0135] The server records user emotion data and detected anomaly data, and stores it in a format that can be analyzed later. This allows users to analyze their own emotional tendencies and use that information to consider further security measures.

[0136] (Example 2)

[0137] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0138] Conventional security systems, while capable of detecting anomalies in the environment, struggled to respond in a way that considered the user's psychological state, failing to provide users with a sense of psychological security. Furthermore, insufficient means of data collection while on the move and inadequate real-time anomaly notifications meant that delays could occur in situations requiring a rapid response.

[0139] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0140] In this invention, the server includes means for acquiring visual data, means for analyzing data, means for notifying information, means for analyzing emotions, and means for storing information. This makes it possible to grasp the user's emotional state in real time and respond more quickly and appropriately.

[0141] A "visual data acquisition means" is a device that has the function of capturing and acquiring surrounding video and images.

[0142] "Data analysis means" refers to a function that analyzes acquired visual data and sensor data to detect anomalies or specific situations.

[0143] An "information notification means" is a function that sends alerts or notifications to relevant parties when an anomaly is detected.

[0144] "Emotional analysis tools" are functions that analyze a user's facial expressions and voice data to identify their psychological state.

[0145] "Information storage means" refers to a function that records detected anomaly information and user sentiment data, making them accessible later.

[0146] "Spatial movement means" refers to a function that allows a system or device to autonomously move along a predetermined route and collect data over a wide area.

[0147] "Environmental sensor means" refers to a function that uses sensors to detect ambient sounds and movements, and to detect abnormalities when they occur.

[0148] The security system in this invention is composed of multiple means and, in particular, has a function to provide users with a sense of psychological security. This system is mainly divided into two main components: a "terminal" and a "server".

[0149] The terminal is the primary device for collecting ambient environmental data. Specifically, it incorporates a camera as a means of acquiring visual data, continuously capturing images of the environment. Furthermore, a spatial movement mechanism is used for the terminal to autonomously patrol a pre-set route, enabling environmental data collection while moving. The terminal also incorporates environmental sensors, allowing it to detect sound and movement. This enables the terminal to detect environmental anomalies at an early stage.

[0150] The server receives and analyzes visual and sensor data transmitted from terminals. Using AI technology for data analysis, it identifies abnormal individuals and situations within images. Furthermore, it can analyze facial expressions and voice data transmitted from the user's smartphone app using emotion analysis tools to understand the user's emotional state. Based on this information, the server immediately sends alerts to relevant parties using information notification tools when an anomaly is detected. These alerts are sent via email or a dedicated app to encourage prompt action.

[0151] The recorded data can be accessed by the user later through information storage means and used for purposes such as analyzing emotional trends. For example, if a suspicious person approaches at night, the terminal can detect this, and the server can immediately send a notification, enabling a rapid response.

[0152] An example of a prompt message is, "Explain how to send an alert when a suspicious person is detected, and provide an example of a response based on the user's emotion recognition." This illustrates how the system provides a comprehensive safety environment.

[0153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0154] Step 1:

[0155] The device collects environmental data while moving along a pre-set patrol route. It receives spatial visual data and sensor data for sound and motion as input. Specifically, it captures video with its built-in camera and detects sounds and movement in the environment with its sensors. All of this data is acquired in real time, enabling early detection of anomalies. The collected visual and sensor data are generated as output.

[0156] Step 2:

[0157] The device sends the collected data to the server. The inputs are the visual and sensor data obtained in step 1. The data is sent to the server using an appropriate communication protocol. Specific operations include transferring data via Wi-Fi or a wired network. The output is the data received by the server.

[0158] Step 3:

[0159] The server analyzes the received visual and sensor data in real time. The input is the data transmitted in step 2. AI technology is used as the data analysis method to identify abnormal people or situations from the image data. Abnormal sounds and movements are also detected from the sensor data. Specifically, an image processing algorithm is executed to determine the abnormality. The output is a result of whether an abnormality was identified, and alert information is generated based on that result.

[0160] Step 4:

[0161] The server issues an alert using an information notification system when an anomaly is detected. The input is the alert information generated in step 3. Specifically, it sends notifications to administrators and residents via email or a dedicated app. The output is information that the alert has reached the relevant parties and prompts them to take prompt action.

[0162] Step 5:

[0163] The user collects emotional data using a smartphone app and sends it to a server. The input consists of the user's facial expression data and voice data. Specifically, the app uses the smartphone's camera and microphone to capture facial expressions and voice, and sends this data to the server. The output is the user's emotional data.

[0164] Step 6:

[0165] The server analyzes the received emotional data to identify the user's psychological state. The input is the emotional data sent in step 5. Using an emotional analysis tool, it determines the user's emotional state. Specifically, it executes a facial recognition algorithm to analyze whether the user is feeling anxiety or fear. The output is the emotional state as a result of the analysis, and the alert priority is adjusted as needed.

[0166] Step 7:

[0167] The server stores the analyzed anomaly information and sentiment data using recording devices. The input is the analysis results obtained in steps 3 and 6. Specifically, the information is recorded in a database and made accessible later. The output is the stored information, which the user can use to analyze their own sentiment tendencies.

[0168] (Application Example 2)

[0169] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0170] In modern society, there is a need to quickly and accurately detect suspicious individuals and unusual situations, while ensuring the psychological safety of users. However, conventional security systems only detect physical anomalies and lack consideration for the emotional state of the user. As a result, even when using security systems, users may not be able to completely eliminate their anxiety and fear.

[0171] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0172] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify suspicious persons, and an emotion analysis means for analyzing the user's emotional state and adjusting the priority of alerts based on those emotions. This makes it possible to accurately identify suspicious persons and anomalies while responding to and issuing warnings in accordance with the user's emotions.

[0173] "Image acquisition means" refers to a function that collects visual information from the environment using cameras or other visual sensors.

[0174] "Image analysis means" refers to techniques for analyzing acquired image data to identify suspicious individuals or unusual situations, and often utilizes AI technology.

[0175] A "notification system" is a system that informs users and administrators of detected anomalies or important information, and has the function of sending alerts and messages.

[0176] A "recording system" is a data storage mechanism that saves detected information so that it can be reviewed and analyzed later.

[0177] "Emotional analysis methods" are technologies that analyze a user's emotional state and determine their emotions based on data such as facial expressions and tone of voice.

[0178] "Means of transportation" refers to a method by which a system autonomously moves within a designated area while collecting data, and may use wheels or propellers.

[0179] "Sensor means" refers to devices for detecting abnormal sounds or movements, and includes acoustic sensors and motion sensors.

[0180] In order to implement this invention, the entire system must operate in a coordinated manner. The system mainly consists of three elements: a server, a terminal, and a user.

[0181] The server plays a central role in analyzing the environment in real time. Specifically, it collects image data and sentiment data acquired by terminals and analyzes them using image analysis software (e.g., OpenCV) and sentiment analysis software (e.g., IBM Watson® Tone Analyzer). This makes it possible to identify suspicious individuals and abnormal situations, as well as understand the emotional state of users.

[0182] The device moves autonomously along a pre-set patrol route, acquiring data from the environment using cameras and sensors. The acquired data is immediately sent to a server for analysis. Robots using wheels or propellers are suitable for movement.

[0183] Users interface with this system using smart glasses or other mobile devices. Emotion analysis tools analyze the user's emotions in real time, and if an abnormality or danger is detected, an alert is immediately displayed to the user. This helps to support a sense of psychological security.

[0184] As a concrete example, consider a user walking down a quiet street at night using smart glasses to monitor their surroundings. A sensor detects a suspicious noise from behind, and the server analyzes it. Furthermore, if an expression of anxiety is detected on the user's face, an advanced warning is displayed on the glasses, and a notification is sent to nearby security personnel. An example of a prompt message might be, "Please initiate the process of identifying a suspicious person and detecting an expression of anxiety from the audio data, and then intensify the alert and notify security."

[0185] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0186] Step 1:

[0187] The device collects visual data from the environment using image acquisition means. The device's built-in camera captures the surrounding video and transmits this video data to the server in real time. In this process, the input is visual information of the environment, and the output is image data to be processed on the server side.

[0188] Step 2:

[0189] The server analyzes the transmitted image data using image analysis tools. It performs image modeling and comparison processing via OpenCV to identify suspicious individuals, unusual objects, and movements. At this stage, the input is image data sent from the terminal, and the output is the identification results for suspicious individuals, etc.

[0190] Step 3:

[0191] The terminal collects sound and motion data using sensor devices. The sound sensor and motion sensor acquire information from the surroundings, and this data is transmitted to the server. The input is sound and motion information from the surrounding environment, and the output is sensor data that is further analyzed on the server.

[0192] Step 4:

[0193] The server uses emotion analysis tools to analyze the user's emotional state. Here, facial and audio data sent from the user's smart glasses are processed, and AI technology is used to identify emotional states such as anxiety and fear. At this stage, the input is facial and audio data from the glasses, and the output is the analysis result of the user's emotional state.

[0194] Step 5:

[0195] The server uses various notification methods based on the analysis results to quickly issue alerts. If a suspicious person is identified or user anxiety is detected, the server displays a warning on the user's smart glasses and notifies administrators or security personnel as needed. The input is the analysis results of images and emotions, and the output is the alert content and identification of the recipient.

[0196] Step 6:

[0197] The server utilizes recording mechanisms to meticulously record each piece of detected information. Image data, suspicious person identification, sensor data, emotional state, and other information are stored in a database for later reference. The input consists of all analysis results, and the output consists of data managed as records.

[0198] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0199] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search)<url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0200] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0201] [Second Embodiment]

[0202] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0203] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0204] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0205] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0206] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0207] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0208] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0209] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0210] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0211] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0212] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0213] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0214] As one embodiment of the present invention, the security robot system consists of an autonomous mobile terminal equipped with various sensors and cameras, and a server that analyzes and manages the data. The terminal autonomously patrols a designated area, acquiring images of its surroundings using its cameras, and can also detect surrounding sounds and movements using its sensors. This allows for the collection of data on the environment in real time.

[0215] The collected data is sent from the terminal to the server. The server uses advanced AI technology to analyze the data and identify suspicious individuals or unusual situations. For example, the server uses image recognition technology to identify people's actions and faces in the video and compare them to pre-set behavioral patterns. This makes it possible to detect unusual behavior or intrusion into unauthorized areas with high accuracy.

[0216] If an anomaly is detected, the server immediately generates an alert and notifies the management company and the resident user via a notification system. The notification is sent in real time through a smartphone app, and the user can view the video feed at that time through the app. This allows the user to obtain information in real time to take prompt action.

[0217] Furthermore, the system has the capability to save all records, with the server using recording devices to save detected situations and video footage. This allows residents and management companies to review events that occurred later and use them as evidence if necessary. Through this series of functions, the system significantly enhances security in the living environment and supports a safer living environment.

[0218] The following describes the processing flow.

[0219] Step 1:

[0220] The device autonomously begins moving along a pre-configured patrol route. It uses its built-in sensors and GPS to determine its current location and move precisely.

[0221] Step 2:

[0222] While the device is patrolling, it uses its camera to acquire image data of its surroundings. At the same time, sound sensors and motion sensors are activated to collect data on sounds and movements in the environment.

[0223] Step 3:

[0224] The device transmits collected image data and sensor data to the server. The data is transmitted in real time using wireless communication technology.

[0225] Step 4:

[0226] The server uses AI technology to analyze transmitted image data and detect suspicious individuals or unusual situations. This analysis includes facial recognition and motion analysis.

[0227] Step 5:

[0228] If an anomaly is detected, the server generates an alert based on that information. The alert includes details of the detected situation.

[0229] Step 6:

[0230] The server sends alerts to the management company and resident users via a notification system. Notifications are delivered in real time through a smartphone app.

[0231] Step 7:

[0232] Users receive notifications via a smartphone app and can check the situation. If necessary, users can take action such as contacting the police or administrators.

[0233] Step 8:

[0234] Anomalies are recorded and saved on the server. The saved data can be used later for verification or as evidence.

[0235] (Example 1)

[0236] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0237] Ensuring safety in modern society is a crucial issue, and it is especially important to quickly detect and respond to intruders and abnormal situations. However, existing surveillance systems are insufficient in acquiring visual information and detecting anomalies, and they have limitations in real-time notification and record keeping. In this situation, there is a need to build a system that can effectively monitor the environment and quickly notify of anomalies.

[0238] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0239] In this invention, the server includes a visual sensor means for acquiring image information, a sensing means for detecting sound and movement, and an information processing means for analyzing the acquired data and identifying the characteristics of a person. This enables more accurate and rapid anomaly detection and notification.

[0240] A "visual sensor means" is a device for acquiring video information of a target, which allows for the visual detection of surrounding conditions and abnormalities.

[0241] A "sensing means" is a device that detects sound or the movement of objects, and has the function of detecting changes in the environment.

[0242] "Information processing means" refers to technologies that analyze acquired data and identify specific characteristics, and are means of extracting useful information from data using AI algorithms.

[0243] A "communication means" is a system that transmits information to a remote location when an anomaly is detected, and is a device that enables rapid information transmission via a network.

[0244] A "storage system" is a system that records and securely stores detected data, serving as a foundation for later verification and analysis of that data.

[0245] A "means of transport" is a device that autonomously moves within a designated area to collect information, enabling efficient patrol and surveillance.

[0246] "Networking means" refers to technologies that transmit and receive information via communication networks, and is a system that enables remote monitoring and operation.

[0247] This invention is designed as a security and surveillance system and consists of a terminal equipped with various sensors and cameras, a server that analyzes and manages information, and users that receive and utilize the information.

[0248] The server processes data using advanced AI technology to detect anomalies. Specifically, the server analyzes image data acquired by visual sensors using image recognition software to identify specific behaviors and characteristics. It also analyzes data sent from sound and motion detection devices to identify abnormal sounds and movements. To achieve this processing, the server uses a computer equipped with high-performance CPUs and GPUs.

[0249] The terminal is equipped with a means of mobility to collect environmental data while autonomously moving around the area. The terminal transmits data to a server via Wi-Fi or 5G communication, providing environmental information in real time. In this way, the terminal efficiently monitors a specific area and automatically looks for any suspicious activity.

[0250] When an anomaly is detected, the user receives a notification from the server via the network. The notification is sent through a smartphone app, allowing the user to view real-time video and detection information on the app. This enables the user to take swift action and ensure safety.

[0251] As a concrete example, in nighttime surveillance of a commercial facility, a terminal detects an intruder during patrol, and a server analyzes the details. After confirming the anomaly, the server sends an alert to the facility manager, prompting a quick response. In such a situation, the user can view detailed video footage through the app and take measures such as reporting to the police.

[0252] An example of a prompt using a generative AI model is, "Please tell me more about the security robot system for commercial facilities. What are the system's main functions and the technologies used?" This prompt allows the generative AI to obtain specific details and technical information about the invention.

[0253] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0254] Step 1:

[0255] The terminal autonomously patrols a designated area and acquires image information using visual sensors. The input to the terminal is ambient environmental data, and the output is the acquired image data. It also activates sound and motion detection sensors to collect ambient audio and motion data. The terminal temporarily stores this data in its internal storage.

[0256] Step 2:

[0257] The device transmits collected image and audio data to the server. The input consists of various data stored within the device, while the output is the data transferred to the server. Transmission utilizes Wi-Fi or 5G communication, and the data is compressed in real time and transmitted via protocols designed to minimize network latency.

[0258] Step 3:

[0259] The server analyzes the received image data using AI technology. The input data is raw data sent from the terminal, and the AI ​​model operates, producing output that identifies suspicious individuals and abnormal behavioral patterns. Specifically, an image recognition algorithm is used to analyze the characteristics of a person and compare them with pre-set behavioral patterns.

[0260] Step 4:

[0261] The server analyzes audio data and identifies abnormal sounds. The input data is audio sent from the terminal, and the output is information on whether or not an abnormal sound was detected. The server uses audio analysis software to process sounds that have patterns different from the norm.

[0262] Step 5:

[0263] Based on the analysis results, the server activates a communication system that sends an alert to the user if an anomaly is detected. The input is the analysis results, and the output is a real-time notification to the user. The user can receive the notification, understand the situation, and view the video feed via a smartphone app.

[0264] Step 6:

[0265] The server records all detection information and analysis results using storage mechanisms. The input is comprehensive detection data, and the output is securely stored data records. The stored data can be reviewed later and used for further analysis to enhance security.

[0266] (Application Example 1)

[0267] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0268] Conventional security systems have the capability to detect anomalies, but they lack sufficient means to provide the detected information to the user's external devices in real time. Furthermore, there are challenges in enabling users to respond quickly to environmental monitoring while on the move or to immediate notifications.

[0269] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0270] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify a suspicious person, a notification means for generating an alert when an anomaly is detected and notifying an external device via a communication device, a recording means for storing the detected information, and a means for transmitting video in real time via communication with an external device. This enables the user to check abnormal events in real time and respond quickly.

[0271] "Image acquisition means for detecting environmental conditions" refers to a device that has the function of acquiring still images or videos to visualize the surrounding conditions.

[0272] An "image analysis device" is a device that uses a data processing algorithm to identify specific objects or abnormal movements based on acquired image data.

[0273] A "notification means that generates alerts and notifies external devices via a communication device" is a system that compiles warnings when an anomaly is detected and provides that information to remote users.

[0274] "Recording means for storing detected information" refers to a device or platform for storing collected data and analysis results in digital format for a long period of time.

[0275] "Means of transmitting video in real time through communication with external devices" refers to communication devices and software functions for immediately providing acquired video data to external parties via the internet or network.

[0276] In this security system, the terminal is a multi-functional mobile device that autonomously patrols the environment, acquiring detailed image and audio data. Specifically, the camera and sensors mounted on the terminal simultaneously collect visual information and ambient sounds. This makes it possible to understand the environment's situation in real time.

[0277] The server receives the collected data and analyzes it using advanced image analysis techniques. The analysis utilizes AI frameworks such as TensorFlow, employing generative AI models to identify abnormal behavior within the images and detect suspicious individuals. Furthermore, if an anomaly is detected, a notification message is immediately generated and sent to the user's smartphone or smart glasses.

[0278] Users can receive this notification in real time and view the video stream at that moment through a dedicated app. The app utilizes a mobile application platform built with Android Studio and iOS Xcode. This allows users to take quick and accurate action.

[0279] As a concrete example, suppose one afternoon the device detects unusual activity in an outdoor parking lot. In this case, an alert notification is immediately sent to the user's smartphone, and the user can view the video footage of the scene in real time via the app and quickly contact the security company.

[0280] Furthermore, an example of a prompt message to be input to the generating AI model is, "Please utilize an advanced image analysis algorithm that identifies suspicious behavior in this image and immediately reports any anomalies." Based on this prompt message, the AI ​​model operates to achieve highly accurate anomaly detection.

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

[0282] Step 1:

[0283] While the terminal patrols the environment, it acquires surrounding images and sounds using a camera and sensors. The input is the surrounding environmental information, which is output as digital data. Specifically, it captures video with a camera and detects sound waves and vibrations with sensors.

[0284] Step 2:

[0285] The terminal transmits the acquired digital data to the server. The input is the digital data generated in Step 1, and it is output by sending it to the server via network communication. As a specific operation, data transmission is performed using a communication method such as Wi-Fi or LTE.

[0286] Step 3:

[0287] The server analyzes the received data. The input is the digital data transmitted in Step 2, and it is subjected to image analysis processing using an AI model to obtain an output. Specifically, a generative AI model such as TensorFlow is utilized to perform image analysis to identify suspicious persons and abnormal behaviors. Instructions for the analysis algorithm are also given simultaneously using prompt sentences.

[0288] Step 4:

[0289] The server generates an alert based on the analysis result. The input is the analysis result obtained in Step 3. Based on this analysis result, an abnormality determination is made, and an alert message is generated and transmitted to the user device in real time. The specific operation is to send a push notification to an external device such as a smartphone using a notification system.

[0290] Step 5:

[0291] Based on the alert notification received by the user, a dedicated app is launched to view real-time video. The input is the alert notification from the server, and the output is the display of the corresponding video stream in the app based on this. Specifically, live video is streamed on the interface to provide the user with visual information.

[0292] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0293] As a specific embodiment of the present invention, the security robot system is equipped with a means of movement, an image acquisition means, an image analysis means, a notification means, a recording means, and a sensor means, in addition to an emotion engine. This allows the system to provide a function that recognizes and responds to the user's emotions, in addition to normal security functions.

[0294] The device autonomously moves along a pre-configured patrol route, using its camera to acquire visual data from the environment and collecting data from sound and motion sensors. This data is then transmitted from the device to a server.

[0295] The server analyzes image data and sensor data in real time. The image analysis system uses AI technology to identify and record suspicious individuals and unusual situations. If an anomaly is detected, the server also sends alerts to the management company and residents via notification systems.

[0296] The emotion engine acquires facial and voice data through the user's smartphone app camera and analyzes the user's emotional state. For example, if the emotion engine detects anxiety or fear in the user, the server prioritizes the alert and provides a prompt notification. In addition, the user's emotional data is recorded, allowing the user to analyze their own emotional tendencies based on their system usage.

[0297] As a specific example, when a user at home at night senses the approach of a suspicious person, the terminal identifies this from image data and sensor data and reports it to the server. In parallel, the emotion engine analyzes the user's facial expressions and voice to detect emotions such as uneasiness and tension. Based on such information, the server can send enhanced alerts to the residents and the management company to prompt a prompt response. As a result, in addition to the normal security function, this system provides a comprehensive safe environment considering the psychological sense of security of the user.

[0298] The processing flow will be described below.

[0299] Step 1:

[0300] While the terminal moves along a predetermined patrol route, it uses a camera to acquire images of the surroundings. At the same time, it collects data in the environment using sound and motion sensors.

[0301] Step 2:

[0302] The terminal transmits the acquired image data and sensor data to the server. The data is transmitted in real time using wireless communication.

[0303] Step 3:

[0304] The server analyzes the received image data using AI technology to identify suspicious persons and abnormal situations. The detected abnormal information is stored by the recording means.

[0305] Step 4:

[0306] The server acquires the user's facial expressions and voice data through the emotion engine via the smartphone app and analyzes the user's emotional state.

[0307] Step 5:

[0308] The emotion engine analyzes the user's emotions, and if it detects anxiety or fear, the server adjusts the alert priority. Based on the priority, it sends appropriate alerts to the management company and the user using notification methods.

[0309] Step 6:

[0310] Users receive alerts via a smartphone app and check the situation. If necessary, users can take action, such as contacting the police or administrators.

[0311] Step 7:

[0312] The server records user emotion data and detected anomaly data, and stores it in a format that can be analyzed later. This allows users to analyze their own emotional tendencies and use that information to consider further security measures.

[0313] (Example 2)

[0314] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0315] Conventional security systems, while capable of detecting anomalies in the environment, struggled to respond in a way that considered the user's psychological state, failing to provide users with a sense of psychological security. Furthermore, insufficient means of data collection while on the move and inadequate real-time anomaly notifications meant that delays could occur in situations requiring a rapid response.

[0316] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0317] In this invention, the server includes means for acquiring visual data, means for analyzing data, means for notifying information, means for analyzing emotions, and means for storing information. This makes it possible to grasp the user's emotional state in real time and respond more quickly and appropriately.

[0318] A "visual data acquisition means" is a device that has the function of capturing and acquiring surrounding video and images.

[0319] "Data analysis means" refers to a function that analyzes acquired visual data and sensor data to detect anomalies or specific situations.

[0320] An "information notification means" is a function that sends alerts or notifications to relevant parties when an anomaly is detected.

[0321] "Emotional analysis tools" are functions that analyze a user's facial expressions and voice data to identify their psychological state.

[0322] "Information storage means" refers to a function that records detected anomaly information and user sentiment data, making them accessible later.

[0323] "Spatial movement means" refers to a function that allows a system or device to autonomously move along a predetermined route and collect data over a wide area.

[0324] "Environmental sensor means" refers to a function that uses sensors to detect ambient sounds and movements, and to detect abnormalities when they occur.

[0325] The security system in this invention is composed of multiple means and, in particular, has a function to provide users with a sense of psychological security. This system is mainly divided into two main components: a "terminal" and a "server".

[0326] The terminal is the primary device for collecting ambient environmental data. Specifically, it incorporates a camera as a means of acquiring visual data, continuously capturing images of the environment. Furthermore, a spatial movement mechanism is used for the terminal to autonomously patrol a pre-set route, enabling environmental data collection while moving. The terminal also incorporates environmental sensors, allowing it to detect sound and movement. This enables the terminal to detect environmental anomalies at an early stage.

[0327] The server receives and analyzes visual and sensor data transmitted from terminals. Using AI technology for data analysis, it identifies abnormal individuals and situations within images. Furthermore, it can analyze facial expressions and voice data transmitted from the user's smartphone app using emotion analysis tools to understand the user's emotional state. Based on this information, the server immediately sends alerts to relevant parties using information notification tools when an anomaly is detected. These alerts are sent via email or a dedicated app to encourage prompt action.

[0328] The recorded data can be accessed by the user later through information storage means and used for purposes such as analyzing emotional trends. For example, if a suspicious person approaches at night, the terminal can detect this, and the server can immediately send a notification, enabling a rapid response.

[0329] An example of a prompt message is, "Explain how to send an alert when a suspicious person is detected, and provide an example of a response based on the user's emotion recognition." This illustrates how the system provides a comprehensive safety environment.

[0330] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0331] Step 1:

[0332] The device collects environmental data while moving along a pre-set patrol route. It receives spatial visual data and sensor data for sound and motion as input. Specifically, it captures video with its built-in camera and detects sounds and movement in the environment with its sensors. All of this data is acquired in real time, enabling early detection of anomalies. The collected visual and sensor data are generated as output.

[0333] Step 2:

[0334] The device sends the collected data to the server. The inputs are the visual and sensor data obtained in step 1. The data is sent to the server using an appropriate communication protocol. Specific operations include transferring data via Wi-Fi or a wired network. The output is the data received by the server.

[0335] Step 3:

[0336] The server analyzes the received visual and sensor data in real time. The input is the data transmitted in step 2. AI technology is used as the data analysis method to identify abnormal people or situations from the image data. Abnormal sounds and movements are also detected from the sensor data. Specifically, an image processing algorithm is executed to determine the abnormality. The output is a result of whether an abnormality was identified, and alert information is generated based on that result.

[0337] Step 4:

[0338] The server issues an alert using an information notification system when an anomaly is detected. The input is the alert information generated in step 3. Specifically, it sends notifications to administrators and residents via email or a dedicated app. The output is information that the alert has reached the relevant parties and prompts them to take prompt action.

[0339] Step 5:

[0340] The user collects emotional data using a smartphone app and sends it to a server. The input consists of the user's facial expression data and voice data. Specifically, the app uses the smartphone's camera and microphone to capture facial expressions and voice, and sends this data to the server. The output is the user's emotional data.

[0341] Step 6:

[0342] The server analyzes the received emotional data to identify the user's psychological state. The input is the emotional data sent in step 5. Using an emotional analysis tool, it determines the user's emotional state. Specifically, it executes a facial recognition algorithm to analyze whether the user is feeling anxiety or fear. The output is the emotional state as a result of the analysis, and the alert priority is adjusted as needed.

[0343] Step 7:

[0344] The server stores the analyzed anomaly information and sentiment data using recording devices. The input is the analysis results obtained in steps 3 and 6. Specifically, the information is recorded in a database and made accessible later. The output is the stored information, which the user can use to analyze their own sentiment tendencies.

[0345] (Application Example 2)

[0346] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0347] In modern society, there is a need to quickly and accurately detect suspicious individuals and unusual situations, while ensuring the psychological safety of users. However, conventional security systems only detect physical anomalies and lack consideration for the emotional state of the user. As a result, even when using security systems, users may not be able to completely eliminate their anxiety and fear.

[0348] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0349] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify suspicious persons, and an emotion analysis means for analyzing the user's emotional state and adjusting the priority of alerts based on those emotions. This makes it possible to accurately identify suspicious persons and anomalies while responding to and issuing warnings in accordance with the user's emotions.

[0350] "Image acquisition means" refers to a function that collects visual information from the environment using cameras or other visual sensors.

[0351] "Image analysis means" refers to techniques for analyzing acquired image data to identify suspicious individuals or unusual situations, and often utilizes AI technology.

[0352] A "notification system" is a system that informs users and administrators of detected anomalies or important information, and has the function of sending alerts and messages.

[0353] A "recording system" is a data storage mechanism that saves detected information so that it can be reviewed and analyzed later.

[0354] "Emotional analysis methods" are technologies that analyze a user's emotional state and determine their emotions based on data such as facial expressions and tone of voice.

[0355] "Means of transportation" refers to a method by which a system autonomously moves within a designated area while collecting data, and may use wheels or propellers.

[0356] "Sensor means" refers to devices for detecting abnormal sounds or movements, and includes acoustic sensors and motion sensors.

[0357] In order to implement this invention, the entire system must operate in a coordinated manner. The system mainly consists of three elements: a server, a terminal, and a user.

[0358] The server plays a central role in analyzing the environment in real time. Specifically, it collects image data and sentiment data acquired by terminals and analyzes them using image analysis software (e.g., OpenCV) and sentiment analysis software (e.g., IBM Watson Tone Analyzer). This makes it possible to identify suspicious individuals and abnormal situations, as well as understand the emotional state of users.

[0359] The device moves autonomously along a pre-set patrol route, acquiring data from the environment using cameras and sensors. The acquired data is immediately sent to a server for analysis. Robots using wheels or propellers are suitable for movement.

[0360] Users interface with this system using smart glasses or other mobile devices. Emotion analysis tools analyze the user's emotions in real time, and if an abnormality or danger is detected, an alert is immediately displayed to the user. This helps to support a sense of psychological security.

[0361] As a concrete example, consider a user walking down a quiet street at night using smart glasses to monitor their surroundings. A sensor detects a suspicious noise from behind, and the server analyzes it. Furthermore, if an expression of anxiety is detected on the user's face, an advanced warning is displayed on the glasses, and a notification is sent to nearby security personnel. An example of a prompt message might be, "Please initiate the process of identifying a suspicious person and detecting an expression of anxiety from the audio data, and then intensify the alert and notify security."

[0362] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0363] Step 1:

[0364] The device collects visual data from the environment using image acquisition means. The device's built-in camera captures the surrounding video and transmits this video data to the server in real time. In this process, the input is visual information of the environment, and the output is image data to be processed on the server side.

[0365] Step 2:

[0366] The server analyzes the transmitted image data using image analysis tools. It performs image modeling and comparison processing via OpenCV to identify suspicious individuals, unusual objects, and movements. At this stage, the input is image data sent from the terminal, and the output is the identification results for suspicious individuals, etc.

[0367] Step 3:

[0368] The terminal collects sound and motion data using sensor devices. The sound sensor and motion sensor acquire information from the surroundings, and this data is transmitted to the server. The input is sound and motion information from the surrounding environment, and the output is sensor data that is further analyzed on the server.

[0369] Step 4:

[0370] The server uses emotion analysis tools to analyze the user's emotional state. Here, facial and audio data sent from the user's smart glasses are processed, and AI technology is used to identify emotional states such as anxiety and fear. At this stage, the input is facial and audio data from the glasses, and the output is the analysis result of the user's emotional state.

[0371] Step 5:

[0372] The server uses various notification methods based on the analysis results to quickly issue alerts. If a suspicious person is identified or user anxiety is detected, the server displays a warning on the user's smart glasses and notifies administrators or security personnel as needed. The input is the analysis results of images and emotions, and the output is the alert content and identification of the recipient.

[0373] Step 6:

[0374] The server utilizes recording mechanisms to meticulously record each piece of detected information. Image data, suspicious person identification, sensor data, emotional state, and other information are stored in a database for later reference. The input consists of all analysis results, and the output consists of data managed as records.

[0375] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0376] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0377] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0378] [Third Embodiment]

[0379] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0380] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0381] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0382] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0383] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0384] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0385] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0386] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0387] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0388] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0389] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0390] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0391] As one embodiment of the present invention, the security robot system consists of an autonomous mobile terminal equipped with various sensors and cameras, and a server that analyzes and manages the data. The terminal autonomously patrols a designated area, acquiring images of its surroundings using its cameras, and can also detect surrounding sounds and movements using its sensors. This allows for the collection of data on the environment in real time.

[0392] The collected data is sent from the terminal to the server. The server uses advanced AI technology to analyze the data and identify suspicious individuals or unusual situations. For example, the server uses image recognition technology to identify people's actions and faces in the video and compare them to pre-set behavioral patterns. This makes it possible to detect unusual behavior or intrusion into unauthorized areas with high accuracy.

[0393] If an anomaly is detected, the server immediately generates an alert and notifies the management company and the resident user via a notification system. The notification is sent in real time through a smartphone app, and the user can view the video feed at that time through the app. This allows the user to obtain information in real time to take prompt action.

[0394] Furthermore, the system has the capability to save all records, with the server using recording devices to save detected situations and video footage. This allows residents and management companies to review events that occurred later and use them as evidence if necessary. Through this series of functions, the system significantly enhances security in the living environment and supports a safer living environment.

[0395] The following describes the processing flow.

[0396] Step 1:

[0397] The device autonomously begins moving along a pre-configured patrol route. It uses its built-in sensors and GPS to determine its current location and move precisely.

[0398] Step 2:

[0399] While the device is patrolling, it uses its camera to acquire image data of its surroundings. At the same time, sound sensors and motion sensors are activated to collect data on sounds and movements in the environment.

[0400] Step 3:

[0401] The device transmits collected image data and sensor data to the server. The data is transmitted in real time using wireless communication technology.

[0402] Step 4:

[0403] The server uses AI technology to analyze transmitted image data and detect suspicious individuals or unusual situations. This analysis includes facial recognition and motion analysis.

[0404] Step 5:

[0405] If an anomaly is detected, the server generates an alert based on that information. The alert includes details of the detected situation.

[0406] Step 6:

[0407] The server sends alerts to the management company and resident users via a notification system. Notifications are delivered in real time through a smartphone app.

[0408] Step 7:

[0409] Users receive notifications via a smartphone app and can check the situation. If necessary, users can take action such as contacting the police or administrators.

[0410] Step 8:

[0411] Anomalies are recorded and saved on the server. The saved data can be used later for verification or as evidence.

[0412] (Example 1)

[0413] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0414] Ensuring safety in modern society is a crucial issue, and it is especially important to quickly detect and respond to intruders and abnormal situations. However, existing surveillance systems are insufficient in acquiring visual information and detecting anomalies, and they have limitations in real-time notification and record keeping. In this situation, there is a need to build a system that can effectively monitor the environment and quickly notify of anomalies.

[0415] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0416] In this invention, the server includes a visual sensor means for acquiring image information, a sensing means for detecting sound and movement, and an information processing means for analyzing the acquired data and identifying the characteristics of a person. This enables more accurate and rapid anomaly detection and notification.

[0417] A "visual sensor means" is a device for acquiring video information of a target, which allows for the visual detection of surrounding conditions and abnormalities.

[0418] A "sensing means" is a device that detects sound or the movement of objects, and has the function of detecting changes in the environment.

[0419] "Information processing means" refers to technologies that analyze acquired data and identify specific characteristics, and are means of extracting useful information from data using AI algorithms.

[0420] A "communication means" is a system that transmits information to a remote location when an anomaly is detected, and is a device that enables rapid information transmission via a network.

[0421] A "storage system" is a system that records and securely stores detected data, serving as a foundation for later verification and analysis of that data.

[0422] A "means of transport" is a device that autonomously moves within a designated area to collect information, enabling efficient patrol and surveillance.

[0423] "Networking means" refers to technologies that transmit and receive information via communication networks, and is a system that enables remote monitoring and operation.

[0424] This invention is designed as a security and surveillance system and consists of a terminal equipped with various sensors and cameras, a server that analyzes and manages information, and users that receive and utilize the information.

[0425] The server processes data using advanced AI technology to detect anomalies. Specifically, the server analyzes image data acquired by visual sensors using image recognition software to identify specific behaviors and characteristics. It also analyzes data sent from sound and motion detection devices to identify abnormal sounds and movements. To achieve this processing, the server uses a computer equipped with high-performance CPUs and GPUs.

[0426] The terminal is equipped with a means of mobility to collect environmental data while autonomously moving around the area. The terminal transmits data to a server via Wi-Fi or 5G communication, providing environmental information in real time. In this way, the terminal efficiently monitors a specific area and automatically looks for any suspicious activity.

[0427] When an anomaly is detected, the user receives a notification from the server via the network. The notification is sent through a smartphone app, allowing the user to view real-time video and detection information on the app. This enables the user to take swift action and ensure safety.

[0428] As a concrete example, in nighttime surveillance of a commercial facility, a terminal detects an intruder during patrol, and a server analyzes the details. After confirming the anomaly, the server sends an alert to the facility manager, prompting a quick response. In such a situation, the user can view detailed video footage through the app and take measures such as reporting to the police.

[0429] An example of a prompt using a generative AI model is, "Please tell me more about the security robot system for commercial facilities. What are the system's main functions and the technologies used?" This prompt allows the generative AI to obtain specific details and technical information about the invention.

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

[0431] Step 1:

[0432] The terminal autonomously patrols a designated area and acquires image information using visual sensors. The input to the terminal is ambient environmental data, and the output is the acquired image data. It also activates sound and motion detection sensors to collect ambient audio and motion data. The terminal temporarily stores this data in its internal storage.

[0433] Step 2:

[0434] The device transmits collected image and audio data to the server. The input consists of various data stored within the device, while the output is the data transferred to the server. Transmission utilizes Wi-Fi or 5G communication, and the data is compressed in real time and transmitted via protocols designed to minimize network latency.

[0435] Step 3:

[0436] The server analyzes the received image data using AI technology. The input data is raw data sent from the terminal, and the AI ​​model operates, producing output that identifies suspicious individuals and abnormal behavioral patterns. Specifically, an image recognition algorithm is used to analyze the characteristics of a person and compare them with pre-set behavioral patterns.

[0437] Step 4:

[0438] The server analyzes audio data and identifies abnormal sounds. The input data is audio sent from the terminal, and the output is information on whether or not an abnormal sound was detected. The server uses audio analysis software to process sounds that have patterns different from the norm.

[0439] Step 5:

[0440] Based on the analysis results, the server activates a communication system that sends an alert to the user if an anomaly is detected. The input is the analysis results, and the output is a real-time notification to the user. The user can receive the notification, understand the situation, and view the video feed via a smartphone app.

[0441] Step 6:

[0442] The server records all detection information and analysis results using storage mechanisms. The input is comprehensive detection data, and the output is securely stored data records. The stored data can be reviewed later and used for further analysis to enhance security.

[0443] (Application Example 1)

[0444] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0445] Conventional security systems have the capability to detect anomalies, but they lack sufficient means to provide the detected information to the user's external devices in real time. Furthermore, there are challenges in enabling users to respond quickly to environmental monitoring while on the move or to immediate notifications.

[0446] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0447] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify a suspicious person, a notification means for generating an alert when an anomaly is detected and notifying an external device via a communication device, a recording means for storing the detected information, and a means for transmitting video in real time via communication with an external device. This enables the user to check abnormal events in real time and respond quickly.

[0448] "Image acquisition means for detecting environmental conditions" refers to a device that has the function of acquiring still images or videos to visualize the surrounding conditions.

[0449] An "image analysis device" is a device that uses a data processing algorithm to identify specific objects or abnormal movements based on acquired image data.

[0450] A "notification means that generates alerts and notifies external devices via a communication device" is a system that compiles warnings when an anomaly is detected and provides that information to remote users.

[0451] "Recording means for storing detected information" refers to a device or platform for storing collected data and analysis results in digital format for a long period of time.

[0452] "Means of transmitting video in real time through communication with external devices" refers to communication devices and software functions for immediately providing acquired video data to external parties via the internet or network.

[0453] In this security system, the terminal is a multi-functional mobile device that autonomously patrols the environment, acquiring detailed image and audio data. Specifically, the camera and sensors mounted on the terminal simultaneously collect visual information and ambient sounds. This makes it possible to understand the environment's situation in real time.

[0454] The server receives the collected data and analyzes it using advanced image analysis techniques. The analysis utilizes AI frameworks such as TensorFlow, employing generative AI models to identify abnormal behavior within the images and detect suspicious individuals. Furthermore, if an anomaly is detected, a notification message is immediately generated and sent to the user's smartphone or smart glasses.

[0455] Users can receive this notification in real time and view the video stream at that moment through a dedicated app. The app utilizes a mobile application platform built with Android Studio and iOS Xcode. This allows users to take quick and accurate action.

[0456] As a concrete example, suppose one afternoon the device detects unusual activity in an outdoor parking lot. In this case, an alert notification is immediately sent to the user's smartphone, and the user can view the video footage of the scene in real time via the app and quickly contact the security company.

[0457] Furthermore, an example of a prompt message to be input to the generating AI model is, "Please utilize an advanced image analysis algorithm that identifies suspicious behavior in this image and immediately reports any anomalies." Based on this prompt message, the AI ​​model operates to achieve highly accurate anomaly detection.

[0458] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0459] Step 1:

[0460] The device patrols the environment, acquiring images and sounds of its surroundings using its camera and sensors. The input is information about the surrounding environment, which is output as digital data. Specifically, it captures video with the camera and detects sound waves and vibrations with the sensors.

[0461] Step 2:

[0462] The terminal transmits the acquired digital data to the server. The input is the digital data generated in step 1, and the output is obtained by sending it to the server via network communication. Specifically, data transmission is performed using communication methods such as Wi-Fi or LTE.

[0463] Step 3:

[0464] The server analyzes the data it receives. The input is the digital data sent in step 2, which is then subjected to image analysis processing using an AI model to obtain output. Specifically, it utilizes generative AI models such as TensorFlow to perform image analysis to identify suspicious individuals and abnormal behavior. Instructions for the analysis algorithm are also given simultaneously using prompt messages.

[0465] Step 4:

[0466] The server generates an alert based on the analysis results. The input is the analysis results obtained in step 3. Based on these analysis results, it determines if an anomaly has occurred, generates an alert message, and sends it to the user device in real time. Specifically, it uses a notification system to send a push notification to an external device such as a smartphone.

[0467] Step 5:

[0468] Based on the alert notification received by the user, a dedicated app is launched to view real-time video. The input is the alert notification from the server, and the output is the display of the corresponding video stream in the app based on this. Specifically, live video is streamed on the interface to provide the user with visual information.

[0469] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0470] As a specific embodiment of the present invention, the security robot system is equipped with a means of movement, an image acquisition means, an image analysis means, a notification means, a recording means, and a sensor means, in addition to an emotion engine. This allows the system to provide a function that recognizes and responds to the user's emotions, in addition to normal security functions.

[0471] The device autonomously moves along a pre-configured patrol route, using its camera to acquire visual data from the environment and collecting data from sound and motion sensors. This data is then transmitted from the device to a server.

[0472] The server analyzes image data and sensor data in real time. The image analysis system uses AI technology to identify and record suspicious individuals and unusual situations. If an anomaly is detected, the server also sends alerts to the management company and residents via notification systems.

[0473] The emotion engine acquires facial and voice data through the user's smartphone app camera and analyzes the user's emotional state. For example, if the emotion engine detects anxiety or fear in the user, the server prioritizes the alert and provides a prompt notification. In addition, the user's emotional data is recorded, allowing the user to analyze their own emotional tendencies based on their system usage.

[0474] For example, if a user at home at night detects the approach of a suspicious person, the device identifies this using image data and sensor data and reports it to the server. Simultaneously, an emotion engine analyzes the user's facial expressions and voice to detect emotions such as anxiety and tension. Based on this information, the server can send enhanced alerts to residents and management companies, prompting a quick response. This system provides a comprehensive security environment that considers the user's psychological well-being in addition to standard security functions.

[0475] The following describes the processing flow.

[0476] Step 1:

[0477] The device moves along a predetermined patrol route, using its camera to acquire images of its surroundings. Simultaneously, it collects data from the environment using sound and motion sensors.

[0478] Step 2:

[0479] The device transmits collected image data and sensor data to the server. The data is transmitted in real time using wireless communication.

[0480] Step 3:

[0481] The server uses AI technology to analyze the received image data and identify suspicious individuals or unusual situations. The detected anomaly information is stored by recording devices.

[0482] Step 4:

[0483] The server uses an emotion engine to acquire the user's facial expressions and voice data through the smartphone app, and then analyzes the user's emotional state.

[0484] Step 5:

[0485] The emotion engine analyzes the user's emotions, and if it detects anxiety or fear, the server adjusts the alert priority. Based on the priority, it sends appropriate alerts to the management company and the user using notification methods.

[0486] Step 6:

[0487] Users receive alerts via a smartphone app and check the situation. If necessary, users can take action, such as contacting the police or administrators.

[0488] Step 7:

[0489] The server records user emotion data and detected anomaly data, and stores it in a format that can be analyzed later. This allows users to analyze their own emotional tendencies and use that information to consider further security measures.

[0490] (Example 2)

[0491] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0492] Conventional security systems, while capable of detecting anomalies in the environment, struggled to respond in a way that considered the user's psychological state, failing to provide users with a sense of psychological security. Furthermore, insufficient means of data collection while on the move and inadequate real-time anomaly notifications meant that delays could occur in situations requiring a rapid response.

[0493] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0494] In this invention, the server includes means for acquiring visual data, means for analyzing data, means for notifying information, means for analyzing emotions, and means for storing information. This makes it possible to grasp the user's emotional state in real time and respond more quickly and appropriately.

[0495] A "visual data acquisition means" is a device that has the function of capturing and acquiring surrounding video and images.

[0496] "Data analysis means" refers to a function that analyzes acquired visual data and sensor data to detect anomalies or specific situations.

[0497] An "information notification means" is a function that sends alerts or notifications to relevant parties when an anomaly is detected.

[0498] "Emotional analysis tools" are functions that analyze a user's facial expressions and voice data to identify their psychological state.

[0499] "Information storage means" refers to a function that records detected anomaly information and user sentiment data, making them accessible later.

[0500] "Spatial movement means" refers to a function that allows a system or device to autonomously move along a predetermined route and collect data over a wide area.

[0501] "Environmental sensor means" refers to a function that uses sensors to detect ambient sounds and movements, and to detect abnormalities when they occur.

[0502] The security system in this invention is composed of multiple means and, in particular, has a function to provide users with a sense of psychological security. This system is mainly divided into two main components: a "terminal" and a "server".

[0503] The terminal is the primary device for collecting ambient environmental data. Specifically, it incorporates a camera as a means of acquiring visual data, continuously capturing images of the environment. Furthermore, a spatial movement mechanism is used for the terminal to autonomously patrol a pre-set route, enabling environmental data collection while moving. The terminal also incorporates environmental sensors, allowing it to detect sound and movement. This enables the terminal to detect environmental anomalies at an early stage.

[0504] The server receives and analyzes visual and sensor data transmitted from terminals. Using AI technology for data analysis, it identifies abnormal individuals and situations within images. Furthermore, it can analyze facial expressions and voice data transmitted from the user's smartphone app using emotion analysis tools to understand the user's emotional state. Based on this information, the server immediately sends alerts to relevant parties using information notification tools when an anomaly is detected. These alerts are sent via email or a dedicated app to encourage prompt action.

[0505] The recorded data can be accessed by the user later through information storage means and used for purposes such as analyzing emotional trends. For example, if a suspicious person approaches at night, the terminal can detect this, and the server can immediately send a notification, enabling a rapid response.

[0506] An example of a prompt message is, "Explain how to send an alert when a suspicious person is detected, and provide an example of a response based on the user's emotion recognition." This illustrates how the system provides a comprehensive safety environment.

[0507] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0508] Step 1:

[0509] The device collects environmental data while moving along a pre-set patrol route. It receives spatial visual data and sensor data for sound and motion as input. Specifically, it captures video with its built-in camera and detects sounds and movement in the environment with its sensors. All of this data is acquired in real time, enabling early detection of anomalies. The collected visual and sensor data are generated as output.

[0510] Step 2:

[0511] The device sends the collected data to the server. The inputs are the visual and sensor data obtained in step 1. The data is sent to the server using an appropriate communication protocol. Specific operations include transferring data via Wi-Fi or a wired network. The output is the data received by the server.

[0512] Step 3:

[0513] The server analyzes the received visual and sensor data in real time. The input is the data transmitted in step 2. AI technology is used as the data analysis method to identify abnormal people or situations from the image data. Abnormal sounds and movements are also detected from the sensor data. Specifically, an image processing algorithm is executed to determine the abnormality. The output is a result of whether an abnormality was identified, and alert information is generated based on that result.

[0514] Step 4:

[0515] The server issues an alert using an information notification system when an anomaly is detected. The input is the alert information generated in step 3. Specifically, it sends notifications to administrators and residents via email or a dedicated app. The output is information that the alert has reached the relevant parties and prompts them to take prompt action.

[0516] Step 5:

[0517] The user collects emotional data using a smartphone app and sends it to a server. The input consists of the user's facial expression data and voice data. Specifically, the app uses the smartphone's camera and microphone to capture facial expressions and voice, and sends this data to the server. The output is the user's emotional data.

[0518] Step 6:

[0519] The server analyzes the received emotional data to identify the user's psychological state. The input is the emotional data sent in step 5. Using an emotional analysis tool, it determines the user's emotional state. Specifically, it executes a facial recognition algorithm to analyze whether the user is feeling anxiety or fear. The output is the emotional state as a result of the analysis, and the alert priority is adjusted as needed.

[0520] Step 7:

[0521] The server stores the analyzed anomaly information and sentiment data using recording devices. The input is the analysis results obtained in steps 3 and 6. Specifically, the information is recorded in a database and made accessible later. The output is the stored information, which the user can use to analyze their own sentiment tendencies.

[0522] (Application Example 2)

[0523] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0524] In modern society, there is a need to quickly and accurately detect suspicious individuals and unusual situations, while ensuring the psychological safety of users. However, conventional security systems only detect physical anomalies and lack consideration for the emotional state of the user. As a result, even when using security systems, users may not be able to completely eliminate their anxiety and fear.

[0525] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0526] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify suspicious persons, and an emotion analysis means for analyzing the user's emotional state and adjusting the priority of alerts based on those emotions. This makes it possible to accurately identify suspicious persons and anomalies while responding to and issuing warnings in accordance with the user's emotions.

[0527] "Image acquisition means" refers to a function that collects visual information from the environment using cameras or other visual sensors.

[0528] "Image analysis means" refers to techniques for analyzing acquired image data to identify suspicious individuals or unusual situations, and often utilizes AI technology.

[0529] A "notification system" is a system that informs users and administrators of detected anomalies or important information, and has the function of sending alerts and messages.

[0530] A "recording system" is a data storage mechanism that saves detected information so that it can be reviewed and analyzed later.

[0531] "Emotional analysis methods" are technologies that analyze a user's emotional state and determine their emotions based on data such as facial expressions and tone of voice.

[0532] "Means of transportation" refers to a method by which a system autonomously moves within a designated area while collecting data, and may use wheels or propellers.

[0533] "Sensor means" refers to devices for detecting abnormal sounds or movements, and includes acoustic sensors and motion sensors.

[0534] In order to implement this invention, the entire system must operate in a coordinated manner. The system mainly consists of three elements: a server, a terminal, and a user.

[0535] The server plays a central role in analyzing the environment in real time. Specifically, it collects image data and sentiment data acquired by terminals and analyzes them using image analysis software (e.g., OpenCV) and sentiment analysis software (e.g., IBM Watson Tone Analyzer). This makes it possible to identify suspicious individuals and abnormal situations, as well as understand the emotional state of users.

[0536] The device moves autonomously along a pre-set patrol route, acquiring data from the environment using cameras and sensors. The acquired data is immediately sent to a server for analysis. Robots using wheels or propellers are suitable for movement.

[0537] Users interface with this system using smart glasses or other mobile devices. Emotion analysis tools analyze the user's emotions in real time, and if an abnormality or danger is detected, an alert is immediately displayed to the user. This helps to support a sense of psychological security.

[0538] As a concrete example, consider a user walking down a quiet street at night using smart glasses to monitor their surroundings. A sensor detects a suspicious noise from behind, and the server analyzes it. Furthermore, if an expression of anxiety is detected on the user's face, an advanced warning is displayed on the glasses, and a notification is sent to nearby security personnel. An example of a prompt message might be, "Please initiate the process of identifying a suspicious person and detecting an expression of anxiety from the audio data, and then intensify the alert and notify security."

[0539] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0540] Step 1:

[0541] The device collects visual data from the environment using image acquisition means. The device's built-in camera captures the surrounding video and transmits this video data to the server in real time. In this process, the input is visual information of the environment, and the output is image data to be processed on the server side.

[0542] Step 2:

[0543] The server analyzes the transmitted image data using image analysis tools. It performs image modeling and comparison processing via OpenCV to identify suspicious individuals, unusual objects, and movements. At this stage, the input is image data sent from the terminal, and the output is the identification results for suspicious individuals, etc.

[0544] Step 3:

[0545] The terminal collects sound and motion data using sensor devices. The sound sensor and motion sensor acquire information from the surroundings, and this data is transmitted to the server. The input is sound and motion information from the surrounding environment, and the output is sensor data that is further analyzed on the server.

[0546] Step 4:

[0547] The server uses emotion analysis tools to analyze the user's emotional state. Here, facial and audio data sent from the user's smart glasses are processed, and AI technology is used to identify emotional states such as anxiety and fear. At this stage, the input is facial and audio data from the glasses, and the output is the analysis result of the user's emotional state.

[0548] Step 5:

[0549] The server uses various notification methods based on the analysis results to quickly issue alerts. If a suspicious person is identified or user anxiety is detected, the server displays a warning on the user's smart glasses and notifies administrators or security personnel as needed. The input is the analysis results of images and emotions, and the output is the alert content and identification of the recipient.

[0550] Step 6:

[0551] The server utilizes recording mechanisms to meticulously record each piece of detected information. Image data, suspicious person identification, sensor data, emotional state, and other information are stored in a database for later reference. The input consists of all analysis results, and the output consists of data managed as records.

[0552] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0553] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0554] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0555] [Fourth Embodiment]

[0556] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0557] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0558] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0559] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0560] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0561] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0562] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0563] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0564] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0565] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0566] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0567] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0568] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0569] As one embodiment of the present invention, the security robot system consists of an autonomous mobile terminal equipped with various sensors and cameras, and a server that analyzes and manages the data. The terminal autonomously patrols a designated area, acquiring images of its surroundings using its cameras, and can also detect surrounding sounds and movements using its sensors. This allows for the collection of data on the environment in real time.

[0570] The collected data is sent from the terminal to the server. The server uses advanced AI technology to analyze the data and identify suspicious individuals or unusual situations. For example, the server uses image recognition technology to identify people's actions and faces in the video and compare them to pre-set behavioral patterns. This makes it possible to detect unusual behavior or intrusion into unauthorized areas with high accuracy.

[0571] If an anomaly is detected, the server immediately generates an alert and notifies the management company and the resident user via a notification system. The notification is sent in real time through a smartphone app, and the user can view the video feed at that time through the app. This allows the user to obtain information in real time to take prompt action.

[0572] Furthermore, the system has the capability to save all records, with the server using recording devices to save detected situations and video footage. This allows residents and management companies to review events that occurred later and use them as evidence if necessary. Through this series of functions, the system significantly enhances security in the living environment and supports a safer living environment.

[0573] The following describes the processing flow.

[0574] Step 1:

[0575] The device autonomously begins moving along a pre-configured patrol route. It uses its built-in sensors and GPS to determine its current location and move precisely.

[0576] Step 2:

[0577] While the device is patrolling, it uses its camera to acquire image data of its surroundings. At the same time, sound sensors and motion sensors are activated to collect data on sounds and movements in the environment.

[0578] Step 3:

[0579] The device transmits collected image data and sensor data to the server. The data is transmitted in real time using wireless communication technology.

[0580] Step 4:

[0581] The server uses AI technology to analyze transmitted image data and detect suspicious individuals or unusual situations. This analysis includes facial recognition and motion analysis.

[0582] Step 5:

[0583] If an anomaly is detected, the server generates an alert based on that information. The alert includes details of the detected situation.

[0584] Step 6:

[0585] The server sends alerts to the management company and resident users via a notification system. Notifications are delivered in real time through a smartphone app.

[0586] Step 7:

[0587] Users receive notifications via a smartphone app and can check the situation. If necessary, users can take action such as contacting the police or administrators.

[0588] Step 8:

[0589] Anomalies are recorded and saved on the server. The saved data can be used later for verification or as evidence.

[0590] (Example 1)

[0591] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0592] Ensuring safety in modern society is a crucial issue, and it is especially important to quickly detect and respond to intruders and abnormal situations. However, existing surveillance systems are insufficient in acquiring visual information and detecting anomalies, and they have limitations in real-time notification and record keeping. In this situation, there is a need to build a system that can effectively monitor the environment and quickly notify of anomalies.

[0593] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0594] In this invention, the server includes a visual sensor means for acquiring image information, a sensing means for detecting sound and movement, and an information processing means for analyzing the acquired data and identifying the characteristics of a person. This enables more accurate and rapid anomaly detection and notification.

[0595] A "visual sensor means" is a device for acquiring video information of a target, which allows for the visual detection of surrounding conditions and abnormalities.

[0596] A "sensing means" is a device that detects sound or the movement of objects, and has the function of detecting changes in the environment.

[0597] "Information processing means" refers to technologies that analyze acquired data and identify specific characteristics, and are means of extracting useful information from data using AI algorithms.

[0598] A "communication means" is a system that transmits information to a remote location when an anomaly is detected, and is a device that enables rapid information transmission via a network.

[0599] A "storage system" is a system that records and securely stores detected data, serving as a foundation for later verification and analysis of that data.

[0600] A "means of transport" is a device that autonomously moves within a designated area to collect information, enabling efficient patrol and surveillance.

[0601] "Networking means" refers to technologies that transmit and receive information via communication networks, and is a system that enables remote monitoring and operation.

[0602] This invention is designed as a security and surveillance system and consists of a terminal equipped with various sensors and cameras, a server that analyzes and manages information, and users that receive and utilize the information.

[0603] The server processes data using advanced AI technology to detect anomalies. Specifically, the server analyzes image data acquired by visual sensors using image recognition software to identify specific behaviors and characteristics. It also analyzes data sent from sound and motion detection devices to identify abnormal sounds and movements. To achieve this processing, the server uses a computer equipped with high-performance CPUs and GPUs.

[0604] The terminal is equipped with a means of mobility to collect environmental data while autonomously moving around the area. The terminal transmits data to a server via Wi-Fi or 5G communication, providing environmental information in real time. In this way, the terminal efficiently monitors a specific area and automatically looks for any suspicious activity.

[0605] When an anomaly is detected, the user receives a notification from the server via the network. The notification is sent through a smartphone app, allowing the user to view real-time video and detection information on the app. This enables the user to take swift action and ensure safety.

[0606] As a concrete example, in nighttime surveillance of a commercial facility, a terminal detects an intruder during patrol, and a server analyzes the details. After confirming the anomaly, the server sends an alert to the facility manager, prompting a quick response. In such a situation, the user can view detailed video footage through the app and take measures such as reporting to the police.

[0607] An example of a prompt using a generative AI model is, "Please tell me more about the security robot system for commercial facilities. What are the system's main functions and the technologies used?" This prompt allows the generative AI to obtain specific details and technical information about the invention.

[0608] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0609] Step 1:

[0610] The terminal autonomously patrols a designated area and acquires image information using visual sensors. The input to the terminal is ambient environmental data, and the output is the acquired image data. It also activates sound and motion detection sensors to collect ambient audio and motion data. The terminal temporarily stores this data in its internal storage.

[0611] Step 2:

[0612] The device transmits collected image and audio data to the server. The input consists of various data stored within the device, while the output is the data transferred to the server. Transmission utilizes Wi-Fi or 5G communication, and the data is compressed in real time and transmitted via protocols designed to minimize network latency.

[0613] Step 3:

[0614] The server analyzes the received image data using AI technology. The input data is raw data sent from the terminal, and the AI ​​model operates, producing output that identifies suspicious individuals and abnormal behavioral patterns. Specifically, an image recognition algorithm is used to analyze the characteristics of a person and compare them with pre-set behavioral patterns.

[0615] Step 4:

[0616] The server analyzes audio data and identifies abnormal sounds. The input data is audio sent from the terminal, and the output is information on whether or not an abnormal sound was detected. The server uses audio analysis software to process sounds that have patterns different from the norm.

[0617] Step 5:

[0618] Based on the analysis results, the server activates a communication system that sends an alert to the user if an anomaly is detected. The input is the analysis results, and the output is a real-time notification to the user. The user can receive the notification, understand the situation, and view the video feed via a smartphone app.

[0619] Step 6:

[0620] The server records all detection information and analysis results using storage mechanisms. The input is comprehensive detection data, and the output is securely stored data records. The stored data can be reviewed later and used for further analysis to enhance security.

[0621] (Application Example 1)

[0622] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0623] Conventional security systems have the capability to detect anomalies, but they lack sufficient means to provide the detected information to the user's external devices in real time. Furthermore, there are challenges in enabling users to respond quickly to environmental monitoring while on the move or to immediate notifications.

[0624] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0625] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify a suspicious person, a notification means for generating an alert when an anomaly is detected and notifying an external device via a communication device, a recording means for storing the detected information, and a means for transmitting video in real time via communication with an external device. This enables the user to check abnormal events in real time and respond quickly.

[0626] "Image acquisition means for detecting environmental conditions" refers to a device that has the function of acquiring still images or videos to visualize the surrounding conditions.

[0627] An "image analysis device" is a device that uses a data processing algorithm to identify specific objects or abnormal movements based on acquired image data.

[0628] A "notification means that generates alerts and notifies external devices via a communication device" is a system that compiles warnings when an anomaly is detected and provides that information to remote users.

[0629] "Recording means for storing detected information" refers to a device or platform for storing collected data and analysis results in digital format for a long period of time.

[0630] "Means of transmitting video in real time through communication with external devices" refers to communication devices and software functions for immediately providing acquired video data to external parties via the internet or network.

[0631] In this security system, the terminal is a multi-functional mobile device that autonomously patrols the environment, acquiring detailed image and audio data. Specifically, the camera and sensors mounted on the terminal simultaneously collect visual information and ambient sounds. This makes it possible to understand the environment's situation in real time.

[0632] The server receives the collected data and analyzes it using advanced image analysis techniques. The analysis utilizes AI frameworks such as TensorFlow, employing generative AI models to identify abnormal behavior within the images and detect suspicious individuals. Furthermore, if an anomaly is detected, a notification message is immediately generated and sent to the user's smartphone or smart glasses.

[0633] Users can receive this notification in real time and view the video stream at that moment through a dedicated app. The app utilizes a mobile application platform built with Android Studio and iOS Xcode. This allows users to take quick and accurate action.

[0634] As a concrete example, suppose one afternoon the device detects unusual activity in an outdoor parking lot. In this case, an alert notification is immediately sent to the user's smartphone, and the user can view the video footage of the scene in real time via the app and quickly contact the security company.

[0635] Furthermore, an example of a prompt message to be input to the generating AI model is, "Please utilize an advanced image analysis algorithm that identifies suspicious behavior in this image and immediately reports any anomalies." Based on this prompt message, the AI ​​model operates to achieve highly accurate anomaly detection.

[0636] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0637] Step 1:

[0638] The device patrols the environment, acquiring images and sounds of its surroundings using its camera and sensors. The input is information about the surrounding environment, which is output as digital data. Specifically, it captures video with the camera and detects sound waves and vibrations with the sensors.

[0639] Step 2:

[0640] The terminal transmits the acquired digital data to the server. The input is the digital data generated in step 1, and the output is obtained by sending it to the server via network communication. Specifically, data transmission is performed using communication methods such as Wi-Fi or LTE.

[0641] Step 3:

[0642] The server analyzes the data it receives. The input is the digital data sent in step 2, which is then subjected to image analysis processing using an AI model to obtain output. Specifically, it utilizes generative AI models such as TensorFlow to perform image analysis to identify suspicious individuals and abnormal behavior. Instructions for the analysis algorithm are also given simultaneously using prompt messages.

[0643] Step 4:

[0644] The server generates an alert based on the analysis results. The input is the analysis results obtained in step 3. Based on these analysis results, it determines if an anomaly has occurred, generates an alert message, and sends it to the user device in real time. Specifically, it uses a notification system to send a push notification to an external device such as a smartphone.

[0645] Step 5:

[0646] Based on the alert notification received by the user, a dedicated app is launched to view real-time video. The input is the alert notification from the server, and the output is the display of the corresponding video stream in the app based on this. Specifically, live video is streamed on the interface to provide the user with visual information.

[0647] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0648] As a specific embodiment of the present invention, the security robot system is equipped with a means of movement, an image acquisition means, an image analysis means, a notification means, a recording means, and a sensor means, in addition to an emotion engine. This allows the system to provide a function that recognizes and responds to the user's emotions, in addition to normal security functions.

[0649] The device autonomously moves along a pre-configured patrol route, using its camera to acquire visual data from the environment and collecting data from sound and motion sensors. This data is then transmitted from the device to a server.

[0650] The server analyzes image data and sensor data in real time. The image analysis system uses AI technology to identify and record suspicious individuals and unusual situations. If an anomaly is detected, the server also sends alerts to the management company and residents via notification systems.

[0651] The emotion engine acquires facial and voice data through the user's smartphone app camera and analyzes the user's emotional state. For example, if the emotion engine detects anxiety or fear in the user, the server prioritizes the alert and provides a prompt notification. In addition, the user's emotional data is recorded, allowing the user to analyze their own emotional tendencies based on their system usage.

[0652] For example, if a user at home at night detects the approach of a suspicious person, the device identifies this using image data and sensor data and reports it to the server. Simultaneously, an emotion engine analyzes the user's facial expressions and voice to detect emotions such as anxiety and tension. Based on this information, the server can send enhanced alerts to residents and management companies, prompting a quick response. This system provides a comprehensive security environment that considers the user's psychological well-being in addition to standard security functions.

[0653] The following describes the processing flow.

[0654] Step 1:

[0655] The device moves along a predetermined patrol route, using its camera to acquire images of its surroundings. Simultaneously, it collects data from the environment using sound and motion sensors.

[0656] Step 2:

[0657] The device transmits collected image data and sensor data to the server. The data is transmitted in real time using wireless communication.

[0658] Step 3:

[0659] The server uses AI technology to analyze the received image data and identify suspicious individuals or unusual situations. The detected anomaly information is stored by recording devices.

[0660] Step 4:

[0661] The server uses an emotion engine to acquire the user's facial expressions and voice data through the smartphone app, and then analyzes the user's emotional state.

[0662] Step 5:

[0663] The emotion engine analyzes the user's emotions, and if it detects anxiety or fear, the server adjusts the alert priority. Based on the priority, it sends appropriate alerts to the management company and the user using notification methods.

[0664] Step 6:

[0665] Users receive alerts via a smartphone app and check the situation. If necessary, users can take action, such as contacting the police or administrators.

[0666] Step 7:

[0667] The server records user emotion data and detected anomaly data, and stores it in a format that can be analyzed later. This allows users to analyze their own emotional tendencies and use that information to consider further security measures.

[0668] (Example 2)

[0669] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0670] Conventional security systems, while capable of detecting anomalies in the environment, struggled to respond in a way that considered the user's psychological state, failing to provide users with a sense of psychological security. Furthermore, insufficient means of data collection while on the move and inadequate real-time anomaly notifications meant that delays could occur in situations requiring a rapid response.

[0671] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0672] In this invention, the server includes means for acquiring visual data, means for analyzing data, means for notifying information, means for analyzing emotions, and means for storing information. This makes it possible to grasp the user's emotional state in real time and respond more quickly and appropriately.

[0673] A "visual data acquisition means" is a device that has the function of capturing and acquiring surrounding video and images.

[0674] "Data analysis means" refers to a function that analyzes acquired visual data and sensor data to detect anomalies or specific situations.

[0675] An "information notification means" is a function that sends alerts or notifications to relevant parties when an anomaly is detected.

[0676] "Emotional analysis tools" are functions that analyze a user's facial expressions and voice data to identify their psychological state.

[0677] "Information storage means" refers to a function that records detected anomaly information and user sentiment data, making them accessible later.

[0678] "Spatial movement means" refers to a function that allows a system or device to autonomously move along a predetermined route and collect data over a wide area.

[0679] "Environmental sensor means" refers to a function that uses sensors to detect ambient sounds and movements, and to detect abnormalities when they occur.

[0680] The security system in this invention is composed of multiple means and, in particular, has a function to provide users with a sense of psychological security. This system is mainly divided into two main components: a "terminal" and a "server".

[0681] The terminal is the primary device for collecting ambient environmental data. Specifically, it incorporates a camera as a means of acquiring visual data, continuously capturing images of the environment. Furthermore, a spatial movement mechanism is used for the terminal to autonomously patrol a pre-set route, enabling environmental data collection while moving. The terminal also incorporates environmental sensors, allowing it to detect sound and movement. This enables the terminal to detect environmental anomalies at an early stage.

[0682] The server receives and analyzes visual and sensor data transmitted from terminals. Using AI technology for data analysis, it identifies abnormal individuals and situations within images. Furthermore, it can analyze facial expressions and voice data transmitted from the user's smartphone app using emotion analysis tools to understand the user's emotional state. Based on this information, the server immediately sends alerts to relevant parties using information notification tools when an anomaly is detected. These alerts are sent via email or a dedicated app to encourage prompt action.

[0683] The recorded data can be accessed by the user later through information storage means and used for purposes such as analyzing emotional trends. For example, if a suspicious person approaches at night, the terminal can detect this, and the server can immediately send a notification, enabling a rapid response.

[0684] An example of a prompt message is, "Explain how to send an alert when a suspicious person is detected, and provide an example of a response based on the user's emotion recognition." This illustrates how the system provides a comprehensive safety environment.

[0685] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0686] Step 1:

[0687] The device collects environmental data while moving along a pre-set patrol route. It receives spatial visual data and sensor data for sound and motion as input. Specifically, it captures video with its built-in camera and detects sounds and movement in the environment with its sensors. All of this data is acquired in real time, enabling early detection of anomalies. The collected visual and sensor data are generated as output.

[0688] Step 2:

[0689] The device sends the collected data to the server. The inputs are the visual and sensor data obtained in step 1. The data is sent to the server using an appropriate communication protocol. Specific operations include transferring data via Wi-Fi or a wired network. The output is the data received by the server.

[0690] Step 3:

[0691] The server analyzes the received visual and sensor data in real time. The input is the data transmitted in step 2. AI technology is used as the data analysis method to identify abnormal people or situations from the image data. Abnormal sounds and movements are also detected from the sensor data. Specifically, an image processing algorithm is executed to determine the abnormality. The output is a result of whether an abnormality was identified, and alert information is generated based on that result.

[0692] Step 4:

[0693] The server issues an alert using an information notification system when an anomaly is detected. The input is the alert information generated in step 3. Specifically, it sends notifications to administrators and residents via email or a dedicated app. The output is information that the alert has reached the relevant parties and prompts them to take prompt action.

[0694] Step 5:

[0695] The user collects emotional data using a smartphone app and sends it to a server. The input consists of the user's facial expression data and voice data. Specifically, the app uses the smartphone's camera and microphone to capture facial expressions and voice, and sends this data to the server. The output is the user's emotional data.

[0696] Step 6:

[0697] The server analyzes the received emotional data to identify the user's psychological state. The input is the emotional data sent in step 5. Using an emotional analysis tool, it determines the user's emotional state. Specifically, it executes a facial recognition algorithm to analyze whether the user is feeling anxiety or fear. The output is the emotional state as a result of the analysis, and the alert priority is adjusted as needed.

[0698] Step 7:

[0699] The server stores the analyzed anomaly information and sentiment data using recording devices. The input is the analysis results obtained in steps 3 and 6. Specifically, the information is recorded in a database and made accessible later. The output is the stored information, which the user can use to analyze their own sentiment tendencies.

[0700] (Application Example 2)

[0701] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0702] In modern society, there is a need to quickly and accurately detect suspicious individuals and unusual situations, while ensuring the psychological safety of users. However, conventional security systems only detect physical anomalies and lack consideration for the emotional state of the user. As a result, even when using security systems, users may not be able to completely eliminate their anxiety and fear.

[0703] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0704] In this invention, the server includes an image acquisition means for detecting the situation in the environment, an image analysis means for analyzing the acquired image data to identify suspicious persons, and an emotion analysis means for analyzing the user's emotional state and adjusting the priority of alerts based on those emotions. This makes it possible to accurately identify suspicious persons and anomalies while responding to and issuing warnings in accordance with the user's emotions.

[0705] "Image acquisition means" refers to a function that collects visual information from the environment using cameras or other visual sensors.

[0706] "Image analysis means" refers to techniques for analyzing acquired image data to identify suspicious individuals or unusual situations, and often utilizes AI technology.

[0707] A "notification system" is a system that informs users and administrators of detected anomalies or important information, and has the function of sending alerts and messages.

[0708] A "recording system" is a data storage mechanism that saves detected information so that it can be reviewed and analyzed later.

[0709] "Emotional analysis methods" are technologies that analyze a user's emotional state and determine their emotions based on data such as facial expressions and tone of voice.

[0710] "Means of transportation" refers to a method by which a system autonomously moves within a designated area while collecting data, and may use wheels or propellers.

[0711] "Sensor means" refers to devices for detecting abnormal sounds or movements, and includes acoustic sensors and motion sensors.

[0712] In order to implement this invention, the entire system must operate in a coordinated manner. The system mainly consists of three elements: a server, a terminal, and a user.

[0713] The server plays a central role in analyzing the environment in real time. Specifically, it collects image data and sentiment data acquired by terminals and analyzes them using image analysis software (e.g., OpenCV) and sentiment analysis software (e.g., IBM Watson Tone Analyzer). This makes it possible to identify suspicious individuals and abnormal situations, as well as understand the emotional state of users.

[0714] The device moves autonomously along a pre-set patrol route, acquiring data from the environment using cameras and sensors. The acquired data is immediately sent to a server for analysis. Robots using wheels or propellers are suitable for movement.

[0715] Users interface with this system using smart glasses or other mobile devices. Emotion analysis tools analyze the user's emotions in real time, and if an abnormality or danger is detected, an alert is immediately displayed to the user. This helps to support a sense of psychological security.

[0716] As a concrete example, consider a user walking down a quiet street at night using smart glasses to monitor their surroundings. A sensor detects a suspicious noise from behind, and the server analyzes it. Furthermore, if an expression of anxiety is detected on the user's face, an advanced warning is displayed on the glasses, and a notification is sent to nearby security personnel. An example of a prompt message might be, "Please initiate the process of identifying a suspicious person and detecting an expression of anxiety from the audio data, and then intensify the alert and notify security."

[0717] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0718] Step 1:

[0719] The device collects visual data from the environment using image acquisition means. The device's built-in camera captures the surrounding video and transmits this video data to the server in real time. In this process, the input is visual information of the environment, and the output is image data to be processed on the server side.

[0720] Step 2:

[0721] The server analyzes the transmitted image data using image analysis tools. It performs image modeling and comparison processing via OpenCV to identify suspicious individuals, unusual objects, and movements. At this stage, the input is image data sent from the terminal, and the output is the identification results for suspicious individuals, etc.

[0722] Step 3:

[0723] The terminal collects sound and motion data using sensor devices. The sound sensor and motion sensor acquire information from the surroundings, and this data is transmitted to the server. The input is sound and motion information from the surrounding environment, and the output is sensor data that is further analyzed on the server.

[0724] Step 4:

[0725] The server uses emotion analysis tools to analyze the user's emotional state. Here, facial and audio data sent from the user's smart glasses are processed, and AI technology is used to identify emotional states such as anxiety and fear. At this stage, the input is facial and audio data from the glasses, and the output is the analysis result of the user's emotional state.

[0726] Step 5:

[0727] The server uses various notification methods based on the analysis results to quickly issue alerts. If a suspicious person is identified or user anxiety is detected, the server displays a warning on the user's smart glasses and notifies administrators or security personnel as needed. The input is the analysis results of images and emotions, and the output is the alert content and identification of the recipient.

[0728] Step 6:

[0729] The server utilizes recording mechanisms to meticulously record each piece of detected information. Image data, suspicious person identification, sensor data, emotional state, and other information are stored in a database for later reference. The input consists of all analysis results, and the output consists of data managed as records.

[0730] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0731] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0732] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0733] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0734] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0735] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0736] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0737] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0738] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0739] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0740] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0741] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0742] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0743] 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.

[0744] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0745] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0746] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0747] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0748] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0749] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0750] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0751] The following is further disclosed regarding the embodiments described above.

[0752] (Claim 1)

[0753] An image acquisition means for detecting conditions in the environment,

[0754] Image analysis means for analyzing acquired image data to identify suspicious persons,

[0755] A notification system that generates and notifies alerts when an anomaly is detected,

[0756] A recording means for storing the detected information,

[0757] A system that includes this.

[0758] (Claim 2)

[0759] The system according to claim 1, further comprising means for collecting environmental data while in motion.

[0760] (Claim 3)

[0761] The system according to claim 1, further comprising sensor means for detecting abnormal sounds or movements.

[0762] "Example 1"

[0763] (Claim 1)

[0764] A visual sensor means for acquiring image information,

[0765] A sensing means for detecting sound and movement,

[0766] Information processing means for analyzing acquired data to identify the characteristics of a person,

[0767] A communication means that generates and transmits an alarm when an anomaly is detected,

[0768] A storage means for storing the detected data,

[0769] A system that includes this.

[0770] (Claim 2)

[0771] The system according to claim 1, further comprising means for autonomously moving within a designated area to collect information.

[0772] (Claim 3)

[0773] The system according to claim 1, further comprising network means for notifying users in remote locations via a communication network.

[0774] "Application Example 1"

[0775] (Claim 1)

[0776] An image acquisition means for detecting conditions in the environment,

[0777] Image analysis means for analyzing acquired image data to identify suspicious persons,

[0778] A notification means that generates an alert when an anomaly is detected and notifies an external device via a communication device,

[0779] A recording means for storing the detected information,

[0780] A means of transmitting video in real time through communication with an external device,

[0781] A system that includes this.

[0782] (Claim 2)

[0783] The system according to claim 1, further comprising means for moving to collect data while moving and for transmitting real-time video to an external device.

[0784] (Claim 3)

[0785] The system according to claim 1, further comprising sensor means for detecting abnormal sounds or movements and transmitting data to an external device.

[0786] "Example 2 of combining an emotion engine"

[0787] (Claim 1)

[0788] A means for acquiring visual data to obtain image data,

[0789] A data analysis means for analyzing acquired visual data and sensor data to identify anomalies,

[0790] An information notification system that generates an alert when an anomaly is detected and notifies relevant parties,

[0791] A means of analyzing the emotional state of a user,

[0792] Information storage means for storing detected information and user sentiment data,

[0793] A system that includes this.

[0794] (Claim 2)

[0795] The system according to claim 1, further comprising a spatial movement means for collecting environmental data while in motion.

[0796] (Claim 3)

[0797] The system according to claim 1, further comprising environmental sensor means for detecting abnormal sounds or movements.

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

[0799] (Claim 1)

[0800] An image acquisition means for detecting conditions in the environment,

[0801] Image analysis means for analyzing acquired image data to identify suspicious persons,

[0802] A notification system that generates and notifies alerts when an anomaly is detected,

[0803] A recording means for storing the detected information,

[0804] An emotion analysis means that analyzes the user's emotional state and adjusts the priority of alerts based on that emotion,

[0805] A system that includes this.

[0806] (Claim 2)

[0807] The system according to claim 1, further comprising means of transport for collecting environmental data while in motion, and which modifies the content of warnings according to the results of the user's emotion analysis.

[0808] (Claim 3)

[0809] The system according to claim 1, further comprising sensor means for detecting abnormal sounds or movements, integrating the detected phenomenon with emotion analysis results to prompt an appropriate response. [Explanation of Symbols]

[0810] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An image acquisition means for detecting conditions in the environment, Image analysis means for analyzing acquired image data to identify suspicious persons, A notification system that generates and notifies alerts when an anomaly is detected, A recording means for storing the detected information, A system that includes this.

2. The system according to claim 1, further comprising means for collecting environmental data while in motion.

3. The system according to claim 1, further comprising sensor means for detecting abnormal sounds or movements.

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