system

Abstract

We provide the system. [Solution] A means for processing video data acquired from one or more cameras installed in the park by an acquisition means, A means for analyzing the video data using video analysis means to identify the movement or behavioral patterns of a person and to detect suspicious behavior, A means for sending a warning to the administrator or user terminal via a notification means when an anomaly is detected, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In modern society, in public places such as parks, ensuring the safety of children is an important issue. However, it is not realistic for guardians or relevant parties to monitor the site 24 hours a day, and a system that can efficiently and effectively detect suspicious persons and dangerous behaviors is required. In addition, it is necessary to quickly respond to problems such as children getting lost and potential dangers due to environmental changes. 【Means for Solving the Problems】 【0005】 The present invention provides a means for processing video data acquired from one or more cameras installed in a park by an acquisition means. Furthermore, it includes a means for analyzing the video data by an image analysis means to identify the movement or behavioral patterns of people and to detect suspicious behavior. In addition, if an anomaly is detected, a notification means sends a warning to the administrator or user terminal, enabling a rapid response. Moreover, by providing a means for identifying and tracking the current location of children in the park by a location information acquisition means, it facilitates the discovery of lost children, and by detecting surrounding weather data and equipment status by an environmental monitoring means and issuing a warning when dangerous conditions occur, safety is further enhanced. 【0006】 "Acquisition means" refers to a device or method that has the function of collecting video data from a camera installed in the park. 【0007】 "Video analysis means" refers to a device or method that has the function of analyzing acquired video data and identifying the movements and behavioral patterns of people shown therein. 【0008】 "Notification means" refers to a device or method that has the function of sending a warning to the administrator's or user's terminal when an anomaly is detected. 【0009】 "Location information acquisition means" refers to a device or method that has the function of identifying the current location of a child within a park and managing that information. 【0010】 "Environmental monitoring means" refers to a device or method that has the function of detecting surrounding weather data and equipment status, and is used to quickly identify dangerous conditions. [Brief explanation of the drawing] 【0011】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0012】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0013】 First, let's explain the terminology used in the following explanation. 【0014】 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. 【0015】 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. 【0016】 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, etc. 【0017】 In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc. 【0018】 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." 【0019】 [First Embodiment] 【0020】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0021】 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. 【0022】 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). 【0023】 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. 【0024】 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. 【0025】 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. 【0026】 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. 【0027】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0028】 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. 【0029】 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. 【0030】 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. 【0031】 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". 【0032】 This invention relates to a system for protecting the safety of children in parks, and aims to improve park safety by providing an acquisition means, a video analysis means, a notification means, a location information acquisition means, and an environmental monitoring means as embodiments of the system. 【0033】 First, let's explain the acquisition method. The terminal acquires video data in real time from one or more cameras installed within the park. This video data is used to clearly monitor various areas within the park. 【0034】 Next is the video analysis method. The server analyzes the acquired video data and uses an AI module to evaluate the movements and behavioral patterns of people. This evaluation makes it possible to immediately detect the presence of suspicious individuals or dangerous behavior. 【0035】 If abnormal behavior is detected, a notification system is activated. The server generates an alert and sends its contents to the administrator's and park users' devices. This allows for a swift response. 【0036】 The location acquisition method is designed with user experience in mind. It can accurately track a child's current location using location information from the user's mobile device or a dedicated device. This feature is particularly useful when trying to find a lost child. 【0037】 Furthermore, environmental monitoring devices can be used to continuously monitor the weather and the condition of the playground equipment. The weather data obtained from the terminals and the usage status of the playground equipment are analyzed on the server, and if a danger is detected, an appropriate warning is sent again to the relevant parties. 【0038】 As a concrete example, suppose a camera captures a child approaching a suspicious person in a park one day. The server immediately analyzes the footage and, upon confirming that it matches the suspicious person's behavior pattern, sends a notification to the administrator and nearby parent users. This rapid warning allows administrators to rush to the scene and ensure safety. The system is also utilized in response to sudden weather changes; for example, in the event of a sudden thunderstorm, it sends a notification to restrict the use of playground equipment, playing a role in protecting the safety of users. 【0039】 As described above, this system is designed to constantly monitor safety within the park and enable appropriate responses by combining these means. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 The terminal acquires video data in real time from a camera installed in the park. The acquired data is transmitted to a server via the network. 【0043】 Step 2: 【0044】 The server receives the acquired video data and preprocesses it into an analyzable format. This includes noise reduction and resolution adjustment to prepare the data for efficient analysis. 【0045】 Step 3: 【0046】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to extract people's movements and behavioral patterns, and to determine whether or not suspicious behavior is present. 【0047】 Step 4: 【0048】 The server reviews the analysis results, and if abnormal behavior is detected, it immediately sends a warning to the administrator's or park user's device using a notification system. 【0049】 Step 5: 【0050】 Users track their children's location through a dedicated application. The device obtains location information from the user's device and sends it to the server. 【0051】 Step 6: 【0052】 The server analyzes location information to pinpoint the child's current location. In the case of a lost child, camera footage and location information are used in combination to efficiently locate the child. 【0053】 Step 7: 【0054】 The device continuously collects data about the surrounding environment, such as weather and the condition of playground equipment. 【0055】 Step 8: 【0056】 The server analyzes environmental data, and if an anomaly is detected, it sends a warning to the user about changes in weather or dangers related to playground equipment, prompting them to take safety precautions. 【0057】 (Example 1) 【0058】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0059】 To ensure safety within a region, it is necessary to quickly identify suspicious behavior by individuals in designated areas and dangerous environmental conditions, and to immediately warn relevant parties. In particular, there is a need for an efficient and accurate system that can pinpoint locations in real time and respond to environmental changes. 【0060】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0061】 In this invention, the server includes means for collecting visual data obtained from one or more image acquisition devices placed within the area using acquisition means, means for processing the visual data using image analysis means to evaluate the movements and behavioral patterns of the object to be identified and to identify irregular behavior, and means for transmitting a warning to a manager or user's information terminal using notification means when irregular behavior is detected. This makes it possible to monitor safety within the area quickly and accurately. 【0062】 "Acquisition means" refers to means that have the function of collecting visual data from image acquisition devices placed within a region. 【0063】 "Image analysis means" refers to means that process acquired visual data and have the function of evaluating the actions and behavioral patterns of the object to be identified. 【0064】 "Irregular behavior" refers to actions that deviate from typical activity patterns and is a term used to indicate behaviors that require special attention from the system. 【0065】 A "notification means" is a means that has the function of transmitting warnings about detected irregular behavior or dangerous conditions to the administrator's or user's information terminal. 【0066】 A "location identification means" is a means that has the function of identifying a person's current location and tracking their movements in real time. 【0067】 "Surrounding monitoring means" refers to means that have the function of identifying surrounding weather information and the status of equipment, and issuing a warning if a potential danger occurs. 【0068】 This system is designed to enhance safety in parks and similar public areas, providing peace of mind to users. The following describes specific implementations of the invention. 【0069】 The terminal first acquires visual data in real time from one or more image acquisition devices installed within the area, such as high-resolution cameras. This data undergoes initial processing within the terminal and is then sent to the server. 【0070】 The server uses advanced image analysis software to analyze the received visual data. Specifically, an AI module is launched on hardware equipped with a high-speed processor for running generative AI models. This AI module has the ability to evaluate human movements and behavioral patterns and instantly identify irregular behavior. 【0071】 If irregular behavior is detected, the server immediately generates a warning via a notification system and transmits it to the relevant parties. This notification quickly and clearly informs administrators and users of the situation on their mobile devices. Users' devices are equipped with location-based apps and periodically send their current location information to the server, allowing for real-time tracking of the movements of children and other users. 【0072】 Furthermore, the terminal uses surrounding monitoring means to acquire weather information and device status through installed environmental sensors. The server analyzes this information and has the function to issue another warning if it detects dangerous weather conditions or device malfunctions. 【0073】 For example, if a sudden thunderstorm is predicted, the terminal will analyze weather data obtained from sensors on a server, and if it determines that a thunderstorm is approaching, it will issue a warning to park managers and users urging them to quickly ensure their safety. 【0074】 Examples of prompts include, "What AI module would be appropriate to improve park safety?" This enables the concrete and effective implementation of a safety monitoring system. 【0075】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0076】 Step 1: 【0077】 The terminal acquires visual data in real time from high-resolution cameras placed throughout the park. The input is video footage directly from the cameras, which is initially processed digitally before being sent to the server as a dataset for appropriate analysis. Specifically, this process includes noise reduction and frame rate standardization. 【0078】 Step 2: 【0079】 The server inputs visual data sent from the terminal into the AI ​​module and begins analysis using a generative AI model. The visual data provided as input is processed by a data processing algorithm to detect human movement and behavioral patterns. The output consists of detection results for irregular behavior and specific movement patterns, which are organized into a list. Specific actions include anomaly detection using deep learning techniques. 【0080】 Step 3: 【0081】 The server generates warnings via notification mechanisms based on anomaly detection results obtained through AI analysis. It uses behavior detection results as input, analyzing them to identify suspicious behavior. The output is a warning message, which is sent to the administrator's or user's information terminal. Specific actions include rapid message delivery via email or SMS. 【0082】 Step 4: 【0083】 Users collect their own and their children's location information in real time using a location-based app on their device. The input is location data from a GPS sensor, which is periodically updated and sent to the server. The output is organized on the server as current location information and stored in a tracking database. Specific operations include periodic location information updates and accuracy checks. 【0084】 Step 5: 【0085】 The terminal collects weather data and device status from surrounding monitoring devices and sends it to a server for analysis. Inputs are time-series data from temperature sensors and anemometers, and outputs are warning indicators based on risk analysis. This allows for a rapid response in the event of sudden weather changes or device malfunctions. Specifically, it determines the conditions for alarm activation and notifies relevant parties as needed. 【0086】 (Application Example 1) 【0087】 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." 【0088】 In public spaces, it is necessary to enhance safety by monitoring diverse data in real time, including activity dynamics and weather conditions. However, current systems have limited ability to respond quickly to individual situations, and immediate action is required against factors that threaten safety. 【0089】 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. 【0090】 In this invention, the server includes means for processing image data acquired from one or more imaging devices installed in a public space by acquisition means; means for analyzing the image data by image analysis means to identify the dynamics or behavioral patterns of activity and to detect abnormal behavior; means for sending notifications to relevant parties or user terminals by notification means when an abnormality is detected; means for identifying and tracking the current location of individual users within the park by location information acquisition means; and means for detecting surrounding weather data and the status of facilities by environmental monitoring means and issuing warnings when dangerous conditions occur. This enables real-time monitoring of safety in public spaces and rapid response. 【0091】 "Acquisition means" refers to a device or method that has the function of acquiring image data from one or more imaging devices installed in a public space. 【0092】 "Image analysis means" refers to a function or process for detecting suspicious behavior by analyzing acquired image data to identify the dynamics and behavioral patterns of activity. 【0093】 "Notification means" refers to technology or equipment for sending notifications to relevant parties or user terminals when an anomaly is detected. 【0094】 "Location information acquisition means" refers to a technology or method for identifying and tracking the current location of individual users within a park. 【0095】 "Environmental monitoring means" refers to technology or devices that have the function of detecting ambient weather data and the condition of equipment, and issuing warnings when dangerous conditions occur. 【0096】 A "generative AI model" is an artificial intelligence technology that generates prompt messages as recommended countermeasures for stakeholders based on analysis results. 【0097】 A "prompt message" is a sentence output by a generative AI model that contains instructions or suggestions to encourage appropriate action from stakeholders. 【0098】 The system for realizing this invention is designed to improve safety in public spaces. The system consists of multiple components and is implemented with the following elements: 【0099】 The server collects image data in real time from image acquisition devices installed in public spaces. These devices consist of multiple cameras that cover a wide area. The server inputs the collected image data into an image analysis module to analyze the dynamics of activities and behaviors. Image recognition software such as OpenCV and YOLOv5 is used for this analysis. This makes it possible to smoothly identify abnormal behavior and suspicious individuals. 【0100】 If abnormal behavior is detected, a notification module sends an alert to relevant parties and user devices. By using services like Firebase Cloud Messaging to send notifications, rapid and efficient information distribution is achieved. 【0101】 Furthermore, the server has a location information acquisition function that accurately tracks the location of users within public spaces. This function utilizes the Google® Maps API to understand the movement patterns of individual users in detail. This enables a rapid response, especially to problems such as lost children. 【0102】 Furthermore, the system monitors surrounding weather data and equipment status through its environmental monitoring function. This information is collected from environmental sensors and analyzed on a server. It also has a function to automatically issue warnings to users in the event of sudden changes in weather conditions or when dangerous situations are predicted. 【0103】 Furthermore, by utilizing a generative AI model, prompt messages containing appropriate countermeasures and advice are created based on the analysis results and provided to relevant parties. For example, the analysis can generate a prompt message stating, "A suspicious person has been observed on the west side of the park. Surrounding area managers should take immediate action," and send it to relevant parties immediately. 【0104】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0105】 Step 1: 【0106】 The server receives image data in real time from image acquisition devices installed in public spaces. These images are captured by cameras and transmitted to the server as image data. The acquired image data is then used for subsequent analysis processes. 【0107】 Step 2: 【0108】 The server inputs the received image data into an image analysis module to analyze the dynamics of activity and behavior within the image. This analysis uses image recognition software such as OpenCV or YOLOv5. The input here is image data, and the output is the detection results of identified dynamics and abnormal behavior. The server identifies the analysis results and proceeds to the next stage. 【0109】 Step 3: 【0110】 The server generates information for sending notifications when abnormal behavior is detected through analysis. It uses the Firebase Cloud Messaging service to create notification data for sending warnings and information to relevant parties and user devices. The input here is information about the abnormal behavior identified through analysis, and the output is the generated notification message. 【0111】 Step 4: 【0112】 The server uses location information acquisition functionality to determine the user's current location within a public space. It uses the Google Maps API to collect the user's location information and stores it on the server. The input is the user's location coordinates, and the output is a record of the location information. 【0113】 Step 5: 【0114】 The server uses environmental monitoring functions to detect ambient weather data and equipment status. It analyzes data obtained from environmental sensors to evaluate weather conditions and equipment status. The input here is data from environmental sensors, and the output is the analyzed environmental status. 【0115】 Step 6: 【0116】 The server utilizes a generative AI model to generate prompt messages based on analysis results and the current situation. The input consists of various collected analysis data, and the output is a prompt message intended for stakeholders. This prompt message specifically instructs stakeholders on the appropriate course of action. 【0117】 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. 【0118】 This invention is a system for highly protecting the safety of children in public spaces such as parks, and by incorporating acquisition means, video analysis means, notification means, location information acquisition means, environmental monitoring means, and emotion engine, it realizes an environment in which children can play with greater peace of mind. 【0119】 First, let's explain the data acquisition method. The terminal uses cameras installed in the park to collect video data in real time and transmit it to the server. This video data serves as basic information for comprehensively monitoring various situations within the park. 【0120】 Next, the server processes this video data using video analysis tools. The analysis primarily utilizes AI modules to identify the movements and behavioral patterns of individuals, and to detect suspicious behavior. If suspicious behavior is detected, a notification system is activated, immediately sending a warning to administrators and users. 【0121】 Furthermore, an emotion engine will be introduced as a new addition to this system. This emotion engine is implemented on the server and analyzes people's facial expressions and actions from video data to recognize their emotional state. For example, if a child is crying or has an angry expression, the system will recognize that emotional state and, if necessary, generate additional alerts or countermeasures. 【0122】 Furthermore, the location information acquisition method identifies the child's current location through the user's mobile device or specific device and provides that information to administrators or guardians as needed. This function makes the search for lost children particularly more efficient. 【0123】 Environmental monitoring devices are used to monitor surrounding weather changes and the condition of playground equipment. The server analyzes this data and issues appropriate warnings to park users if a hazard is detected. 【0124】 As a concrete example, suppose the server detects through video analysis that a child is playing inappropriately on playground equipment, and the emotion engine detects from the child's facial expression that they are feeling anxious. In this case, the server immediately notifies the user of the situation via the terminal and urges them to take prompt action. Also, if environmental monitoring measures detect that a thunderstorm is approaching, the server will issue a warning to restrict the use of playground equipment, playing a role in ensuring the safety of users. 【0125】 In this way, the system is designed to implement a high level of safety and security for children within the park by combining various means. 【0126】 The following describes the processing flow. 【0127】 Step 1: 【0128】 The terminal acquires video data in real time from multiple cameras installed in the park. The acquired video data is transmitted to a server via the network. 【0129】 Step 2: 【0130】 The server preprocesses the video data it receives. Preprocessing involves noise removal and resolution adjustment to prepare the data for accurate analysis. 【0131】 Step 3: 【0132】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to identify people's movements and behavioral patterns, and to detect suspicious behavior. 【0133】 Step 4: 【0134】 The emotion engine analyzes a person's facial expressions and gestures from video data to recognize their emotional state. If the emotional change is significant, that information is used to guide the next step. 【0135】 Step 5: 【0136】 If the server detects abnormal behavior or significant emotional states through analysis, it will use notification mechanisms to send warnings to administrators and park users' devices. 【0137】 Step 6: 【0138】 This system allows users to check their child's location on their mobile device. The device periodically acquires location information and sends it to the server, providing the user with real-time information. 【0139】 Step 7: 【0140】 The server tracks the child's current location based on location data and provides supplementary information to help find the lost child. If necessary, it can be linked with camera data to determine the exact location. 【0141】 Step 8: 【0142】 The device acquires environmental data for the park and its surroundings. This primarily involves recording weather conditions and any abnormalities in playground equipment. 【0143】 Step 9: 【0144】 The server analyzes environmental data it acquires and sends a warning to the user if it detects dangerous weather conditions or the state of playground equipment. This allows the user to take appropriate safety measures. 【0145】 Step 10: 【0146】 The server saves all recorded data as logs, which can be used for review and training as needed. 【0147】 (Example 2) 【0148】 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 will be referred to as the "terminal." 【0149】 Improving safety in public spaces is particularly important in facilities frequently used by children. However, conventional systems primarily rely on human visual monitoring and simple sensors, making it difficult to immediately detect and notify of suspicious behavior or changes in emotions. Furthermore, rapid responses to location information and sudden environmental changes were insufficient. As a result, improving safety and a sense of security within these facilities remained a challenge. 【0150】 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. 【0151】 In this invention, the server includes means for processing data acquired from one or more imaging devices installed in public facilities by acquisition means, means for analyzing the data by video analysis means to identify dynamic or behavioral patterns and detect suspicious behavior, and means for analyzing a person's facial expressions or movements by emotion engine and recognizing their emotional state. This enables the rapid detection of suspicious behavior or changes in emotional state in public facilities and the immediate notification of necessary warnings, thereby improving safety and providing a sense of security to users. 【0152】 "Acquisition means" refers to means for collecting and processing video data in real time from one or more imaging devices installed in a public facility. 【0153】 "Video analysis means" refers to means that have the ability to analyze acquired video data and identify dynamics or behavioral patterns. 【0154】 "Means for detecting suspicious behavior" refers to methods for identifying suspicious behavior and prompting caution based on dynamic or behavioral patterns identified through video analysis. 【0155】 An "emotion engine" is a method for recognizing a person's emotional state by analyzing their facial expressions and movements from video data. 【0156】 A "notification mechanism" is a means of sending a warning to an administrator or user when an abnormal or specific emotional state is detected. 【0157】 "Location information acquisition means" refers to a means of identifying the current location of a subject within a public facility and providing that information. 【0158】 "Environmental monitoring means" refers to measures for monitoring surrounding weather data and equipment conditions, and for issuing appropriate warnings when dangerous conditions occur. 【0159】 This invention is a system for improving safety in public facilities and is implemented by combining multiple functional modules. Specifically, it achieves real-time monitoring and notification through cooperation between a server, terminals, and users. 【0160】 The terminal is responsible for collecting video data using multiple cameras installed within the facility. These cameras are standard surveillance cameras capable of capturing high resolution and wide areas. This data is transmitted to the server in real time. 【0161】 The server uses an AI module as a video analysis tool to analyze the acquired video data. The AI ​​module utilizes deep learning technology to identify movement and behavioral patterns from the captured video and detect suspicious behavior. If necessary, an emotion engine analyzes the person's facial expressions and movements to recognize their emotional state. For example, if a child is using playground equipment in a dangerous manner, or if emotional changes such as crying are detected, these are recognized as suspicious behaviors. 【0162】 Using location information acquisition methods, it is possible to obtain a child's location information from the user's mobile device or specific device. This information is processed by a server and provided to administrators or guardians when needed. This makes the search for lost children more efficient. 【0163】 Furthermore, environmental monitoring devices allow the terminal to monitor surrounding weather changes and the condition of the equipment. Through this function, if a sudden change in weather occurs or if the playground equipment is found to be unsafe, it will issue a warning to alert the user. This ensures the safety of users. 【0164】 As an example of how to use this system, one could input the prompt "Please tell me how to assess the safety situation of children in the park and notify me of suspicious behavior or emotional states" into the generating AI model. This would allow us to verify how to operate the system effectively. 【0165】 Thus, the objective of this invention is to enhance safety within public facilities and provide an environment where people can use them with peace of mind, by having each of these means work together. 【0166】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0167】 Step 1: 【0168】 The terminal acquires video data in real time from cameras installed within public facilities. The acquired data is first compressed and then sent to the server. The input here is the video from the camera, and the output is the compressed video data. 【0169】 Step 2: 【0170】 The server decompresses the received compressed video data and inputs it into an AI module. This module uses deep learning algorithms to analyze the dynamics and behavioral patterns within the video. Suspicious behavior and unusual movements are identified through data calculations. The input is the decompressed video data, and the output is suspicious behavior and specific behavioral patterns. 【0171】 Step 3: 【0172】 The server then uses an emotion engine to analyze a person's facial expressions and body movements from the same video data and evaluate their emotional state. For example, it might detect if a child is crying. The input is the video data, and the output is the detected emotional state. 【0173】 Step 4: 【0174】 When suspicious behavior or a specific emotional state is detected, the server activates a notification system. This sends a warning message to the administrator's or user's mobile device via the terminal. The input is information about the suspicious behavior or emotional state, and the output is the sent warning message. 【0175】 Step 5: 【0176】 The location information acquisition method obtains the child's current location from the user's device. The server integrates this location data into a map application and provides it to the user as visualized information. The input is location information from the device, and the output is a map displaying the location information. 【0177】 Step 6: 【0178】 The terminal continuously monitors weather data and equipment status through environmental monitoring devices. The server analyzes this data and, if it detects a dangerous situation, such as a sudden change in weather, issues a warning to the user. The input is weather data and equipment status information, and the output is the issued warning. 【0179】 (Application Example 2) 【0180】 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". 【0181】 In recent years, ensuring safety in public spaces has become a socially important issue. However, guaranteeing safety is particularly difficult in places where many children gather, posing a major challenge for parents and administrators. Current systems are slow to detect and report dangerous situations, making rapid response difficult. Furthermore, accurately analyzing human emotions and making appropriate judgments is also required. Solving these problems and improving safety is essential. 【0182】 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. 【0183】 In this invention, the server includes means for processing information media data acquired by acquisition means from one or more imaging devices installed in a public space; means for analyzing the information media data by information analysis means to identify human movements or behavioral patterns and detect suspicious behavior; and means for analyzing human facial expressions and behavior from video data by emotion analysis means to recognize emotional states and generate additional warnings as necessary. This makes it possible to detect potential dangers occurring in public spaces early and respond quickly. 【0184】 "Acquisition means" refers to a mechanism for collecting information media data from a camera installed in a public space. 【0185】 "Information analysis means" refers to technology that processes acquired information media data, identifies human movements and behavioral patterns, and has the function of detecting suspicious behavior. 【0186】 A "notification method" is a method for sending a warning to supervisors or user devices when an anomaly is detected. 【0187】 An "emotion analysis method" is a system that analyzes human facial expressions and behavior from video data, recognizes emotional states, and generates additional warnings as needed. 【0188】 "Environmental monitoring measures" refer to methods for monitoring surrounding environmental data and the status of equipment, and issuing warnings when dangerous conditions occur. 【0189】 This invention illustrates an embodiment of a system for improving safety in public spaces. A server acquires information media data in real time from imaging devices installed in public spaces via an acquisition means. The acquired data is diverse, including environmental data and dynamic information, and an information analysis means operates based on this data. The information analysis means uses the image processing library OpenCV and the machine learning framework TENSORFLOW® to detect the movement of people and suspicious behavior. 【0190】 Furthermore, emotion analysis capabilities are implemented, allowing for the recognition of human emotional states from video data. The technology used combines image recognition and emotion detection algorithms to enable accurate information provision. Firebase and WebSocket are used as notification methods, and warnings are quickly sent to administrators and user devices when an anomaly is detected. 【0191】 Environmental monitoring methods include weather sensors and equipment sensors, which are used to detect the occurrence of dangerous conditions. This allows the server to issue warnings in advance, ensuring the safety of users. 【0192】 As a concrete example, if a child is behaving dangerously on playground equipment in a park, the server analyzes the behavior and notifies parents in real time via SmartNews. In this scenario, safety is improved without compromising comfort. An example of a prompt to the generating AI model is, "Consider the design of a safety monitoring system for public spaces. Analyze the data from the acquisition methods and suggest ways to improve safety." 【0193】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0194】 Step 1: 【0195】 The server acquires video data in real time from cameras installed in public spaces through acquisition means. This data is transmitted to the server in its initial raw state and used as basic information for further analysis. 【0196】 Step 2: 【0197】 The server processes the video data acquired using information analysis tools. In this step, it performs frame-by-frame image processing using OpenCV and applies a motion detection algorithm. It receives frame data as input, performs contour extraction and object tracking to identify human movement and behavioral patterns, and outputs results that detect suspicious behavioral patterns. 【0198】 Step 3: 【0199】 The server analyzes individual facial expressions from pre-processed video data using emotion analysis tools. This process utilizes TensorFlow and an emotion recognition model to estimate emotional states. Based on the image data provided as input, it outputs emotional states as labels and records them when abnormal emotions are detected. 【0200】 Step 4: 【0201】 If an anomaly is detected, the server promptly sends a warning to administrators and user terminals via a notification system for confirmation. In this step, settings are configured to send alert notifications in real time via Firebase communication. The input is an anomaly detection event, and the output is a warning message. 【0202】 Step 5: 【0203】 The device tracks the individual's location in real time using location information acquisition methods and transmits the location data to the server. Using location measurement technologies such as GPS, it determines the individual's current location based on the input location information and outputs that information. 【0204】 Step 6: 【0205】 The server acquires sensor information that continuously monitors the surrounding environment and equipment status via environmental monitoring devices. In this step, weather conditions and equipment status data are used as input, a hazard detection algorithm with set thresholds is applied, and a warning is output when a hazard is detected. 【0206】 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. 【0207】 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. 【0208】 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. 【0209】 [Second Embodiment] 【0210】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0211】 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. 【0212】 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). 【0213】 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. 【0214】 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. 【0215】 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). 【0216】 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. 【0217】 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. 【0218】 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. 【0219】 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. 【0220】 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. 【0221】 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". 【0222】 This invention relates to a system for protecting the safety of children in parks, and aims to improve park safety by providing an acquisition means, a video analysis means, a notification means, a location information acquisition means, and an environmental monitoring means as embodiments of the system. 【0223】 First, let's explain the acquisition method. The terminal acquires video data in real time from one or more cameras installed within the park. This video data is used to clearly monitor various areas within the park. 【0224】 Next is the video analysis method. The server analyzes the acquired video data and uses an AI module to evaluate the movements and behavioral patterns of people. This evaluation makes it possible to immediately detect the presence of suspicious individuals or dangerous behavior. 【0225】 If abnormal behavior is detected, a notification system is activated. The server generates an alert and sends its contents to the administrator's and park users' devices. This allows for a swift response. 【0226】 The location acquisition method is designed with user experience in mind. It can accurately track a child's current location using location information from the user's mobile device or a dedicated device. This feature is particularly useful when trying to find a lost child. 【0227】 Furthermore, environmental monitoring devices can be used to continuously monitor the weather and the condition of the playground equipment. The weather data obtained from the terminals and the usage status of the playground equipment are analyzed on the server, and if a danger is detected, an appropriate warning is sent again to the relevant parties. 【0228】 As a concrete example, suppose a camera captures a child approaching a suspicious person in a park one day. The server immediately analyzes the footage and, upon confirming that it matches the suspicious person's behavior pattern, sends a notification to the administrator and nearby parent users. This rapid warning allows administrators to rush to the scene and ensure safety. The system is also utilized in response to sudden weather changes; for example, in the event of a sudden thunderstorm, it sends a notification to restrict the use of playground equipment, playing a role in protecting the safety of users. 【0229】 As described above, this system is designed to constantly monitor safety within the park and enable appropriate responses by combining these means. 【0230】 The following describes the processing flow. 【0231】 Step 1: 【0232】 The terminal acquires video data in real time from a camera installed in the park. The acquired data is transmitted to a server via the network. 【0233】 Step 2: 【0234】 The server receives the acquired video data and preprocesses it into an analyzable format. This includes noise reduction and resolution adjustment to prepare the data for efficient analysis. 【0235】 Step 3: 【0236】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to extract people's movements and behavioral patterns, and to determine whether or not suspicious behavior is present. 【0237】 Step 4: 【0238】 The server reviews the analysis results, and if abnormal behavior is detected, it immediately sends a warning to the administrator's or park user's device using a notification system. 【0239】 Step 5: 【0240】 Users track their children's location through a dedicated application. The device obtains location information from the user's device and sends it to the server. 【0241】 Step 6: 【0242】 The server analyzes location information to pinpoint the child's current location. In the case of a lost child, camera footage and location information are used in combination to efficiently locate the child. 【0243】 Step 7: 【0244】 The device continuously collects data about the surrounding environment, such as weather and the condition of playground equipment. 【0245】 Step 8: 【0246】 The server analyzes environmental data, and if an anomaly is detected, it sends a warning to the user about changes in weather or dangers related to playground equipment, prompting them to take safety precautions. 【0247】 (Example 1) 【0248】 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." 【0249】 To ensure safety within a region, it is necessary to quickly identify suspicious behavior by individuals in designated areas and dangerous environmental conditions, and to immediately warn relevant parties. In particular, there is a need for an efficient and accurate system that can pinpoint locations in real time and respond to environmental changes. 【0250】 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. 【0251】 In this invention, the server includes means for collecting visual data obtained from one or more image acquisition devices placed within the area using acquisition means, means for processing the visual data using image analysis means to evaluate the movements and behavioral patterns of the object to be identified and to identify irregular behavior, and means for transmitting a warning to a manager or user's information terminal using notification means when irregular behavior is detected. This makes it possible to monitor safety within the area quickly and accurately. 【0252】 "Acquisition means" refers to means that have the function of collecting visual data from image acquisition devices placed within a region. 【0253】 "Image analysis means" refers to means that process acquired visual data and have the function of evaluating the actions and behavioral patterns of the object to be identified. 【0254】 "Irregular behavior" refers to actions that deviate from typical activity patterns and is a term used to indicate behaviors that require special attention from the system. 【0255】 A "notification means" is a means that has the function of transmitting warnings about detected irregular behavior or dangerous conditions to the administrator's or user's information terminal. 【0256】 A "location identification means" is a means that has the function of identifying a person's current location and tracking their movements in real time. 【0257】 "Surrounding monitoring means" refers to means that have the function of identifying surrounding weather information and the status of equipment, and issuing a warning if a potential danger occurs. 【0258】 This system is designed to enhance safety in parks and similar public areas, providing peace of mind to users. The following describes specific implementations of the invention. 【0259】 The terminal first acquires visual data in real time from one or more image acquisition devices installed within the area, such as high-resolution cameras. This data undergoes initial processing within the terminal and is then sent to the server. 【0260】 The server uses advanced image analysis software to analyze the received visual data. Specifically, an AI module is launched on hardware equipped with a high-speed processor for running generative AI models. This AI module has the ability to evaluate human movements and behavioral patterns and instantly identify irregular behavior. 【0261】 If irregular behavior is detected, the server immediately generates a warning via a notification system and transmits it to the relevant parties. This notification quickly and clearly informs administrators and users of the situation on their mobile devices. Users' devices are equipped with location-based apps and periodically send their current location information to the server, allowing for real-time tracking of the movements of children and other users. 【0262】 Furthermore, the terminal uses surrounding monitoring means to acquire weather information and device status through installed environmental sensors. The server analyzes this information and has the function to issue another warning if it detects dangerous weather conditions or device malfunctions. 【0263】 For example, if a sudden thunderstorm is predicted, the terminal will analyze weather data obtained from sensors on a server, and if it determines that a thunderstorm is approaching, it will issue a warning to park managers and users urging them to quickly ensure their safety. 【0264】 Examples of prompts include, "What AI module would be appropriate to improve park safety?" This enables the concrete and effective implementation of a safety monitoring system. 【0265】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0266】 Step 1: 【0267】 The terminal acquires visual data in real time from high-resolution cameras placed throughout the park. The input is video footage directly from the cameras, which is initially processed digitally before being sent to the server as a dataset for appropriate analysis. Specifically, this process includes noise reduction and frame rate standardization. 【0268】 Step 2: 【0269】 The server inputs visual data sent from the terminal into the AI ​​module and begins analysis using a generative AI model. The visual data provided as input is processed by a data processing algorithm to detect human movement and behavioral patterns. The output consists of detection results for irregular behavior and specific movement patterns, which are organized into a list. Specific actions include anomaly detection using deep learning techniques. 【0270】 Step 3: 【0271】 The server generates warnings via notification mechanisms based on anomaly detection results obtained through AI analysis. It uses behavior detection results as input, analyzing them to identify suspicious behavior. The output is a warning message, which is sent to the administrator's or user's information terminal. Specific actions include rapid message delivery via email or SMS. 【0272】 Step 4: 【0273】 Users collect their own and their children's location information in real time using a location-based app on their device. The input is location data from a GPS sensor, which is periodically updated and sent to the server. The output is organized on the server as current location information and stored in a tracking database. Specific operations include periodic location information updates and accuracy checks. 【0274】 Step 5: 【0275】 The terminal collects weather data and device status from surrounding monitoring devices and sends it to a server for analysis. Inputs are time-series data from temperature sensors and anemometers, and outputs are warning indicators based on risk analysis. This allows for a rapid response in the event of sudden weather changes or device malfunctions. Specifically, it determines the conditions for alarm activation and notifies relevant parties as needed. 【0276】 (Application Example 1) 【0277】 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." 【0278】 In public spaces, it is necessary to enhance safety by monitoring diverse data in real time, including activity dynamics and weather conditions. However, current systems have limited ability to respond quickly to individual situations, and immediate action is required against factors that threaten safety. 【0279】 The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means respectively. 【0280】 In this invention, the server includes: means for processing image data acquired from one or more imaging devices installed in a public space by acquisition means; means for analyzing the image data by image analysis means to identify the dynamics or behavior patterns of activities and detect abnormal behaviors; means for, when abnormal detection is performed, sending a notification to a relevant person or a user terminal by notification means; means for identifying and tracking the current position of an individual user in a park by position information acquisition means; and means for detecting surrounding weather data and the status of facilities by environmental monitoring means and warning when dangerous conditions occur. Thereby, real-time monitoring and prompt response of safety in a public space become possible. 【0281】 The "acquisition means" is a device or method having a function of acquiring image data from one or more imaging devices installed in a public space. 【0282】 The "image analysis means" is a function or process for identifying the dynamics of activities and behavior patterns and detecting suspicious behaviors by analyzing the acquired image data. 【0283】 The "notification means" is a technology or device for sending a notification to a relevant person or a user terminal when abnormal detection is performed. 【0284】 The "position information acquisition means" is a technology or method for identifying and tracking the current position of an individual user in a park. 【0285】 The "environmental monitoring means" is a technology or device having a function of detecting surrounding weather data and the status of facilities and giving a warning when dangerous conditions occur. 【0286】 The "generative AI model" is an artificial intelligence technology for generating prompt texts as recommended countermeasures for relevant persons based on analysis results. 【0287】 A "prompt text" is a text output by a generative AI model and includes instructions and suggestions for prompting appropriate actions for relevant parties. 【0288】 The system for realizing this invention is designed to improve the safety of public spaces. The system consists of multiple components and is implemented by the following elements. 【0289】 The server collects image data in real time from image acquisition devices installed in public spaces. This image acquisition device is composed of multiple cameras covering many areas. The server inputs the collected image data into an image analysis module to analyze the dynamics of activities and behaviors. Image recognition software such as OpenCV and YOLOv5 is used for this analysis. This enables the smooth identification of abnormal behaviors and suspicious persons. 【0290】 When an abnormal behavior is detected, a warning is sent to relevant parties and user terminals through the notification module. By using a service such as Firebase Cloud Messaging for sending notifications, rapid and efficient information distribution is achieved. 【0291】 Furthermore, the server has a location information acquisition function to accurately track the locations of users within public spaces. By utilizing the Google Maps API for this function, the movement patterns of individual users can be grasped in detail. This enables a rapid response especially to problems such as lost children. 【0292】 Also, the environmental monitoring function monitors the surrounding weather data and equipment status. This information is collected from environmental sensors and analyzed on the server. It has a function of automatically issuing a warning to users when the weather conditions change suddenly or a dangerous state is predicted. 【0293】 Furthermore, by utilizing a generative AI model, prompt messages containing appropriate countermeasures and advice are created based on the analysis results and provided to relevant parties. For example, the analysis can generate a prompt message stating, "A suspicious person has been observed on the west side of the park. Surrounding area managers should take immediate action," and send it to relevant parties immediately. 【0294】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0295】 Step 1: 【0296】 The server receives image data in real time from image acquisition devices installed in public spaces. These images are captured by cameras and transmitted to the server as image data. The acquired image data is then used for subsequent analysis processes. 【0297】 Step 2: 【0298】 The server inputs the received image data into an image analysis module to analyze the dynamics of activity and behavior within the image. This analysis uses image recognition software such as OpenCV or YOLOv5. The input here is image data, and the output is the detection results of identified dynamics and abnormal behavior. The server identifies the analysis results and proceeds to the next stage. 【0299】 Step 3: 【0300】 The server generates information for sending notifications when abnormal behavior is detected through analysis. It uses the Firebase Cloud Messaging service to create notification data for sending warnings and information to relevant parties and user devices. The input here is information about the abnormal behavior identified through analysis, and the output is the generated notification message. 【0301】 Step 4: 【0302】 The server uses the location information acquisition function to grasp the current location of the user in the public space. Using the Google Maps API, it collects the user's location information and stores that information in the server. The input is the user's location coordinates, and the output is the record of the location information. 【0303】 Step 5: 【0304】 The server uses the environmental monitoring function to detect the surrounding weather data and equipment status. It analyzes the data obtained from the environmental sensors and evaluates the weather conditions and the status of the equipment. The input here is the data from the environmental sensors, and the output is the analyzed environmental status. 【0305】 Step 6: 【0306】 The server utilizes the generative AI model to generate prompt texts based on the analysis results and situations. The input here is the various integrated analysis data, and the output is the prompt text for providing to the relevant parties. This prompt text specifically instructs the corresponding measures to be taken by the relevant parties. 【0307】 Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions. 【0308】 The present invention is a system for highly protecting the safety of children in a park, which is a public place. By comprising an acquisition means, a video analysis means, a notification means, a location information acquisition means, an environmental monitoring means, and an emotion engine, it realizes an environment where people can play more safely. 【0309】 First, the acquisition means will be described. The terminal uses the cameras installed in the park to collect video data in real time and transmit it to the server. This video data serves as the basic information for comprehensively monitoring various situations in the park. 【0310】 Next, the server processes this video data using video analysis tools. The analysis primarily utilizes AI modules to identify the movements and behavioral patterns of individuals, and to detect suspicious behavior. If suspicious behavior is detected, a notification system is activated, immediately sending a warning to administrators and users. 【0311】 Furthermore, an emotion engine will be introduced as a new addition to this system. This emotion engine is implemented on the server and analyzes people's facial expressions and actions from video data to recognize their emotional state. For example, if a child is crying or has an angry expression, the system will recognize that emotional state and, if necessary, generate additional alerts or countermeasures. 【0312】 Furthermore, the location information acquisition method identifies the child's current location through the user's mobile device or specific device and provides that information to administrators or guardians as needed. This function makes the search for lost children particularly more efficient. 【0313】 Environmental monitoring devices are used to monitor surrounding weather changes and the condition of playground equipment. The server analyzes this data and issues appropriate warnings to park users if a hazard is detected. 【0314】 As a concrete example, suppose the server detects through video analysis that a child is playing inappropriately on playground equipment, and the emotion engine detects from the child's facial expression that they are feeling anxious. In this case, the server immediately notifies the user of the situation via the terminal and urges them to take prompt action. Also, if environmental monitoring measures detect that a thunderstorm is approaching, the server will issue a warning to restrict the use of playground equipment, playing a role in ensuring the safety of users. 【0315】 In this way, the system is designed to implement a high level of safety and security for children within the park by combining various means. 【0316】 The following describes the processing flow. 【0317】 Step 1: 【0318】 The terminal acquires video data in real time from multiple cameras installed in the park. The acquired video data is transmitted to a server via the network. 【0319】 Step 2: 【0320】 The server preprocesses the video data it receives. Preprocessing involves noise removal and resolution adjustment to prepare the data for accurate analysis. 【0321】 Step 3: 【0322】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to identify people's movements and behavioral patterns, and to detect suspicious behavior. 【0323】 Step 4: 【0324】 The emotion engine analyzes a person's facial expressions and gestures from video data to recognize their emotional state. If the emotional change is significant, that information is used to guide the next step. 【0325】 Step 5: 【0326】 If the server detects abnormal behavior or significant emotional states through analysis, it will use notification mechanisms to send warnings to administrators and park users' devices. 【0327】 Step 6: 【0328】 This system allows users to check their child's location on their mobile device. The device periodically acquires location information and sends it to the server, providing the user with real-time information. 【0329】 Step 7: 【0330】 The server tracks the child's current location based on location data and provides supplementary information to help find the lost child. If necessary, it can be linked with camera data to determine the exact location. 【0331】 Step 8: 【0332】 The device acquires environmental data for the park and its surroundings. This primarily involves recording weather conditions and any abnormalities in playground equipment. 【0333】 Step 9: 【0334】 The server analyzes environmental data it acquires and sends a warning to the user if it detects dangerous weather conditions or the state of playground equipment. This allows the user to take appropriate safety measures. 【0335】 Step 10: 【0336】 The server saves all recorded data as logs, which can be used for review and training as needed. 【0337】 (Example 2) 【0338】 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". 【0339】 Improving safety in public spaces is particularly important in facilities frequently used by children. However, conventional systems primarily rely on human visual monitoring and simple sensors, making it difficult to immediately detect and notify of suspicious behavior or changes in emotions. Furthermore, rapid responses to location information and sudden environmental changes were insufficient. As a result, improving safety and a sense of security within these facilities remained a challenge. 【0340】 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. 【0341】 In this invention, the server includes means for processing data acquired from one or more imaging devices installed in public facilities by acquisition means, means for analyzing the data by video analysis means to identify dynamic or behavioral patterns and detect suspicious behavior, and means for analyzing a person's facial expressions or movements by emotion engine and recognizing their emotional state. This enables the rapid detection of suspicious behavior or changes in emotional state in public facilities and the immediate notification of necessary warnings, thereby improving safety and providing a sense of security to users. 【0342】 "Acquisition means" refers to means for collecting and processing video data in real time from one or more imaging devices installed in a public facility. 【0343】 "Video analysis means" refers to means that have the ability to analyze acquired video data and identify dynamics or behavioral patterns. 【0344】 "Means for detecting suspicious behavior" refers to methods for identifying suspicious behavior and prompting caution based on dynamic or behavioral patterns identified through video analysis. 【0345】 An "emotion engine" is a method for recognizing a person's emotional state by analyzing their facial expressions and movements from video data. 【0346】 A "notification mechanism" is a means of sending a warning to an administrator or user when an abnormal or specific emotional state is detected. 【0347】 "Location information acquisition means" refers to a means of identifying the current location of a subject within a public facility and providing that information. 【0348】 "Environmental monitoring means" refers to measures for monitoring surrounding weather data and equipment conditions, and for issuing appropriate warnings when dangerous conditions occur. 【0349】 This invention is a system for improving safety in public facilities and is implemented by combining multiple functional modules. Specifically, it achieves real-time monitoring and notification through cooperation between a server, terminals, and users. 【0350】 The terminal is responsible for collecting video data using multiple cameras installed within the facility. These cameras are standard surveillance cameras capable of capturing high resolution and wide areas. This data is transmitted to the server in real time. 【0351】 The server uses an AI module as a video analysis tool to analyze the acquired video data. The AI ​​module utilizes deep learning technology to identify movement and behavioral patterns from the captured video and detect suspicious behavior. If necessary, an emotion engine analyzes the person's facial expressions and movements to recognize their emotional state. For example, if a child is using playground equipment in a dangerous manner, or if emotional changes such as crying are detected, these are recognized as suspicious behaviors. 【0352】 Using location information acquisition methods, it is possible to obtain a child's location information from the user's mobile device or specific device. This information is processed by a server and provided to administrators or guardians when needed. This makes the search for lost children more efficient. 【0353】 Furthermore, environmental monitoring devices allow the terminal to monitor surrounding weather changes and the condition of the equipment. Through this function, if a sudden change in weather occurs or if the playground equipment is found to be unsafe, it will issue a warning to alert the user. This ensures the safety of users. 【0354】 As an example of how to use this system, one could input the prompt "Please tell me how to assess the safety situation of children in the park and notify me of suspicious behavior or emotional states" into the generating AI model. This would allow us to verify how to operate the system effectively. 【0355】 Thus, the objective of this invention is to enhance safety within public facilities and provide an environment where people can use them with peace of mind, by having each of these means work together. 【0356】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0357】 Step 1: 【0358】 The terminal acquires video data in real time from cameras installed within public facilities. The acquired data is first compressed and then sent to the server. The input here is the video from the camera, and the output is the compressed video data. 【0359】 Step 2: 【0360】 The server decompresses the received compressed video data and inputs it into an AI module. This module uses deep learning algorithms to analyze the dynamics and behavioral patterns within the video. Suspicious behavior and unusual movements are identified through data calculations. The input is the decompressed video data, and the output is suspicious behavior and specific behavioral patterns. 【0361】 Step 3: 【0362】 The server then uses an emotion engine to analyze a person's facial expressions and body movements from the same video data and evaluate their emotional state. For example, it might detect if a child is crying. The input is the video data, and the output is the detected emotional state. 【0363】 Step 4: 【0364】 When suspicious behavior or a specific emotional state is detected, the server activates a notification system. This sends a warning message to the administrator's or user's mobile device via the terminal. The input is information about the suspicious behavior or emotional state, and the output is the sent warning message. 【0365】 Step 5: 【0366】 The location information acquisition method obtains the child's current location from the user's device. The server integrates this location data into a map application and provides it to the user as visualized information. The input is location information from the device, and the output is a map displaying the location information. 【0367】 Step 6: 【0368】 The terminal continuously monitors weather data and equipment status through environmental monitoring devices. The server analyzes this data and, if it detects a dangerous situation, such as a sudden change in weather, issues a warning to the user. The input is weather data and equipment status information, and the output is the issued warning. 【0369】 (Application Example 2) 【0370】 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." 【0371】 In recent years, ensuring safety in public spaces has become a socially important issue. However, guaranteeing safety is particularly difficult in places where many children gather, posing a major challenge for parents and administrators. Current systems are slow to detect and report dangerous situations, making rapid response difficult. Furthermore, accurately analyzing human emotions and making appropriate judgments is also required. Solving these problems and improving safety is essential. 【0372】 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. 【0373】 In this invention, the server includes means for processing information media data acquired by acquisition means from one or more imaging devices installed in a public space; means for analyzing the information media data by information analysis means to identify human movements or behavioral patterns and detect suspicious behavior; and means for analyzing human facial expressions and behavior from video data by emotion analysis means to recognize emotional states and generate additional warnings as necessary. This makes it possible to detect potential dangers occurring in public spaces early and respond quickly. 【0374】 "Acquisition means" refers to a mechanism for collecting information media data from a camera installed in a public space. 【0375】 "Information analysis means" refers to technology that processes acquired information media data, identifies human movements and behavioral patterns, and has the function of detecting suspicious behavior. 【0376】 A "notification method" is a method for sending a warning to supervisors or user devices when an anomaly is detected. 【0377】 An "emotion analysis method" is a system that analyzes human facial expressions and behavior from video data, recognizes emotional states, and generates additional warnings as needed. 【0378】 "Environmental monitoring measures" refer to methods for monitoring surrounding environmental data and the status of equipment, and issuing warnings when dangerous conditions occur. 【0379】 This invention illustrates an embodiment of a system for improving safety in public spaces. A server acquires information media data in real time from a camera installed in a public space via an acquisition means. The acquired data is diverse, including environmental data and dynamic information, and an information analysis means operates based on this data. The information analysis means uses the image processing library OpenCV and the machine learning framework TensorFlow to detect the movement of people and suspicious behavior. 【0380】 Furthermore, emotion analysis capabilities are implemented, allowing for the recognition of human emotional states from video data. The technology used combines image recognition and emotion detection algorithms to enable accurate information provision. Firebase and WebSocket are used as notification methods, and warnings are quickly sent to administrators and user devices when an anomaly is detected. 【0381】 Environmental monitoring methods include weather sensors and equipment sensors, which are used to detect the occurrence of dangerous conditions. This allows the server to issue warnings in advance, ensuring the safety of users. 【0382】 As a concrete example, if a child is behaving dangerously on playground equipment in a park, the server analyzes the behavior and notifies parents in real time via SmartNews. In this scenario, safety is improved without compromising comfort. An example of a prompt to the generating AI model is, "Consider the design of a safety monitoring system for public spaces. Analyze the data from the acquisition methods and suggest ways to improve safety." 【0383】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0384】 Step 1: 【0385】 The server acquires video data in real time from cameras installed in public spaces through acquisition means. This data is transmitted to the server in its initial raw state and used as basic information for further analysis. 【0386】 Step 2: 【0387】 The server processes the video data acquired using information analysis tools. In this step, it performs frame-by-frame image processing using OpenCV and applies a motion detection algorithm. It receives frame data as input, performs contour extraction and object tracking to identify human movement and behavioral patterns, and outputs results that detect suspicious behavioral patterns. 【0388】 Step 3: 【0389】 The server analyzes individual facial expressions from pre-processed video data using emotion analysis tools. This process utilizes TensorFlow and an emotion recognition model to estimate emotional states. Based on the image data provided as input, it outputs emotional states as labels and records them when abnormal emotions are detected. 【0390】 Step 4: 【0391】 If an anomaly is detected, the server promptly sends a warning to administrators and user terminals via a notification system for confirmation. In this step, settings are configured to send alert notifications in real time via Firebase communication. The input is an anomaly detection event, and the output is a warning message. 【0392】 Step 5: 【0393】 The device tracks the individual's location in real time using location information acquisition methods and transmits the location data to the server. Using location measurement technologies such as GPS, it determines the individual's current location based on the input location information and outputs that information. 【0394】 Step 6: 【0395】 The server acquires sensor information that continuously monitors the surrounding environment and equipment status via environmental monitoring devices. In this step, weather conditions and equipment status data are used as input, a hazard detection algorithm with set thresholds is applied, and a warning is output when a hazard is detected. 【0396】 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. 【0397】 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. 【0398】 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. 【0399】 [Third Embodiment] 【0400】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0401】 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. 【0402】 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). 【0403】 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. 【0404】 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. 【0405】 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). 【0406】 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. 【0407】 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. 【0408】 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. 【0409】 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. 【0410】 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. 【0411】 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". 【0412】 This invention relates to a system for protecting the safety of children in parks, and aims to improve park safety by providing an acquisition means, a video analysis means, a notification means, a location information acquisition means, and an environmental monitoring means as embodiments of the system. 【0413】 First, let's explain the acquisition method. The terminal acquires video data in real time from one or more cameras installed within the park. This video data is used to clearly monitor various areas within the park. 【0414】 Next is the video analysis method. The server analyzes the acquired video data and uses an AI module to evaluate the movements and behavioral patterns of people. This evaluation makes it possible to immediately detect the presence of suspicious individuals or dangerous behavior. 【0415】 If abnormal behavior is detected, a notification system is activated. The server generates an alert and sends its contents to the administrator's and park users' devices. This allows for a swift response. 【0416】 The location acquisition method is designed with user experience in mind. It can accurately track a child's current location using location information from the user's mobile device or a dedicated device. This feature is particularly useful when trying to find a lost child. 【0417】 Furthermore, environmental monitoring devices can be used to continuously monitor the weather and the condition of the playground equipment. The weather data obtained from the terminals and the usage status of the playground equipment are analyzed on the server, and if a danger is detected, an appropriate warning is sent again to the relevant parties. 【0418】 As a concrete example, suppose a camera captures a child approaching a suspicious person in a park one day. The server immediately analyzes the footage and, upon confirming that it matches the suspicious person's behavior pattern, sends a notification to the administrator and nearby parent users. This rapid warning allows administrators to rush to the scene and ensure safety. The system is also utilized in response to sudden weather changes; for example, in the event of a sudden thunderstorm, it sends a notification to restrict the use of playground equipment, playing a role in protecting the safety of users. 【0419】 As described above, this system is designed to constantly monitor safety within the park and enable appropriate responses by combining these means. 【0420】 The following describes the processing flow. 【0421】 Step 1: 【0422】 The terminal acquires video data in real time from a camera installed in the park. The acquired data is transmitted to a server via the network. 【0423】 Step 2: 【0424】 The server receives the acquired video data and preprocesses it into an analyzable format. This includes noise reduction and resolution adjustment to prepare the data for efficient analysis. 【0425】 Step 3: 【0426】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to extract people's movements and behavioral patterns, and to determine whether or not suspicious behavior is present. 【0427】 Step 4: 【0428】 The server reviews the analysis results, and if abnormal behavior is detected, it immediately sends a warning to the administrator's or park user's device using a notification system. 【0429】 Step 5: 【0430】 Users track their children's location through a dedicated application. The device obtains location information from the user's device and sends it to the server. 【0431】 Step 6: 【0432】 The server analyzes location information to pinpoint the child's current location. In the case of a lost child, camera footage and location information are used in combination to efficiently locate the child. 【0433】 Step 7: 【0434】 The device continuously collects data about the surrounding environment, such as weather and the condition of playground equipment. 【0435】 Step 8: 【0436】 The server analyzes environmental data, and if an anomaly is detected, it sends a warning to the user about changes in weather or dangers related to playground equipment, prompting them to take safety precautions. 【0437】 (Example 1) 【0438】 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." 【0439】 To ensure safety within a region, it is necessary to quickly identify suspicious behavior by individuals in designated areas and dangerous environmental conditions, and to immediately warn relevant parties. In particular, there is a need for an efficient and accurate system that can pinpoint locations in real time and respond to environmental changes. 【0440】 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. 【0441】 In this invention, the server includes means for collecting visual data obtained from one or more image acquisition devices placed within the area using acquisition means, means for processing the visual data using image analysis means to evaluate the movements and behavioral patterns of the object to be identified and to identify irregular behavior, and means for transmitting a warning to a manager or user's information terminal using notification means when irregular behavior is detected. This makes it possible to monitor safety within the area quickly and accurately. 【0442】 "Acquisition means" refers to means that have the function of collecting visual data from image acquisition devices placed within a region. 【0443】 "Image analysis means" refers to means that process acquired visual data and have the function of evaluating the actions and behavioral patterns of the object to be identified. 【0444】 "Irregular behavior" refers to actions that deviate from typical activity patterns and is a term used to indicate behaviors that require special attention from the system. 【0445】 A "notification means" is a means that has the function of transmitting warnings about detected irregular behavior or dangerous conditions to the administrator's or user's information terminal. 【0446】 A "location identification means" is a means that has the function of identifying a person's current location and tracking their movements in real time. 【0447】 "Surrounding monitoring means" refers to means that have the function of identifying surrounding weather information and the status of equipment, and issuing a warning if a potential danger occurs. 【0448】 This system is designed to enhance safety in parks and similar public areas, providing peace of mind to users. The following describes specific implementations of the invention. 【0449】 The terminal first acquires visual data in real time from one or more image acquisition devices installed within the area, such as high-resolution cameras. This data undergoes initial processing within the terminal and is then sent to the server. 【0450】 The server uses advanced image analysis software to analyze the received visual data. Specifically, an AI module is launched on hardware equipped with a high-speed processor for running generative AI models. This AI module has the ability to evaluate human movements and behavioral patterns and instantly identify irregular behavior. 【0451】 If irregular behavior is detected, the server immediately generates a warning via a notification system and transmits it to the relevant parties. This notification quickly and clearly informs administrators and users of the situation on their mobile devices. Users' devices are equipped with location-based apps and periodically send their current location information to the server, allowing for real-time tracking of the movements of children and other users. 【0452】 Furthermore, the terminal uses surrounding monitoring means to acquire weather information and device status through installed environmental sensors. The server analyzes this information and has the function to issue another warning if it detects dangerous weather conditions or device malfunctions. 【0453】 For example, if a sudden thunderstorm is predicted, the terminal will analyze weather data obtained from sensors on a server, and if it determines that a thunderstorm is approaching, it will issue a warning to park managers and users urging them to quickly ensure their safety. 【0454】 Examples of prompts include, "What AI module would be appropriate to improve park safety?" This enables the concrete and effective implementation of a safety monitoring system. 【0455】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0456】 Step 1: 【0457】 The terminal acquires visual data in real time from high-resolution cameras placed throughout the park. The input is video footage directly from the cameras, which is initially processed digitally before being sent to the server as a dataset for appropriate analysis. Specifically, this process includes noise reduction and frame rate standardization. 【0458】 Step 2: 【0459】 The server inputs visual data sent from the terminal into the AI ​​module and begins analysis using a generative AI model. The visual data provided as input is processed by a data processing algorithm to detect human movement and behavioral patterns. The output consists of detection results for irregular behavior and specific movement patterns, which are organized into a list. Specific actions include anomaly detection using deep learning techniques. 【0460】 Step 3: 【0461】 The server generates warnings via notification mechanisms based on anomaly detection results obtained through AI analysis. It uses behavior detection results as input, analyzing them to identify suspicious behavior. The output is a warning message, which is sent to the administrator's or user's information terminal. Specific actions include rapid message delivery via email or SMS. 【0462】 Step 4: 【0463】 Users collect their own and their children's location information in real time using a location-based app on their device. The input is location data from a GPS sensor, which is periodically updated and sent to the server. The output is organized on the server as current location information and stored in a tracking database. Specific operations include periodic location information updates and accuracy checks. 【0464】 Step 5: 【0465】 The terminal collects weather data and device status from surrounding monitoring devices and sends it to a server for analysis. Inputs are time-series data from temperature sensors and anemometers, and outputs are warning indicators based on risk analysis. This allows for a rapid response in the event of sudden weather changes or device malfunctions. Specifically, it determines the conditions for alarm activation and notifies relevant parties as needed. 【0466】 (Application Example 1) 【0467】 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." 【0468】 In public spaces, it is necessary to enhance safety by monitoring diverse data in real time, including activity dynamics and weather conditions. However, current systems have limited ability to respond quickly to individual situations, and immediate action is required against factors that threaten safety. 【0469】 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. 【0470】 In this invention, the server includes means for processing image data acquired from one or more imaging devices installed in a public space by acquisition means; means for analyzing the image data by image analysis means to identify the dynamics or behavioral patterns of activity and to detect abnormal behavior; means for sending notifications to relevant parties or user terminals by notification means when an abnormality is detected; means for identifying and tracking the current location of individual users within the park by location information acquisition means; and means for detecting surrounding weather data and the status of facilities by environmental monitoring means and issuing warnings when dangerous conditions occur. This enables real-time monitoring of safety in public spaces and rapid response. 【0471】 "Acquisition means" refers to a device or method that has the function of acquiring image data from one or more imaging devices installed in a public space. 【0472】 "Image analysis means" refers to a function or process for detecting suspicious behavior by analyzing acquired image data to identify the dynamics and behavioral patterns of activity. 【0473】 "Notification means" refers to technology or equipment for sending notifications to relevant parties or user terminals when an anomaly is detected. 【0474】 "Location information acquisition means" refers to a technology or method for identifying and tracking the current location of individual users within a park. 【0475】 "Environmental monitoring means" refers to technology or devices that have the function of detecting ambient weather data and the condition of equipment, and issuing warnings when dangerous conditions occur. 【0476】 A "generative AI model" is an artificial intelligence technology that generates prompt messages as recommended countermeasures for stakeholders based on analysis results. 【0477】 A "prompt message" is a sentence output by a generative AI model that contains instructions or suggestions to encourage appropriate action from stakeholders. 【0478】 The system for realizing this invention is designed to improve safety in public spaces. The system consists of multiple components and is implemented with the following elements: 【0479】 The server collects image data in real time from image acquisition devices installed in public spaces. These devices consist of multiple cameras that cover a wide area. The server inputs the collected image data into an image analysis module to analyze the dynamics of activities and behaviors. Image recognition software such as OpenCV and YOLOv5 is used for this analysis. This makes it possible to smoothly identify abnormal behavior and suspicious individuals. 【0480】 If abnormal behavior is detected, a notification module sends an alert to relevant parties and user devices. By using services like Firebase Cloud Messaging to send notifications, rapid and efficient information distribution is achieved. 【0481】 Furthermore, the server has location acquisition capabilities, accurately tracking the location of users within public spaces. This functionality utilizes the Google Maps API to gain a detailed understanding of individual user movement patterns. This enables a rapid response, particularly to issues such as lost children. 【0482】 Furthermore, the system monitors surrounding weather data and equipment status through its environmental monitoring function. This information is collected from environmental sensors and analyzed on a server. It also has a function to automatically issue warnings to users in the event of sudden changes in weather conditions or when dangerous situations are predicted. 【0483】 Furthermore, by utilizing a generative AI model, prompt messages containing appropriate countermeasures and advice are created based on the analysis results and provided to relevant parties. For example, the analysis can generate a prompt message stating, "A suspicious person has been observed on the west side of the park. Surrounding area managers should take immediate action," and send it to relevant parties immediately. 【0484】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0485】 Step 1: 【0486】 The server receives image data in real time from image acquisition devices installed in public spaces. These images are captured by cameras and transmitted to the server as image data. The acquired image data is then used for subsequent analysis processes. 【0487】 Step 2: 【0488】 The server inputs the received image data into an image analysis module to analyze the dynamics of activity and behavior within the image. This analysis uses image recognition software such as OpenCV or YOLOv5. The input here is image data, and the output is the detection results of identified dynamics and abnormal behavior. The server identifies the analysis results and proceeds to the next stage. 【0489】 Step 3: 【0490】 The server generates information for sending notifications when abnormal behavior is detected through analysis. It uses the Firebase Cloud Messaging service to create notification data for sending warnings and information to relevant parties and user devices. The input here is information about the abnormal behavior identified through analysis, and the output is the generated notification message. 【0491】 Step 4: 【0492】 The server uses location information acquisition functionality to determine the user's current location within a public space. It uses the Google Maps API to collect the user's location information and stores it on the server. The input is the user's location coordinates, and the output is a record of the location information. 【0493】 Step 5: 【0494】 The server uses environmental monitoring functions to detect ambient weather data and equipment status. It analyzes data obtained from environmental sensors to evaluate weather conditions and equipment status. The input here is data from environmental sensors, and the output is the analyzed environmental status. 【0495】 Step 6: 【0496】 The server utilizes a generative AI model to generate prompt messages based on analysis results and the current situation. The input consists of various collected analysis data, and the output is a prompt message intended for stakeholders. This prompt message specifically instructs stakeholders on the appropriate course of action. 【0497】 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. 【0498】 This invention is a system for highly protecting the safety of children in public spaces such as parks, and by incorporating acquisition means, video analysis means, notification means, location information acquisition means, environmental monitoring means, and emotion engine, it realizes an environment in which children can play with greater peace of mind. 【0499】 First, let's explain the data acquisition method. The terminal uses cameras installed in the park to collect video data in real time and transmit it to the server. This video data serves as basic information for comprehensively monitoring various situations within the park. 【0500】 Next, the server processes this video data using video analysis tools. The analysis primarily utilizes AI modules to identify the movements and behavioral patterns of individuals, and to detect suspicious behavior. If suspicious behavior is detected, a notification system is activated, immediately sending a warning to administrators and users. 【0501】 Furthermore, an emotion engine will be introduced as a new addition to this system. This emotion engine is implemented on the server and analyzes people's facial expressions and actions from video data to recognize their emotional state. For example, if a child is crying or has an angry expression, the system will recognize that emotional state and, if necessary, generate additional alerts or countermeasures. 【0502】 Furthermore, the location information acquisition method identifies the child's current location through the user's mobile device or specific device and provides that information to administrators or guardians as needed. This function makes the search for lost children particularly more efficient. 【0503】 Environmental monitoring devices are used to monitor surrounding weather changes and the condition of playground equipment. The server analyzes this data and issues appropriate warnings to park users if a hazard is detected. 【0504】 As a concrete example, suppose the server detects through video analysis that a child is playing inappropriately on playground equipment, and the emotion engine detects from the child's facial expression that they are feeling anxious. In this case, the server immediately notifies the user of the situation via the terminal and urges them to take prompt action. Also, if environmental monitoring measures detect that a thunderstorm is approaching, the server will issue a warning to restrict the use of playground equipment, playing a role in ensuring the safety of users. 【0505】 In this way, the system is designed to implement a high level of safety and security for children within the park by combining various means. 【0506】 The following describes the processing flow. 【0507】 Step 1: 【0508】 The terminal acquires video data in real time from multiple cameras installed in the park. The acquired video data is transmitted to a server via the network. 【0509】 Step 2: 【0510】 The server preprocesses the video data it receives. Preprocessing involves noise removal and resolution adjustment to prepare the data for accurate analysis. 【0511】 Step 3: 【0512】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to identify people's movements and behavioral patterns, and to detect suspicious behavior. 【0513】 Step 4: 【0514】 The emotion engine analyzes a person's facial expressions and gestures from video data to recognize their emotional state. If the emotional change is significant, that information is used to guide the next step. 【0515】 Step 5: 【0516】 If the server detects abnormal behavior or significant emotional states through analysis, it will use notification mechanisms to send warnings to administrators and park users' devices. 【0517】 Step 6: 【0518】 This system allows users to check their child's location on their mobile device. The device periodically acquires location information and sends it to the server, providing the user with real-time information. 【0519】 Step 7: 【0520】 The server tracks the child's current location based on location data and provides supplementary information to help find the lost child. If necessary, it can be linked with camera data to determine the exact location. 【0521】 Step 8: 【0522】 The device acquires environmental data for the park and its surroundings. This primarily involves recording weather conditions and any abnormalities in playground equipment. 【0523】 Step 9: 【0524】 The server analyzes environmental data it acquires and sends a warning to the user if it detects dangerous weather conditions or the state of playground equipment. This allows the user to take appropriate safety measures. 【0525】 Step 10: 【0526】 The server saves all recorded data as logs, which can be used for review and training as needed. 【0527】 (Example 2) 【0528】 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." 【0529】 Improving safety in public spaces is particularly important in facilities frequently used by children. However, conventional systems primarily rely on human visual monitoring and simple sensors, making it difficult to immediately detect and notify of suspicious behavior or changes in emotions. Furthermore, rapid responses to location information and sudden environmental changes were insufficient. As a result, improving safety and a sense of security within these facilities remained a challenge. 【0530】 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. 【0531】 In this invention, the server includes means for processing data acquired from one or more imaging devices installed in public facilities by acquisition means, means for analyzing the data by video analysis means to identify dynamic or behavioral patterns and detect suspicious behavior, and means for analyzing a person's facial expressions or movements by emotion engine and recognizing their emotional state. This enables the rapid detection of suspicious behavior or changes in emotional state in public facilities and the immediate notification of necessary warnings, thereby improving safety and providing a sense of security to users. 【0532】 "Acquisition means" refers to means for collecting and processing video data in real time from one or more imaging devices installed in a public facility. 【0533】 "Video analysis means" refers to means that have the ability to analyze acquired video data and identify dynamics or behavioral patterns. 【0534】 "Means for detecting suspicious behavior" refers to methods for identifying suspicious behavior and prompting caution based on dynamic or behavioral patterns identified through video analysis. 【0535】 An "emotion engine" is a method for recognizing a person's emotional state by analyzing their facial expressions and movements from video data. 【0536】 A "notification mechanism" is a means of sending a warning to an administrator or user when an abnormal or specific emotional state is detected. 【0537】 "Location information acquisition means" refers to a means of identifying the current location of a subject within a public facility and providing that information. 【0538】 "Environmental monitoring means" refers to measures for monitoring surrounding weather data and equipment conditions, and for issuing appropriate warnings when dangerous conditions occur. 【0539】 This invention is a system for improving safety in public facilities and is implemented by combining multiple functional modules. Specifically, it achieves real-time monitoring and notification through cooperation between a server, terminals, and users. 【0540】 The terminal is responsible for collecting video data using multiple cameras installed within the facility. These cameras are standard surveillance cameras capable of capturing high resolution and wide areas. This data is transmitted to the server in real time. 【0541】 The server uses an AI module as a video analysis tool to analyze the acquired video data. The AI ​​module utilizes deep learning technology to identify movement and behavioral patterns from the captured video and detect suspicious behavior. If necessary, an emotion engine analyzes the person's facial expressions and movements to recognize their emotional state. For example, if a child is using playground equipment in a dangerous manner, or if emotional changes such as crying are detected, these are recognized as suspicious behaviors. 【0542】 Using location information acquisition methods, it is possible to obtain a child's location information from the user's mobile device or specific device. This information is processed by a server and provided to administrators or guardians when needed. This makes the search for lost children more efficient. 【0543】 Furthermore, environmental monitoring devices allow the terminal to monitor surrounding weather changes and the condition of the equipment. Through this function, if a sudden change in weather occurs or if the playground equipment is found to be unsafe, it will issue a warning to alert the user. This ensures the safety of users. 【0544】 As an example of how to use this system, one could input the prompt "Please tell me how to assess the safety situation of children in the park and notify me of suspicious behavior or emotional states" into the generating AI model. This would allow us to verify how to operate the system effectively. 【0545】 Thus, the objective of this invention is to enhance safety within public facilities and provide an environment where people can use them with peace of mind, by having each of these means work together. 【0546】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0547】 Step 1: 【0548】 The terminal acquires video data in real time from cameras installed within public facilities. The acquired data is first compressed and then sent to the server. The input here is the video from the camera, and the output is the compressed video data. 【0549】 Step 2: 【0550】 The server decompresses the received compressed video data and inputs it into an AI module. This module uses deep learning algorithms to analyze the dynamics and behavioral patterns within the video. Suspicious behavior and unusual movements are identified through data calculations. The input is the decompressed video data, and the output is suspicious behavior and specific behavioral patterns. 【0551】 Step 3: 【0552】 The server then uses an emotion engine to analyze a person's facial expressions and body movements from the same video data and evaluate their emotional state. For example, it might detect if a child is crying. The input is the video data, and the output is the detected emotional state. 【0553】 Step 4: 【0554】 When suspicious behavior or a specific emotional state is detected, the server activates a notification system. This sends a warning message to the administrator's or user's mobile device via the terminal. The input is information about the suspicious behavior or emotional state, and the output is the sent warning message. 【0555】 Step 5: 【0556】 The location information acquisition method obtains the child's current location from the user's device. The server integrates this location data into a map application and provides it to the user as visualized information. The input is location information from the device, and the output is a map displaying the location information. 【0557】 Step 6: 【0558】 The terminal continuously monitors weather data and equipment status through environmental monitoring devices. The server analyzes this data and, if it detects a dangerous situation, such as a sudden change in weather, issues a warning to the user. The input is weather data and equipment status information, and the output is the issued warning. 【0559】 (Application Example 2) 【0560】 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." 【0561】 In recent years, ensuring safety in public spaces has become a socially important issue. However, guaranteeing safety is particularly difficult in places where many children gather, posing a major challenge for parents and administrators. Current systems are slow to detect and report dangerous situations, making rapid response difficult. Furthermore, accurately analyzing human emotions and making appropriate judgments is also required. Solving these problems and improving safety is essential. 【0562】 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. 【0563】 In this invention, the server includes means for processing information media data acquired by acquisition means from one or more imaging devices installed in a public space; means for analyzing the information media data by information analysis means to identify human movements or behavioral patterns and detect suspicious behavior; and means for analyzing human facial expressions and behavior from video data by emotion analysis means to recognize emotional states and generate additional warnings as necessary. This makes it possible to detect potential dangers occurring in public spaces early and respond quickly. 【0564】 "Acquisition means" refers to a mechanism for collecting information media data from a camera installed in a public space. 【0565】 "Information analysis means" refers to technology that processes acquired information media data, identifies human movements and behavioral patterns, and has the function of detecting suspicious behavior. 【0566】 A "notification method" is a method for sending a warning to supervisors or user devices when an anomaly is detected. 【0567】 An "emotion analysis method" is a system that analyzes human facial expressions and behavior from video data, recognizes emotional states, and generates additional warnings as needed. 【0568】 "Environmental monitoring measures" refer to methods for monitoring surrounding environmental data and the status of equipment, and issuing warnings when dangerous conditions occur. 【0569】 This invention illustrates an embodiment of a system for improving safety in public spaces. A server acquires information media data in real time from a camera installed in a public space via an acquisition means. The acquired data is diverse, including environmental data and dynamic information, and an information analysis means operates based on this data. The information analysis means uses the image processing library OpenCV and the machine learning framework TensorFlow to detect the movement of people and suspicious behavior. 【0570】 Furthermore, emotion analysis capabilities are implemented, allowing for the recognition of human emotional states from video data. The technology used combines image recognition and emotion detection algorithms to enable accurate information provision. Firebase and WebSocket are used as notification methods, and warnings are quickly sent to administrators and user devices when an anomaly is detected. 【0571】 Environmental monitoring methods include weather sensors and equipment sensors, which are used to detect the occurrence of dangerous conditions. This allows the server to issue warnings in advance, ensuring the safety of users. 【0572】 As a concrete example, if a child is behaving dangerously on playground equipment in a park, the server analyzes the behavior and notifies parents in real time via SmartNews. In this scenario, safety is improved without compromising comfort. An example of a prompt to the generating AI model is, "Consider the design of a safety monitoring system for public spaces. Analyze the data from the acquisition methods and suggest ways to improve safety." 【0573】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0574】 Step 1: 【0575】 The server acquires video data in real time from cameras installed in public spaces through acquisition means. This data is transmitted to the server in its initial raw state and used as basic information for further analysis. 【0576】 Step 2: 【0577】 The server processes the video data acquired using information analysis tools. In this step, it performs frame-by-frame image processing using OpenCV and applies a motion detection algorithm. It receives frame data as input, performs contour extraction and object tracking to identify human movement and behavioral patterns, and outputs results that detect suspicious behavioral patterns. 【0578】 Step 3: 【0579】 The server analyzes individual facial expressions from pre-processed video data using emotion analysis tools. This process utilizes TensorFlow and an emotion recognition model to estimate emotional states. Based on the image data provided as input, it outputs emotional states as labels and records them when abnormal emotions are detected. 【0580】 Step 4: 【0581】 If an anomaly is detected, the server promptly sends a warning to administrators and user terminals via a notification system for confirmation. In this step, settings are configured to send alert notifications in real time via Firebase communication. The input is an anomaly detection event, and the output is a warning message. 【0582】 Step 5: 【0583】 The device tracks the individual's location in real time using location information acquisition methods and transmits the location data to the server. Using location measurement technologies such as GPS, it determines the individual's current location based on the input location information and outputs that information. 【0584】 Step 6: 【0585】 The server acquires sensor information that continuously monitors the surrounding environment and equipment status via environmental monitoring devices. In this step, weather conditions and equipment status data are used as input, a hazard detection algorithm with set thresholds is applied, and a warning is output when a hazard is detected. 【0586】 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. 【0587】 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. 【0588】 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. 【0589】 [Fourth Embodiment] 【0590】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0591】 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. 【0592】 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). 【0593】 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. 【0594】 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. 【0595】 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). 【0596】 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. 【0597】 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. 【0598】 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. 【0599】 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. 【0600】 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. 【0601】 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. 【0602】 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". 【0603】 This invention relates to a system for protecting the safety of children in parks, and aims to improve park safety by providing an acquisition means, a video analysis means, a notification means, a location information acquisition means, and an environmental monitoring means as embodiments of the system. 【0604】 First, let's explain the acquisition method. The terminal acquires video data in real time from one or more cameras installed within the park. This video data is used to clearly monitor various areas within the park. 【0605】 Next is the video analysis method. The server analyzes the acquired video data and uses an AI module to evaluate the movements and behavioral patterns of people. This evaluation makes it possible to immediately detect the presence of suspicious individuals or dangerous behavior. 【0606】 If abnormal behavior is detected, a notification system is activated. The server generates an alert and sends its contents to the administrator's and park users' devices. This allows for a swift response. 【0607】 The location acquisition method is designed with user experience in mind. It can accurately track a child's current location using location information from the user's mobile device or a dedicated device. This feature is particularly useful when trying to find a lost child. 【0608】 Furthermore, environmental monitoring devices can be used to continuously monitor the weather and the condition of the playground equipment. The weather data obtained from the terminals and the usage status of the playground equipment are analyzed on the server, and if a danger is detected, an appropriate warning is sent again to the relevant parties. 【0609】 As a concrete example, suppose a camera captures a child approaching a suspicious person in a park one day. The server immediately analyzes the footage and, upon confirming that it matches the suspicious person's behavior pattern, sends a notification to the administrator and nearby parent users. This rapid warning allows administrators to rush to the scene and ensure safety. The system is also utilized in response to sudden weather changes; for example, in the event of a sudden thunderstorm, it sends a notification to restrict the use of playground equipment, playing a role in protecting the safety of users. 【0610】 As described above, this system is designed to constantly monitor safety within the park and enable appropriate responses by combining these means. 【0611】 The following describes the processing flow. 【0612】 Step 1: 【0613】 The terminal acquires video data in real time from a camera installed in the park. The acquired data is transmitted to a server via the network. 【0614】 Step 2: 【0615】 The server receives the acquired video data and preprocesses it into an analyzable format. This includes noise reduction and resolution adjustment to prepare the data for efficient analysis. 【0616】 Step 3: 【0617】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to extract people's movements and behavioral patterns, and to determine whether or not suspicious behavior is present. 【0618】 Step 4: 【0619】 The server reviews the analysis results, and if abnormal behavior is detected, it immediately sends a warning to the administrator's or park user's device using a notification system. 【0620】 Step 5: 【0621】 Users track their children's location through a dedicated application. The device obtains location information from the user's device and sends it to the server. 【0622】 Step 6: 【0623】 The server analyzes location information to pinpoint the child's current location. In the case of a lost child, camera footage and location information are used in combination to efficiently locate the child. 【0624】 Step 7: 【0625】 The device continuously collects data about the surrounding environment, such as weather and the condition of playground equipment. 【0626】 Step 8: 【0627】 The server analyzes environmental data, and if an anomaly is detected, it sends a warning to the user about changes in weather or dangers related to playground equipment, prompting them to take safety precautions. 【0628】 (Example 1) 【0629】 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". 【0630】 To ensure safety within a region, it is necessary to quickly identify suspicious behavior by individuals in designated areas and dangerous environmental conditions, and to immediately warn relevant parties. In particular, there is a need for an efficient and accurate system that can pinpoint locations in real time and respond to environmental changes. 【0631】 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. 【0632】 In this invention, the server includes means for collecting visual data obtained from one or more image acquisition devices placed within the area using acquisition means, means for processing the visual data using image analysis means to evaluate the movements and behavioral patterns of the object to be identified and to identify irregular behavior, and means for transmitting a warning to a manager or user's information terminal using notification means when irregular behavior is detected. This makes it possible to monitor safety within the area quickly and accurately. 【0633】 "Acquisition means" refers to means that have the function of collecting visual data from image acquisition devices placed within a region. 【0634】 "Image analysis means" refers to means that process acquired visual data and have the function of evaluating the actions and behavioral patterns of the object to be identified. 【0635】 "Irregular behavior" refers to actions that deviate from typical activity patterns and is a term used to indicate behaviors that require special attention from the system. 【0636】 A "notification means" is a means that has the function of transmitting warnings about detected irregular behavior or dangerous conditions to the administrator's or user's information terminal. 【0637】 A "location identification means" is a means that has the function of identifying a person's current location and tracking their movements in real time. 【0638】 "Surrounding monitoring means" refers to means that have the function of identifying surrounding weather information and the status of equipment, and issuing a warning if a potential danger occurs. 【0639】 This system is designed to enhance safety in parks and similar public areas, providing peace of mind to users. The following describes specific implementations of the invention. 【0640】 The terminal first acquires visual data in real time from one or more image acquisition devices installed within the area, such as high-resolution cameras. This data undergoes initial processing within the terminal and is then sent to the server. 【0641】 The server uses advanced image analysis software to analyze the received visual data. Specifically, an AI module is launched on hardware equipped with a high-speed processor for running generative AI models. This AI module has the ability to evaluate human movements and behavioral patterns and instantly identify irregular behavior. 【0642】 If irregular behavior is detected, the server immediately generates a warning via a notification system and transmits it to the relevant parties. This notification quickly and clearly informs administrators and users of the situation on their mobile devices. Users' devices are equipped with location-based apps and periodically send their current location information to the server, allowing for real-time tracking of the movements of children and other users. 【0643】 Furthermore, the terminal uses surrounding monitoring means to acquire weather information and device status through installed environmental sensors. The server analyzes this information and has the function to issue another warning if it detects dangerous weather conditions or device malfunctions. 【0644】 For example, if a sudden thunderstorm is predicted, the terminal will analyze weather data obtained from sensors on a server, and if it determines that a thunderstorm is approaching, it will issue a warning to park managers and users urging them to quickly ensure their safety. 【0645】 Examples of prompts include, "What AI module would be appropriate to improve park safety?" This enables the concrete and effective implementation of a safety monitoring system. 【0646】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0647】 Step 1: 【0648】 The terminal acquires visual data in real time from high-resolution cameras placed throughout the park. The input is video footage directly from the cameras, which is initially processed digitally before being sent to the server as a dataset for appropriate analysis. Specifically, this process includes noise reduction and frame rate standardization. 【0649】 Step 2: 【0650】 The server inputs visual data sent from the terminal into the AI ​​module and begins analysis using a generative AI model. The visual data provided as input is processed by a data processing algorithm to detect human movement and behavioral patterns. The output consists of detection results for irregular behavior and specific movement patterns, which are organized into a list. Specific actions include anomaly detection using deep learning techniques. 【0651】 Step 3: 【0652】 The server generates warnings via notification mechanisms based on anomaly detection results obtained through AI analysis. It uses behavior detection results as input, analyzing them to identify suspicious behavior. The output is a warning message, which is sent to the administrator's or user's information terminal. Specific actions include rapid message delivery via email or SMS. 【0653】 Step 4: 【0654】 Users collect their own and their children's location information in real time using a location-based app on their device. The input is location data from a GPS sensor, which is periodically updated and sent to the server. The output is organized on the server as current location information and stored in a tracking database. Specific operations include periodic location information updates and accuracy checks. 【0655】 Step 5: 【0656】 The terminal collects weather data and device status from surrounding monitoring devices and sends it to a server for analysis. Inputs are time-series data from temperature sensors and anemometers, and outputs are warning indicators based on risk analysis. This allows for a rapid response in the event of sudden weather changes or device malfunctions. Specifically, it determines the conditions for alarm activation and notifies relevant parties as needed. 【0657】 (Application Example 1) 【0658】 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". 【0659】 In public spaces, it is necessary to enhance safety by monitoring diverse data in real time, including activity dynamics and weather conditions. However, current systems have limited ability to respond quickly to individual situations, and immediate action is required against factors that threaten safety. 【0660】 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. 【0661】 In this invention, the server includes means for processing image data acquired from one or more imaging devices installed in a public space by acquisition means; means for analyzing the image data by image analysis means to identify the dynamics or behavioral patterns of activity and to detect abnormal behavior; means for sending notifications to relevant parties or user terminals by notification means when an abnormality is detected; means for identifying and tracking the current location of individual users within the park by location information acquisition means; and means for detecting surrounding weather data and the status of facilities by environmental monitoring means and issuing warnings when dangerous conditions occur. This enables real-time monitoring of safety in public spaces and rapid response. 【0662】 "Acquisition means" refers to a device or method that has the function of acquiring image data from one or more imaging devices installed in a public space. 【0663】 "Image analysis means" refers to a function or process for detecting suspicious behavior by analyzing acquired image data to identify the dynamics and behavioral patterns of activity. 【0664】 "Notification means" refers to technology or equipment for sending notifications to relevant parties or user terminals when an anomaly is detected. 【0665】 "Location information acquisition means" refers to a technology or method for identifying and tracking the current location of individual users within a park. 【0666】 "Environmental monitoring means" refers to technology or devices that have the function of detecting ambient weather data and the condition of equipment, and issuing warnings when dangerous conditions occur. 【0667】 A "generative AI model" is an artificial intelligence technology that generates prompt messages as recommended countermeasures for stakeholders based on analysis results. 【0668】 A "prompt message" is a sentence output by a generative AI model that contains instructions or suggestions to encourage appropriate action from stakeholders. 【0669】 The system for realizing this invention is designed to improve safety in public spaces. The system consists of multiple components and is implemented with the following elements: 【0670】 The server collects image data in real time from image acquisition devices installed in public spaces. These devices consist of multiple cameras that cover a wide area. The server inputs the collected image data into an image analysis module to analyze the dynamics of activities and behaviors. Image recognition software such as OpenCV and YOLOv5 is used for this analysis. This makes it possible to smoothly identify abnormal behavior and suspicious individuals. 【0671】 If abnormal behavior is detected, a notification module sends an alert to relevant parties and user devices. By using services like Firebase Cloud Messaging to send notifications, rapid and efficient information distribution is achieved. 【0672】 Furthermore, the server has location acquisition capabilities, accurately tracking the location of users within public spaces. This functionality utilizes the Google Maps API to gain a detailed understanding of individual user movement patterns. This enables a rapid response, particularly to issues such as lost children. 【0673】 Furthermore, the system monitors surrounding weather data and equipment status through its environmental monitoring function. This information is collected from environmental sensors and analyzed on a server. It also has a function to automatically issue warnings to users in the event of sudden changes in weather conditions or when dangerous situations are predicted. 【0674】 Furthermore, by utilizing a generative AI model, prompt messages containing appropriate countermeasures and advice are created based on the analysis results and provided to relevant parties. For example, the analysis can generate a prompt message stating, "A suspicious person has been observed on the west side of the park. Surrounding area managers should take immediate action," and send it to relevant parties immediately. 【0675】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0676】 Step 1: 【0677】 The server receives image data in real time from image acquisition devices installed in public spaces. These images are captured by cameras and transmitted to the server as image data. The acquired image data is then used for subsequent analysis processes. 【0678】 Step 2: 【0679】 The server inputs the received image data into an image analysis module to analyze the dynamics of activity and behavior within the image. This analysis uses image recognition software such as OpenCV or YOLOv5. The input here is image data, and the output is the detection results of identified dynamics and abnormal behavior. The server identifies the analysis results and proceeds to the next stage. 【0680】 Step 3: 【0681】 The server generates information for sending notifications when abnormal behavior is detected through analysis. It uses the Firebase Cloud Messaging service to create notification data for sending warnings and information to relevant parties and user devices. The input here is information about the abnormal behavior identified through analysis, and the output is the generated notification message. 【0682】 Step 4: 【0683】 The server uses location information acquisition functionality to determine the user's current location within a public space. It uses the Google Maps API to collect the user's location information and stores it on the server. The input is the user's location coordinates, and the output is a record of the location information. 【0684】 Step 5: 【0685】 The server uses environmental monitoring functions to detect ambient weather data and equipment status. It analyzes data obtained from environmental sensors to evaluate weather conditions and equipment status. The input here is data from environmental sensors, and the output is the analyzed environmental status. 【0686】 Step 6: 【0687】 The server utilizes a generative AI model to generate prompt messages based on analysis results and the current situation. The input consists of various collected analysis data, and the output is a prompt message intended for stakeholders. This prompt message specifically instructs stakeholders on the appropriate course of action. 【0688】 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. 【0689】 This invention is a system for highly protecting the safety of children in public spaces such as parks, and by incorporating acquisition means, video analysis means, notification means, location information acquisition means, environmental monitoring means, and emotion engine, it realizes an environment in which children can play with greater peace of mind. 【0690】 First, let's explain the data acquisition method. The terminal uses cameras installed in the park to collect video data in real time and transmit it to the server. This video data serves as basic information for comprehensively monitoring various situations within the park. 【0691】 Next, the server processes this video data using video analysis tools. The analysis primarily utilizes AI modules to identify the movements and behavioral patterns of individuals, and to detect suspicious behavior. If suspicious behavior is detected, a notification system is activated, immediately sending a warning to administrators and users. 【0692】 Furthermore, an emotion engine will be introduced as a new addition to this system. This emotion engine is implemented on the server and analyzes people's facial expressions and actions from video data to recognize their emotional state. For example, if a child is crying or has an angry expression, the system will recognize that emotional state and, if necessary, generate additional alerts or countermeasures. 【0693】 Furthermore, the location information acquisition method identifies the child's current location through the user's mobile device or specific device and provides that information to administrators or guardians as needed. This function makes the search for lost children particularly more efficient. 【0694】 Environmental monitoring devices are used to monitor surrounding weather changes and the condition of playground equipment. The server analyzes this data and issues appropriate warnings to park users if a hazard is detected. 【0695】 As a concrete example, suppose the server detects through video analysis that a child is playing inappropriately on playground equipment, and the emotion engine detects from the child's facial expression that they are feeling anxious. In this case, the server immediately notifies the user of the situation via the terminal and urges them to take prompt action. Also, if environmental monitoring measures detect that a thunderstorm is approaching, the server will issue a warning to restrict the use of playground equipment, playing a role in ensuring the safety of users. 【0696】 In this way, the system is designed to implement a high level of safety and security for children within the park by combining various means. 【0697】 The following describes the processing flow. 【0698】 Step 1: 【0699】 The terminal acquires video data in real time from multiple cameras installed in the park. The acquired video data is transmitted to a server via the network. 【0700】 Step 2: 【0701】 The server preprocesses the video data it receives. Preprocessing involves noise removal and resolution adjustment to prepare the data for accurate analysis. 【0702】 Step 3: 【0703】 The server uses video analysis tools to analyze pre-processed video data. An AI module is used to identify people's movements and behavioral patterns, and to detect suspicious behavior. 【0704】 Step 4: 【0705】 The emotion engine analyzes a person's facial expressions and gestures from video data to recognize their emotional state. If the emotional change is significant, that information is used to guide the next step. 【0706】 Step 5: 【0707】 If the server detects abnormal behavior or significant emotional states through analysis, it will use notification mechanisms to send warnings to administrators and park users' devices. 【0708】 Step 6: 【0709】 This system allows users to check their child's location on their mobile device. The device periodically acquires location information and sends it to the server, providing the user with real-time information. 【0710】 Step 7: 【0711】 The server tracks the child's current location based on location data and provides supplementary information to help find the lost child. If necessary, it can be linked with camera data to determine the exact location. 【0712】 Step 8: 【0713】 The device acquires environmental data for the park and its surroundings. This primarily involves recording weather conditions and any abnormalities in playground equipment. 【0714】 Step 9: 【0715】 The server analyzes environmental data it acquires and sends a warning to the user if it detects dangerous weather conditions or the state of playground equipment. This allows the user to take appropriate safety measures. 【0716】 Step 10: 【0717】 The server saves all recorded data as logs, which can be used for review and training as needed. 【0718】 (Example 2) 【0719】 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". 【0720】 Improving safety in public spaces is particularly important in facilities frequently used by children. However, conventional systems primarily rely on human visual monitoring and simple sensors, making it difficult to immediately detect and notify of suspicious behavior or changes in emotions. Furthermore, rapid responses to location information and sudden environmental changes were insufficient. As a result, improving safety and a sense of security within these facilities remained a challenge. 【0721】 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. 【0722】 In this invention, the server includes means for processing data acquired from one or more imaging devices installed in public facilities by acquisition means, means for analyzing the data by video analysis means to identify dynamic or behavioral patterns and detect suspicious behavior, and means for analyzing a person's facial expressions or movements by emotion engine and recognizing their emotional state. This enables the rapid detection of suspicious behavior or changes in emotional state in public facilities and the immediate notification of necessary warnings, thereby improving safety and providing a sense of security to users. 【0723】 "Acquisition means" refers to means for collecting and processing video data in real time from one or more imaging devices installed in a public facility. 【0724】 "Video analysis means" refers to means that have the ability to analyze acquired video data and identify dynamics or behavioral patterns. 【0725】 "Means for detecting suspicious behavior" refers to methods for identifying suspicious behavior and prompting caution based on dynamic or behavioral patterns identified through video analysis. 【0726】 An "emotion engine" is a method for recognizing a person's emotional state by analyzing their facial expressions and movements from video data. 【0727】 A "notification mechanism" is a means of sending a warning to an administrator or user when an abnormal or specific emotional state is detected. 【0728】 "Location information acquisition means" refers to a means of identifying the current location of a subject within a public facility and providing that information. 【0729】 "Environmental monitoring means" refers to measures for monitoring surrounding weather data and equipment conditions, and for issuing appropriate warnings when dangerous conditions occur. 【0730】 This invention is a system for improving safety in public facilities and is implemented by combining multiple functional modules. Specifically, it achieves real-time monitoring and notification through cooperation between a server, terminals, and users. 【0731】 The terminal is responsible for collecting video data using multiple cameras installed within the facility. These cameras are standard surveillance cameras capable of capturing high resolution and wide areas. This data is transmitted to the server in real time. 【0732】 The server uses an AI module as a video analysis tool to analyze the acquired video data. The AI ​​module utilizes deep learning technology to identify movement and behavioral patterns from the captured video and detect suspicious behavior. If necessary, an emotion engine analyzes the person's facial expressions and movements to recognize their emotional state. For example, if a child is using playground equipment in a dangerous manner, or if emotional changes such as crying are detected, these are recognized as suspicious behaviors. 【0733】 Using location information acquisition methods, it is possible to obtain a child's location information from the user's mobile device or specific device. This information is processed by a server and provided to administrators or guardians when needed. This makes the search for lost children more efficient. 【0734】 Furthermore, environmental monitoring devices allow the terminal to monitor surrounding weather changes and the condition of the equipment. Through this function, if a sudden change in weather occurs or if the playground equipment is found to be unsafe, it will issue a warning to alert the user. This ensures the safety of users. 【0735】 As an example of how to use this system, one could input the prompt "Please tell me how to assess the safety situation of children in the park and notify me of suspicious behavior or emotional states" into the generating AI model. This would allow us to verify how to operate the system effectively. 【0736】 Thus, the objective of this invention is to enhance safety within public facilities and provide an environment where people can use them with peace of mind, by having each of these means work together. 【0737】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0738】 Step 1: 【0739】 The terminal acquires video data in real time from cameras installed within public facilities. The acquired data is first compressed and then sent to the server. The input here is the video from the camera, and the output is the compressed video data. 【0740】 Step 2: 【0741】 The server decompresses the received compressed video data and inputs it into an AI module. This module uses deep learning algorithms to analyze the dynamics and behavioral patterns within the video. Suspicious behavior and unusual movements are identified through data calculations. The input is the decompressed video data, and the output is suspicious behavior and specific behavioral patterns. 【0742】 Step 3: 【0743】 The server then uses an emotion engine to analyze a person's facial expressions and body movements from the same video data and evaluate their emotional state. For example, it might detect if a child is crying. The input is the video data, and the output is the detected emotional state. 【0744】 Step 4: 【0745】 When suspicious behavior or a specific emotional state is detected, the server activates a notification system. This sends a warning message to the administrator's or user's mobile device via the terminal. The input is information about the suspicious behavior or emotional state, and the output is the sent warning message. 【0746】 Step 5: 【0747】 The location information acquisition method obtains the child's current location from the user's device. The server integrates this location data into a map application and provides it to the user as visualized information. The input is location information from the device, and the output is a map displaying the location information. 【0748】 Step 6: 【0749】 The terminal continuously monitors weather data and equipment status through environmental monitoring devices. The server analyzes this data and, if it detects a dangerous situation, such as a sudden change in weather, issues a warning to the user. The input is weather data and equipment status information, and the output is the issued warning. 【0750】 (Application Example 2) 【0751】 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". 【0752】 In recent years, ensuring safety in public spaces has become a socially important issue. However, guaranteeing safety is particularly difficult in places where many children gather, posing a major challenge for parents and administrators. Current systems are slow to detect and report dangerous situations, making rapid response difficult. Furthermore, accurately analyzing human emotions and making appropriate judgments is also required. Solving these problems and improving safety is essential. 【0753】 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. 【0754】 In this invention, the server includes means for processing information media data acquired by acquisition means from one or more imaging devices installed in a public space; means for analyzing the information media data by information analysis means to identify human movements or behavioral patterns and detect suspicious behavior; and means for analyzing human facial expressions and behavior from video data by emotion analysis means to recognize emotional states and generate additional warnings as necessary. This makes it possible to detect potential dangers occurring in public spaces early and respond quickly. 【0755】 "Acquisition means" refers to a mechanism for collecting information media data from a camera installed in a public space. 【0756】 "Information analysis means" refers to technology that processes acquired information media data, identifies human movements and behavioral patterns, and has the function of detecting suspicious behavior. 【0757】 A "notification method" is a method for sending a warning to supervisors or user devices when an anomaly is detected. 【0758】 An "emotion analysis method" is a system that analyzes human facial expressions and behavior from video data, recognizes emotional states, and generates additional warnings as needed. 【0759】 "Environmental monitoring measures" refer to methods for monitoring surrounding environmental data and the status of equipment, and issuing warnings when dangerous conditions occur. 【0760】 This invention illustrates an embodiment of a system for improving safety in public spaces. A server acquires information media data in real time from a camera installed in a public space via an acquisition means. The acquired data is diverse, including environmental data and dynamic information, and an information analysis means operates based on this data. The information analysis means uses the image processing library OpenCV and the machine learning framework TensorFlow to detect the movement of people and suspicious behavior. 【0761】 Furthermore, emotion analysis capabilities are implemented, allowing for the recognition of human emotional states from video data. The technology used combines image recognition and emotion detection algorithms to enable accurate information provision. Firebase and WebSocket are used as notification methods, and warnings are quickly sent to administrators and user devices when an anomaly is detected. 【0762】 Environmental monitoring methods include weather sensors and equipment sensors, which are used to detect the occurrence of dangerous conditions. This allows the server to issue warnings in advance, ensuring the safety of users. 【0763】 As a concrete example, if a child is behaving dangerously on playground equipment in a park, the server analyzes the behavior and notifies parents in real time via SmartNews. In this scenario, safety is improved without compromising comfort. An example of a prompt to the generating AI model is, "Consider the design of a safety monitoring system for public spaces. Analyze the data from the acquisition methods and suggest ways to improve safety." 【0764】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0765】 Step 1: 【0766】 The server acquires video data in real time from cameras installed in public spaces through acquisition means. This data is transmitted to the server in its initial raw state and used as basic information for further analysis. 【0767】 Step 2: 【0768】 The server processes the video data acquired using information analysis tools. In this step, it performs frame-by-frame image processing using OpenCV and applies a motion detection algorithm. It receives frame data as input, performs contour extraction and object tracking to identify human movement and behavioral patterns, and outputs results that detect suspicious behavioral patterns. 【0769】 Step 3: 【0770】 The server analyzes individual facial expressions from pre-processed video data using emotion analysis tools. This process utilizes TensorFlow and an emotion recognition model to estimate emotional states. Based on the image data provided as input, it outputs emotional states as labels and records them when abnormal emotions are detected. 【0771】 Step 4: 【0772】 If an anomaly is detected, the server promptly sends a warning to administrators and user terminals via a notification system for confirmation. In this step, settings are configured to send alert notifications in real time via Firebase communication. The input is an anomaly detection event, and the output is a warning message. 【0773】 Step 5: 【0774】 The device tracks the individual's location in real time using location information acquisition methods and transmits the location data to the server. Using location measurement technologies such as GPS, it determines the individual's current location based on the input location information and outputs that information. 【0775】 Step 6: 【0776】 The server acquires sensor information that continuously monitors the surrounding environment and equipment status via environmental monitoring devices. In this step, weather conditions and equipment status data are used as input, a hazard detection algorithm with set thresholds is applied, and a warning is output when a hazard is detected. 【0777】 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. 【0778】 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. 【0779】 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. 【0780】 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. 【0781】 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. 【0782】 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. 【0783】 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. 【0784】 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. 【0785】 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." 【0786】 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. 【0787】 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. 【0788】 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. 【0789】 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. 【0790】 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. 【0791】 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. 【0792】 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. 【0793】 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. 【0794】 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. 【0795】 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. 【0796】 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. 【0797】 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 as being incorporated by reference. 【0798】 The following is further disclosed regarding the embodiments described above. 【0799】 (Claim 1) 【0800】 A means for processing video data acquired from one or more cameras installed in the park by an acquisition means, 【0801】 A means for analyzing the video data using video analysis means to identify the movement or behavioral patterns of a person and to detect suspicious behavior, 【0802】 A means for sending a warning to the administrator or user terminal via a notification means when an anomaly is detected, 【0803】 A system that includes this. 【0804】 (Claim 2) 【0805】 The system according to claim 1, comprising means for identifying and tracking the current location of a child in a park using means for acquiring location information. 【0806】 (Claim 3) 【0807】 The system according to claim 1, further comprising means for detecting surrounding weather data and equipment status using environmental monitoring means, and for issuing a warning when dangerous conditions occur. 【0808】 "Example 1" 【0809】 (Claim 1) 【0810】 A means for collecting visual data obtained from one or more image acquisition devices placed within a region by means of acquisition, 【0811】 A means for processing the visual data using image analysis means, evaluating the movements and behavioral patterns of the object to be identified, and identifying irregular behavior, 【0812】 A means of transmitting a warning to the administrator or user's information terminal via a notification means when irregular behavior is detected, 【0813】 A means of determining and tracking the current location of a person within a region using location tracking means, 【0814】 A means of identifying surrounding weather information and the status of equipment through surrounding monitoring means, and issuing a warning when a critical situation occurs, 【0815】 A system that includes this. 【0816】 (Claim 2) 【0817】 The system according to claim 1, which uses location information acquired within a region to identify the whereabouts of a person and tracks their movements in real time. 【0818】 (Claim 3) 【0819】 The system according to claim 1, which evaluates acquired environmental information, identifies sudden changes in weather or equipment malfunctions, and issues warnings as necessary. 【0820】 "Application Example 1" 【0821】 (Claim 1) 【0822】 A means for processing image data acquired from one or more imaging devices installed in a public space by means of acquisition, 【0823】 The system includes means for analyzing the image data using image analysis means to identify the dynamics or behavioral patterns of the activity and to detect abnormal behavior, 【0824】 A means for sending a notification to relevant parties or user terminals via a notification means when an anomaly is detected, 【0825】 A means of identifying and tracking the current location of individual users within the park using location information acquisition means, 【0826】 Environmental monitoring means detect surrounding weather data and equipment status, and provide warnings when dangerous conditions occur. 【0827】 A system that includes this. 【0828】 (Claim 2) 【0829】 The system according to claim 1, further comprising means for optimizing warnings to users in a specific activity area based on location information. 【0830】 (Claim 3) 【0831】 The system according to claim 1, comprising a means for generating prompt statements as recommended countermeasures for stakeholders based on the analysis results using a generative AI model. 【0832】 "Example 2 of combining an emotion engine" 【0833】 (Claim 1) 【0834】 A means for processing data acquired from one or more imaging devices installed in a public facility by means of acquisition, 【0835】 A means for analyzing the data using video analysis means, identifying movement or behavioral patterns, and detecting suspicious behavior, 【0836】 An emotion engine analyzes a person's facial expressions or movements to recognize their emotional state, 【0837】 A notification mechanism that sends a warning when an abnormal or specific emotional state is detected, 【0838】 A system that includes this. 【0839】 (Claim 2) 【0840】 The system according to claim 1, comprising means for identifying the current location of an object located within a public facility using means for acquiring location information, and means for providing location information. 【0841】 (Claim 3) 【0842】 The system according to claim 1, further comprising means for detecting surrounding weather data and equipment status using environmental monitoring means, and for issuing a warning when dangerous conditions occur. 【0843】 "Application example 2 when combining with an emotional engine" 【0844】 (Claim 1) 【0845】 A means for processing information media data acquired from one or more imaging devices installed in a public space by means of acquisition, 【0846】 A means for analyzing the information medium data using information analysis means, identifying human movement or behavioral patterns, and detecting suspicious behavior, 【0847】 A means for sending a warning to a supervisor or user terminal via a notification means when an anomaly is detected, 【0848】 A means for analyzing human facial expressions and behavior from video data using emotion analysis means, recognizing emotional states, and generating additional warnings as needed, 【0849】 A system that includes this. 【0850】 (Claim 2) 【0851】 The system according to claim 1, comprising means for identifying and tracking the current location of an individual in a public space using means for acquiring location information. 【0852】 (Claim 3) 【0853】 The system according to claim 1, further comprising means for detecting surrounding environmental data and equipment status using environmental monitoring means, and for issuing a warning when dangerous conditions occur. [Explanation of Symbols] 【0854】 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

[Claim 1] A means for processing video data acquired from one or more cameras installed in the park by an acquisition means, A means for analyzing the video data using video analysis means to identify the movement or behavioral patterns of a person and to detect suspicious behavior, A means for sending a warning to the administrator or user terminal via a notification means when an anomaly is detected, A system that includes this. [Claim 2] The system according to claim 1, further comprising means for identifying and tracking the current location of a child in a park using means for acquiring location information. [Claim 3] The system according to claim 1, further comprising means for detecting surrounding weather data and equipment status using environmental monitoring means, and for issuing a warning when dangerous conditions occur.

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